HK40103142A - In vivo crispr screening system for discovering therapeutic targets in cd8 t cells - Google Patents

Description

In vivo CRISPR screening system for discovering therapeutic targets in CD8 T cells

Cross-references to related applications

This application is entitled to priority under 35 U.S.C. §119(e) to U.S. Provisional Patent Application No. 63/153,191, filed February 24, 2021, which is hereby incorporated herein by reference in its entirety.

Statement regarding federally funded research or development

This invention was developed with government support from the National Institutes of Health (NIH) under license numbers AI105343, AI117950, AI082630, AI112521, AI115712, AI108545, CA210944, CA234842, CA009140, MH109905, and HG010480. The government holds certain rights to this invention.

Background Technology

Understanding the mechanisms of regulatory effector CD8 T cell ( _TEFF ) differentiation is crucial for improving treatments for cancer and other diseases. During acute remission of infection or after vaccination, activation of naive CD8 T cells ( _TN ) leads to differentiation into _TEFF cells, accompanied by transcriptional and epigenetic remodeling. Following antigen clearance, the terminally differentiated subset of _TEFF cells dies within days to weeks, while a small fraction of memory precursors ( _TMPs ) differentiate into long-term memory CD8 T cells ( _TMEMs ). However, during chronic infection and cancer, CD8 T cell differentiation tilts (diverts) along a path of exhaustion. Under these conditions, _TEFF cells become overstimulated and poorly persistent, while the activated precursor population differentiates into exhausted CD8 T cells ( _TEXs ). _TEXs exhibit high expression of multiple inhibitory receptors (including PD-1), reduced effector function, altered homeostasis (compared to _TMEMs ), and unique transcriptional and epigenetic programs. Blocking inhibitory receptors such as PD-1 can revitalize T _cells (TEX), temporarily restoring proliferation and certain effector-like properties, demonstrating clinical benefit in various cancer types. However, despite the success of checkpoint blockade, most patients do not experience durable clinical benefit, and there is a great need to enhance T cell differentiation and effector-like activity after checkpoint blockade or during cell therapy for cancer or other diseases.

There is great interest in defining the T cell population that responds to checkpoint blockade and exploring the optimal differentiation state for cell therapy. _TEX cells are prominent in human tumors and are likely the primary source of tumor-reactive T cells. PD-1 pathway blockade mediates clinical benefit, at least in part, due to the reactivation of _TEX cells, which allows these cells to re-enter a portion of the T _EFF cell program. However, limited therapeutic efficacy is associated with suboptimal reactivation of _TEX cells. CAR T cell therapy failure is also associated with exhaustion, and methods to antagonize exhaustion are under active investigation. However, the ability to effectively participate in robust effector programs, including numerical amplification and activation of effector activity, is crucial for both checkpoint blockade response and cell therapy for cancer control. Understanding the underlying molecular mechanisms controlling this effector activity is necessary to effectively design therapeutic interventions for chronic infections and cancer.

The role of transcription factors (TFs) in regulating T _EFF differentiation relative to T _MEM or T _EX has received considerable attention. For example, TFs Batf and Irf4 play an early role in T cell activation and also trigger a second wave of transcriptional induction of effector genes. Runx3 induces T _EFF gene expression via T-bet and Eomes and is important for tissue-resident memory CD8 T cells ( _TRM ). Runx3 also antagonizes the fate of follicle-like CD8 T cells by inhibiting TCF-1 expression. Runx1, on the other hand, is antagonized by Runx3 during T _EFF differentiation. Most T _EFF -related genes and their associated cognate cis-regulatory regions are inaccessible in the _TN state, linking the role of effector-driven TFs to changes in chromatin accessibility that occur during the _TN- to- _TEFF transition. Indeed, there is evidence that some of these early-operating TFs (such as Batf) may contribute to T _EFF gene accessibility through chromatin remodeling, but other control mechanisms remain to be determined.

In addition to TFs that promote T _EFF formation, the opposite mechanism also moderates the complete commitment of effector differentiation, thus preserving a more durable T cell population for future or ongoing responses. The two alternating cell fates of _{T MEM} and T _EX cannot form from fully committed T _EFFs , suggesting that partial T _EFF programs must be antagonized for T _MEM and T _EX differentiation to occur. High mobility group (HMG) TFs (e.g., TCF-1) are crucial for the development and maintenance of T _MEM and T _EX . TCF-1 inhibits T _EFF -driving TFs (such as T-bet and Blimp-1) and promotes epigenetic changes. Furthermore, a second HMG TF (Tox) is essential for the development of T _EX cell fate, inhibiting T _EFF lineage differentiation. Despite this work, little is known about the mechanisms preventing T _EFF differentiation commitment. Such information could potentially enable immunotherapies for cancer and chronic infections. However, while inactivation pathways such as TCF-1 or Tox that de-repress the entire T _EFF differentiation process are of interest, this approach can lead to terminal T _EFFs and may have limited therapeutic benefits because such cells cannot maintain a sustained response.

Therefore, there is a need in the art to discover mechanisms that selectively inhibit key aspects of _TEFF differentiation, particularly those involving the control of numerical amplification and/or protective immunity. This invention addresses this need.

Summary of the Invention

In one aspect, this article provides modified immune cells or their precursors containing modifications at an endogenous locus encoding Fli1.

In another aspect, this article provides modified immune cells or their precursors in which the endogenous Fli1 gene or protein is disrupted.

In some embodiments, the modification or disruption is performed by a method selected from: CRISPR system, antibody, siRNA, miRNA, antagonist, drug, small molecule inhibitor, PROTAC target, TALEN, and zinc finger nuclease.

In some embodiments, the CRISPR system includes at least one sgRNA, which includes any one of SEQ ID NO:152-156 or SEQ ID NO:676-713.

In some embodiments, the cells are human cells. In some embodiments, the cells are T cells. In some embodiments, the T cells are resistant to T cell exhaustion.

In another aspect, this document provides pharmaceutical compositions comprising an inhibitor of Fli1. In some embodiments, the inhibitor is selected from CRISPR systems, antibodies, siRNAs, miRNAs, antagonists, pharmaceuticals, small molecule inhibitors, PROTAC targets, TALENs, and zinc finger nucleases. In some embodiments, the CRISPR system comprises at least one sgRNA, said at least one sgRNA comprising any one of SEQ ID NO:152-156 or SEQ ID NO:676-713.

In another aspect, the invention includes a method for treating a disease or disorder in a subject in need. The method includes administering any cells or compositions as conceived herein to the subject.

In some implementations, the disease or obstacle is an infection. In some implementations, the disease is cancer.

In another aspect, this article provides a method for screening T cells. The method includes i) introducing a Cas enzyme (or a nucleic acid encoding Cas) and an sgRNA library into activated T cells, ii) administering the T cells to infected mice, iii) isolating the T cells from the infected mice, and iv) analyzing the T cells.

In some embodiments, the sgRNA library comprises multiple sgRNAs targeting multiple transcription factors. In some embodiments, the multiple transcription factors include any of the transcription factors listed in Table 1. In some embodiments, each sgRNA targets the DNA-binding domain of each transcription factor. In some embodiments, the sgRNA library comprises at least one sequence selected from SEQ ID NO:1-675. In some embodiments, the sgRNA library consists of nucleotide sequences listed in SEQ ID NO:1-675.

In some embodiments, the screening assesses T cell exhaustion. In some embodiments, the method identifies novel transcription factors that govern T _EFF and T _EX cell differentiation.

In some embodiments, the analysis of the cells includes methods selected from sequencing, PCR, MACS, and FACS. In some embodiments, sequencing reveals targets of interest. In some embodiments, drugs are designed to target the targets of interest. In some embodiments, when the drug is administered to the T cells, at least one T cell response is increased.

In some embodiments, 1 x ^10⁵ T cells are administered to the infected mice.

Attached Figure Description

The foregoing and other features and advantages of this disclosure will be more fully understood through the following detailed description of illustrative embodiments in conjunction with the accompanying drawings.

Figures 1A - 1F: Profiling of CD8 T cell transcription programs using the OpTICS system. Figure 1A: Optimized experimental design for in vivo CRISPR screening of T cells (OpTICS). On day 0 (D0), CD8 T cells were isolated from CD45.2 ⁺ C9P14 mice and activated in vitro; CD45.1 ⁺ WT recipient mice were infected with LCMV. At D1 pi, activated C9P14 cells were transduced with an RV-sgRNA library for 6 hours. At D2 pi, Cas9 ⁺ sgRNA ⁺ P14 cells were purified, 5-10% of sorted cells were frozen for D2 baseline (T0 time point), and the remaining cells were adoptively transferred to LCMV-infected recipient mice. At the indicated day, Cas9 ⁺ sgRNA ⁺ P14 cells were isolated from recipient mice by MACS and FACS (T1 time point). Targeted PCR was performed on the sgRNA cassette using sequencing adaptors, and the PCR products were sequenced. The CRISPR score (CS) was calculated as shown in Figure 1B. Figure 1B: CS compares the T1 time point (T0 time point, D2 baseline) of target genes from Cas9 ⁺ sgRNA ⁺ cells originating from the spleen at Arm piD8 or D15, and Cl13 piD9 or D14. The X-axis shows the targeted genes; the y-axis shows the CS for each targeted gene (using 4-5 sgRNAs). Figure 1C: Heatmap of CS for the targeted genes. The heatmap ranks the geometric mean of the CS for each gene. Figure 1D: Distribution of Ctrl, Pdcd1, and Fli1 sgRNAs. The axes represent log2 fold changes (FC). The histogram shows the distribution of all sgRNAs. Black bars represent the targeted sgRNAs, and gray bars represent all other sgRNAs. Figure 1E: Western blot of Fli1 protein from sorted Cas9 ⁺ sgFli1 ⁺ P14 cells and paired Cas9 ⁺ sgFli1- ^P14 cells from the spleen. Two Fli1-sgRNAs (sgFli1_290 and sgFli1_360) were used. Combined (mixed, pooled) mice (3–5 mice for Arm, 10–15 mice for Cl13) were used. The bars represent the normalized band intensity of Fli1. Fli1 was first normalized to GAPDH, and then the ratio between Cas9 ⁺ sgFli1 ⁺ and Cas9 ^{+ sgFli1-} was calculated and displayed. Figure 1F: Normalized Cas9 ⁺ sgRNA (VEX) ⁺ cell numbers from the spleen in the Arm piD8, Arm piD15, Cl13 piD9, and Cl13 piD14 groups, and the 2Fli1-sgRNA (sgFli1_290 and sgFli1_360) groups. Cell numbers normalized to the sgCtrl group based on D2 in vitro transduction efficiency (see Figures 10B and 10D). Compared with control, *P<0.05, **P<0.01, ***P<0.001, ****P<0.001 (univariate Anova analysis). For Figure 1F, data represent 4 independent experiments (mean ± sem), with at least 4 mice/group.

Figures 2A-2E: Fli1 inhibits _TEFF cell proliferation and differentiation during acute infection. Figure 2A: Flow cytometry plots and statistical analysis of KLRG1 ^Hi CD127 ^Lo terminal effector (TE) and KLRG1 ^Lo CD127 ^Hi memory precursor (MP). Frequency (left) and number (right) of spleen-derived cells in the sgCtrl and 2sgFli1 groups at Arm pi D8 and D15. Gated Cas9(GFP) ⁺ sgRNA(VEX) ⁺ P14 cells. Figure 2B: Flow cytometry plots and statistical analysis of frequency (left) and number (right) of CX3CR1 ⁺ CXCR3 ^- _TEFF cells and CX3CR1 ^- CXCR3 ⁺ early T _MEM cells from the spleen in the sgCtrl and 2sgFli1 groups at Arm pi D8 and D15. Gated Cas9 ⁺ sgRNA ⁺ P14 cells. Figures 2C-2E: Experimental design. At D0, CD45.1 ⁺ P14 cells were activated and recipient mice were infected with Arm. At D1 pi, activated P14 cells were transduced with empty-RV or Fli1-overexpression (OE)-RV. At D2 p.i., VEX ⁺ P14 cells from each group were purified and 5 × ^10⁴ cells were adoptively transferred to infected recipient mice. Figure 2C: Flow cytometry plots of CD45.2 ⁺ VEX ⁺ cell frequencies and statistical analysis of CD45.2 ⁺ VEX ⁺ cell numbers under empty-RV and Fli1-OE-RV conditions. Figure 2D: Flow cytometry plots and statistical analysis of KLRG1 ^{HiCD127 Lo} TE and KLRG1 ^{LoCD127 Hi} MP frequencies from the spleen in the empty-RV and Fli1-OE-RV groups at Arm pi D8 and D15. VEX ⁺ P14 cell gating was performed. Figure 2E: Flow cytometry plots and statistical analysis of the frequencies of CX3CR1 ⁺ CXCR3 ^- T _EFF cells and CX3CR1 ^- CXCR3 ⁺ early T _MEM cells from the spleen in the Arm piD8 and D15 spatiotemporal-RV and Fli1-OE-RV groups. VEX ⁺ P14 cells were gated. Compared with controls, *P<0.05, **P<0.01, ***P<0.001, ****P<0.001 (two-tailed Student's t-test and one-way ANOVA analysis). Data represent 2–4 independent experiments (mean ± sem), with at least 3 mice/group.

Figures 3A-3G: Fli1 antagonizes T _EFF -like cell differentiation during chronic infection. Figure 3A: Flow cytometry plots and statistical analysis of the frequencies of Ly108 ^- CD39 ⁺ or TCF-1 ^- Gzmb ⁺ T _EFF- like cells and Ly108 ^{+ CD39-} or TCF-1 ⁺ Gzmb ^- _TEX precursors from the spleen in the sgCtrl and 2sgFli1 groups at D8 and D15 of Cl13. Gated cells were Cas9(GFP) ⁺ sgRNA(VEX) ⁺ P14. Figure 3B: Statistical analysis of the frequencies of CX3CR1 ⁺ and Tim-3 ⁺ cells, as well as KLRG1 and PD-1MFI, from the spleen in the sgCtrl and 2sgFli1 groups at D8 and D15 of Cl13. Gated cells were Cas9 ⁺ sgRNA ⁺ P14. Figure 3C: Heatmap of differentially expressed genes between the sgCtrl and 2sgFli1 groups. Figure 3D: Gene Ontology (GO) enrichment analysis of the sgFli1 group. Figure 3E: GO enrichment analysis of the sgCtrl group. Figure 3F: Gene Set Enrichment Analysis (GSEA) of T _EX precursor features between the sgCtrl and sgFli1 groups. Figure 3G: GSEA of T _EFF -like features between the sgCtrl and sgFli1 groups. Compared with control, *P<0.05, **P<0.01, ***P<0.001, ****P<0.001 (two-tailed Student's t-test and one-way ANOVA analysis). Data represent 4 independent experiments (mean ± sem), with at least 4 mice/group in A and B.

Figures 4A-4K: Fli1 remodels the epigenetic profile of CD8 T cells and suppresses the expression of T _EFF -related genes. Figure 4A: PCA plots of ATAC-seq data from the sgCtrl, sgFli1_290, and sgFli1_360 groups at Cl13 piD9. Figure 4B: Changes in overall open chromatin region (OCR) peaks in the sgFli1 group compared to the sgCtrl group. Figure 4C: Categories of cis-element OCR peaks that changed between the sgCtrl and sgFli1 groups. The left panel represents all changes; the right panel represents changes with increased or decreased accessibility. Figure 4D: Heatmap showing the differentially accessible peaks between the sgCtrl and 2sgFli1 groups (adjusted p-value < 0.05, Log ₁₀ fold change > 0.6). The selected genes assigned to these peaks are indicated. Figure 4E: Venn plot of overlap between genes with differentially accessible (DA) peaks and differentially expressed genes in Figure 3C. Figure 4F: Pearson correlation between peak accessibility of the nearest gene and differential gene expression. Figure 4G: Gain or loss of transcription factor (TF) motifs associated with Fli1 loss. The X-axis represents the logP value of motif enrichment. The Y-axis represents the fold change in motif enrichment. Targeted motifs in OCRs that changed between the sgCtrl and sgFli1 groups were compared to the genome-wide background to calculate p-values and fold changes. Figure 4H: IgG or Fli1 binding signals from CUT&RUN on P14 cells at Cl13 piD8, and OCR signals detected by ATAC-seq at the CD28, Cx3cr1, and Havcr2 loci in the sgCtrl-sgRNA, sgFli1_290, and sgFli1_360 groups. Figure 4I: Histograms and statistical analysis of CD28 staining in the sgCtrl, sgFli1_290, and sgFli1_360 groups at Cl13 piD8. Gray shows CD28 staining in CD44 ^- naive T cells. Figure 4J: Heatmap showing the overlap of the differentially accessible (DA) peaks between the sgCtrl and 2sgFli1 groups with the Fli1 CUT&RUN binding peaks. The selected genes assigned to these peaks are indicated. Figure 4K: Showing the top 4 enriched TF motifs in the Fli1 CUT&RUN peaks. *P < 0.05, **P < 0.01 compared to control (univariate Anova analysis). Data represent two independent experiments (mean ± sem), and Figure 4I requires at least 5 mice per group.

Figures 5A-5G: Overexpression of Runx1 or Runx3 in CD8 T cells under Fli1-deficient conditions. Figure 5A: Experimental design. At D0, CD45.2 ⁺ C9P14 donor mice were isolated and activated; CD45.1 ⁺ WT recipient mice were infected with Cl13. At piD1, activated C9P14 cells were transduced with sgRNA-RV or OE-RV and 1× ^10⁵ transduced cells were adoptively transferred to infected recipient mice. Figures 5B-5D: Flow cytometry plots (Figure 5B) and statistical analysis (Figures 5C-5D) of VEX ⁺ mCherry ⁺ C9P14 cells and Ly108CD39 ⁺ /Ly108 ⁺ CD39- C9P14 cells from the spleen at Cl13 piD8 for sgCtrl-VEX+ empty-mCherry, sgCtrl-VEX+Runx1-mCherry, sgFli1_290-VEX ⁺ empty-mCherry, and sgFli1_290-VEX+Runx1-mCherry. Gating was performed on Cas9(GFP) ⁺ CD45.2 ⁺ P14 cells. Figures 5E-5G: Flow cytometry plots (Figure 5E) and statistical analyses (Figures 5F-5G) of VEX ⁺ mCherry+ C9P14 cells and Ly108 ^- CD39 ⁺ /Ly108 ⁺ CD39- C9P14 cells from the spleen at Cl13 piD8, including sgCtrl-mCherry+empty-VEX, sgCtrl-mCherry ⁺ Runx3-VEX, sgFli1_290 ^- mCherry+empty-VEX, and sgFli1_290-mCherry+Runx3-VEX. Cas9 ⁺ CD45.2 ⁺ P14 cell gating was performed. Compared with controls, *P<0.05, **P<0.01, ***P<0.001, ****P<0.001 (univariate Anova analysis). Data represent two independent experiments (mean ± sem), with at least 5 mice per group.

Figures 6A-6F: Fli1 deficiency in CD8 T cells enhances protective immunity against infection. Figure 6A: Experimental design. On day 0, CD8 T cells were isolated and activated from CD45.2 ⁺ C9P14 donor mice; CD45.1 ⁺ WT recipient mice were infected with LCMV Cl13, influenza virus PR8-GP33, or Listeria monocytogenes-GP33 (LM-GP33). On day 1 pi, activated C9P14 cells were transduced with sgCtrl or sgFli1 RV. On day 2 pi, Cas9 ⁺ sgRNA (VEX) ⁺ P14 cells from the sgCtrl or sgFli1 groups were purified by flow cytometry and adoptively transferred to infected recipient mice. For Cl13, 1.5 × ^10⁵ VEX ⁺ C9P14 cells were transferred per mouse; for PR8-GP33 and LM-GP33, 1.0 × ^10⁵ VEX ⁺ C9P14 cells were transferred per mouse. Figure 6B: LCMV viral load was measured by plaque assay in the liver, kidney, and serum of indicated mice at Cl13 piD15. Data were combined from two independent experiments. Figure 6C: Body weight curves of PR8-GP33-infected mice from the NT, sgCtrl ⁺ cell transfer, or sgFli1 ⁺ cell transfer groups. The dashed line represents the time of C9P14 adoptive transfer. Figure 6D: PR8-GP33 viral RNA load in the lungs of NT, sgCtrl ⁺ , or sgFli1 ⁺ C9P14 recipient mice. The dashed line indicates the detection limit. Lung samples from juvenile mice and spleen samples from PR8-GP33-infected mice were used as negative controls. Figure 6E: Adjusted survival curves of LM-GP33-infected mice to NT, sgCtrl ⁺ , or sgFli1 ⁺ C9P14 recipient mice. The dashed line represents the time of C9P14 adoptive transfer. Figure 6F: LM-GP33 bacterial load in the spleen and liver of surviving NT, sgCtrl ⁺ , or sgFli1 ⁺ C9P14 recipient mice at D7 pi. Compared with control, *p<0.05, **p<0.01, ***p<0.001, ****p<0.001 (6B-6D, 6F are univariate Anova analyses, 6E is a Mantel-Cox test). Data represent 2 independent experiments (mean ± sem), with at least 3 mice/group.

Figures 7A-7G: Loss of Fli1 in CD8 T cells enhances anti-tumor immunity. Figure 7A: Experimental design. On day 0, CD45.2 ⁺ Rag2-/- mice were inoculated with 1.0 × ^10⁵ B16-Dbgp33 cells. On day 3 (pt) post-tumor inoculation, CD8 T cells were isolated from CD45.1 ⁺ C9P14 mice and activated. On day 4 (pt), activated C9P14 cells were transduced with sgCtrl or sgFli1 RV. On day 5 (pt), sgRNA(VEX) ⁺ Cas9(GFP) ⁺ P14 cells were sorted from the sgCtrl or sgFli1 group, and 1 × ^10⁶ purified VEX ⁺ C9P14 cells were adoptively transferred to tumor-bearing mice. Figure 7B: Tumor volume curves of mice receiving NT, sgCtrl ⁺ , or sgFli1 ⁺ C9P14 cells. Figure 7C: Tumor weight of mice receiving NT, sgCtrl ⁺ , or sgFli1 ⁺ C9P14 cells at D23 p.t. Figures 7D-7E: Flow cytometry plots (Figure 7D) and statistical analysis (Figure 7E) of CD45.1 ⁺ sgRNA(VEX) ⁺ Cas9 ⁺ P14 cells and Ly108 ^- CD39 ⁺ /Ly108 ⁺ CD39 ^- C9P14 cells from the tumor in the sgCtrl or sgFli1 group at D23 pt. Figures 7F-7G: Flow cytometry plots (Figure 7F) and statistical analysis (Figure 7G) of CD45.1 ⁺ sgRNA ⁺ Cas9 ⁺ P14 cells and Ly108 ^- CD39 ⁺ /Ly108 ⁺ CD39 ^- C9P14 cells from the spleen in the sgCtrl or sgFli1 group at D23 pt. Compared with the control, *p<0.05, **p<0.01, ***p<0.001, ****p<0.001 (two-tailed Student's t-test and one-way ANOVA analysis). Data represent two independent experiments (mean ± sem), with at least 5 mice per group.

Figures 8A-8K: Efficient in vivo gene editing and screening using retrovirally transduced sgRNA in Cas9 ⁺ antigen-specific CD8 T cells. Figure 8A: Optimization of the sgRNA backbone compared to the original sgRNA. Figure 8B: Experimental design for the in vivo gene editing assay. On day 0 (D0), CD8 T cells were isolated from CD45.1 ⁺ LSL-Cas9 ⁺ CD4 ^CRE+ P14 (C9P14) donor mice and activated with anti-CD3, anti-CD28, and IL-2; CD45.2 ⁺ recipient mice were infected with Cl13. At D1 pi, activated C9P14 cells were transduced with Ctrl-sgRNA (sgCtrl) or Pdcd1-sgRNA (sgPdcd1). Six hours after transduction, 5 × ^10⁴ activated donor cells were adoptively transferred to infected recipient mice. C9P14 cells were then isolated from different organs of the recipient mice at indicated times for analysis. Figure 8C: D2 in vitro transduction efficiency of C9P14 cells activated with sgRNA vector (mCherry). Gating was based on the non-transduction control setting. Figure 8D: Flow cytometry plot of Cas9(GFP) ⁺ sgRNA(mCherry) ⁺ population in spleen of sgCtrl and sgPdcd1 groups at D9 pi. Figure 8E: Histogram of PD-1 expression and statistical analysis of PD-1 ⁺ population from Cas9 ⁺ sgRNA ⁺ P14 cells in blood (D7 pi), spleen (D9 pi), or liver (D9p.i.). Figure 8F: Sanger sequencing results of Pdcd1 locus from FACS-purified Cas9 ⁺ sgRNA ⁺ P14 cells from sgCtrl group (5 mice combined) or sgPdcd1 group (2 mice combined). Figure 8G: Histograms of KLRG1 or CXCR3 expression in Cas9 ⁺ sgRNA ⁺ P14 cells from the spleen (Armp.i.D8) between the targeted sgRNA and the sgCtrl group, and statistical analysis of the KLRG1 ⁺ or CXCR3 ⁺ populations. Figure 8H: Log ₂ fold change (L2FC) from D8 pi (T1) to D2 baseline (T0) for different sgRNAs from the spleen or liver under three conditions during Arm infection. The x-axis represents different sgRNAs, and the y-axis represents the L2FC from D8 pi (T1) to D2 baseline (T0). Condition 1: Unoptimized sorting, average input coverage of approximately 100 cells/sgRNA, Cas9 ^+/+ P14 donor. Condition 2: Optimized sorting (in Materials and Methods), average input coverage of approximately 400 cells/sgRNA, Cas9 ^+/+ P14 donor. Condition 3: Optimized sorting, average input coverage of approximately 400 cells/sgRNA, Cas9 ^+/- P14 donors. Example target genes are highlighted with an indicator color. Figure 8I: Rank correlation of targeted genes between two independent screenings in the Cas9 ^+/+ or Cas9 ^+/- donor P14 groups. The mean sgRNA L2FC of each targeted gene was calculated and ranked according to independent screenings. Pearson correlation of rankings was calculated. Figure 8J: Fold change enrichment of sgPdcd1 in spleen with Cl13p.i.D14. Data from screenings performed in Figures 1A-1C. Figure 8K: Pearson correlation of different samples from screenings performed in Figures 1A-1C. Presented by sample collection time (pi days), LCMV infection, and sorted Cas9 ⁺ sgRNA ⁺ cells in the organ. Compared with the control, *P<0.05, **P<0.01, ***P<0.001, ****P<0.001 (two-tailed Student's t-test). Data represent two independent experiments (mean ± sem), with at least 3 mice per group.

Figures 9A-9E: Fli1 gene deletion leads to greater T cell expansion. Figure 9A: TIDE assay results showing the efficiency of Fli1 locus in disrupting the genome of Cas9 ⁺ Fli1-sgRNA (sgFli1) ⁺ cells. Genome disruption was detected by Sanger sequencing. Figure 9B: Flow cytometry plots of Cas9(GFP) ⁺ sgRNA(VEX) ⁺ populations from spleen cells from the sgCtrl group or the 2Fli1-sgRNA (sgFli1_290 and sgFli1_360) group (gated to donor P14 cells) at D2, Arm pi, D8, and D15 after in vitro transduction. At D1 pi, 5 × ^10⁴ activated donor cells were adoptively transferred to homologous infected recipient mice. Figure 9C: Normalized Cas9 ⁺ sgRNA ⁺ cell numbers from blood, liver, and lung cells from the sgCtrl and two sgFli1 groups at Arm pi, D8, and D15. Cell numbers normalized to the sgCtrl group based on D2 in vitro transduction efficiency. Figure 9D: Flow cytometry plots of Cas9 ⁺ sgRNA ⁺ P14 cells from the sgCtrl group and the two sgFli1 groups at D2, Cl13 (spleen) pi D9, and D15 after in vitro transduction (gated to donor P14 cells). At D1 pi, 5 × ^10⁴ activated donor P14 cells were adoptively transferred to infected recipient mice. Figure 9E: Normalized Cas9 ⁺ sgRNA ⁺ cell numbers from blood, liver, and lungs of the sgCtrl group and the two sgFli1 groups at Cl13 pi D9 and D15. Cell numbers normalized to the sgCtrl group based on D2 in vitro transduction efficiency. Compared with control, *P<0.05, **P<0.01, ***P<0.001, ****P<0.001 (univariate Anova analysis). Data represent 2–4 independent experiments (mean ± sem), with at least 3 mice per group.

Figures 10A-10J: Fli1 inhibits terminal T _EFF differentiation without affecting T _MEM cell formation. Figure 10A: Flow cytometry plots and statistical analysis of KLRG1 ^Lo CD127 ^Lo cells. Frequency (left) and number (right) of cells originating from the spleen in the sgCtrl and 2sgFli1 groups at Arm pi D8 and D15. Gating of Cas9(GFP) ⁺ sgRNA(VEX) ⁺ P14 cells. Figure 10B: Flow cytometry plots and statistical analysis of GzmB ⁺ and TCF-1 ⁺ C9P14 cells. Frequency of cells originating from the spleen in the sgCtrl and sgFli1 (2sgRNA combination) groups at Arm pi D8. Gating of Cas9(GFP) ⁺ sgRNA(VEX) ⁺ P14 cells. Figure 10C: Histograms and statistical analysis of T-bet and Eomes expression in spleen-derived C9P14 cells from the sgCtrl and sgFli1 (2sgRNA combination) groups at Arm piD8. Gating of Cas9(GFP) ⁺ sgRNA(VEX) ⁺ P14 cells. Naïve T cells ( ^CD44- ) are stained in gray. Figure 10D: Flow cytometry plots and statistical analysis of C9P14 cells producing cytokines 5 hours after stimulation. Frequency (left) and number (right) of IFNγ ⁺ , IFNγ ⁺ TNF ⁺ , and MIP1α ⁺ CD107a ⁺ cells from spleen-derived cells from the unstimulated P14 cells, sgCtrl, and sgFli1 (2sgRNA combination) groups at Arm piD8. Gating of Cas9(GFP) ⁺ sgRNA(VEX) ⁺ P14 cells. Figure 10E: Statistical analysis of the total terminal effector (TE) or memory precursor (MP) C9P14 cell counts in the blood of the sgCtrl and sgFli1 (2sgRNA combination) groups at Arm pi D8, D20, and D29. Data are normalized to sgCtrl ⁺ D2 pi transduction efficiency. At transfer day (D1 pi), the normalized sgRNA ⁺ C9P14 cell count was approximately 75 cells/1 x ^10⁶ PBMCs. Figure 10F: Statistical analysis of the frequency of TE or MP C9P14 and the total number of TE or MP C9P14 cells in the spleen of the sgCtrl and sgFli1 (2sgRNA combination) groups at Arm pi D29. Data are normalized to sgCtrl ⁺ D2 pi transduction efficiency. Figure 10G: Histograms of Bcl-2, Bcl-XL, and Bim expression in total C9P14 cells from the spleen in the sgCtrl and sgFli1 (2sgRNA combination) groups at Arm piD15. Gating of Cas9(GFP) ⁺ sgRNA(VEX) ⁺ P14 cells. Naïve T cells ( ^CD44- ) are shown in gray. Figures 10H-10J: Statistical analysis of Bcl-2, Bcl-XL, and Bim expression in total (Figure 10H), TE (Figure 10I), and MP (Figure 10J) C9P14 cells from the spleen in the Arm piD15 group. Gating of Cas9(GFP) ⁺ sgRNA(VEX) ⁺ P14 cells. Compared with the control, *P<0.05, **P<0.01, ***P<0.001, ****P<0.001 (univariate Anova analysis). Data represent two independent experiments (mean ± sem), with at least 4 mice per group.

Figures 11A-11H: Fli1 inhibits T _EFF- like differentiation during chronic infection. Figures 11A-11B: Statistical analysis of the number of Ly108 ^- CD39 ⁺ or TCF-1 ^- GzmB ⁺ T _EFF- like cells and Ly108 ^{+ CD39-} or TCF-1 ⁺ GzmB T _EX precursor cells from the spleen in the sgCtrl group and the two sgFli1 groups at Cl13 piD8 (Figure 11A) and D15 (Figure 11B). Gating of Cas9(GFP) ⁺ sgRNA(VEX) ⁺ P14 cells. Figure 11C: Histograms and statistical analysis of Eomes, T-bet, and Tox expression in C9P14 cells from the spleen in the sgCtrl group and sgFli1 group at Cl13 piD8 and D15. Gating of Cas9(GFP) ⁺ sgRNA(VEX) ⁺ P14 cells. Naïve T cells ( ^CD44- ) are stained and shown in gray. Figure 11D: Flow cytometry plots and statistical analysis of C9P14 cells producing cytokines 5 hours after stimulation. Frequency (left) and number (right) of IFNγ ⁺ , IFNγ ⁺ TNF ⁺ , and MIP1α ⁺ CD107a ⁺ cells from the spleen in the unstimulated P14 cells, sgCtrl, and sgFli1 (2sgRNA combination) groups at Cl13 piD8. Gating to Cas9(GFP) ⁺ sgRNA(VEX) ⁺ P14 cells. Figure 11E: Flow cytometry plots and statistical analysis of the number of CD45.2 ⁺ VEX ⁺ P14 cells in the space-RV group and the Fli1-OE-RV group at Cl13 piD8 and D16. At D0, CD45.2 ⁺ P14 cells were activated and CD45.1 ⁺ recipient mice were infected with Cl13. At D1p.i., activated P14 cells were transduced with empty-RV or Fli1-OE-RV for 6 hours. At D2p., VEX ⁺ P14 cells were sorted from each RV transduction group and ¹ x 10⁵ cells were adoptively transferred to infected recipients. Figures 11F-11G: Flow cytometry plots and statistical analysis of Ly108 ^- CD39 ⁺ or TCF-1 ^- Gzmb ⁺ _TEFF -like cells and Ly108 ^{+ CD39-} or TCF-1 ⁺ Gzmb ^- TE _EX precursor frequencies in the empty-RV and Fli1-OE-RV groups at D8 and D16 at C13p. Gated VEX ⁺ P14 cells. Figure 11H: Statistical analysis of CX3CR1 ⁺ and Tim-3 ⁺ frequencies in the empty-RV and Fli1-OE-RV groups at D8 and D16 at C13p. Gated VEX ⁺ P14 cells. Compared with the control, *P<0.05, **P<0.01, ***P<0.001 (univariate Anova analysis). For Figures 11A-11D, data represent 3 independent experiments (mean ± sem), with at least 4 mice/group.

Figures 12A-12I: Transcriptional and epigenetic profiling resolved the issue of Fli1 suppressing T _EFF -like differentiation by coordinating with Runx1 and antagonizing Runx3 function. Figure 12A: PCA plot of RNA-seq data from the sgCtrl, sgFli1_290, and sgFli1_360 groups at Cl13 piD8. Figure 12B: Overlap of all CUT&RUN Fli1 binding peaks with peaks detected by ATAC-seq in the sgCtrl and sgFli1 groups. Figure 12C: Histogram of colocalization of all CUT&RUN peaks with ATAC-seq peaks. Peaks colocalized with ATAC-seq peaks are gray; non-colocalized peaks are black. Figure 12D: CUT&RUN IgG or Fli1 binding signals in P14 cells at D9 pi, and chromatin open region signals detected by ATAC-seq in the sgCtrl, sgFli1_290, and sgFli1_360 groups at Tcf7 and Id3 loci. Figure 12E: Flow cytometry plots and statistical analysis of CD45.1 ⁺ mCherry ⁺ and Ly108 ^- CD39 ⁺ /Ly108 ^{+ CD39-} P14 cell numbers in vitro at D2 and D7 pi using empty-RV or Runx1-OE-RV. At D0, CD45.1 ⁺ P14 cells were activated and CD45.2 ⁺ recipient mice were infected with Cl13; at D1 pi, activated P14 cells were transduced with empty-RV or Runx1-OE-RV for 6 hours, and ¹ x 10⁵ transduced P14 cells were adoptively transferred to infected recipient mice. Flow cytometry images of CD45.1 ⁺ P14 cells gated. Figure 12F: D2 in vitro transduction efficiency of sgCtrl-VEX+Empty-mCherry, sgCtrl-VEX+Runx1-mCherry, sgFli1_290-VEX+Empty-mCherry, and sgFli1_290-VEX+Runx1-mCherry C9P14 cells. Figure 12G: Statistical analysis of the number of VEX+mCherry+ C9P14 cells and Ly108-CD39+/Ly108 ^{+ CD39-} cells from the spleen in the sgCtrl-VEX+Empty-mCherry, sgCtrl-VEX+Runx1-mCherry, sgFli1_290-VEX ⁺ Empty ^- mCherry, and sgFli1_290-VEX ⁺ Runx1 ^- mCherry groups at Cl13 piD7. Gating of Cas9(GFP) ⁺ CD45.2 ⁺ P14 cells. Figure 12H: D2 in vitro transduction efficiency of sgCtrl-mCherry+empty-VEX, sgCtrl-mCherry+Runx3-VEX, sgFli1_290-mCherry+empty-VEX, and sgFli1_290-mCherry+Runx3-VEX C9P14 cells. Figure 12I: Statistical analysis of the number of VEX+mCherry+C9P14 cells and Ly108-CD39 ^{+ /} Ly108 ⁺ CD39- cells from the spleen in sgCtrl-mCherry+empty-VEX, sgCtrl-mCherry+Runx3-VEX, sgFli1_290-mCherry ⁺ empty-VEX, and sgFli1_290-mCherry ⁺ Runx3 ^- VEX cells at Cl13 piD8. Gating of Cas9 ⁺ CD45.2 ⁺ P14 cells. Compared with control, *P<0.05, **P<0.01 (two-tailed Student's t-test). Data represent two independent experiments (mean ± sem), with at least 5 mice per group.

Figures 13A-13E: Fli1 deficiency leads to CD8 T cell expansion during influenza virus or Listeria monocytogenes infection. Figure 13A: Adjusted survival curves of LCMV Cl13-infected mice against sgCtrl ⁺ , sgFli1_290 ⁺ , and sgFli1_360 ⁺ C9P14 receptor mice (1.5 × ^10⁵ cells/mouse, N = 5/group). Note that JAX receptor mice were used here instead of NCI receptor mice to differentiate the pathogenesis. Dashed lines represent the time of C9P14 adoptive transfer. Figure 13B: Flow cytometry plot of sgRNA(VEX) ⁺ C9P14 cells in the lungs of influenza virus (PR8-GP33)-infected mice at D8 pi, compared with the non-transfer (NT), sgCtrl, and sgFli1 groups. “Recovery” was defined as complete recovery of body weight at D8 pi. Figure 13C: Correlation between sgRNA ⁺ C9P14 cell number and body weight ratio (D8 pi/D2 pi) during PR8-GP3 infection. Further comparisons of sgRNA ⁺ C9P14 cell number were made in the "no recovery of body weight" group (body weight ratio between 0.7 and 1.0). Figure 13D: Flow cytometry plots and statistical analysis of sgRNA+ C9P14 cells in the spleens of PR8-GP33-infected recipient mice in the non-metastatic (NT), sgCtrl, and sgFli1 groups at D8 pi. Figure 13E: Flow cytometry plots and statistical analysis of sgRNA ⁺ C9P14 cells in the spleens of Listeria monocytogenes-infected recipient mice in the non-metastatic (NT), sgCtrl ^, and sgFli1 groups at D7 pi. *P<0.05, **P<0.01 compared to controls (two-tailed Student's t-test and one-way ANOVA analysis). Data represent two independent experiments (mean ± sem), with at least 6 mice/group.

Figures 14A-14G: Fli1 deletion in CD8 T cells produces better tumor protection in immunocompetent mice. Figure 14A: Experimental design. On D0, CD45.2 ⁺ Cas9 ⁺ P14 mice were inoculated with 2× ^10⁵ B16-Dbgp33 cells. On D3 (pt) post-tumor inoculation, CD8 T cells were isolated from CD45.2 ⁺ C9P14 donor mice and activated. The next day, activated C9P14 cells were transduced with sgCtrl or sgFli1 RV for 6 hours. On D5 (pt), sgRNA(VEX) ⁺ P14 cells were sorted from the sgCtrl or sgFli1 group, and 3× ^10⁶ purified VEX ⁺ C9P14 cells were adoptively transferred to tumor-bearing mice. Figure 14B: Tumor volume curves of tumor-bearing mice from the NT, sgCtrl ⁺ , and sgFli1 ⁺ C9P14 cell transfer groups. Figure 14C: Tumor weights of NT, sgCtrl ⁺ , and sgFli1 ⁺ C9P14 metastatic mice at D24 p.t. Figures 14D-14E: Flow cytometry plots (Figure 14D) and statistical analysis (Figure 14E) of sgRNA(VEX) ⁺ C9P14 cells and Ly108-CD39 ⁺ /Ly108 ⁺ CD39 populations from tumors in the sgCtrl and sgFli1 groups at D24 pt. Figures 14F-14G: Statistical analysis of sgRNA ⁺ C9P14 cells and Ly108 ^- CD39 ⁺ or Ly108 ^{+ CD39-} populations from draining lymph nodes (dLN, Figure 14F) and spleen (Figure 14G) in the sgCtrl and sgFli1 groups at D24 pt. Compared with the control, *p<0.05, **p<0.01, ***p<0.001, ****p<0.001 (two-tailed Student's t-test and one-way ANOVA analysis). Data represent 3 independent experiments (mean ± sem), with at least 6 mice per group.

Detailed Implementation

Enhancing the effector activity of antigen-specific T cells is a primary goal of cancer immunotherapy. Although several effector T cell ( _TEF )-driven transcription factors (TFs) have been identified, the transcriptional coordination role of _TEF biology remains poorly understood. In this paper, an in vivo T cell CRISPR screening platform was developed. A novel mechanism for suppressing _TEF biology via the ETS family TF, Fli1, was identified. Deletion of the Fli1 gene enhances _TEF responses without impairing memory or exhaustion precursors. Fli1 suppresses _TEF lineage differentiation by binding to cis-regulatory elements of effector-related genes. Loss of Fli1 increases chromatin accessibility at the ETS:RUNX motif, resulting in more effective Runx3-driven _TEF biology. CD8 T cells lacking Fli1 provide significantly better protection against a variety of infections and tumors. These data suggest that Fli1 protects the developing CD8 T cell transcriptional landscape from excessive ETS:RUNX-driven _TEF cell differentiation. Furthermore, Fli1 gene deletion improves _TEF differentiation and protective immunity against infection and cancer.

It should be understood that the methods described in this disclosure are not limited to the specific methods and experimental conditions disclosed herein, as such methods and conditions can vary. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

Furthermore, unless otherwise stated, the experiments described herein utilize conventional molecular and cell biology and immunology techniques within the scope of the art. These techniques are well known to those skilled in the art and are well explained in the literature. See, for example, Ausubel, et al., ed., Current Protocols in Molecular Biology, John Wiley & Sons, Inc., NY, N.Y. (1987–2008) (including all supplements), MR Green and J. Sambrook, Molecular Cloning: A Laboratory Manual (4th edition), and Harlow et al., Antibodies: A Laboratory Manual, Chapter 14, Cold Spring Harbor Laboratory, Cold Spring Harbor (2nd edition, 2013).

A. Definition

Unless otherwise defined, the technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. In cases of any potential ambiguity, the definitions provided herein take precedence over any dictionary or external definition. Unless the context requires otherwise, singular terms shall include plural terms, and plural terms shall include singular terms. Unless otherwise stated, the use of “or” means “and/or”. The use of the term “including” and other forms such as “includes” and “included” is not restrictive.

In general, the nomenclature used in cell and tissue culture, molecular biology, immunology, microbiology, genetics, and protein and nucleic acid chemistry, as well as hybridization, as described herein, is well known and commonly used in the art. Unless otherwise stated, the methods and techniques provided herein are generally performed according to conventional methods well known in the art and described in the various general and more specific references cited and discussed throughout this specification. Enzymatic reactions and purification techniques are performed according to the manufacturer's instructions, as is commonly done in the art or as described herein. The nomenclature used in analytical chemistry, synthetic organic chemistry, and pharmaceutical and medicinal chemistry, as well as the laboratory procedures and techniques described herein, are those well known and commonly used in the art. Standard techniques are used for chemical synthesis, chemical analysis, drug preparation, formulation and delivery, and patient treatment.

To facilitate understanding of this disclosure, the selected terms are defined as follows.

The articles “a” and “a kind” are used in this text to refer to one or more (i.e., at least one) of the grammatical objects of the article. For example, “an element” means one element or more.

As used herein, “about” when referring to a measurable value such as quantity, duration of time, etc., means including a variation of ±20% or ±10% from the specified value, more preferably ±5%, even more preferably ±1%, and even more preferably ±0.1%, as long as such variation is suitable for performing the disclosed method.

As used in this article, “activation” refers to the state of T cells that have been adequately stimulated to induce detectable cell proliferation. Activation can also be associated with induced cytokine production and detectable effector function. The term “activated T cell” refers to T cells undergoing cell division, etc.

As used in this article, “alleviating” a disease means reducing the severity of one or more symptoms of the disease.

As used herein, the term "antigen" is defined as a molecule that elicits an immune response. This immune response may involve antibody production, or activation of specific immune-active cells, or both. Those skilled in the art will understand that any macromolecule—indeed, all proteins or peptides—can act as an antigen.

Furthermore, antigens can be derived from recombinant DNA or genomic DNA. Those skilled in the art will understand that any DNA—containing a nucleotide sequence or partial nucleotide sequence encoding a protein that elicits an immune response—is encoded as such by the term "antigen" as used herein. Furthermore, those skilled in the art will understand that antigens do not necessarily consist of the full-length nucleotide sequence of a gene alone. It is readily apparent that this disclosure includes, but is not limited to, the use of partial nucleotide sequences of more than one gene, and that these nucleotide sequences are arranged in various combinations to elicit a desired immune response. Furthermore, those skilled in the art will understand that antigens do not necessarily have to be encoded by a "gene" at all. It is readily apparent that antigens can be synthesized or derived from biological samples. Such biological samples may include, but are not limited to, tissue samples, tumor samples, cells, or biological fluids.

As used in this article, the term "self" means any substance that originates from the same individual and is subsequently reintroduced into that individual.

"Costimulatory molecules" refer to associated binding partners on T cells that specifically bind to costimulatory ligands, thereby mediating costimulatory responses on T cells—such as, but not limited to, proliferation. Costimulatory molecules include, but are not limited to, MHC class I molecules, BTLA, and Toll ligand receptors.

As used in this article, “co-stimulatory signals” refer to signals that bind to primary signals, such as TCR/CD3 linkages, leading to T cell proliferation and/or upregulation or downregulation of key molecules.

"Disease" is a state of health in an animal in which the animal is unable to maintain homeostasis, and in which the animal's health continues to deteriorate if the disease is not treated. In contrast, "disorder" in an animal is a state of health in which the animal is able to maintain homeostasis, but in which the animal's health is less favorable than it would be without the disorder. Without treatment, disorder does not necessarily lead to a further decline in the animal's health.

As used in this article, “downregulation” refers to a reduction or elimination of gene expression in one or more genes.

The terms "effective amount" or "therapeutic effective amount" are used interchangeably herein and refer to the amount of a compound, formulation, material, or composition as described herein that is effective in achieving a specific biological outcome or providing a therapeutic or preventative benefit. Such an outcome may include, but is not limited to, an amount that, when administered to a mammal, causes a detectable level of immunosuppression or tolerance compared to an immune response detected in the absence of the compositions disclosed herein. Immune responses can be readily assessed using a wide range of methods recognized in the art. Those skilled in the art will understand that the amount of the compositions administered herein varies and can be readily determined based on a number of factors, such as the disease or condition being treated, the age and health status and physical condition of the mammal being treated, the severity of the disease, the specific compound being administered, etc.

"Encoding" refers to the inherent property of a specific sequence of nucleotides in a polynucleotide, such as a gene, cDNA, or mRNA, to serve as a template for the synthesis of other polymers and macromolecules in a biological process. These polymers and macromolecules possess any of the defined sequences of nucleotides (i.e., rRNA, tRNA, and mRNA) or amino acids, and the biological properties derived from them. Therefore, if the transcription and translation of mRNA corresponding to a gene produces a protein in a cell or other biological system, then the gene encodes that protein. Both the nucleotide sequence equivalent to the mRNA sequence and typically provided in the sequence listing (coding strand) and the non-coding strand used as a template for transcribing a gene or cDNA can be referred to as the protein or other product encoding that gene or cDNA.

As used in this article, “endogenous” means any substance that originates from or is produced within an organism, cell, tissue, or system.

As used herein, the term "epitope" is defined as a small chemical molecule on an antigen that can elicit an immune response, including a B-cell or T-cell response. An antigen may have one or more epitopes. Most antigens have multiple epitopes; that is, they are multivalent. Generally, an epitope is about 10 amino acids and/or sugars in size. Preferably, an epitope is about 4-18 amino acids, more preferably about 5-16 amino acids, even more preferably 6-14 amino acids, more preferably about 7-12 amino acids, and most preferably about 8-10 amino acids. Those skilled in the art will understand that, generally speaking, the overall three-dimensional structure of the molecule, rather than the specific linear sequence of the molecule, is the primary criterion for antigen specificity, and thus for distinguishing one epitope from another. Based on this disclosure, peptides used herein may be epitopes.

As used herein, the term “exogenous” means any substance introduced from or produced outside of an organism, cell, tissue, or system.

As used herein, the term "amplification" refers to an increase in quantity, such as an increase in the number of T cells. In one embodiment, the number of T cells expanded in vitro is increased relative to the number originally present in the culture. In another embodiment, the number of T cells expanded in vitro is increased relative to other cell types in the culture. As used herein, the term "in vitro" means cells that have been removed from a living organism (e.g., a human) and multiplied outside that organism (e.g., in a culture dish, test tube, or bioreactor).

As used herein, the term “expression” is defined as the transcription and/or translation of a sequence driven by a promoter of a specific nucleotide sequence.

"Expression vector" refers to a vector containing a recombinant polynucleotide that includes an expression control sequence operatively linked to a nucleotide sequence to be expressed. The expression vector contains sufficient cis-acting elements for expression; other elements for expression may be provided by a host cell or in an in vitro expression system. Expression vectors include all those known in the art, such as viscera, plasmids (e.g., naked or contained in liposomes), and viruses (e.g., Sendai virus, lentivirus, retrovirus, adenovirus, and adeno-associated virus) containing the recombinant polynucleotide.

As used herein, “identity” refers to the identity of subunit sequences between two polymer molecules, particularly between two amino acid molecules, such as two polypeptide molecules. Two amino acid sequences are identical when they have the same residues at the same positions; for example, if each of two polypeptide molecules has a position occupied by arginine, then they are identical at that position. In alignment, the identity or degree of identical residues at the same positions of two amino acid sequences is often expressed as a percentage. Identity between two amino acid sequences is a direct function of the number of matched or identical positions; for example, if half the positions in two sequences (e.g., five positions in a ten-amino acid-long polymer) are identical, then the two sequences are 50% identical; if 90% of the positions (e.g., nine out of ten) are matched or identical, then the two amino acid sequences are 90% identical.

As used in this article, the term "immune response" is defined as a cellular response against an antigen that occurs when lymphocytes recognize an antigen molecule as a foreign substance and induce the formation of antibodies and/or activation of lymphocytes to remove the antigen.

The term “immunosuppression” is used in this article to refer to a reduction in the overall immune response.

"Insertion/deletion," often abbreviated as "indel," is a type of gene polymorphism in which a specific nucleotide sequence is present (inserted) or absent (deleted) in the genome.

"Separated" means altered or removed from its native state. For example, nucleic acids or peptides naturally present in living animals are not "separated," but the same nucleic acid or peptide that is partially or completely separated from its native coexisting material is "separated." Separated nucleic acids or proteins can exist in a substantially purified form or in non-native environments, such as, for example, host cells.

As used in this article, “knockdown” refers to a reduction in the expression of one or more genes.

As used herein, the term "knockin" refers to a foreign nucleic acid sequence that has been inserted into a target sequence (e.g., an endogenous locus). In some embodiments, when the target sequence is a gene, the knock-in results in an operatively connected foreign nucleic acid sequence to any upstream and/or downstream regulatory element controlling the expression of the target gene. In some embodiments, the knock-in results in an operatively connected foreign nucleic acid sequence to any upstream and/or downstream regulatory element controlling the expression of the target gene.

As used in this article, “knockout” refers to the removal of gene expression from one or more genes.

As used in this article, "lentivirus" refers to a genus within the family Retroviridae. Lentivirals are unique among retroviruses in their ability to infect non-dividing cells; they can transfer significant amounts of genetic information into the host cell's DNA, making them one of the most efficient gene delivery vectors. HIV, SIV, and FIV are all examples of lentiviruses. Lentiviral-derived vectors provide a means to achieve significant levels of gene transfer in vivo.

As used herein, the term "modified" refers to an altered state or structure of the molecules or cells disclosed herein. Molecules can be modified in a variety of ways, including chemically, structurally, and functionally. Cells can be modified by introducing nucleic acids.

As used herein, the term "modulation" means mediating a detectable increase or decrease in the level of response in a subject compared to the level of response in a subject where no treatment or compound is present, and/or compared to the level of response in a otherwise identical but untreated subject. This term encompasses disrupting and/or influencing natural signals or responses, thereby mediating a beneficial therapeutic response in a subject (preferably, a human).

In the context of this disclosure, the following abbreviations for common nucleic acid bases are used. “A” refers to adenosine, “C” refers to cytosine, “G” refers to guanosine, “T” refers to thymidine, and “U” refers to uridine.

The term "oligonucleotide" generally refers to short polynucleotides. It should be understood that when nucleotide sequences are represented by DNA sequences (i.e., A, T, C, G), this also includes RNA sequences (i.e., A, U, C, G) – where "U" replaces "T".

Unless otherwise specified, "nucleotide sequence encoding an amino acid sequence" includes all nucleotide sequences that are degenerate to each other and encode the same amino acid sequence. A phrase encoding a protein or RNA nucleotide sequence may also include introns, provided that the nucleotide sequence encoding that protein may contain one or more introns in some translations.

"Parenteral" administration of immunogenic compositions includes techniques such as subcutaneous (s.c.), intravenous (i.v.), intramuscular (i.m.), or intrasternal injection or infusion.

As used herein, the term "polynucleotide" is defined as a nucleotide chain. Furthermore, nucleic acids are polymers of nucleotides. Therefore, as used herein, nucleic acids and polynucleotides are interchangeable. Those skilled in the art have general knowledge that nucleic acids are polynucleotides that can be hydrolyzed into monomeric "nucleotides." Monomeric nucleotides can be hydrolyzed into nucleosides. Polynucleotides as used herein include, but are not limited to, all nucleic acid sequences obtained by any means available in the art—non-limitingly including recombinant means, i.e., cloning nucleic acid sequences from recombinant libraries or cell genomes using common cloning techniques and PCR, and by synthetic means.

As used herein, the terms “peptide,” “polypeptide,” and “protein” are used interchangeably and refer to compounds consisting of amino acid residues covalently linked by peptide bonds. A protein or peptide must contain at least two amino acids, and there is no limit to the maximum number of amino acids that can constitute a protein or peptide sequence. A polypeptide includes any peptide or protein containing two or more amino acids linked together by peptide bonds. As used herein, the term refers to both short chains (also commonly referred to in the art as, for example, peptides, oligopeptides, and oligomers) and longer chains (commonly referred to in the art as proteins, which come in many types). “Polypeptide” includes, for example, biologically active fragments, substantially homologous polypeptides, oligopeptides, homodimers, heterodimers, variants of polypeptides, modified polypeptides, derivatives, analogs, fusion proteins, etc. Polypeptides include native peptides, recombinant peptides, synthetic peptides, or combinations thereof.

As used herein with respect to antibodies, the term "specific binding" refers to an antibody that recognizes a specific antigen but does not substantially recognize or bind to other molecules in the sample. For example, an antibody that specifically binds to an antigen from one species may also bind to that antigen from one or more species. However, such cross-species reactivity does not itself change the antibody class to specific. In another instance, an antibody that specifically binds to an antigen may also bind to different allelic forms of that antigen. However, such cross-reactivity does not itself change the antibody class to specific. In some cases, the terms "specific binding" or "specific binding" may be used with respect to the interaction of an antibody, protein, or peptide with a second chemical substance, meaning that the interaction depends on the presence of a specific structure (e.g., an antigenic determinant or epitope) on that chemical substance; for example, the antibody recognizes and binds to a specific protein structure rather than generally recognizing and binding to proteins. If an antibody is specific to epitope "A," the presence of a molecule containing epitope A (or free, unlabeled A) in a reaction containing labeled "A" and the antibody will reduce the amount of labeled A bound to the antibody.

The term "stimulus" refers to a primary response induced by the binding of a stimulating molecule (e.g., the TCR/CD3 complex) to its associated ligand, thereby mediating a signal transduction event—such as, but not limited to, signal transduction via the TCR/CD3 complex. Stimuli can mediate altered expression of certain molecules, such as downregulation of TGF-β and/or reorganization of the cytoskeleton.

"Stimulating molecule," as used in this article, refers to a molecule on T cells that specifically binds to an associated stimulating ligand present on antigen-presenting cells.

As used herein, “stimulatory ligand” refers to a ligand that, when present on antigen-presenting cells (e.g., aAPCs, dendritic cells, B cells, etc.), can specifically bind to associated binding partners on T cells (referred to herein as “stimulatory molecules”), thereby mediating the primary response of T cells, including but not limited to activation, initiation of an immune response, and proliferation. Stimulatory ligands are well known in the art and encompass, in particular, MHC class I molecules loaded with peptides, anti-CD3 antibodies, superagonist anti-CD28 antibodies, and superagonist anti-CD2 antibodies.

The term "object" is intended to include any living organism (e.g., a mammal) in which an immune response can be elicited. As used herein, "object" or "patient" can be a human or a non-human mammal. Non-human mammals include, for example, livestock and pets such as sheep, cattle, pigs, dogs, cats, and rodents. Preferably, the object is a human.

"Target site" or "target sequence" refers to a nucleic acid sequence that defines the portion of the nucleic acid in which a binding molecule can specifically bind under conditions sufficient to allow binding to occur. In some embodiments, the target sequence refers to a genomic nucleic acid sequence that defines the portion of the nucleic acid in which a binding molecule can specifically bind under conditions sufficient to allow binding to occur.

As used in this article, the term "therapeutic" means treatment and/or prevention. Therapeutic effects are achieved through the suppression, relief, or eradication of the disease state.

"Transplant" refers to a biocompatible lattice or donor tissue, organ, or cell to be transplanted. Examples of transplants include, but are not limited to, skin cells or tissues, bone marrow, and solid organs such as the heart, pancreas, kidney, lung, and liver. A transplant can also refer to any material to be administered to a host. For example, a transplant can refer to nucleic acids or proteins.

As used herein, the terms “transfected,” “transformed,” or “transduced” refer to a process in which exogenous nucleic acids are transferred or introduced into host cells. “Transfected,” “transformed,” or “transduced” cells are cells that have been transfected, transformed, or transduced with exogenous nucleic acids. These cells include primary target cells and their progeny.

As used in this article, “treatment” of a disease means reducing the frequency or severity of at least one sign or symptom of a disease or disorder experienced by the subject.

A “vector” is a composition of substances containing isolated nucleic acids and capable of being used to deliver those isolated nucleic acids into the cell. Various vectors are known in the art, including, but not limited to, linear polynucleotides, polynucleotides bound to ionic or amphiphilic compounds, plasmids, and viruses. Therefore, the term “vector” includes autonomously replicating plasmids or viruses. The term should also be interpreted to include non-plasmid and non-viral compounds that facilitate the transfer of nucleic acids into cells, such as, for example, polylysine compounds, liposomes, etc. Examples of viral vectors include, but are not limited to, Sendai virus vectors, adenovirus vectors, adeno-associated virus vectors, retroviral vectors, lentiviral vectors, etc.

Scope: Throughout this disclosure, various aspects of the invention may be presented in a scope format. It should be understood that the scope format is for convenience and brevity only and should not be construed as a rigid limitation on the scope of the invention. Therefore, the scope description should be considered as specifically disclosing all possible sub-scopes and individual numerical values within those scopes. For example, a scope such as 1 to 6 should be considered as specifically disclosing sub-scopes such as 1 to 3, 1 to 4, 1 to 5, 2 to 4, 2 to 6, 3 to 6, etc., and individual numbers within those scopes, such as 1, 2, 2.7, 3, 4, 5, 5.3, and 6. This applies regardless of the width of the scope.

B. Modified immune cells

This article provides modified immune cells or their precursors (e.g., T cells) in which endogenous Fli1 has been disrupted. Endogenous Fli1 can be disrupted at the gene or protein level by any means known to those skilled in the art. Such methods of disrupting Fli1 include, but are not limited to, CRISPR systems, antibodies, siRNA, miRNA, drugs, antagonists, small molecule inhibitors, and PROTAC targets.

In one aspect, this disclosure provides modified immune cells or precursors thereof (e.g., T cells) comprising modifications at an endogenous locus encoding Fli1. In some embodiments, the cells contain nucleic acids capable of downregulating the expression of the gene for endogenous Fli1.

In one aspect, this disclosure provides modified immune cells or their precursors (e.g., T cells) comprising CRISPR-mediated modifications at an endogenous locus encoding Fli1, said modifications being capable of downregulating the gene expression of endogenous Fli1.

In some implementations, the modified cells are human cells.

This disclosure provides gene-edited modified cells. In some embodiments, the modifications of this disclosure are gene-edited to disrupt the expression of an endogenous locus encoding Fli1. In some embodiments, the gene-edited immune cells (e.g., T cells) have downregulated, reduced, deleted, eliminated, knocked out, or disrupted expression of endogenous Fli1.

Immunotherapy has shown various therapeutic effects in treating cancer patients. One of the major problems limiting its effectiveness is the exhaustion of T cells after continuous stimulation by tumor cells. Exhausted T cells have reduced effector functions, such as cytokine production and cytotoxicity against tumor cells, and they express higher levels of checkpoint inhibitory molecules, such as PD-1 and CTLA-4. PD-1 and CTLA-4 antibodies have been used clinically to treat a variety of cancer types.

In some embodiments, the modified cells of this disclosure are genetically edited to disrupt the expression of additional endogenous genes. For example, the cells may be further edited to disrupt the endogenous PDCD1 gene product (e.g., programmed death-1 receptor; PD-1). Disruption of endogenous PD-1 expression may generate "checkpoint" resistant modified cells, thereby enhancing tumor control. Checkpoint resistance modified cells can also be generated by disrupting the expression of, but not limited to, adenosine A2A receptor (A2AR), B7-H3 (CD276), B7-H4 (VTCN1), B and T lymphocyte attenuator protein (BTLA/CD272), CD96, cytotoxic T lymphocyte-associated protein 4 (CTLA-4/CD152), indoleamine 2,3-dioxygenase (IDO), killer cell immunoglobulin-like receptor (KIR), lymphocyte activation gene-3 (LAG3), T cell immune receptor with Ig and ITIM domains (TIGIT), T cell immunoglobulin domain and mucin domain 3 (TIM-3), or T cell activation V domain Ig inhibitor (VISTA).

Various gene editing techniques are known to those skilled in the art. These techniques include, but are not limited to, regressive endonucleases, zinc finger nucleases (ZFNs), transcription activator-like effector (TALE) nucleases (TALENs), and CRISPR-associated protein 9 (Cas9). Regressive endonucleases typically cleave their DNA substrates in a dimer form and do not have distinct binding and cleavage domains. ZFNs recognize target sites consisting of two zinc finger binding sites located flanking the 5- to 7-base-pair spacer sequence recognized by the FokI cleavage domain. TALENs recognize target sites consisting of two TALE DNA binding sites located flanking the 12- to 20-bp spacer sequence recognized by the FokI cleavage domain. The DNA sequence targeted by the Cas9 nuclease is complementary to the target sequence within the single guide RNA (gRNA), immediately upstream of the protospacer adjacent motif (PAM). Therefore, those skilled in the art will be able to select a suitable gene-editing technique for this disclosure.

In some aspects, disruption is carried out by gene editing using RNA-guided nucleases such as the CRISPR-Cas system (e.g., the CRISPR-Cas9 system), which is specific to the gene being disrupted (e.g., Fli1). In some embodiments, an agent—containing Cas9 and a guide RNA (gRNA) containing a targeting domain of the target locus region—is introduced into the cell. In some embodiments, the agent is or comprises a ribonucleoprotein (RNP) complex of Cas9 polypeptide and gRNA (Cas9/gRNA RNP). In some embodiments, the introduction includes contacting the agent or a portion thereof with cells in vitro, which may include culturing or incubating cells and the agent for up to 24, 36, or 48 hours or 3, 4, 5, 6, 7, or 8 days. In some embodiments, the introduction may also include efficient delivery of the agent into the cells. In various embodiments, the methods, compositions, and cells according to this disclosure utilize the direct delivery of the Cas9/gRNA ribonucleoprotein (RNP) complex into cells, for example, via electroporation. In some embodiments, the RNP complex comprises a gRNA that has been modified to include a 3' polyadenylated tail and a 5' anti-reverse cap analog (ARCA) cap.

The CRISPR/Cas9 system is an readily available and efficient system for inducing targeted gene alterations. Cas9 protein target recognition requires a "seed" sequence within the guide RNA (gRNA) and a conserved dinucleotide protospacer adjacent motif (PAM) upstream of the gRNA-binding region. The CRISPR/Cas9 system can then be engineered by redesigning the gRNA to cleave virtually any DNA sequence in cell lines (e.g., 293T cells), primary cells, and TCR T cells. The CRISPR/Cas9 system can simultaneously target multiple genomic loci by co-expressing a single Cas9 protein with two or more gRNAs, making it suitable for multiplex gene editing or synergistic activation of target genes.

The Cas9 protein and guide RNA form a complex that recognizes and cleaves target sequences. Cas9 consists of six domains: REC I, REC II, Bridge Helix, PAM interaction, HNH, and RuvC. The REC I domain binds to the guide RNA, while the Bridge Helix binds to the target DNA. The HNH and RuvC domains are nuclease domains. The guide RNA is engineered to have a 5' end complementary to the target DNA sequence. When the guide RNA binds to the Cas9 protein, a conformational change occurs, activating the protein. Once activated, Cas9 searches for target DNA by binding to a sequence that matches its protospacer adjacent motif (PAM) sequence. A PAM is a two- or three-nucleotide sequence located one nucleotide downstream of a region complementary to the guide RNA. In a non-limiting example, the PAM sequence is 5'-NGG-3'. When the Cas9 protein finds its target sequence via the appropriate PAM, it melts the bases upstream of the PAM and pairs them with the complementary region on the guide RNA. Then the RuvC and HNH nuclease domains cleave the target DNA after the third nucleotide base upstream of PAM.

A non-limiting example of a CRISPR/Cas system for inhibiting gene expression, CRISPRi, is described in U.S. Patent Application Publication No. US20140068797. CRISPRi induces permanent gene damage by using an RNA-guided Cas9 endonuclease to introduce DNA double-strand breaks, thereby triggering a biased error repair pathway, leading to frameshift mutations. Catalytically dead Cas9 lacks endonuclease activity. When co-expressed with guide RNA, it generates a DNA recognition complex that specifically interferes with transcriptional elongation, RNA polymerase binding, or transcription factor binding. This CRISPRi system effectively inhibits the expression of the targeted gene.

CRISPR/Cas gene disruption occurs when a target gene-specific guide nucleic acid sequence and a Cas endonuclease are introduced into the cell and form a complex that enables the Cas endonuclease to introduce double-strand breaks at the target gene. In some embodiments, the CRISPR/Cas system includes an expression vector, such as, but not limited to, the pAd5F35-CRISPR vector. In other embodiments, the Cas expression vector induces the expression of the Cas9 endonuclease. Other endonucleases may also be used, including but not limited to Cas12a (Cpf1), T7, Cas3, Cas8a, Cas8b, Cas10d, Cse1, Csy1, Csn2, Cas4, Cas10, Csm2, Cmr5, Fok1, other nucleases known in the art, and any combination thereof.

In some embodiments, the inducible Cas expression vector includes exposing cells to an agent that activates an inducible promoter in the Cas expression vector. In such embodiments, the Cas expression vector includes an inducible promoter, such as a promoter that can be induced by exposure to an antibiotic (e.g., by tetracycline or a tetracycline derivative, such as doxycycline). Other inducible promoters known to those skilled in the art may also be used. The inducer may be a selective condition that leads to the induction of the inducible promoter (e.g., exposure to an agent, such as an antibiotic). This results in the expression of the Cas expression vector.

As used herein, the term “guide RNA” or “gRNA” refers to any nucleic acid that promotes the specific binding (or “targeting”) of RNA-guided nucleases such as Cas9 to target sequences in the cell (e.g., genomic or episodic sequences).

As used herein, the “modular” or “dual RNA” guideline involves more than one, typically two separate RNA molecules, such as CRISPR RNA (crRNA) and trans-activating crRNA (tracrRNA), which are usually linked together, for example, by duplexing. gRNA and its components are described throughout the literature (see, for example, Briner et al. Mol. Cell, 56(2), 333-339 (2014), which is incorporated herein by reference).

As used herein, “single gRNA,” “chimeric gRNA,” or “single guide RNA (sgRNA)” refers to a single RNA molecule. sgRNA can be a crRNA and a tracrRNA linked together. For example, the 3’ end of crRNA can be linked to the 5’ end of tracrRNA. crRNA and tracrRNA can be linked together to form a single single-molecule or chimeric gRNA, for example, through a tetranucleotide (e.g., GAAA) “tetranucleotide loop” or “linker” sequence bridging the complementary regions of crRNA (at its 3’ end) and tracrRNA (at its 5’ end).

As used in this article, a “repetitive” sequence or region is a nucleotide sequence at or near the 3’ end of crRNA that is complementary to the inverted repeat sequence of tracrRNA.

As used in this article, an "inverted repeat" sequence or region is a nucleotide sequence at or near the 5' end of the tracrRNA that is complementary to the repeat sequence of the crRNA.

Further details regarding the guiding RNA structure and function, including the gRNA/Cas9 complex used for genome editing, can be found at least in: Mali et al. Science, 339(6121), 823-826 (2013); Jiang et al. Nat. Biotechnol. 31(3), 233-239 (2013); and Jinek et al. Science, 337(6096), 816-821 (2012); which are incorporated herein by reference.

As used herein, a “guide sequence” or “target sequence” refers to the nucleotide sequence of a gRNA, whether single-molecule or modular, that is fully or partially complementary to a target domain or target polynucleotide within the DNA sequence of the cell genome to be edited. Guide sequences are typically 10–30 nucleotides in length, preferably 16–24 nucleotides (e.g., 16, 17, 18, 19, 20, 21, 22, 23, or 24 nucleotides in length), and are located at or near the 5’ end of the Cas9 gRNA.

As used in this article, a “target domain” or “target polynucleotide sequence” or “target sequence” is a DNA sequence in the cell genome that is complementary to the guide sequence of the gRNA.

In the context of CRISPR complex formation, the "target sequence" refers to a sequence to which the guide sequence is designed to have some complementarity, where hybridization between the target and guide sequences promotes CRISPR complex formation. Perfect complementarity is not required as long as sufficient complementarity is sufficient to induce hybridization and promote CRISPR complex formation. The target sequence can include any polynucleotide, such as DNA or RNA polynucleotides. In some embodiments, the target sequence is located in the cell nucleus or cytoplasm. In other embodiments, the target sequence can be within organelles of eukaryotic cells, such as mitochondria or the nucleus. Typically, in the context of a CRISPR system, the formation of the CRISPR complex (including the guide sequence that hybridizes with the target sequence and complexes with one or more Cas proteins) results in the cleavage of one or both strands of the target sequence in or near it (e.g., within about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 50, or more base pairs). Similar to the target sequence, perfect complementarity is believed to be unnecessary as long as it is sufficient to function.

In some implementations, one or more vectors driving the expression of one or more elements of the CRISPR system are introduced into a host cell, such that the expression of these elements of the CRISPR system guides the formation of the CRISPR complex at one or more target sites. For example, Cas nucleases, crRNA, and tracrRNA can each be operatively linked to separate regulatory elements on separate vectors. Alternatively, two or more elements expressed by the same or different regulatory elements can be combined in a single vector, wherein one or more additional vectors provide any components of the CRISPR system not included in the first vector. The CRISPR system elements combined in a single vector can be arranged in any suitable orientation, such as one element being located at 5’ (“upstream”) or 3’ (“downstream”) relative to the second element. The coding sequence of one element can be located on the same or opposite strand of the coding sequence of the second element and oriented in the same or opposite directions. In some implementations, a single promoter drives the expression of one or more of the transcript encoding the CRISPR enzyme and the guide sequence, the tracr chaperone sequence (optionally operably linked to the guide sequence), and the tracr sequence embedded in one or more intron sequences (e.g., each in a different intron, two or more in at least one intron, or all in a single intron).

In some embodiments, the CRISPR enzyme is part of a fusion protein comprising one or more heterologous protein domains (e.g., about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more domains in addition to the CRISPR enzyme). The CRISPR enzyme fusion protein may comprise any additional protein sequence, and optionally a linker sequence between any two domains. Examples of protein domains that can be fused to a CRISPR enzyme include, but are not limited to, epitope tags, reporter gene sequences, and protein domains having one or more of the following activities: methyltransferase activity, demethyltransferase activity, transcriptional activation activity, transcriptional repression activity, transcription release factor activity, histone modification activity, RNA cleavage activity, and nucleic acid binding activity. Other domains that may form part of a fusion protein comprising a CRISPR enzyme are described in U.S. Patent Application Publication No. US20110059502 (which is incorporated herein by reference). In some embodiments, the tagged CRISPR enzyme is used to identify the location of a target sequence.

Conventional virus-based and non-virus-based gene transfer methods can be used to introduce nucleic acids into mammalian and non-mammal cells or target tissues. Such methods can be used to administer nucleic acids encoding components of the CRISPR system to cells in culture or in a host organism. Non-viral vector delivery systems include DNA plasmids, RNA (e.g., transcripts of the vectors described herein), naked nucleic acids, and nucleic acids complexed with delivery media such as liposomes. Viral vector delivery systems include DNA viruses and RNA viruses that, upon delivery to cells, possess an appendage or integrated genome (Anderson, 1992, Science 256:808-813; and Yu, et al., 1994, Gene Therapy 1:13-26).

In some embodiments, CRISPR/Cas is derived from a type II CRISPR/Cas system. In other embodiments, the CRISPR/Cas system is derived from a Cas9 nuclease. Exemplary Cas9 nucleases that may be used in this disclosure include, but are not limited to, *Streptococcus pyogenes* Cas9 (SpCas9), *Staphylococcus aureus* Cas9 (SaCas9), *Streptococcus thermophilus* Cas9 (StCas9), *Neisseria meningitidis* Cas9 (NmCas9), *Campylobacter jejuni* Cas9 (CjCas9), and *Geobacillus Cas9 (GeoCas9).

Typically, Cas proteins contain at least one RNA recognition and/or RNA binding domain. This RNA recognition and/or RNA binding domain interacts with a guide RNA. Cas proteins may also contain nuclease domains (i.e., DNase or RNase domains), DNA-binding domains, helicase domains, RNase domains, protein-protein interaction domains, dimerization domains, and other domains. Cas proteins can be modified to increase nucleic acid binding affinity and/or specificity, alter enzymatic activity, and/or change other properties of the protein. In some embodiments, the Cas-like protein of the fusion protein may be derived from a wild-type Cas9 protein or a fragment thereof. In other embodiments, Cas may be derived from a modified Cas9 protein. For example, the amino acid sequence of the Cas9 protein may be modified to alter one or more properties of the protein (e.g., nuclease activity, affinity, stability, etc.). Optionally, domains of the Cas9 protein that do not participate in RNA-guided cleavage may be removed, resulting in a modified Cas9 protein smaller than the wild-type Cas9 protein. Typically, Cas9 proteins contain at least two nuclease (i.e., DNase) domains. For example, the Cas9 protein may contain a RuvC-like nuclease domain and an HNH-like nuclease domain. The RuvC and HNH domains work together to cleave single strands, thereby creating double-strand breaks in DNA (Jinek, et al., 2012, Science, 337:816-821). In some embodiments, the Cas9-derived protein may be modified to contain only one functional nuclease domain (a RuvC-like or HNH-like nuclease domain). For example, the Cas9-derived protein may be modified such that one of the nuclease domains is deleted or mutated, rendering it nonfunctional (i.e., nuclease activity is absent). In some embodiments where one of the nuclease domains is inactive, the Cas9-derived protein can introduce a nick into the double-stranded nucleic acid (this protein is called a "nickase") but does not cleave double-stranded DNA. In any of the above embodiments, any or all of the nuclease domains may be inactivated using known methods (such as site-directed mutagenesis, PCR-mediated mutagenesis, and total gene synthesis) and other methods known in the art, by one or more deletion mutations, insertion mutations, and/or substitution mutations.

In one non-limiting embodiment, the vector drives the expression of the CRISPR system. The art is rich with suitable vectors useful in this disclosure. The vectors to be used are adapted for replication and optionally integration in eukaryotic cells. Typical vectors contain transcription and translation terminators, initiation sequences, and promoters that can be used to regulate the expression of desired nucleic acid sequences. The vectors of this disclosure can also be used in standard nucleic acid gene delivery protocols. Methods of gene delivery are known in the art (US Patent Nos. 5,399,346, 5,580,859, and 5,589,466, which are incorporated herein by reference in their entirety).

Furthermore, the vector can be provided to cells in the form of a viral vector. Viral vector technology is well known in the art and has been described in, for example, Sambrook et al. (4th edition, Molecular Cloning: A Laboratory Manual, ColdSpring Harbor Laboratory, New York, 2012) and other virology and molecular biology manuals. Viruses that can be used as vectors include, but are not limited to, retroviruses, adenoviruses, adeno-associated viruses, herpesviruses, Sindbis viruses, gamma retroviruses, and lentiviruses. Typically, a suitable vector contains a source that has replication function in at least one organism, a promoter sequence, a convenient restriction endonuclease site, and one or more selective markers (e.g., WO 01/96584; WO 01/29058; and U.S. Patent No. 6,326,193).

In some embodiments, guide RNA (one or more) and Cas9 can be delivered to cells as a ribonucleoprotein (RNP) complex (e.g., a Cas9/RNA protein complex). RNPs, consisting of purified Cas9 protein complexed with gRNA, are known in the art to be efficiently delivered to various cell types—including but not limited to stem cells and immune cells (Addgene, Cambridge, MA, Mirus Bio LLC, Madison, WI). In some embodiments, the Cas9/RNA protein complex is delivered to cells via electroporation.

In some embodiments, CRISPR/Cas9 is used to edit the modified cells disclosed herein to disrupt the endogenous locus encoding Fli1. Suitable gRNAs for disrupting Fli1 are listed herein (see Tables 1 and 2) and include, but are not limited to, SEQ ID NO: 152-156 and SEQ ID NO: 676-713. Those skilled in the art will understand that the guide RNA sequence may be described using thymidine (T) or uridine (U) nucleotides.

Table 2: Human Fli1 sgRNA

Non-restrictive types of CRISPR-mediated modifications include substitution, insertion, deletion, and insertion/deletion (INDEL). Modifications can be located at any part of the endogenous locus encoding Fli1, including but not limited to exons, splice donors, or splice acceptors.

In some embodiments, the guide RNA comprises a guide sequence that is sufficiently complementary to a target sequence at an endogenous locus encoding Fli1. In some embodiments, the guide RNA comprises a guide sequence that is sufficiently complementary to a target sequence at an endogenous locus encoding Fli1, such as, for example, a guide sequence comprising any one of the sequences listed in SEQ ID NO:152-156 or SEQ ID NO:676-713.

In some embodiments, the modified cells are resistant to cell dysfunction. In some embodiments, the modified cells are resistant to cell exhaustion. In some embodiments, the modified cells are autologous cells. In some embodiments, the modified cells are cells isolated from a human subject. In some embodiments, the modified cells are modified immune cells. In some embodiments, the modified cells are modified T cells. In some embodiments, the modified cells are modified T cells resistant to T cell exhaustion. In some embodiments, the modified cells are modified T cells resistant to T cell dysfunction.

In some aspects, the provided compositions and methods include those in which at least or more than about 50%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95% of the immune cells in the immune cell composition contain the desired gene modification. For example, in a cell composition in which an agent (e.g., gRNA/Cas9) for knocking out or gene-damaging an endogenous gene (e.g., Fli1) is introduced (e.g., gRNA/Cas9), about 50%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95% of the immune cells contain gene-damage; do not express the targeted endogenous polypeptide, or do not contain adjacent and/or functional copies of the targeted gene. In some embodiments, the methods, compositions, and cells according to this disclosure include those in which at least or more than about 50%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95% of the cells in a cell composition incorporating an agent for knocking out or gene-destroying the targeted gene (e.g., gRNA/Cas9) do not express the targeted polypeptide, such as on the surface of immune cells. In some embodiments, in a cell composition incorporating an agent for knocking out or gene-destroying the targeted gene (e.g., gRNA/Cas9), at least or more than about 50%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95% of the cells are knocked out in two alleles, i.e., such a percentage of cells contains biallelic deletions.

In some embodiments, compositions and methods are provided in which the Cas9-mediated cleavage efficiency (%indel) in or near the targeted gene (e.g., within 100 or about 100 base pairs, 50 or about 50 base pairs, 25 or about 25 base pairs, or 10 or about 10 base pairs upstream or downstream of the cleavage site) is at least or greater than about 50%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95% in cells in which a cell composition has been introduced with an agent (e.g., gRNA/Cas9) for knocking out or gene-destroying the targeted gene is introduced.

In some embodiments, the provided cells, compositions, and methods result in a reduction or disruption of signals delivered endogenously in at least or more than about 50%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95% of cells in a cell composition in which an agent (e.g., gRNA/Cas9) for knocking out or gene-destroying the targeted gene is introduced.

In some embodiments, compositions comprising cells modified with a recombinant receptor and containing reduced, deleted, eliminated, knocked-out, or disrupted endogenous gene expression (e.g., disruption of the Fli1 gene), according to the provided disclosure, maintain receptor functionality or activity when evaluated under the same conditions, compared to receptors expressed in modified cells of corresponding or reference compositions containing the receptor but without gene disruption or expressing a peptide. In some embodiments, modified cells of the provided compositions, when evaluated under the same conditions, maintain functionality or activity compared to corresponding or reference compositions containing such recombinant receptor-modified cells but without gene disruption or expressing the targeted peptide. In some embodiments, cells retain cytotoxicity, proliferation, survival, or cytokine secretion compared to such corresponding or reference compositions.

In some embodiments, the immune cells in the composition, when evaluated under the same conditions, maintain the phenotype of the immune cells compared to the cells in the corresponding or reference composition. In some embodiments, the cells in the composition include naive cells, effector memory cells, central memory cells, stem central memory cells, effector memory cells, and long-lived effector memory cells. In some embodiments, the percentage of T cells containing gene disruption of the targeted gene (e.g., Fli1) exhibits the same or substantially the same inactive long-lived or central memory phenotype as the corresponding or reference population or composition of cells not containing gene disruption. In some embodiments, such properties, activities, or phenotypes can be measured in an in vitro assay. In some embodiments, any evaluated activity, property, or phenotype can be assessed at various numbers of days after electroporation or other introduction of the agent, such as 3, 4, 5, 6, 7 days or up to 3, 4, 5, 6, 7 days. In some embodiments, when evaluated under the same conditions, at least 80%, 85%, 90%, 95%, or 100% of the cells in the composition retain such activity, properties, or phenotypes compared to the activity of the corresponding composition containing cells with gene damage that does not contain the targeted gene.

As used herein, references to “corresponding composition” or “corresponding immune cell population” (also referred to as “reference composition” or “reference cell population”) mean immune cells (e.g., T cells) obtained, isolated, generated, produced, and/or incubated under the same or substantially the same conditions, except that the agent was not introduced into the immune cells or immune cell population. In some aspects, such immune cells, except for the absence of agent introduction, are subjected to the same or substantially the same treatment as immune cells in which the agent has been introduced, such that any one or more conditions capable of affecting cell activity or properties (including the upregulation or expression of inhibitory molecules) are unchanged or substantially unchanged between cells—other than the introduction of the agent.

Methods and techniques for assessing the expression and/or levels of T-cell markers are known in the art. Antibodies and reagents for detecting such markers are well known in the art and are readily available. Assays and methods for detecting such markers include, but are not limited to, flow cytometry, including intracellular flow cytometry, ELISA, ELISPOT, flow cytometry bead arrays or other multiplex methods, Western blotting, and other immunoaffinity-based methods. In some embodiments, the expression of cell-specific markers can be detected by flow cytometry or other immunoaffinity-based methods, and then these cells can be co-stained to detect one or more other cell surface markers.

In some embodiments, the cells, compositions, and methods provide the absence, knockout, disruption, or reduction of target gene expression in immune cells (e.g., T cells) to be adopted. In some embodiments, the methods are performed ex vivo on primary cells, such as primary immune cells (e.g., T cells) from the subject. In some aspects, methods for producing or generating such genetically modified T cells include introducing one or more agents capable of disrupting a target gene (e.g., Fli1) into a population of cells containing immune cells (e.g., T cells). As used herein, the term "introduction" covers various methods of introducing DNA into cells in vitro or in vivo, including transformation, transduction, transfection (e.g., electroporation), and infection. Vectors can be used to introduce DNA-encoding molecules into cells. Possible vectors include plasmid vectors and viral vectors. Viral vectors include retroviral vectors, lentiviral vectors, or other vectors such as adenovirus vectors or adeno-associated vectors.

The cell population containing T cells can be cells obtained from the subject, such as cells obtained from peripheral blood mononuclear cell (PBMC) samples, ungraded T cell samples, lymphocyte samples, leukocyte samples, products of apheresis, or products of leukocyte extraction. In some embodiments, T cells can be isolated or selected using positive or negative selection and enrichment methods to enrich the T cells in the population. In some embodiments, the population comprises CD4+, CD8+, or CD4+ and CD8+ T cells. In some embodiments, the steps of introducing nucleic acids encoding genetically modified antigen receptors and introducing agents (e.g., Cas9/gRNA RNPs) can occur simultaneously or sequentially. In some embodiments, after introducing exogenous receptors and one or more gene-editing agents (e.g., Cas9/gRNA RNPs), the cells are cultured or incubated under conditions that stimulate cell expansion and/or proliferation.

Therefore, cells, compositions, and methods are provided to enhance the function of immune cells, such as T cells, in adoptive cell therapy, including those that provide improved efficacy, such as by increasing the activity and potency of the applied genetically modified cells while maintaining persistence or exposure to the transferred cells over time. In some embodiments, the genetically modified cells exhibit increased amplification and/or persistence when administered to a subject in vivo, compared to certain available methods. In some embodiments, the provided immune cells exhibit increased persistence when administered to a subject in vivo. In some embodiments, the persistence of the genetically modified immune cells in the subject after administration is greater than that achievable by alternative methods—such as those involving the administration of the genetically modified cells by means of agents that do not reduce the expression of genes encoding endogenous receptors or disrupt those genes in T cells. In some implementations, the durability is increased by at least 1.5 times, 2 times, 3 times, 4 times, 5 times, 6 times, 7 times, 8 times, 9 times, 10 times, 20 times, 30 times, 50 times, 60 times, 70 times, 80 times, 90 times, 100 times or more.

In some embodiments, the persistence or degree of persistence of the applied cells can be detected or quantified after administration to the subject. For example, in some aspects, quantitative PCR (qPCR) is used to assess the number of cells in the subject's blood or serum or organ or tissue (e.g., disease site). In some aspects, persistence is quantified as the copy number of DNA or plasmid encoding a foreign receptor per microgram of DNA, or the number of cells expressing the receptor per microliter of sample (e.g., blood or serum), or the total number of peripheral blood mononuclear cells (PBMCs), leukocytes, or T cells per microliter of sample. In some embodiments, flow cytometry assays can also be performed, which typically use cell-specific antibodies to detect cells. Cell-based assays can also be used to detect the number or percentage of functional cells—such as cells capable of binding and/or neutralizing and/or inducing responses against disease or condition or cells expressing antigens recognized by the receptor (e.g., cytotoxic responses). In any such embodiment, the degree or level of expression of another cell-related marker can be used to distinguish applied cells from endogenous cells in the subject.

C. Source of immune cells

In some embodiments, the source of immune cells is obtained from the subject for in vitro manipulation. The source of the target cells for in vitro manipulation may also include, for example, autologous or allogeneic donor blood, umbilical cord blood, or bone marrow. For example, the source of immune cells may be the subject to be treated with the modified immune cells of this disclosure, such as the subject's blood, umbilical cord blood, or bone marrow. Non-limiting examples of subjects include humans, dogs, cats, mice, rats, and their transgenic species. Preferably, the subject is a human.

Immune cells can be obtained from a variety of sources, including blood, peripheral blood mononuclear cells, bone marrow, lymph node tissue, spleen tissue, umbilical cord, lymph nodes, or lymphoid organs. Immune cells are cells of the immune system, such as cells of innate or adaptive immunity, for example, myeloid or lymphoid cells, including lymphocytes, typically T cells and/or NK cells. Other exemplary cells include stem cells, such as pluripotent stem cells and multipotent stem cells, including induced pluripotent stem cells (iPSCs). In some respects, these cells are human cells. For the object to be treated, these cells can be allogeneic and/or autologous. These cells are generally primary cells, such as those isolated directly from the object and/or isolated from the object and frozen.

In some embodiments, the immune cells are T cells, such as CD8+ T cells (e.g., CD8+ naive T cells, central memory T cells, or effector memory T cells), CD4+ T cells, natural killer T cells (NKT cells), regulatory T cells (Tregs), stem cell memory T cells, lymphoprogenitor cells, hematopoietic stem cells, natural killer cells (NK cells), or dendritic cells. In some embodiments, the cells are monocytes or granulocytes, such as myeloid cells, macrophages, neutrophils, dendritic cells, mast cells, eosinophils, and/or basophils. In one implementation, the target cell is an induced pluripotent stem cell (iPS) cell or a cell derived from an iPS cell, such as an iPS cell generated from an object, manipulated to alter (e.g., induce mutations in one or more target genes) or manipulate the expression of one or more target genes, and differentiated into, for example, T cells, such as CD8+ T cells (e.g., CD8+ naive T cells, central memory T cells, or effector memory T cells), CD4+ T cells, stem cell memory T cells, lymphoid progenitor cells, or hematopoietic stem cells.

In some embodiments, the cells include one or more T cell subsets or other cell types, such as the entire T cell population, CD4+ cells, CD8+ cells, and their subsets, as defined by function, activation state, maturity, differentiation potential, expansion, recycling, localization and/or persistence, antigen specificity, antigen receptor type, presence in a particular organ or compartment, marker or cytokine secretion profile, and/or degree of differentiation. Among the subtypes and subsets of T cells and/or CD4+ T cells and/or CD8+ T cells are naive T (TN) cells, effector T cells (TEFF), memory T cells and their subtypes, such as stem cell memory T cells (TSCM), central memory T cells (TCM), effector memory T (TEM) or terminally differentiated effector memory T cells, tumor-infiltrating lymphocytes (TIL), immature T cells, mature T cells, helper T cells, cytotoxic T cells, mucosa-associated inertial T (MAIT) cells, naturally occurring and adaptive regulatory T (Treg) cells, and helper T cells, such as TH1 cells, TH2 cells, TH3 cells, TH17 cells, TH9 cells, TH22 cells, follicular helper T cells, α/β T cells, and δ/γ T cells. In some embodiments, any number of T cell lines available in the art may be used.

In some embodiments, the method includes isolating immune cells from a subject, preparing, processing, culturing, and/or modifying them. In some embodiments, the preparation of modified cells includes one or more culturing and/or preparation steps. The cells used for modification may be isolated from a sample (such as a biological sample, e.g., a biological sample obtained from or derived from the subject). In some embodiments, the subject from which cells are isolated is a subject suffering from a disease or condition or requiring or to whom cell therapy will be administered. In some embodiments, the subject is a person requiring a specific therapeutic intervention (such as adoptive cell therapy in which cells are isolated, processed, and/or modified). Thus, the cells in some embodiments are primary cells, e.g., primary human cells. Samples include tissues, fluids, and other samples taken directly from the subject, as well as samples obtained from one or more processing steps, such as isolation, centrifugation, genetic modification (e.g., transduction with a viral vector), washing, and/or incubation. Biological samples may be samples obtained directly from a biological source or processed samples. Biological samples include, but are not limited to, bodily fluids such as blood, plasma, serum, cerebrospinal fluid, synovial fluid, urine, and sweat, tissue and organ samples, including processed samples derived therefrom.

In some aspects, the sample from which cells are derived or isolated is a blood sample or a blood-derived sample, or a product of apheresis or leukocyte extraction. Exemplary samples include whole blood, peripheral blood mononuclear cells (PBMCs), leukocytes, bone marrow, thymus, tissue biopsy, tumors, leukemia, lymphoma, lymph nodes, intestinal-associated lymphoid tissue, mucosa-associated lymphoid tissue, spleen, other lymphoid tissues, liver, lungs, stomach, intestines, colon, kidneys, pancreas, breast, bone, prostate, cervix, testes, ovaries, tonsils, or other organs and/or cells derived therefrom. In the context of cell therapy (e.g., adoptive cell therapy), samples include those from autologous and allogeneic sources.

In some embodiments, the cells are derived from cell lines, such as T cell lines. In some embodiments, the cells are obtained from xenogeneic sources, such as mice, rats, non-human primates, and pigs. In some embodiments, cell isolation includes one or more preparation steps and/or affinity-based cell isolation steps. In some instances, cells are washed, centrifuged, and/or incubated in the presence of one or more reagents to, for example, remove unwanted components, enrich desired components, lyse, or remove cells sensitive to a particular reagent. In some instances, cells are isolated based on one or more properties, such as density, adhesion properties, size, sensitivity, and/or resistance to a particular component.

In some instances, cells are obtained from the subject's circulating blood, for example, through apheresis or leukocyte extraction. In some aspects, the sample contains lymphocytes, including T cells, monocytes, granulocytes, B cells, other nucleated leukocytes, erythrocytes, and/or platelets, while in others it contains cells other than erythrocytes and platelets. In some embodiments, the blood cells collected from the subject are washed, thereby removing, for example, the plasma fraction and placing the cells in a suitable buffer or medium for subsequent processing steps. In some embodiments, the cells are washed with phosphate-buffered saline (PBS). In some aspects, the washing step is performed by tangential flow filtration (TFF) according to the manufacturer's instructions. In some embodiments, the cells are resuspended in a variety of biocompatible buffers after washing. In some embodiments, components of the blood cell sample are removed and the cells are directly resuspended in a culture medium. In some embodiments, the method includes density-based cell separation methods, such as preparing leukocytes from peripheral blood by lysing erythrocytes and then centrifuging via Percoll or Ficoll gradient.

In one implementation, an immune response is obtained from an individual's circulating blood via apheresis or leukocyte extraction. Apheresis products typically contain lymphocytes, including T cells, monocytes, granulocytes, B cells, other nucleated leukocytes, erythrocytes, and platelets. Cells collected via apheresis can be washed to remove the plasma fraction and placed in a suitable buffer or medium, such as phosphate-buffered saline (PBS), or a wash solution that is calcium-deficient and may be magnesium-deficient or lack many (or even all) divalent cations for subsequent processing steps. After washing, cells can be resuspended in various biocompatible buffers, such as, for example, calcium- and magnesium-free PBS. Alternatively, unwanted components of the apheresis sample can be removed and the cells directly resuspended in a culture medium.

In some embodiments, the separation method includes separating different cell types based on the expression or presence of one or more specific molecules, such as surface markers (e.g., surface proteins), intracellular markers, or nucleic acids in the cells. In some embodiments, any known separation method based on such markers can be used. In some embodiments, separation is based on affinity or immunoaffinity. For example, in some aspects, separation includes the separation of cells and cell populations based on the expression of cells or the expression level of one or more markers (typically cell surface markers), for example, by incubation with an antibody or binding partner that specifically binds to such a marker, followed by a generally washing step and separation of cells bound to the antibody or binding partner from cells not bound to that antibody or binding partner.

This separation step can be based on positive selection, where cells that have bound the reagent are retained for further use, and/or on negative selection, where cells that have not bound the antibody or binding partner are retained. In some instances, both portions are retained for further use. In some aspects, negative selection is particularly useful when no antibodies are available to specifically identify cell types in a heterogeneous population, making separation based on a marker expressed by cells other than the desired population optimal. Separation does not need to result in 100% enrichment or depletion of a specific cell population or cells expressing a specific marker. For example, positive selection or enrichment of a specific cell type (such as cells expressing a marker) means increasing the number or percentage of such cells, but does not necessarily result in the complete absence of cells that do not express the marker. Similarly, negative selection, depletion, or exhaustion of a specific cell type (such as cells expressing a marker) means reducing the number or percentage of such cells, but does not necessarily result in the complete removal of all such cells.

In some instances, multiple rounds of separation steps are performed, where a portion of a step undergoes positive or negative selection followed by another separation step, such as subsequent positive or negative selection. In some instances, a single separation step can simultaneously deplete cells expressing multiple markers, such as by incubating cells with multiple antibodies or binding partners, each specific for the marker targeted by negative selection. Similarly, multiple cell types can be positively selected simultaneously by incubating cells with multiple antibodies or binding partners expressed on various cell types.

In some implementations, one or more T cell populations are enriched or depleted from cells that are positive for or express at high levels of one or more specific markers (such as surface ^markers ), or cells that are negative for or express at relatively ^low levels of one or more markers (such as ^surface markers), or cells that are negative for or express at relatively low levels of one or more markers (such as ^surface markers). For example, in some aspects, specific subsets of T cells, such as cells that are positive for or express at high levels of one or more surface markers, such as CD28+, CD62L+, CCR7+, CD27+, CD127+, CD4+, CD8+, CD45RA+, and/or CD45RO+ T cells, are isolated by positive or negative selection techniques. In some cases, such markers are absent or expressed at relatively low levels in some T cell populations (such as non-memory cells), but present or expressed at relatively high levels in some other T cell populations (such as memory cells). In one implementation, cells (i.e., positive selection) are enriched (i.e., positively selected) against cells that are positive for or express high surface levels of CD45RO, CCR7, CD28, CD27, CD44, CD127, and/or CD62L, and/or depleted (e.g., negative selection) from cells that are positive for or express high surface levels of CD45RA. In some implementations, cells are enriched or depleted against cells that are positive for or express high surface levels of CD122, CD95, CD25, CD27, and/or IL7-Ra (CD127). In some instances, CD8+ T cells are enriched against cells that are positive for CD45RO (or negative for CD45RA) and positive for CD62L. For example, CD3+, CD28+ T cells can be positively selected using CD3/CD28 conjugated magnetic beads (e.g., M-450 CD3/CD28T Cell Expander).

In some embodiments, T cells are isolated from PBMC samples by negative selection of markers (such as CD14) expressed on non-T cells (such as B cells, monocytes, or other leukocytes). In some aspects, a CD4+ or CD8+ selection step is used to isolate CD4+ helper T cells and CD8+ cytotoxic T cells. Such CD4+ and CD8+ populations can be further sorted into subpopulations by positive or negative selection of markers expressed or expressed to relatively high levels on one or more naive, memory, and/or effector T cell subsets. In some embodiments, CD8+ cells are further enriched or depleted from naive, central memory, effector memory, and/or central memory stem cells, such as by positive or negative selection based on surface antigens associated with the respective subpopulations. In some embodiments, central memory T (TCM) cells are enriched to improve efficacy, thereby enhancing long-term survival, expansion, and/or transplantation after administration, which is particularly robust in some respects to such subpopulations. In some implementations, combining TCM-enriched CD8+ T cells with CD4+ T cells further enhances efficacy.

In some embodiments, memory T cells are present in the CD62L+ and CD62L- subsets of CD8+ peripheral blood lymphocytes. PBMCs can be enriched or depleted from the CD62L-CD8+ and/or CD62L+CD8+ fractions, for example, using anti-CD8 and anti-CD62L antibodies. In some embodiments, the CD4+ T cell population and CD8+ T cell subsets are, for example, subsets enriched for central memory T (TCM) cells. In some embodiments, enrichment of central memory T (TCM) cells is based on positive or high surface expression of CD45RO, CD62L, CCR7, CD28, CD3, and/or CD127; in some aspects, it is based on negative selection of cells expressing or highly expressing CD45RA and/or granzyme B. In some aspects, the isolation of a CD8+ population enriched for TCM cells is performed by depleting cells expressing CD4, CD14, and CD45RA, and by positive selection or enrichment of cells expressing CD62L. On one hand, enrichment of central memory T (TCM) cells begins with a negative fraction of cells selected based on CD4 expression, which undergoes negative selection based on CD14 and CD45RA expression, and then positive selection based on CD62L. In some aspects, this selection is performed simultaneously, while in others, it is performed sequentially in any order. In some aspects, the same CD4 expression-based selection step used to prepare a CD8+ cell population or subset is also used to generate a CD4+ cell population or subset, such that both positive and negative fractions from CD4-based isolation are preserved, and optionally used in subsequent steps of the method after one or more other positive or negative selection steps.

CD4+ T helper cells are sorted into naive cells, central memory cells, and effector cells by identifying cell populations with cell surface antigens. CD4+ lymphocytes can be obtained using standard methods. In some embodiments, naive CD4+ T lymphocytes are CD45RO-, CD45RA+, CD62L+, and CD4+ T cells. In some embodiments, central memory CD4+ cells are CD62L+ and CD45RO+. In some embodiments, effector CD4+ cells are CD62L- and CD45RO. In one example, to enrich CD4+ cells by negative selection, a monoclonal antibody mixture typically includes antibodies against CD14, CD20, CD11b, CD16, HLA-DR, and CD8. In some embodiments, the antibody or binding partner is bound to a solid carrier or matrix such as magnetic beads or paramagnetic beads to allow the separation of cells for positive and/or negative selection.

In some embodiments, cells are incubated and/or cultured prior to or in conjunction with genetic modification. The incubation step may include culture, cultivation, stimulation, activation, and/or proliferation. In some embodiments, the composition or cells are incubated in the presence of stimulating conditions or stimulants. Such conditions include those designed to induce cell proliferation, expansion, activation, and/or survival in a population to mimic antigen exposure, or to initiate cell genetic modification (such as for the introduction of recombinant antigen receptors). These conditions may include one or more of the following: specific culture media, temperature, oxygen content, carbon dioxide content, time, agents, such as nutrients, amino acids, antibiotics, ions, and/or stimulating factors (such as cytokines, chemokines, antigens, binding partners, fusion proteins, recombinant soluble receptors), and any other agents designed to activate cells. In some embodiments, the stimulating conditions or agents include one or more agents, such as ligands, capable of activating the intracellular signaling domains of the TCR complex. In some aspects, this agent turns on or initiates the TCR/CD3 intracellular signaling cascade in T cells. Such agents may include antibodies, such as antibodies specific to TCR components and/or co-stimulatory receptors, for example, anti-CD3, anti-CD28, and/or one or more cytokines bound to a solid carrier (such as beads). Optionally, the amplification method may further include the step of adding anti-CD3 and/or anti-CD28 antibodies (e.g., at a concentration of at least about 0.5 ng/mL) to the culture medium. In some embodiments, the stimulant includes IL-2 and/or IL-15, for example, an IL-2 concentration of at least about 10 units/mL.

In another embodiment, T cells are separated from peripheral blood by lysing red blood cells and exhausting monocytes, for example by PERCOLL ^™ gradient centrifugation. Optionally, T cells can be separated from the umbilical cord. In any case, specific T cell subsets can be further separated using either positive or negative selection techniques.

Umbilical cord blood mononuclear cells isolated in this way can be depleted from cells expressing certain antigens, including but not limited to CD34, CD8, CD14, CD19, and CD56. Depletion of these cells can be accomplished using isolated antibodies, biological samples containing antibodies (such as ascites), antibodies bound to a physical carrier, and cell-binding antibodies.

Enriching T cell populations by negative selection can be achieved using a combination of antibodies targeting surface markers specific to the negatively selected cells. A preferred method is cell sorting and/or selection via negative magnetic immunoadhesion or flow cytometry using a mixture of monoclonal antibodies targeting cell surface markers present on the negatively selected cells. For example, to enrich CD4 ⁺ cells by negative selection, a mixture of monoclonal antibodies typically includes antibodies against CD14, CD20, CD11b, CD16, HLA-DR, and CD8.

To separate a desired cell population via positive or negative selection, the cell concentration and surface area (e.g., particles, such as beads) can be varied. In some embodiments, it is desirable to significantly reduce the volume of beads and cells mixed together (i.e., increase the cell concentration) to ensure maximum contact between cells and beads. For example, in one embodiment, a concentration of 2 billion cells/ml is used. In another embodiment, a concentration of 1 billion cells/ml is used. In other embodiments, a concentration greater than 100 million cells/ml is used. In other embodiments, cell concentrations of 10 million, 15 million, 20 million, 25 million, 30 million, 35 million, 40 million, 45 million, or 50 million cells/ml are used. In yet another embodiment, cell concentrations of 75 million, 80 million, 85 million, 90 million, 95 million, or 100 million cells/ml are used. In other embodiments, a concentration of 125 million or 150 million cells/ml can be used. Using high concentrations can lead to increased cell yield, cell activation, and cell expansion.

T cells can also be frozen after the washing step, without the need for monocyte removal. While not wishing to be bound by theory, freezing and subsequent thawing provide a more homogeneous product by removing granulocytes from the cell population and, to some extent, monocytes. After the washing step to remove plasma and platelets, the cells can be suspended in a freezing solution. While many freezing solutions and parameters are known in the art and would be useful in this context, in a non-limiting example, one method involves using PBS containing 20% DMSO and 8% human serum albumin, or other suitable cell freezing media. The cells are then frozen to -80°C at a rate of 1°C per minute and stored in the vapor phase of a liquid nitrogen tank. Other controlled freezing methods can be used, or uncontrolled freezing can be performed immediately at -20°C or in liquid nitrogen.

In one embodiment, the T cell population is comprised of cells such as peripheral blood mononuclear cells, umbilical cord blood cells, purified T cell populations, and T cell lines. In another embodiment, peripheral blood mononuclear cells comprise a T cell population. In yet another embodiment, purified T cells comprise a T cell population.

In some embodiments, T regulatory cells (Tregs) can be isolated from a sample. The sample may include, but is not limited to, cord blood or peripheral blood. In some embodiments, Tregs are isolated by flow cytometry sorting. Prior to isolation, Tregs in the sample can be enriched by any means known in the art. The isolated Tregs can be cryopreserved and/or amplified before use. Methods for isolating Tregs are described in U.S. Patent Nos. 7,754,482, 8,722,400, and 9,555,105, and U.S. Patent Application No. 13/639,927 (the contents of which are incorporated herein by reference in their entirety).

D. Methods for generating modified immune cells

This disclosure provides a method for producing or generating modified immune cells or their precursors (e.g., T cells).

In some embodiments, this disclosure provides a method for generating modified immune cells or precursor cells thereof, including introducing a CRISPR system into the immune cells or precursor cells, said CRISPR system comprising one or more polypeptides and/or nucleic acids capable of downregulating the expression of endogenous Fli1 genes.

In some implementations, nucleic acids are introduced into cells via expression vectors. Suitable expression vectors include lentiviral vectors, gamma retroviral vectors, foam virus vectors, adeno-associated virus (AAV) vectors, adenovirus vectors, modified hybrid viruses, naked DNA, including but not limited to transposon-mediated vectors such as Sleeping Beauty, Piggybak, and integrase-like vectors such as Phi31. Some other suitable expression vectors include herpes simplex virus (HSV) expression vectors and retroviral expression vectors.

In some embodiments, nucleic acids are introduced into cells via viral transduction. In some embodiments, viral transduction involves contacting immune cells or precursor cells with a viral vector containing nucleic acids. In some embodiments, the viral vector is an adeno-associated virus (AAV) vector. In some embodiments, the AAV vector includes a 5' ITR and a 3' ITR. In some embodiments, the AAV vector contains a woodchuck hepatitis virus post-transcriptional regulatory element (WPRE). In some embodiments, the AAV vector contains a polyadenylated (polyA) sequence. In some embodiments, the polyA sequence is a bovine growth hormone (BGH) polyA sequence.

Adenoviral expression vectors are based on adenoviruses, which have a low ability to integrate into genomic DNA but a high efficiency in transfecting host cells. The adenoviral sequence contained in an adenoviral expression vector is sufficient to: (a) support the packaging of the expression vector and (b) ultimately express the target sequence in the host cell. In some embodiments, the adenoviral genome is a 36 kb linear double-stranded DNA in which a foreign DNA sequence can be inserted to replace a large fragment of the adenoviral DNA, thereby creating the expression vector disclosed herein (see, for example, Danthinne and Imperiale, Gene Therapy (2000) 7(20):1707-1714).

Another expression vector is based on adeno-associated virus (AAV), which utilizes an adenovirus-coupled system. This AAV expression vector integrates into the host genome at a high frequency. It can infect non-dividing cells, thus enabling its use for gene delivery into mammalian cells, for example, in tissue cultures or in vivo. AAV vectors are infectious to a broad host range. Details regarding the generation and use of AAV vectors are described in U.S. Patent Nos. 5,139,941 and 4,797,368.

Retroviral expression vectors can integrate into the host genome, thereby delivering large amounts of foreign genetic material, infecting a broad spectrum of species and cell types, and being packaged into specialized cell lines. Retroviral vectors are constructed by inserting nucleic acids into specific locations within the viral genome, resulting in replication-defective viruses. Although retroviral vectors can infect multiple cell types, gene/protein integration and stable expression require host cell division.

Lentiviral vectors are derived from lentiviruses, which are complex retroviruses. In addition to the common retroviral genes gag, pol, and env, lentiviral vectors also contain other genes with regulatory and structural functions (see, for example, U.S. Patent Nos. 6,013,516 and 5,994,136). Some examples of lentiviruses include human immunodeficiency virus (HIV-1, HIV-2) and simian immunodeficiency virus (SIV). Lentiviral vectors are produced by repeatedly attenuating HIV virulence genes, for example, by deleting genes env, vif, vpr, vpu, and nef, thereby making the vector biologically safe. Lentiviral vectors can infect non-dividing cells and can be used for both in vivo and in vitro gene transfer and expression (see, for example, U.S. Patent No. 5,994,136).

Expression vectors containing nucleic acids of this disclosure can be introduced into host cells by any means known to those skilled in the art. If desired, the expression vector may include a viral sequence for transfection. Optionally, the expression vector may be introduced by fusion, electroporation, bio-projectile, transfection, lipid transfection, etc. Prior to the introduction of the expression vector, the host cells may be grown and amplified in a culture, followed by appropriate treatment for the introduction and integration of the vector. The host cells are then amplified and can be screened using markers present in the vector. Various markers are known to be usable in the art and may include hprt, neomycin resistance, thymidine kinase, hygromycin resistance, etc. As used herein, the terms “cell,” “cell line,” and “cell culture” are used interchangeably. In some embodiments, the host cell is an immune cell or its precursor, such as a T cell, NK cell, or NKT cell.

This disclosure also provides genetically modified cells in which endogenous Fli1 is disrupted. In some embodiments, the genetically modified cells are genetically modified T-lymphocytes (T cells), naive T cells (TN), memory T cells (e.g., central memory T cells (TCM), effector memory cells (TEM)), natural killer cells (NK cells), and macrophages capable of causing therapeutically relevant outcomes. In some embodiments, the genetically modified cells are autologous cells. In some embodiments, the modified cells are resistant to T cell exhaustion. In some embodiments, the modified cells are resistant to T cell dysfunction.

Modified cells can be generated by stable transfection of host cells with an expression vector including nucleic acids of this disclosure. Other methods for generating modified cells of this disclosure, without limitation, include chemical conversion methods (e.g., using calcium phosphate, dendritic macromolecules, liposomes, and/or cationic polymers), non-chemical conversion methods (e.g., electroporation, optical conversion, gene electrotransfer, and/or hydrodynamic delivery), and/or particle-based methods (e.g., impalefection, gene gun, and/or magnetic transfection). Transfected cells of this disclosure can be expanded in vitro.

Physical methods for introducing expression vectors into host cells include calcium phosphate precipitation, liposome transfection, particle bombardment, microinjection, electroporation, etc. Methods for generating cells comprising vectors and/or exogenous nucleic acids are well known in the art. See, for example, Sambrook et al. (2001), Molecular Cloning: A Laboratory Manual, ColdSpring Harbor Laboratory, New York. Chemical methods for introducing expression vectors into host cells include colloidal dispersion systems such as macromolecular complexes, nanocapsules, microspheres, beads, and lipid-based systems including oil-in-water emulsions, micelles, mixed micelles, and liposomes.

Suitable lipids are available from commercial sources. For example, dimyristic phosphatidylcholine (“DMPC”) is available from Sigma, St. Louis, MO; didicetyl phosphate (“DCP”) is available from K&K Laboratories (PlannView, NY); cholesterol (“Choi”) is available from Calbiochem-Behring; dimyristic phosphatidylglycerol (“DMPG”) and other lipids are available from Avanti Polar Lipids, Inc. (Birmingham, AL). Lipid stock solutions in chloroform or chloroform/methanol can be stored at approximately -20°C. Chloroform can be used as the sole solvent because it evaporates more readily than methanol. “Liposome” is a broader term encompassing a variety of single and multilayer lipid mediators formed by the formation of closed lipid bilayers or aggregates. Liposomes are characterized by having a vesicular structure with a phospholipid bilayer membrane and an internal aqueous medium. Multilayered liposomes consist of multiple lipid layers separated by an aqueous medium. They spontaneously form when phospholipids are suspended in excess aqueous solution. The lipid components undergo rearrangement before forming a closed structure, trapping water and dissolved solutes between the lipid bilayers (Ghosh et al., 1991 Glycobiology 5:505-10). Compositions with structures in solution that differ from normal vesicle structures are also included. For example, lipids can exist as micelles or simply as heterogeneous aggregates of lipid molecules. Lipofectamine-nucleic acid complexes are also considered.

Whether used to introduce exogenous nucleic acids into host cells or otherwise expose cells to the inhibitors of this disclosure, various assays can be performed to confirm the presence of nucleic acids in host cells. Such assays include, for example, molecular biological assays known to those skilled in the art, such as DNA blotting and RNA blotting, RT-PCR and PCR; and biochemical assays, such as those for detecting the presence or absence of a specific peptide, for example by immunoassays (ELISA and Western blotting) or by assays for identification agents described herein that fall within the scope of this disclosure.

In one embodiment, the nucleic acid introduced into the host cell is RNA. In another embodiment, the RNA is mRNA, which comprises in vitro transcribed RNA or synthetic RNA. RNA can be produced by in vitro transcription using a template generated by polymerase chain reaction (PCR). DNA of interest from any source can be directly converted into a template by PCR for in vitro synthesis of mRNA using appropriate primers and RNA polymerase. The DNA source can be, for example, genomic DNA, plasmid DNA, bacteriophage DNA, cDNA, synthetic DNA sequences, or any other suitable DNA source.

PCR can be used to generate templates for in vitro transcription of mRNA, which are then introduced into cells. Methods for performing PCR are well known in the art. Primers used for PCR are designed to have regions substantially complementary to the DNA region used as the PCR template. As used herein, “substantially complementary” is a nucleotide sequence in the primer sequence that is complementary to most or all of its bases. Substantially complementary sequences are capable of annealing or hybridizing with the intended DNA template under annealing conditions used for PCR. Primers can be designed to be substantially complementary to any portion of the DNA template. For example, primers can be designed to amplify portions of a gene that are typically transcribed in cells (open reading frames), including the 5’UTR and 3’UTR. Primers can also be designed to amplify portions of a gene that encode a specific domain of interest. In one embodiment, primers are designed to amplify the coding region of human cDNA, including all or part of the 5’UTR and 3’UTR. Primers used for PCR are generated by synthetic methods well known in the art. A “forward primer” is a primer containing a nucleotide region substantially complementary to a nucleotide on the DNA template upstream of the DNA sequence to be amplified. In this document, "upstream" refers to the 5' position of the DNA sequence being amplified relative to the coding strand. "Reverse primer" is a primer containing a nucleotide region that is substantially complementary to the double-stranded DNA template downstream of the DNA sequence to be amplified. "Downstream" in this document refers to the 3' position of the DNA sequence being amplified relative to the coding strand.

Chemical structures that promote RNA stability and/or translation efficiency can also be used. The RNA preferably has a 5'UTR and a 3'UTR. In one embodiment, the length of the 5'UTR is between 0 and 3000 nucleotides. The lengths of the 5'UTR and 3'UTR sequences added to the coding region can be altered by various methods, including, but not limited to, designing PCR primers that anneal different regions of the UTR. Using this method, those skilled in the art can modify the 5'UTR and 3'UTR lengths required to achieve optimal translation efficiency after transfection of transcribed RNA.

The 5'UTR and 3'UTR can be naturally occurring endogenous 5'UTR and 3'UTR of the gene of interest. Alternatively, these UTR sequences can be added by incorporating UTR sequences that are not endogenous to the gene of interest into the forward and reverse primers or by any other modification to the template. The use of UTR sequences that are not endogenous to the gene of interest can be used to alter RNA stability and/or translation efficiency. For example, it is known that AU-rich elements in the 3'UTR sequence reduce mRNA stability. Therefore, 3'UTRs can be selected or designed based on characteristics of UTRs known in the art to improve the stability of transcribed RNA.

In one embodiment, the 5'UTR may contain the Kozak sequence of an endogenous gene. Alternatively, when a non-endogenous 5'UTR for the gene of interest is added by PCR as described above, a shared Kozak sequence can be redesigned by adding this 5'UTR sequence. Kozak sequences can improve the translation efficiency of some RNA transcripts, but not all RNAs require a Kozak sequence for efficient translation. The requirement for a Kozak sequence for many mRNAs is known in the art. In other embodiments, the 5'UTR may be derived from an RNA virus whose RNA genome is stable in the cell. In other embodiments, various nucleotide analogs may be used in the 3'UTR or 5'UTR to prevent exonuclease degradation of the mRNA.

To enable RNA synthesis from a DNA template without gene cloning, a transcription promoter should be attached to the DNA template upstream of the sequence to be transcribed. When the sequence acting as the RNA polymerase promoter is added to the 5' end of the forward primer, the RNA polymerase promoter is incorporated into the PCR product upstream of the open reading frame to be transcribed. In one embodiment, as described elsewhere herein, the promoter is the T7 polymerase promoter. Other useful promoters include, but are not limited to, the T3 and SP6 RNA polymerase promoters. Common nucleotide sequences of the T7, T3, and SP6 promoters are known in the art.

In one implementation, the mRNA has a cap at the 5' end and a 3' poly(A) tail, which determines ribosome binding, translation initiation, and mRNA stability in the cell. On a circular DNA template (e.g., plasmid DNA), RNA polymerase produces a long polynucleotide product unsuitable for expression in eukaryotic cells. Transcription of plasmid DNA linearized at the 3' UTR end produces normal-sized mRNA, which has no effect in eukaryotic transfection even after post-transcriptional polyadenylation.

On a linear DNA template, phage T7 RNA polymerase can extend the 3' end of the transcript beyond the last base of the template (Schenborn and Mierendorf, Nuc Acids Res., 13:6223-36 (1985); Nacheva and Berzal-Herranz, Eur. J. Biochem., 270:1485-65 (2003).

Poly(A) fragments of the transcribed DNA template can be generated during PCR using a reverse primer containing a poly(T) tail (e.g., a 100T tail, the size of which can range from 50 to 5000T)), or after PCR by any other method (including but not limited to DNA ligation or in vitro recombination). The poly(A) tail also provides stability to the RNA and reduces its degradation. Generally, the length of the poly(A) tail is positively correlated with the stability of the transcribed RNA. In one embodiment, the poly(A) tail is between 100 and 5000 adenosine.

Using poly(A) polymerases, such as E. coli poly(A) polymerase (E-PAP), the poly(A) tail of RNA can be further extended after in vitro transcription. In one embodiment, increasing the length of the poly(A) tail from 100 nucleotides to between 300 and 400 nucleotides results in approximately a two-fold increase in RNA translation efficiency. Additionally, the attachment of different chemical groups at the 3' end can improve mRNA stability. This attachment can include modified/artificial nucleotides, aptamers, and other compounds. For example, ATP analogs can be incorporated into the poly(A) tail using poly(A) polymerase. ATP analogs can further enhance RNA stability.

The 5' cap also provides stability to the RNA molecule. In a preferred embodiment, the RNA produced by the methods disclosed herein includes a 5' cap. The 5' cap is provided using techniques known in the art and described herein (Cougot, et al., Trendsin Biochem. Sci., 29:436-444 (2001); Stepinski, et al., RNA, 7:1468-95 (2001); Elango, et al., Biochim. Biophys. Res. Commun., 330:958-966 (2005)).

In some implementations, RNA is electroporated into cells in the form of in vitro transcribed RNA. Any solute suitable for cell electroporation may be included—it may contain factors that promote cell permeability and viability, such as sugars, peptides, lipids, proteins, antioxidants, and surfactants.

The disclosed methods can be applied to modulate T cell activity in basic research and treatment in the fields of cancer, stem cells, acute and chronic infections and autoimmune diseases, including assessing the ability of genetically modified T cells to kill target cancer cells.

These methods also provide the ability to control expression levels over a wide range by changing, for example, the promoter or the amount of input RNA, thus enabling the individual regulation of expression levels. Furthermore, PCR-based mRNA generation technologies have greatly facilitated the design of mRNAs with different structures and combinations of their domains.

One advantage of the RNA transfection method disclosed herein is that RNA transfection is essentially transient and vector-free. RNA transgenes can be delivered into lymphocytes and expressed therein after a brief in vitro cell activation—as a minimal expression cassette without requiring any other viral sequences. Under these conditions, transgene integration into the host cell genome is impossible. Due to the high transfection efficiency of RNA and its ability to uniformly modify the entire lymphocyte population, cell cloning is not required.

Genetic modification of T cells using in vitro transcribed RNA (IVT-RNA) employed two different strategies, both of which have been tested in various animal models. Cells were transfected with the in vitro transcribed RNA via liposome transfection or electroporation. To achieve long-term expression of the transferred IVT-RNA, various modifications were employed to stabilize the IVT-RNA.

Several IVT vectors are known in the literature to be used in a standardized manner as templates for in vitro transcription and to be genetically modified in a way that produces stable RNA transcripts. The current approach in this field is based on a plasmid vector with the following structure: a 5' RNA polymerase promoter for RNA transcription, followed by a gene of interest with an untranslated region (UTR) at the 3' and/or 5' sides, and a 3' polyadenylated cassette containing 50–70 A nucleotides. Prior to in vitro transcription, the circular plasmid is linearized downstream of the polyadenylated cassette by a type II restriction enzyme (the recognition sequence corresponds to the cleavage site). Thus, the polyadenylated cassette corresponds to the subsequent poly(A) sequence in the transcript. This procedure results in some nucleotides remaining as part of the cleavage site after linearization and extending or masking the 3' poly(A) sequence. It is unclear whether this non-physiological overhang affects the amount of protein produced intracellularly by this construct.

On the other hand, RNA constructs are delivered into cells via electroporation. For example, see formulations and methods for electroporating nucleic acid constructs into mammalian cells taught in US 2004/0014645, US 2005/0052630A1, US 2005/0070841A1, US 2004/0059285A1, and US 2004/0092907A1. The various parameters required for electroporation of any known cell type, including the electric field strength, are generally known in relevant research literature and numerous patents and applications in this field. See, for example, US Patent Nos. 6,678,556, 7,171,264, and 7,173,116. Devices for therapeutic applications of electroporation are commercially available, such as the MedPulser ^™ DNA Electroporation Therapy System (Inovio/Genetronics, San Diego, Calif.), and are described in patents such as U.S. Patent Nos. 6,567,694, 6,516,223, 5,993,434, 6,181,964, 6,241,701, and 6,233,482. Electroporation can also be used for in vitro cell transfection, as described in, for example, US20070128708A1. Electroporation can also be used to deliver nucleic acids into cells in vitro. Therefore, electroporation-mediated delivery of nucleic acids (including expression constructs) into cells using any of the various available devices and electroporation systems known to those skilled in the art demonstrates exciting new means for delivering RNA of interest to target cells.

In some embodiments, immune cells (e.g., T cells) may be incubated or cultured before, during, and/or after the introduction of a nucleic acid molecule encoding a gene-editing agent (e.g., Cas9/gRNA RNP). In some embodiments, the method includes activating or stimulating cells with a stimulant or activator (e.g., anti-CD3/anti-CD28 antibody) before the introduction of the gene-editing agent, such as Cas9/gRNA RNP. In some embodiments, cells are allowed to rest prior to the introduction, for example, by removing any stimulant or activator. In some embodiments, the stimulant or activator and/or cytokines are not removed prior to the introduction.

E. Using cell modification treatment methods

The modified cells (e.g., T cells) described herein may be included in compositions for immunotherapy. These compositions may include pharmaceutical compositions and pharmaceutically acceptable carriers. A therapeutically effective amount of the pharmaceutical composition containing modified T cells may be administered.

In one aspect, this document provides a method for adoptive cell transfer therapy comprising administering the modified cells of this disclosure to a subject in need. In another aspect, this document provides a method for treating a disease or condition of a subject comprising administering a population of modified cells to the subject in need. Methods for treating a disease or condition of a subject in need are also included, comprising administering gene-edited modified cells (e.g., including downregulation of endogenous Fli1 expression) to the subject.

Methods of administering immune cells for adoptive cell therapy are known and can be used in combination with the provided methods and compositions. For example, adoptive T-cell therapy methods are described in U.S. Patent Application Publication No. 2003/0170238 to Gruenberg et al.; U.S. Patent No. 4,690,915 to Rosenberg; Rosenberg (2011) Nat Rev Clin Oncol. 8(10):577-85. See, for example, Themeli et al. (2013) Nat Biotechnol. 31(10):928-933; Tsukahara et al. (2013) Biochem Biophys Res Commun 438(1):84-9; Davila et al. (2013) PLoS ONE 8(4):e61338. In some implementations, cell therapy (e.g., adoptive T-cell therapy) is performed via autologous transfer, wherein cells are isolated from and/or otherwise prepared from the subject receiving the cell therapy, or derived from a sample originating from such a subject. Thus, in some aspects, cells are derived from the subject (e.g., a patient requiring treatment), and the cells are applied to the same subject after isolation and processing.

In some embodiments, cell therapy (e.g., adoptive T-cell therapy) is administered via allogeneic transfer, wherein cells are isolated from and/or otherwise prepared from a subject other than the recipient or eventual recipient of the cell therapy (e.g., a first subject). In such embodiments, the cells are then administered to a different subject of the same species, such as a second subject. In some embodiments, the first and second subjects are genetically identical. In some embodiments, the first and second subjects are genetically similar. In some embodiments, the second subject expresses the same HLA class or supertype as the first subject.

In some embodiments, the subject has been treated with a therapeutic agent targeting a disease or condition (e.g., tumor) prior to the administration of the cells or a cell-containing composition. In some aspects, the subject is refractory to or unresponsive to other therapeutic agents. In some embodiments, the subject has a persistent or relapsed disease, for example, following treatment with other therapeutic interventions, including chemotherapy, radiation, and/or hematopoietic stem cell transplantation (HSCT), e.g., allogeneic HSCT. In some embodiments, the administration is still effective in treating the subject despite resistance to other therapies.

In some embodiments, the subject responds to other therapeutic agents, and treatment with those agents reduces the disease burden. In some aspects, the subject initially responds to a therapeutic agent but exhibits a relapse of the disease or condition over time. In some embodiments, the subject does not relapse. In some such embodiments, the subject is identified as being at risk of relapse, such as being at high risk of relapse, and therefore the cells are administered prophylactically to, for example, reduce the likelihood of relapse or prevent relapse. In some aspects, the subject has not previously received treatment with other therapeutic agents.

In some embodiments, the subject has a persistent or relapsed disease, for example, after treatment with other therapeutic interventions, including chemotherapy, radiation, and/or hematopoietic stem cell transplantation (HSCT), such as allogeneic HSCT. In some embodiments, the subject is treated effectively even though the other therapies have become resistant.

The modified immune cells of this disclosure can be administered to animals, preferably mammals, and even more preferably humans, to treat cancer. Furthermore, the cells of this disclosure can be used to treat any cancer-related condition, particularly a cell-mediated immune response against one or more tumor cells, where treatment or ablation of the disease is desired. Types of cancer to be treated with the modified cells or pharmaceutical compositions of this disclosure include carcinomas, germ cell tumors, and sarcomas, and certain leukemias or lymphomas, benign and malignant tumors, and malignant tumors such as sarcomas, carcinomas, and melanomas. Other exemplary cancers include, but are not limited to, breast cancer, prostate cancer, ovarian cancer, cervical cancer, skin cancer, pancreatic cancer, colorectal cancer, kidney cancer, liver cancer, brain cancer, lymphoma, leukemia, lung cancer, thyroid cancer, etc. Cancer can be a non-solid tumor (such as a hematologic malignancy) or a solid tumor. Adult tumors/cancers and childhood tumors/cancers are also included. In one embodiment, the cancer is a solid tumor or a hematologic malignancy. In one embodiment, the cancer is carcinoma. In one embodiment, the cancer is a sarcoma. In one embodiment, the cancer is leukemia. In one embodiment, the cancer is a solid tumor.

Solid tumors are abnormal masses of tissue that do not typically contain cysts or fluid-filled areas. Solid tumors can be benign or malignant. Different types of solid tumors are named after the cell types that form them (such as sarcoma, carcinoma, and lymphoma). Examples of solid tumors (such as sarcoma and carcinoma) include fibrosarcoma, myxosarcoma, liposarcoma, chondrosarcoma, osteosarcoma and other sarcomas, synovoma, mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, colon cancer, malignant lymphoma, pancreatic cancer, breast cancer, lung cancer, ovarian cancer, prostate cancer, hepatocellular carcinoma, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, medullary thyroid carcinoma, papillary thyroid carcinoma, pheochromocytoma, sebaceous gland carcinoma, papillary carcinoma, papillary adenocarcinoma, medullary carcinoma, bronchial carcinoma, renal cell carcinoma, hepatocellular carcinoma, etc. Bile duct cancer, choriocarcinoma, Wilms' tumor, cervical cancer, testicular tumor, seminoma, bladder cancer, melanoma and CNS tumors (such as gliomas (e.g., brainstem glioma and mixed glioma), glioblastoma (also known as glioblastoma multiforme), astrocytoma, CNS lymphoma, germ cell tumor, medulloblastoma, schwannoma, craniopharyngioma, ependymoma, pineal tumor, hemangioblastoma, acoustic neuroma, oligodendroglioma, meningioma, neurocytoma, retinoblastoma and brain metastases).

Cancers that are amenable to the treatments performed using the methods disclosed herein include, but are not limited to, esophageal cancer, hepatocellular carcinoma, basal cell carcinoma (a form of skin cancer), squamous cell carcinoma (various tissues), bladder cancer (including transitional cell carcinoma (a malignant tumor of the bladder)), bronchial cancer, colon cancer, colorectal cancer, gastric cancer, lung cancer (including small cell lung cancer and non-small cell lung cancer), adrenocortical carcinoma, thyroid cancer, pancreatic cancer, breast cancer, ovarian cancer, prostate cancer, adenocarcinoma, sweat gland cancer, sebaceous gland cancer, papillary carcinoma, papillary adenocarcinoma, cystic adenocarcinoma, medullary carcinoma, renal cell carcinoma, ductal carcinoma in situ or bile duct carcinoma, choriocarcinoma, seminoma, embryonal carcinoma, Wilms' tumor, cervical cancer, uterine cancer, testicular cancer, osteoblastoma, epithelial carcinoma, and nasopharyngeal carcinoma.

Sarcomas for which treatments can be performed in accordance with the methods disclosed herein include, but are not limited to, fibrosarcoma, myxosarcoma, liposarcoma, chondrosarcoma, chordoma, osteosarcoma, osteosarcoma, angiosarcoma, endothelial sarcoma, lymphangiosarcoma, lymphangioendothelial sarcoma, synovial sarcoma, mesothelioma, Ewing's sarcoma, leiomyosarcoma, rhabdomyosarcoma and other soft tissue sarcomas.

In some exemplary embodiments, the modified immune cells of this disclosure are used to treat myeloma or conditions associated with myeloma. Examples of myeloma or conditions associated with myeloma include, but are not limited to, light chain myeloma, non-secreting myeloma, monoclonal gamopathy of undertermined significance (MGUS), plasmacytoma (e.g., solitary, multiple solitary, extramedullary plasmacytoma), amyloidosis, and multiple myeloma. In one embodiment, the method of this disclosure is used to treat multiple myeloma. In one embodiment, the method of this disclosure is used to treat refractory myeloma. In one embodiment, the method of this disclosure is used to treat relapsed myeloma.

In some exemplary embodiments, the modified immune cells of this disclosure are used to treat melanoma or melanoma-related conditions. Examples of melanoma or related conditions include, but are not limited to, superficial expanding melanoma, nodular melanoma, malignant nevus, acral lentigines melanoma, amelanotic malignant melanoma, or cutaneous melanoma (e.g., skin, eye, vulva, vagina, rectal melanoma). In one embodiment, the method of this disclosure is used to treat cutaneous melanoma. In one embodiment, the method of this disclosure is used to treat refractory melanoma. In one embodiment, the method of this disclosure is used to treat recurrent melanoma.

In other exemplary embodiments, the modified immune cells of this disclosure are used to treat sarcomas or sarcoma-related conditions. Examples of sarcomas or related conditions include, but are not limited to, angiosarcoma, chondrosarcoma, Ewing's sarcoma, fibrosarcoma, gastrointestinal stromal tumor, leiomyosarcoma, liposarcoma, malignant peripheral nerve sheath tumor, osteosarcoma, pleomorphic sarcoma, rhabdomyosarcoma, and synovial sarcoma. In one embodiment, the method of this disclosure is used to treat synovial sarcoma. In one embodiment, the method of this disclosure is used to treat liposarcomas, such as myxoid/round cell liposarcoma, differentiated/dedifferentiated liposarcoma, and pleomorphic liposarcoma. In one embodiment, the method of this disclosure is used to treat myxoid/round cell liposarcoma. In one embodiment, the method of this disclosure is used to treat refractory sarcomas. In one embodiment, the method of this disclosure is used to treat recurrent sarcomas.

As to the subject undergoing the therapy, the cells to be applied according to this disclosure may be autologous.

In some exemplary embodiments, the modified immune cells of this disclosure are used to treat an infection. In some embodiments, the infection is an acute infection. In some embodiments, the infection is a chronic infection. In some embodiments, the infection is a viral infection. In some embodiments, the methods of this disclosure are used to treat a disease, disorder, or infection selected from LCMV, HIV, hepatitis B, hepatitis C, malaria, or tuberculosis.

The application of the cells disclosed herein can be carried out in any convenient manner known to those skilled in the art. The cells of this disclosure can be administered to the subject via nebulization, injection, ingestion, infusion, implantation, or transplantation. The compositions described herein can be administered to the patient via artery, subcutaneous, intradermal, intratumorally, intratranodally, intramedullary, intramuscular, intravenous (i.v.), or intraperitoneal injection. In other cases, the cells of this disclosure can be injected directly into the site of inflammation, local disease site, lymph nodes, organs, tumors, etc.

In some embodiments, cells are administered at a desired dose, which in some aspects includes a desired dose or cell number or cell type (one or more) and/or a desired cell type ratio. Thus, in some embodiments, the cell dose is based on the total number of cells (or the number per kg of body weight) and a desired ratio of a single population or subtype, such as the CD4+ to CD8+ ratio. In some embodiments, the cell dose is based on the desired total number of cells (or the number per kg of body weight) in a single population or single cell type. In some embodiments, the dose is based on a combination of characteristics such as the desired total number of cells in a single population, the desired ratio, and the desired total number of cells.

In some embodiments, cell populations or cell subtypes (e.g., CD8 ⁺ T cells and CD4 ⁺ T cells) are administered within or within a permissible variation of the desired dose of total cells (e.g., the desired dose of T cells). In some aspects, the desired dose is the desired number of cells or the desired number of cells per unit body weight of the subject to which the cells are administered, for example, cells/kg. In some aspects, the desired dose is equal to or greater than the minimum number of cells or the minimum number of cells per unit body weight. In some aspects, in the total cells administered at the desired dose, individual populations or subtypes exist at or near the desired output ratio (e.g., the ratio of CD4 ⁺ to CD8 ⁺ ) or within a permissible variation or error of such a ratio.

In some embodiments, cells are administered within or within permissible differences in the desired dose (e.g., the desired dose of CD4+ cells and/or the desired dose of CD8+ cells) of one or more individual cell populations or cell subtypes. In some aspects, the desired dose is the desired number of cells of that subtype or population, or the desired number of such cells per unit body weight of the subject to which the cells are administered, e.g., cells/kg. In some aspects, the desired dose is equal to or greater than the minimum number of cells of that population or subtype, or equal to or greater than the minimum number of cells of that population or subtype per unit body weight. Therefore, in some embodiments, the dose is based on a desired fixed dose and desired ratio of total cells, and/or on a desired fixed dose of one or more (e.g., each) of individual subtypes or subpopulations. Therefore, in some embodiments, the dose is based on a desired fixed dose or minimum dose of T cells and a desired ratio of CD4 ⁺ to CD8 ⁺ cells, and/or on a desired fixed dose or minimum dose of CD4 ⁺ and/or CD8 ⁺ cells.

In some implementations, these cells, or individual populations of cell subtypes, are applied to the object in the range of approximately 1 million to approximately 100 billion cells, such as, for example, 1 million to approximately 50 billion cells (e.g., approximately 5 million cells, approximately 25 million cells, approximately 500 million cells, approximately 1 billion cells, approximately 5 billion cells, approximately 20 billion cells, approximately 30 billion cells, approximately 40 billion cells, or any two of the values defined above), such as approximately 10 million to approximately 100 billion cells (e.g., approximately 20 million cells, approximately 30 million cells, approximately 40 million cells, approximately 60 million cells). Cells, approximately 70 million cells, approximately 80 million cells, approximately 90 million cells, approximately 10 billion cells, approximately 25 billion cells, approximately 50 billion cells, approximately 75 billion cells, approximately 90 billion cells, or any two of the values defined above), and in some cases approximately 100 million cells to approximately 50 billion cells (e.g., approximately 120 million cells, approximately 250 million cells, approximately 350 million cells, approximately 450 million cells, approximately 650 million cells, approximately 800 million cells, approximately 900 million cells, approximately 3 billion cells, approximately 30 billion cells, approximately 45 billion cells) or any value within these ranges.

In some implementations, the dose of total cells and/or the dose of individual subpopulations of cells are in the following ranges: between ¹ x 10⁵ cells/kg and about ¹ x 10¹¹ cells/kg, ^10⁴ , and between ^10¹¹ cells/kg body weight, such as between ^10⁵ and ^10⁶ cells/kg body weight, for example, between 1 x ^10⁵ cells/kg body weight, 1.5 x ^10⁵ cells/kg body weight, 2 x ^10⁵ cells/kg body weight, or 1 x ^10⁶ cells/kg body weight. For example, in some implementations, cells are applied within or within one of the following error ranges: between ^10⁴ and ^10⁹ T cells/kg body weight, such as between ^10⁵ and ^{10⁶ T cells/kg body weight, for example, 1 x 10⁵} T cells/kg body weight, 1.5 x ^10⁵ T cells/kg body weight, ² x ^10⁵ T cells/kg body weight, or 1 x ^10⁶ T cells/kg body weight. In other exemplary embodiments, suitable dose ranges for modified cells used in the methods of this disclosure include, without limitation, about ¹ x 10⁵ cells/kg to about ¹ x 10⁶ cells/kg, about ¹ x 10⁶ cells/kg to about ¹ x 10⁷ cells/kg, about ¹ x 10⁷ cells/kg to about ¹ x 10⁸ cells/kg, about ¹ x 10⁸ cells/kg to about ¹ x 10⁹ cells/kg, about ¹ x 10⁹ cells/kg to about ¹ x 10¹⁰ cells/kg, and about ¹ x 10¹⁰ cells/kg to about ¹ x 10¹¹ cells/kg. In exemplary embodiments, a suitable dose for the methods of this disclosure is about ¹ x 10⁸ cells/kg. In exemplary embodiments, a suitable dose for the methods of this disclosure is about 1 x ^10⁷ cells/kg. In other embodiments, a suitable dose is about ¹ x 10⁷ total cells to about ⁵ x 10⁷ total cells. In some embodiments, a suitable dose is about ¹ x 10⁸ total cells to about 5 x ^10⁸ total cells. In some embodiments, a suitable dose is about 1.4 x ^10⁷ total cells to about 1.1 x ^10⁹ total cells. In an exemplary embodiment, a suitable dose for the method of this disclosure is about 7 x ^10⁹ total cells.

In some implementations, cells are applied within or within one of the following error ranges: between ^10⁴ and 10⁹ ^CD₄⁺ and/or ^CD₈⁺ cells/kg body weight, such as between ^10⁵ and ^{10⁶ CD₄⁺} and/or ^CD₈⁺ cells/kg body weight, for example, 1 x ^10⁵ CD₄⁺ and/or ^CD₈⁺ cells/kg, 1.5 x ^{10⁵ CD₄⁺} and/or ^CD₈⁺ cells/kg body weight, ^{2 x 10⁵ CD₄⁺ and /} or ^CD₈⁺ cells/kg body weight, or 1 x ^{10⁶ CD₄⁺} and/or ^CD₈⁺ cells/kg body weight. In some implementations, cells are applied within or within one of the following error ranges: greater than, and/or at least about 1 x ^10⁶ , about 2.5 x ^10⁶ , about 5 x ^10⁶ , about 7.5 x ^10⁶ , or about 9 x ^10⁶ CD4 ⁺ cells, and/or at least about 1 x ^10⁶ , about 2.5 x ^10⁶ , about 5 x ^10⁶ , about 7.5 x ^10⁶ , or about 9 x ^10⁶ CD8+ cells, and/or at least about 1 x ^10⁶ , about 2.5 x ^10⁶ , about 5 x ^10⁶ , about 7.5 x ^10⁶ , or about 9 x ^10⁶ T cells. In some implementations, cells are administered within or within one of the following error ranges: between approximately ^10⁸ and ^10¹² T cells or between approximately ^10¹⁰ and ^{10¹¹ T cells, between approximately 10⁸ and 10¹² CD⁴⁺ cells} or between approximately ^10¹⁰ and ^{10¹¹ CD⁴⁺} cells, and/or between ^{approximately 10⁸ and 10¹² CD⁸⁺} cells or between approximately ^10¹⁰ and ^{10¹¹ CD⁸⁺} cells.

In some embodiments, cells are administered within or within an acceptable range of the desired output ratio of multiple cell populations or subtypes (such as CD4+ and CD8+ cells or subtypes). In some aspects, the desired ratio can be a specific ratio or a range of ratios. For example, in some embodiments, the desired ratio (e.g., the ratio of CD4 ⁺ cells to CD8 ⁺ cells) is between equal to or about 5:1 and equal to or about 5:1 (or greater than or about 1:5 and less than or about 5:1), or between equal to or about 1:3 and equal to or about 3:1 (or greater than or about 1:3 and less than or about 3:1), such as between equal to or about 2:1 and equal to or about 1:5 (or greater than or about 1:5 and less than or about 2:1, such as equal to or about 5:1, 4.5:1, 4:1, 3.5:1, 3:1, 2.5:1, 2... :1, 1.9:1, 1.8:1, 1.7:1, 1.6:1, 1.5:1, 1.4:1, 1.3:1, 1.2:1, 1.1:1, 1:1, 1:1.1, 1:1.2, 1:1.3, 1:1.4, 1:1.5, 1:1.6, 1:1.7, 1:1.8, 1:1.9, 1:2, 1:2.5, 1:3, 1:3.5, 1:4, 1:4.5, or 1:5). In some respects, the difference is permissible within approximately 1%, approximately 2%, approximately 3%, approximately 4%, approximately 5%, approximately 10%, approximately 15%, approximately 20%, approximately 25%, approximately 30%, approximately 35%, approximately 40%, approximately 45%, and approximately 50% of the desired ratio, including any value between these ranges.

In some embodiments, the modified cells are administered to the recipient in a single or multiple doses. In some embodiments, the modified cells are administered in multiple doses, for example, once a week or every 7 days, once every 2 weeks or every 14 days, once every 3 weeks or every 21 days, once every 4 weeks or every 28 days. In an exemplary embodiment, a single dose of the modified cells is administered to the recipient. In an exemplary embodiment, a single dose of the modified cells is administered to the recipient via rapid intravenous infusion.

For the prevention or treatment of a disease, the appropriate dosage may depend on the type of disease to be treated, the type of cell or recombinant receptor, the severity and course of the disease, whether the cell is being administered for preventative or therapeutic purposes, prior therapy, the subject's clinical history and response to the cell, and the judgment of the attending physician. In some embodiments, the composition and cells are appropriately administered to the subject once or through a series of treatments.

In some embodiments, cells are administered as part of a combination therapy, such as simultaneously or sequentially with other therapeutic interventions (e.g., antibodies or modified cells or receptors, or agents such as cytotoxic agents or therapeutic agents). In some embodiments, cells are administered simultaneously or sequentially with one or more other therapeutic agents, or in combination with another therapeutic intervention. In some settings, cells are co-administered with another therapy at sufficiently close temporal proximity such that the cell population enhances the effect of one or more other therapeutic agents, or vice versa. In some embodiments, cells are administered prior to one or more other therapeutic agents. In some embodiments, cells are administered after one or more other therapeutic agents. In some embodiments, one or more other agents include cytokines, such as IL-2, thereby enhancing persistence, for example. In some embodiments, the method includes the administration of a chemotherapeutic agent.

In some embodiments, the modified cells of this disclosure (e.g., modified cells containing modified endogenous Fli1) may be administered to a subject in combination with immune checkpoint antibodies (e.g., anti-PD1, anti-CTLA-4, or anti-PDL1 antibodies). For example, the modified cells may be administered in combination with antibodies or antibody fragments targeting, for example, PD-1 (programmed death 1 protein). Examples of anti-PD-1 antibodies include, but are not limited to, pembrolizumab (formerly lambolizumab, also known as MK-3475) and nivolumab (BMS-936558, MDX-1106, ONO-4538) or antigen-binding fragments thereof. In some embodiments, the modified cells may be administered in combination with anti-PD-L1 antibodies or antigen-binding fragments thereof. Examples of anti-PD-L1 antibodies include, but are not limited to, BMS-936559, MPDL3280A (atezolizumab), and MEDI4736 (durvalumab, Imfinzi). In some embodiments, the modified cells may be administered in combination with an anti-CTLA-4 antibody or its antigen-binding fragment. Examples of anti-CTLA-4 antibodies include, but are not limited to, ipilimumab (trade name Yervoy). Other types of immune checkpoint modulators may also be used, including, but not limited to, small molecules, siRNA, miRNA, and CRISPR systems. Immune checkpoint modulators may be administered before, after, or concurrently with the modified cells. In some embodiments, combination therapy comprising immune checkpoint modulators may enhance the therapeutic efficacy of therapies comprising the modified cells of this disclosure.

Following cell administration, in some embodiments, the bioactivity of the modified cell population is measured, for example, by any of a variety of known methods. Evaluation parameters include the specific binding of the modified or native T cells or other immune cells to the antigen in vivo (e.g., by imaging) or in vitro (e.g., by ELISA or flow cytometry). In some embodiments, the ability of the modified cells to destroy target cells can be measured using any suitable method known in the art, such as the cytotoxicity assays described, for example, in Kochenderfer et al., J. Immunotherapy, 32(7):689-702 (2009), and Herman et al. J. Immunological Methods, 285(1):25-40 (2004). In some embodiments, cellular bioactivity is measured by determining the expression and/or secretion of one or more cytokines, such as CD107a, IFNy, IL-2, and TNF. In some aspects, bioactivity is measured by assessing clinical outcomes, such as a reduction in tumor burden or load.

In some implementations, the subject is provided with secondary treatment. Secondary treatment includes, but is not limited to, chemotherapy, radiation therapy, surgery, and medication.

In some embodiments, conditioning therapy may be administered to the subject prior to the administration of modified cells. In some embodiments, conditioning therapy includes administering an effective amount of cyclophosphamide to the subject. In some embodiments, conditioning therapy includes administering an effective amount of fludarabine to the subject. In a preferred embodiment, conditioning therapy includes administering an effective amount of a combination of cyclophosphamide and fludarabine to the subject. Administering conditioning therapy prior to modified cells may enhance the efficacy of the modified cells. A method for conditioning a patient for T-cell therapy is described in U.S. Patent No. 9,855,298 (which is incorporated herein by reference in its entirety).

In some embodiments, the specific dosage regimen of this disclosure includes a lymphodepletion step prior to the administration of the modified T cells. In an exemplary embodiment, the lymphodepletion step includes the administration of cyclophosphamide and/or fludarabine.

The cells of this disclosure can be administered according to dosage and route of administration, and sometimes determined in appropriate preclinical and clinical trials and experiments. Cell compositions can be administered multiple times at dosages within these ranges. Administration of the cells of this disclosure can be combined with other methods that may be used to treat desired diseases or conditions as determined by those skilled in the art.

In some embodiments, treatment for cytokine release syndrome (CRS), in which immune activation leads to elevated inflammatory cytokines, can be administered to the subject after the application of modified cells. Therefore, this disclosure provides appropriate CRS management strategies after a CRS diagnosis to alleviate the physiological symptoms of uncontrolled inflammation without diminishing the antitumor efficacy of the modified cells. CRS management strategies are known in the art. For example, systemic corticosteroids can be administered to rapidly reverse the symptoms of sCRS (e.g., grade 3 CRS) without impairing the initial antitumor response. In some embodiments, an anti-IL-6R antibody can be administered. An example of an anti-IL-6R antibody is tocilizumab, also known as atlizumab (marketed as Actemra or RoActemra), a monoclonal antibody approved by the U.S. Food and Drug Administration. Tocilizumab is a humanized monoclonal antibody targeting the interleukin-6 receptor (IL-6R). Administration of tocilizumab has been shown to reverse CRS almost immediately.

The modified immune cells disclosed herein can be used in the therapeutic methods described herein. In some embodiments, the modified immune cells comprise an insertion and/or deletion of a gene at the Fli1 locus capable of downregulating Fli1 expression. In some embodiments, when Fli1 is downregulated, the function of the immune cells is enhanced. For example, without limitation, when downregulated, Fli1 enhances tumor invasion, tumor killing, and/or immune cell resistance to immunosuppression. In some embodiments, when Fli1 is downregulated, T cell exhaustion is reduced or eliminated. In some embodiments, when Fli1 is downregulated, T cell dysfunction is reduced or eliminated.

In one aspect, this disclosure includes a method of treating cancer in a subject in need, comprising administering to the subject any of the modified immune cells or precursor cells disclosed herein. Another aspect of this disclosure includes a method of treating cancer in a subject in need, comprising administering to the subject any of the modified immune cells or precursor cells generated by the methods disclosed herein.

Another aspect of this disclosure includes a method for treating a disease or disorder in a subject in need, comprising administering modified cells to the subject, said modified cells comprising: CRISPR-mediated modification of an endogenous locus encoding Fli1, wherein said modification is capable of downregulating the gene expression of endogenous Fli1.

F. Cell screening methods

This disclosure provides methods for screening cells (e.g., T cells), such as the optimized in vivo CRISPR screening (OpTICS) method for T cells, as illustrated in Figures 1A, 8A, and 8B.

In one aspect, this disclosure provides a method for screening cells, comprising: i) introducing a Cas enzyme (or a nucleic acid encoding Cas) and an sgRNA library into activated cells; ii) administering the cells to infected or tumor-bearing mice; iii) isolating the cells from the infected mice; and iv) analyzing the cells.

In one aspect, this disclosure provides a method for screening T cells, comprising: i) introducing a Cas enzyme and an sgRNA library into activated T cells, ii) administering T cells to infected or tumor-bearing mice, iii) isolating T cells from infected mice, and iv) analyzing the T cells.

An sgRNA library should be interpreted as containing any number of sgRNAs targeting any number of genes of interest, including but not limited to any and all genes with annotated functional domains.

In some embodiments, the sgRNA library contains multiple sgRNAs targeting multiple transcription factors. In some embodiments, the multiple transcription factors include any of the transcription factors listed in Table 1. In some embodiments, each sgRNA targets the DNA-binding domain of each transcription factor. In some embodiments, the sgRNA library contains at least one sequence selected from SEQ ID NO: 1-675. In some embodiments, the sgRNA library consists of nucleotide sequences listed in SEQ ID NO: 1-675. The library should be interpreted as containing any and all numbers of sgRNAs selected from SEQ ID NO: 1-675. For example, the number of sgRNAs in the sgRNA library can be 1, 10, 20, 50, 100, 200, 300, 400, 500, 600, 675, or any and all numbers between 1 and 675.

In some implementations, the method screens T cells to assess T cell exhaustion. In some implementations, the method identifies novel transcription factors that regulate T _EFF and T _EX cell differentiation.

In some embodiments, the method is used for screening in tumor systems, i.e., for identifying genes of interest in tumors/cancers. In some embodiments, the method screens B cells to assess memory B cell and plasma cell formation. In some embodiments, the method screens hematopoietic stem cells or tissue stem cells to assess stem cells and related lineages.

In some embodiments, the cell analysis includes methods selected from sequencing, PCR, MACS, and FACS. In some embodiments, sequencing reveals targets of interest. In some embodiments, drugs are designed to target the targets of interest. In some embodiments, when a drug is administered to T cells, at least one T cell response is increased or induced. In some embodiments, during the analysis, a CRISPR score (CS) is calculated, for example, as shown in Figure 1A.

In some implementations, approximately ¹ x 10⁵ T cells are administered to the infected mouse.

G. Pharmaceutical compositions and formulations

The present disclosure also provides immune cell populations and compositions containing and/or enriching such cells. Among the compositions are pharmaceutical compositions and formulations for administration, such as those for adoptive cell therapy. Treatment methods for administering the cells and compositions to a subject (e.g., a patient) are also provided.

Compositions comprising cells for administration are also provided, comprising pharmaceutical compositions and formulations, such as unit dosage form compositions, which comprise a number of cells administered at a given dose or in a portion thereof. Pharmaceutical compositions and formulations typically comprise one or more optional pharmaceutically acceptable carriers or excipients. In some embodiments, the composition comprises at least one other therapeutic agent.

The term "pharmaceutical formulation" refers to a formulation in which the biological activity of the active ingredient contained therein is effective and without any other components that would have unacceptable toxicity to the subject to which the formulation will be administered. "Pharmaceutically acceptable carrier" refers to a component in a pharmaceutical formulation that, apart from the active ingredient, is non-toxic to the subject. Pharmaceutically acceptable carriers include, but are not limited to, buffers, excipients, stabilizers, or preservatives. In some aspects, the choice of carrier is determined in part by the specific cell and/or method of administration. Therefore, a variety of suitable formulations exist. For example, a pharmaceutical composition may contain a preservative. Suitable preservatives may include, for example, methylparaben, propylparaben, sodium benzoate, and benzalkonium chloride. In some aspects, a mixture of two or more preservatives is used. Preservatives or mixtures thereof are typically present in an amount from about 0.0001% to about 2% by weight of the total composition. For example, Remington's Pharmaceutical Sciences, 16th edition, Osol, A.Ed. (1980) describes carriers. Pharmaceutically acceptable carriers at the doses and concentrations used are generally non-toxic to the recipient and include, but are not limited to: buffers such as phosphates, citrates, and other organic acids; antioxidants, including ascorbic acid and methionine; preservatives (such as octadecyl dimethyl benzyl ammonium chloride; hexamethyl ammonium chloride; benzalkonium chloride; benzyl chloride; phenol, butanol, or benzyl alcohol; alkyl esters of p-hydroxybenzoate, such as methylparaben or propylparaben; catechol; resorcinol; cyclohexanol; 3-pentanol; and m-cresol); low molecular weight (less than about 10). (Residues) polypeptides; proteins, such as serum albumin, gelatin, or immunoglobulins; hydrophilic polymers, such as polyvinylpyrrolidone; amino acids, such as glycine, glutamine, asparagine, histidine, arginine, or lysine; monosaccharides, disaccharides, and other carbohydrates, including glucose, mannose, or dextrin; chelating agents, such as EDTA; sugars, such as sucrose, mannitol, trehalose, or sorbitol; salt-forming counterions, such as sodium; metal complexes (e.g., zinc-protein complexes); and/or nonionic surfactants, such as polyethylene glycol (PEG).

In some aspects, a buffer is included in the composition. Suitable buffers include, for example, citric acid, sodium citrate, phosphoric acid, potassium phosphate, and various other acids and salts. In some aspects, a mixture of two or more buffers is used. The buffer or mixture thereof is typically present in an amount of about 0.001% to about 4% by weight of the total composition. Methods for preparing administerable pharmaceutical compositions are known. Exemplary methods are described in more detail, for example, in Remington: The Science and Practice of Pharmacy, Lippincott Williams &Wilkins; 21st ed. (May 1, 2005).

The formulation may include an aqueous solution. The formulation or composition may also contain more than one active ingredient, which is indicated for a specific indication, disease, or condition for cell therapy, preferably with an activity complementary to that of the cells, wherein the respective activities do not adversely affect each other. Such active ingredients are suitably present in a combination of amounts effective for the intended purpose. Therefore, in some embodiments, the pharmaceutical composition further includes other pharmaceutically active agents or drugs, such as chemotherapeutic agents, for example, asparaginase, busulfan, carboplatin, cisplatin, daunorubicin, doxorubicin, fluorouracil, gemcitabine, hydroxyurea, methotrexate, paclitaxel, rituximab, vinblastine, and/or vincristine. In some embodiments, the pharmaceutical composition contains an amount of cells effective in treating or preventing a disease or condition (e.g., a therapeutically effective amount or a preventatively effective amount). In some embodiments, therapeutic or preventative efficacy is monitored by periodic evaluation of the treated subject. The desired dose may be delivered by a single bolus administration of cells, multiple bolus administration of cells, or continuous infusion administration of cells.

Formulations include those administered orally, intravenously, intraperitoneally, subcutaneously, pulmonaryly, percutaneously, intramuscularly, intranasally, or orally, sublingually, or as suppositories. In some embodiments, cell populations are administered parenterally. As used herein, the term "parenterally" includes intravenous, intramuscular, subcutaneous, rectal, vaginal, and intraperitoneal administration. In some embodiments, cells are administered to the subject via peripheral systemic delivery, via intravenous injection, intraperitoneal injection, or subcutaneous injection. In some embodiments, the composition is provided as a sterile liquid formulation, such as an isotonic aqueous solution, suspension, emulsion, dispersion, or viscous composition, which may be buffered to a selected pH in some respects. Liquid formulations are generally easier to prepare than gels, other viscous compositions, and solid compositions. Additionally, liquid compositions are easier to administer, especially by injection. On the other hand, viscous compositions can be formulated within a suitable viscosity range to provide prolonged contact with a particular tissue. Liquid or viscous compositions may contain a carrier, which may be a solvent or dispersion medium containing, for example, water, brine, phosphate-buffered saline, polyols (e.g., glycerol, propylene glycol, liquid polyethylene glycol) and suitable mixtures thereof.

Sterile injectable solutions can be prepared by incorporating cells into a solvent, such as by mixing with a suitable carrier, diluent, or excipient (e.g., sterile water, physiological saline, glucose, dextrose, etc.). The composition may contain excipients such as wetting agents, dispersants, or emulsifiers (e.g., methylcellulose), pH buffers, gelling or viscosity-enhancing additives, preservatives, flavoring agents, and/or colorants, depending on the route of administration and the desired formulation. In some respects, standard texts can be consulted for the preparation of suitable formulations.

Various additives can be added to enhance the stability and sterility of the composition, including antimicrobial preservatives, antioxidants, chelating agents, and buffers. Various antimicrobial and antifungal agents, such as parabens, chlorobutanol, phenol, and sorbic acid, can ensure protection against microbial action. The absorption of injectable drug forms can be prolonged by using agents that delay absorption (e.g., aluminum monostearate and gelatin).

Preparations intended for in vivo administration are typically sterile. Sterility can be easily achieved, for example, through filtration using a sterile filter membrane.

The contents of any articles, patents and patent applications, and all other documents and information available electronically as mentioned or cited herein are hereby incorporated in their entirety by reference, to the same extent that each individual publication is specifically and independently incorporated by reference. The applicant reserves the right to incorporate any and all materials and information from any such articles, patents, patent applications or other entities and electronic documents into this application.

Although this disclosure has been described with reference to specific embodiments thereof, those skilled in the art will understand that various changes and equivalent substitutions can be made without departing from the true spirit and scope of the invention. It will be apparent to those skilled in the art that other suitable modifications and alterations can be made to the methods described herein using suitable equivalents without departing from the scope of the embodiments disclosed herein. Furthermore, various modifications can be made to adapt specific circumstances, materials, composition, processes, or one or more method steps to the purpose, spirit, and scope of this disclosure. All such modifications are intended to fall within the scope of the appended claims. Certain embodiments have now been described in detail and will become clearer from the following examples, which are included for illustrative purposes only and are not intended to be limiting.

Experimental Examples

The invention will now be described with reference to the following embodiments. These embodiments are provided for illustrative purposes only, and the invention is not limited to these embodiments, but covers all variations that will become apparent from the teachings provided herein.

Materials and methods

Mice: CD4CRE, LSL-Cas9-GFP, and constitutive-Cas9-GFP mice were purchased from Jackson Laboratory. LSL-Cas9-GFP mice were bred by mating with CD4CRE mice and TCR transgenic P14 C57BL/6 mice (a TCR specific to LCMV DbGP33–41), and pre-backcrossing was performed for more than 6 generations. Constitutive-Cas9-GFP mice were bred by mating with TCR transgenic P14 C57BL/6 mice. Constitutive-Cas9-GFP mice were bred in cages for recipient use. 6-8 week old C57BL/6Ly5.2CR(CD45.1) or C57BL/6(CD45.2) mice were purchased from NCI. 6-week old C57BL/6(CD45.2) mice were purchased from Jackson Laboratory. 5-7 week old Rag2-/-C7BL/6 mice were purchased from Jackson Laboratory. LCMV challenge recipient mice were obtained from the NCI unless otherwise indicated in the legend. Both male and female mice were used. All mice were used in accordance with the guidelines of the Institutional Animal Care and Use Committee of the University of Pennsylvania.

Experimental model

LCMV infection: Mice were infected intraperitoneally (ip) with 2 × ^10⁵ plaque-forming units (PFU) Arm or intravenously (iv) with 4 × ^10⁶ PFU Cl13. LCMV Cl13 plaque assays were performed to detect viral load as previously described (Pauken et al., 2016). Essentially, tissue homogenates were incubated on adherent Vero cells for 1 hour with a medium containing serum dilutions of 1:10, ¹ :10², 1: ^10³ , or homogenate tissue dilutions of ^1:10 , 1: ^10² , 1: ^10³ , 1:10⁴, 1: ^10⁵ , and 1: ^10⁶ . Cells were covered with a 1:1 mixture of medium and 1% agarose and cultured for 4 days. Plaques (PFUs) were counted after 16 hours of covering with a 9.5:9.5:1 mixture of medium:1% agarose:neutral red.

Listeria monocytogenes (LM) infection: After overnight culture in brain heart infusion (BHI) medium, the concentration of LM expressing DbGP33 (LM-gp33) was measured by optical density (OD) (1 OD refers to 8 × ^10⁸ LM-gp33). Each recipient mouse was intravenously (iv) infected with 1 × ^10⁵ CFU of LM-gp33. Adjusted survival was based on the remaining mice that were euthanized above the 30% weight reduction cutoff by the Committee on Compulsory Laboratory Animal Management and Use (IACUC). Colony formation per unit of LM-gp33 was calculated using 2% agarose plates containing complete BHI medium for bacterial load calculation. Infected organs were pulverized in 1 ml of BHI medium, and 20 μL (2%) of the organ was collected. Prepare BHI culture medium dilutions of infected organs at ratios of 1:10, 1:102, 1:103, 1:104, 1:105, and 1:106, and plate them onto BHI agarose plates. After incubating the plates at 37°C for 16 hours, count the colonies.

Influenza PR8 Infection: Mice were intranasally (i.n.) infected with the PR8 strain expressing DbGP33 (PR8-gp33) at a dose of 3.0 LD50. Mice were anesthetized prior to i.n. infection. Viral RNA levels were calculated by qPCR detection of PR8 virus as previously described (Laidlaw et al., (2013) PLOS Pathogens 9, e1003207). Total RNA (including host and viral RNA) was purified from the lungs and paired spleens of PR8-GP33-infected mice and then reverse transcribed using random primers. Real-time quantitative PCR was performed on cDNA targeting the influenza PA protein, with three technical replicates. Influenza viral RNA levels were normalized using the influenza PA protein cDNA standard.

Tumor metastasis: B16F10 melanoma cells expressing DbGP33 (B16F10-gp33, (Prévost-Blondeletal., (1998) The Journal of Immunology 161, 2187–2194) were maintained at 37°C in DMEM medium supplemented with 10% FBS, penicillin, streptomycin, and L-glutamine. Tumor cells were subcutaneously injected into the flanks of Rag2-/- mice at a rate of 1 × ^10⁵ cells/recipient and into the flanks of Cas9+B6 mice at a rate of 2 × ^10⁵ cells/recipient. Activated sgRNA+C9P14 cells were sorted and transfected into recipient mice at a rate of 1 × ^10⁶ cells/recipient (for Rag2-/-) or 3 × ^10⁶ cells/recipient (for Cas9+). Tumor size was measured using digital calipers every 2–3 days post-inoculation.

Vector Construction and sgRNA Cloning: In this study, SpCas9 sgRNA was expressed using pSL21-VEX or pSL21-mCherry (U6-sgRNA-EFS-VEX or U6-sgRNA-EFS-mCherry). To generate pSL21-VEX or pSL21-mCherry, the U6-sgRNA expression cassette was cloned from LRG2.1 PCR into the retroviral vector MSCV-Neo, and then the Neo selection marker was exchanged using the VEX or mCherry fluorescent reporter gene. The sgRNA was cloned by annealing two DNA oligomers and ligating T4 DNA into the BBSI-digested pSL21-VEX or pSL21-mCherry vector. To improve the transcription efficiency of the U6 promoter, a 5’G nucleotide was added to the design of all sgRNA oligomers that did not yet start with 5’G. Runx1 and Runx3 constructs were constructed on MIGR or MSCV mCherry constructs, with empty MIGR or MSCV-mCherry used as controls for these vectors.

Cell Culture and In Vitro Stimulation: CD8 T cells were purified from spleen using the EasySep Mouse CD8+ T Cell Isolation Kit (STEMCELL Technologies) via negative selection, following the manufacturer's instructions. Cells were stimulated with 100 U/mL recombinant human IL-2, 1 μg/mL anti-mouse CD3ε, and 5 μg/mL anti-mouse CD28 in RPMI-1640 medium containing 10% fetal bovine serum (FBS), 10 mM HEPES, 100 μM non-essential amino acids (NEAA), 50 U/mL penicillin, 50 μg/mL streptomycin, and 50 μM β-mercaptoethanol.

Retroviral vector (RV) experiments: RVs were generated in 293T cells using Lipofectamine 3000 via MSCV and pCL-Eco plasmid. RV transduction was performed as described (Kurachi et al., (2017) Nature Protocols, 12:9 12, 1980–1998). Briefly, CD8+ T cells were purified from the spleen of P14 mice using the EasySep™ mouse CD8+ T cell isolation kit. After 18–24 hours of in vitro stimulation, P14 cells were transduced with RV (0.5 μg/ml) in the presence of polybrene (0.5 μg/ml) during spin infection (2,000 g for 60 minutes at 32°C), prior to incubation at 37°C—6 hours for single RV and sgRNA libraries, or 12 hours for dual RVs. RV-transduced P14 cells were adopted into recipient mice that were infected 24–48 hours prior to transfer.

Flow cytometry and sorting: For mouse experiments, tissues were processed as described to obtain single-cell suspensions, and the cells were stained (Wherry et al., (2003) Nature Immunology 2006 7:12 4,225–234). Mouse cells were stained with LIVE/DEAD cell staining agent (Invitrogen) and antibodies targeting surface or intracellular proteins. Intracellular cytokine staining was performed after 5 hours of in vitro stimulation with GP33-41 peptide in the presence of GolgiPlug, GolgiStop, and anti-CD107a. After stimulation, cells were stained with surface antibodies according to the manufacturer's instructions, then fixed with fixation/permeation buffer, and then stained with intracellular antibodies against TNF, IFN-γ, and MIP1α using permeation wash buffer. Flow cytometry was performed using an LSRII. Cell sorting experiments were performed using a BD-Aria sorter—which has a 70-micron nozzle and a 4°C circulating cooling system—for sequencing, Western blotting, and TIDE assays.

For sorting in transfer experiments, optimized sorting of RV+ cells was performed using a BD Aria sorter set to 37°C and a 100-micron nozzle at a flow rate below 3.0. During sorting, 3 x ^10⁶ cells were concentrated in 300 μL of 10% pure RPMI containing 100 U/mL recombinant human IL-2. Collection tubes containing 10% pure RPMI (100 U/mL IL-2) were preheated to 37°C. Sorted cells were washed with pure RPMI warmed to 37°C before transfer to the recipient.

TIDE assay: Frozen at least 1 × ^10⁴ Cas9+sgRNA+T cell pellets. Genomic DNA was isolated from these samples using the QIAmp DNA Mini kit. TIDE PCR was performed on each sample using 2x Phusion Flash High-Fidelity PCR Master Mix and primers designed around the genomic region targeting the sgRNA to extract the guiding region from the genomic DNA; the resulting products were then gel-verified, PCR-purified, and sent for Sanger sequencing.

Western blot: 2 × ^10⁵ T cells were sorted using a FACS system and cryoprecipitated. Proteins were extracted from these samples and denatured by boiling at 95°C in 2X working loading buffer (1M Tris-HCl, 10% SDS, glycerol, 10% bromophenol blue). Lysates were run on a 10% SDS-PAGE gel and then transferred to a nitrocellulose membrane. Staining was performed overnight with Fli1 (1:200) and GAPDH (1:1000) antibodies, followed by a second staining with 1:5000 antibodies the following day.

OpTICS Screening

sgRNA candidate selection: 271 TFs that met the following criteria were selected: 1) ranked among the top 50 differentially expressed in (Doering et al., (2012) Immunity 37, 1130–1144) and (Philip et al., (2017) Nature 2017 545:7652 545, 452–456); 2) ranked among the top 10 differentially expressed TF motifs in previously described (Sen et al., (2016) Science 354, 1165–1169), D8 Arm, and D8 Cl13; 3) involved top immunomodulatory families such as IRF and STAT proteins. 120 TFs were manually selected to be included in the TF library based on the following criteria: 1) those with known functions in CD8 T cells; 2) those TF family members associated with immune function, such as IRF, STAT, and Smad; 3) those TFs with the most significant differences in RNA expression in published CD8 T cell datasets; and 4) those TFs with the highest motif enrichment in ATAC-seq data from previous CD8 T cell datasets.

Library Construction: Based on domain sequence information retrieved from the NCBI Conserved Domains Database, 4-5 sgRNAs were designed for each TF's single DNA-binding domain or other functional domain. All sgRNA oligomers, including positive and negative control sgRNAs, were synthesized by Integrated DNA Technologies (IDT) and merged at equimolar concentrations. The merged sgRNA oligomers were then amplified by PCR and cloned into the BsmBI-digested SL21 vector using the Gibson Assembly kit. To verify the identity and relative representativeness of the sgRNAs in the merged plasmids, deep sequencing analysis was performed on a MiSeq system. We confirmed that 100% of the designed sgRNAs were cloned into the SL21 vector, and >95% of the individual sgRNA constructs had abundances within 5-fold of the mean.

Mouse experimental workflow: On day 0, C9P14 cells were isolated from the spleen and lymph nodes of CD45.2 ⁺ C9P14 mice and treated with anti-CD3/CD28 and IL-2 according to the standard T cell activation protocol; on the same day, naive CD45.1 ⁺ recipient mice were infected with LCMV. At D1 pi, activated C9P14 cells were transduced via an RV-sgRNA library and incubated for 6 hours before washing off the RV supernatant. After 18–24 hours, the transduced sgRNA ⁺ Cas9 ⁺ cells were sorted. Then, before any selection, 10% of the sgRNA+Cas9+ T cells were frozen as a baseline (T0 time point) control at D2, while 90% of the cells were transferred to infected recipients (up to 1 x ^10⁵ cells/recipient). At T1 time point (D8 in the figure), sgRNA ⁺ Cas9 ⁺ CD45.2 ⁺ T cells were sorted from multiple organs of the recipients.

Isolation library construction and MiSeq processing: To quantify sgRNA abundance at reference and end time points, sgRNA cassettes were amplified from genomic DNA using high-fidelity polymerase. End repair of the PCR products was performed using T4 DNA polymerase, DNA polymerase I, the large (Klenow) fragment, and T4 polynucleotide kinase. Next, 3'A-protrusions were added to the ends of the blunt-ended DNA fragments using the Klenow fragment (3'-5' exo-). The DNA fragments were ligated to custom barcodes for increased diversity using a Quick ligation kit. Illumina paired-end sequencing adaptors were then attached to the barcoded ligated products via PCR reactions using high-fidelity polymerase. The final products were quantified using a Bioanalyzer AgilentDNA 1000 and pooled together in equimolar ratios, and then paired-end sequencing was performed using MiSeq (Illumina) and MiSeq Reagent Kit V3 150 cycles (Illumia).

Data Processing: Sequencing data were split into individual samples (de-multiplexed) and trimmed to contain only sgRNA sequence cassettes. Read counts for each individual sgRNA were calculated in mismatch-free condition and compared to the sequence of a previously described reference sgRNA (Shi et al., (2015) Nature Biotechnology 2015 33:6 33,661–667). Data for each sample were normalized to the same read count. Waterfall Plot (Fig. 1B): For each gene, the average of the log2 fold change of multiple sgRNAs was calculated. Heatmap (Fig. 1C): For each gene, the average of the log10 fold change of multiple sgRNAs was calculated. Quantile normalization was performed across conditions in the conditional gene matrix to ensure a uniform value distribution for each condition. Genes were sorted by the average of each row. Histogram (Fig. 1D): For each condition, the background (grey bars and histogram) of sgRNAs for all genes was plotted. The 5% and 95% intervals were extracted using the 5th and 95th percentiles of the background values. The red bars show the log fold change (or control) of a gene's sgRNA.

RNA sequencing

Experimental workflow: CD8 T cells were isolated from the spleen of infected recipients at Cl13 D8 pi. VEX ⁺ GFP ⁺ cells were sorted using FACS to a purity >95%. RNA was isolated using the QIAGEN RNeasy Micro kit, ² x 10⁴ cells per sample. cDNA libraries were generated using the SMARTSeq V4 Ultra Low kit. The libraries were quantified by qPCR using the KAPA Library Quant kit (KAPABiosystems). Normalized libraries were pooled, diluted to 1.8 pg/ml, loaded onto a TG NextSeq 500/550 Mid Output Kit v2 (150 cycles, 130M readout, Illumina), and paired-end sequencing was performed on a NextSeq 550 (Illumina). The estimated readout depth for each sample was 15M readout.

Data processing: The raw FASTQ files from RNAseq paired-end sequencing were aligned with a GRCm38/mm10 reference genome using Kallisto (https://pachterlab.github.io/kallisto/). Sequencing reads for 19,357 genes and 8 samples were obtained. Genes with zero reads in more than three conditions were filtered out. After this step, 13,628 genes remained. Differential expression analysis was then performed using the DESeq 2 package.

Significant differences in the expression of 1440 genes were found between the two conditions, with BH-corrected P values < 0.05. GO enrichment analysis was performed using ClusterProfiler. The top 20 most enriched pathways are shown in the figure. GSEA was performed using BroadInstitute software (https://www.broadinstitute.org/gsea/index.jsp). Enrichment scores were calculated by comparing the sgCtrl and sgFli1 groups. _{T EX} precursor gene features were obtained from (Chen et al., (2019)Immunity, 51 6, 970-972). T _EFF gene features were obtained from (Bengsch et al., (2018)Immunity 48, 1029–1045.e5).

ATAC sequencing

Experimental workflow: ATACseq sample preparation was performed with minor adjustments as described in (Buenrostro et al., 2013). VEX ⁺ GFP ⁺ cells were sorted using FACS to a purity >95%. The sorted cells (2.5 × ^10⁴ ) were washed twice in cold PBS and resuspended in 50 μl of cold lysis buffer (10 nM Tris-HCl, pH 7.4, 10 mM NaCl, 3 mM MgCl₂, 0.1% Tween). The lysate was centrifuged (750 x g, 10 min, 4 °C) and the nuclei were resuspended in 50 μl of transposable reaction mixture (TD buffer [25 μl], Tn5 transposase [2.5 μl], and nuclease-free water [22.5 μl]; (Illumina)) and incubated at 37 °C for 30 min. The transposable DNA fragments were purified using a Qiagen Reaction MiniElute kit, barcoded using a NEXTERA dual-index (Illumina) scanner, and amplified by PCR for 11 cycles using NEBNext high-fidelity 2x PCR master mix (NewEngland Biolabs). The PCR products were purified using a PCR purification kit (Qiagen), and the amplified fragment size was verified using a high-sensitivity D1000 ScreenTapes (Agilent Technologies) on a 2200 TapeStation (Agilent Technologies).

Library quantification was performed using the KAPA Library Quant kit (KAPABiosystems) via qPCR. Normalized libraries were pooled, diluted to 1.8 pg/ml, loaded onto a TG NextSeq 500/550 Mid Output Kit v2 (150 cycles, 130M readout, Illumina), and paired-end sequencing was performed on a NextSeq 550 (Illumina). The estimated readout depth for each sample was 10M readout.

Data Processing: Raw ATACseq FASTQ files from paired-end sequencing were processed using scripts available in the repository (https://github.com/wherrylab/jogiles_ATAC). Samples were aligned to a GRCm38/mm10 reference genome using Bowtie2. Samtools was used to remove unmapped, unpaired mitochondrial reads. ENCODE blacklist regions were also removed (https://sites.google.com/site/anshulkundaje/projects/blacklists). PCR replicates were removed using Picard. Peak calling was performed using MACS v2 (FDR q value 0.01). For each experiment, peaks from all samples were combined to create a joint peak list, and overlapping peaks were merged using BedToolsmerge. BedTools coverage was used to determine the number of reads in each peak. Unless otherwise instructed, after DESeq2 normalization, differentially accessible regions were identified using an FDR cutoff value <0.05. Motif enrichment on the peaks with discrepancies between the sgCtrl and sgFli1 groups was calculated using HOMER (default parameters). Transcription binding site prediction analysis was performed using known motif discovery strategies.

CUT&RUN

Experimental workflow: CUT&RUN experiments were performed as previously described (Skene et al., (2018) Nature Protocols 2017 12:913,1006–1019), with adjustments made. In short, ² x 10⁵ sorted cells were washed twice in 1.5 ml tubes with 1 ml of cold wash buffer (20 mM HEPES-NaOH pH 7.5, 150 mM NaCl, 0.5 mM spermidine, and a mixture of protease inhibitors from Sigma). The cells were then resuspended in 1 ml of cold wash buffer and incubated with 10 μl of BioMagPlus concanavalin A (Bangs laboratories) at 4 °C for 25 min to allow cell binding. The tubes were placed on a magnetic stand, and the liquid was removed after the solution became clear. Add 250 μl of antibody in cold antibody buffer (20 mM HEPES-NaOH pH 7.5, 150 mM NaCl, 0.5 mM spermidine, 2 mM EDTA, 0.1% digitalis saponin, and a mixture of protease inhibitors from Sigma) to the tube and incubate overnight at 4°C. The next day, after washing the cells once with 1 ml of cold wash buffer, add 250 μl of protein A-MNase (pA-MN) in cold digitalis saponin buffer (20 mM HEPES-NaOH pH 7.5, 150 mM NaCl, 0.5 mM spermidine, 0.1% digitalis saponin, and a mixture of protease inhibitors from Sigma) to the tube and incubate for 1 h at 4°C. To remove unbound pA-MN, wash the cells twice with 1 ml of cold digitalis saponin buffer and resuspend in 150 μl of cold digitalis saponin buffer. The tubes were placed on a pre-cooled metal block. To initiate pA-MN digestion, the tube was gently tapped 10 times to mix 3 μl of 0.1 M CaCl2 with cells in 150 μl of cold digitalis saponin buffer. The tube was immediately returned to the metal block. After 30 minutes of incubation, digestion was stopped by adding 150 μl of 2x stop buffer (340 mM NaCl, 20 mM EDTA, 4 mM EGTA, 0.02% digitalis saponin, 50 μg/ml RNase A, 50 μg/ml glycogen, and 4 pg/ml yeast heterologous incorporation (spike-in) DNA). Target chromatin was released by incubating the tube on a heated block at 37 °C for 10 minutes. The supernatant was centrifuged at 16,000 g for 5 minutes at 4 °C and then transferred to a new tube. Chromatin was incubated at 70°C with 3 μl of 10% SDS and 2.5 μl of 20 mg/ml proteinase K for 10 min, followed by phenol:chloroform:isoamyl alcohol extraction. The DNA-containing upper phase was mixed with 20 μg of glycogen and incubated overnight at -20°C with 750 μl of cold 100% ethanol. DNA was precipitated by centrifugation at 20,000 g for 30 min at 4°C. The DNA precipitate was washed once with cold 100% ethanol, air-dried, and stored at -20°C for library preparation. Protein A-MNase (batch 6, used at 1:200) and yeast heterologous DNA incorporation were generously provided by Dr. Steve Henikoff. The antibodies used were: Fli1, ab15289, used at 1:50 (abcam), and guinea pig anti-rabbit IgG, used at 1:100, ABIN101961 (antibodies-online).

CUT&RUN DNA libraries were prepared with minor adjustments as previously described (Liu et al., 2018). In short, all DNA precipitated from pA-MN digestion was used for library preparation using the NEBNext Ultra II DNA Library Prep Kit (NEB). The adaptor was diluted to 1:25 for adaptor ligation. The DNA was barcoded and amplified for 14 PCR cycles, and the DNA library was cleaned with AMPure XP beads (Liu et al., 2018). Library quality was checked using Qubit and a bioanalyzer, and library volume was determined by qPCR using the NEBNext Library Quant Kit for Illumina (NEB) according to the manufacturer's instructions. The 18 barcoded libraries were pooled at equimolar concentrations and sequenced on the NextSeq 500/550 High Output Kit (75 cycles) v2.5 on the NextSeq 550 platform. Paired end sequencing was performed (42:6:0:42).

Data processing: Paired-end readouts were aligned with the mm10 reference genome using Bowtie2 v2.3.4.1 with the options suggested by Henikoff (Skene et al., (2018) Nature Protocols 2017 12:9 13, 1006–1019). Picard tool v1.96 was used to remove putative PCR repeats using the MarkDuplicates command. Bam files containing uniquely mapped readouts were created using Samtools v1.1. For downstream analysis, biological repeats (3 replicates per condition) were merged in this step. Bedtools v2.28.0 was used to generate fragment BED files ranging from 40bp to 500bp. Blacklisted regions, random chromosomes, and mitochondria were removed. The filtered BED files were used for downstream analysis.

The `bedGraphToBigWig` function (UCSC) was used to create a read-per-million (RPM) normalized bigwig file for visualizing binding signals. Peaks were identified using MACS v2.1 with broadPeak settings, a p-value cutoff of 1e-8, and `-f BEDPE` and IgG as controls. Genes near the peaks were annotated against the mm10 genome using `annotatePeaks.pl` from HOMER v4. Fli1 binding motifs were identified using `findMotifsGenome.pl` from HOMER v4. A Venn plot comparing the peaks to ATAC-Seq peaks was plotted using the `ChIPpeakAnno` package from the Bioconductor package. The heatmap was generated using the `ComplexHeatmap` package from the Bioconductor package.

Statistical analysis: Statistical significance was calculated using Prism 7 (GraphPad Software) with unpaired two-tailed Student's t-test or one-way ANOVA and Tukey's multiple comparison test. P-values are reported in the legend.

Now, let's describe the experimental results:

Example 1: Optimized CRISPR-Cas9 for in vivo gene editing of primary mouse T cells

To enable gene editing in antigen-specific primary CD8 T cells, LSL-Cas9 ⁺ mice (Plattet et al., (2014) Cell 159, 440–455) were crossed with CD4 ^CRE+ P14 ⁺ mice carrying LCMV ^DbGP _33–41 epitope-specific CD8 T lymphocytes (referred to as Cas9 ⁺ P14, or C9P14). A backbone-optimized Cas9 single-guide RNA (sgRNA) (Grevet et al., (2018) Science 361, 285–290) was expressed, fluorescently labeled in a retroviral (RV) vector (Figure 8A). To assess in vivo gene editing efficiency, C9P14 cells were transduced using an optimized RV transduction protocol (Kurachi et al., (2017) Nature Protocols, 12: 9 12, 1980–1998) with negative control sgRNA (sgCtrl1: AGTGGAAGCCATTGCTCTCG (SEQ ID NO: 714); sgCtrl_2: AATGGCAACTGGTCCCCTTC (SEQ ID NO: 715); sgCtrl_3GAAGATGGGCGGGAGTC TTC (SEQ ID NO: 716)) or sgRNA targeting Pdcd1 (encoding PD-1, sgPdcd1: CAGCTTGTCCAACTGGTCGG (SEQ ID NO: 717)) (Figure 8B). A double-positive cohort of sgRNA (mCherry ⁺ ) and Cas9 (GFP ⁺ ) CD8 T cells (Fig. 8C) was adoptively transferred to homologous recipient mice infected with the chronic LCMV strain (clone 13; Cl13) (Fig. 8B). sgRNA ⁺ C9P14 cells were isolated and evaluated on day 9 post-infection (pi). As expected, sgPdcd1 induced antigen-specific CD8 T cell expansion five-fold compared to control sgRNA (Fig. 8D), consistent with Pdcd1 gene knockout. sgPdcd1 also resulted in a robust reduction in PD-1 protein expression (Fig. 8E) and an indel mutation at the Pdcd1 locus (Fig. 8F). Furthermore, the high gene editing efficiency of this system was demonstrated by designing sgRNAs targeting Klrg1 (sgKlrg1:CCAAAGCCACCATT GCAAAG (SEQ ID NO:718)) and Cxcr3 (sgCxcr3:GAACATCGGCTACAGCCAGG (SEQ ID NO:719)) (Figure 8G). In summary, this system, which involves in vitro sgRNA RV transduction in C9P14 followed by in vivo adoptive transfer, provides a powerful platform for studying the gene regulatory network of mouse CD8 T cells in vivo.

Example 2: OpTICS enables gene screening for in vivo fusion in CD8T cells.

To enable in vivo gene screening in the LCMV infection system, the C9P14 and RV sgRNA platform (Figure 1A) was further optimized. First, the physiological number of adoptive-transferred CD8 T cells for screening was determined, as the number of transferred T cells can influence cancer progression in tumor models or infection outcomes in vivo. Therefore, the number of adoptive-transferred RV-transferred CD8 T cells was limited to ¹ x 10⁵ per mouse (approximately ¹ x 10⁴ after acceptance), a number previously optimized in chronic infection. Next, the system's performance was evaluated in vivo using the LCMV model to target a set of 29 TFs of interest in CD8 T cells. Previously, it has been found that targeting functionally important protein-coding domains with sgRNAs can significantly improve gene screening efficiency, as both in-frame and frameshift mutations contribute to the generation of loss-of-function alleles. An sgRNA library targeting the DNA-binding domains of the 29 TFs and other control genes (e.g., unselected control sgRNAs and Pdcd1) was designed and cloned, with 4–5 sgRNAs per target. Following CD8 T cell transplantation, the average input coverage per sgRNA was approximately 400 cells, which improved the signal-to-noise ratio and successfully identified hits—compared to 100 cells per sgRNA (Fig. 8H). Third, the performance of in vivo screening was evaluated using P14 cells expressing heterozygous and homozygous alleles of the LSL-Cas9 transgene. In terms of signal-to-noise ratio and consistency between independent screening, Cas9 heterozygous P14 cells outperformed Cas9 homozygous P14 cells (Fig. 8H–Fig. 8I), likely due to reduced off-target DNA damage in the heterozygous environment. From these preliminary optimized screenings, we identified Batf, Irf4, and Myc as crucial for early T cell activation, as gene targeting of these genes strongly inhibits T cell activation in vivo (Fig. 8H), consistent with the known roles of Batf, Irf4, and Myc in T _EFF biology. This system is highly efficient, enriching genes essential for CD8 T cell responses up to approximately 100-fold (Fig. 8H) and genes that inhibit T cell activation and differentiation by nearly 20-fold (Fig. 8J).

Example 3: OpTICS identifies novel TFs involved in _TEFF and _TEX cell differentiation

To identify novel T cells that regulate T _EFF and T _EX cell differentiation, another domain-focused sgRNA library targeting 120 T cells was constructed (Table 1). This library contained 675 sgRNAs, including 4–5 sgRNAs per DNA-binding domain, a positive selection control (sgPdcd1), and non-selective controls (e.g., sgAno9, sgRosa26, etc.) (Figure 1A). Using this sgRNA library targeting 120 T cells, in vivo selection and sgRNA enrichment were investigated at acutely resolving LCMV Arm (Arm) or chronic Cl13 pi1 or 2 weeks (Figure 1A). C9P14 cells from different organs (PBMCs, spleen, liver, and lung) were examined to identify T cells that are broadly important in response to CD8 T cell infection. Generally, groups were clustered based on time point and infection rather than anatomical location (Figure 8K). At week 2 pi, data for Arm and Cl13 diverged (Fig. 8K), consistent with the different trajectories of T cell differentiation during acute remission versus chronic infection. Focusing on the spleen, Batf, Irf4, and Myc appeared as some of the strongest negative selectors at both time points in both infections (Fig. 1B–Fig. 1C). Several other known effector-driven T cells were identified, including Tbx21 (encoding T-bet), Id2, Stat5a, Stat5b, and components of the NF-κB complex (Fig. 1B–Fig. 1C). Furthermore, several T cells with potential novel roles in T cell activation and differentiation were revealed, including Smad4, Smad7, and Mybl2 (Fig. 1B–Fig. 1C).

The OpTICS system has also been used as an “UP” screening (Kaelin, (2017) Nature Reviews Cancer 201213:117,441–450) to identify genes that inhibit optimal T cell activation and T _EFF cell differentiation. Such genes, such as Pdcd1, represent potential immunotherapeutic targets for improving T cell responses in cancer or infection. PD-1 served as a typical positive control, and as expected, Pdcd1-sgRNA was strongly positively selected at infection, time points, and in all tissues (Fig. 1B–Fig. 1D). This screening also identified TFs that antagonize robust CD8 T cell responses (Fig. 1B–Fig. 1C). Among them, Smad2 has been shown to limit T _EFF cell responses during both acute and chronic infections. Nfatc2 and Nr4a2 (Fig. 1C) were also identified, both of which are associated with promoting T cell exhaustion, thereby limiting T _EFF responses. In addition, Gata3, identified here, is associated with driving T cell dysfunction and inhibiting T _EFF cell responses. Therefore, this screening identified key TFs known to inhibit _TEFF differentiation and, in some cases, promote exhaustion.

This OpTICS screening also identified novel TFs that inhibit optimal T _EFF differentiation. This group of genes included Atf6, Irf2, Erg, and Fli1, with Fli1 being one of the most potent inhibitors of T _EFF differentiation. Similar identification of Fli1 as an inhibitor of T _EFF differentiation occurred in Arm and Cl13 infections (Figs. 1B–1D), suggesting a general role for this TF in suppressing T _EFF biology. Two Fli1-sgRNAs (sgFli1_290: CGCTGTCGGACAGTAGT TCC (SEQ ID NO: 720) and sgFli1_360: GCCATGGAAGTCAAACTTGT (SEQ ID NO: 721)) were selected, and these sgRNAs were confirmed to effectively edit the Fli1 gene (70%–80% editing; Fig. 9A), resulting in reduced protein expression (Fig. 1E). Targeting Fli1 with these single Fli1-sgRNAs in C9P14 cells in vivo resulted in 5-20 fold expansion at Arm or Cl13 pi 1 to 2 weeks (Fig. 1F and Fig. 9B-Fig. 9E). These data demonstrate the repression of robust CD8 T cell expansion by Fli1 in acute regressive or developing chronic infections.

Example 4: Fli1 gene deletion promotes robust T _EFF differentiation during acute infection regression.

Next, the differentiation status of C9P14 cells transduced with Fli1-sgRNA (sgFli1) or Ctrl-sgRNA (sgCtrl) was investigated during acute infection regression. On day 8 of pi, Fli1 deficiency reduced the proportion of CD127 ^Hi memory precursors ( _TMPs ), while the frequency of the KLRG1 ^Hi terminal effector ( _TEFF ) population remained unchanged, whereas the CD127 ^Lo KLRG1 ^Lo population slightly increased (Figs. 2A and 10A). These effects were more pronounced on day 15 of pi when the frequency of the CD127 ^Hi _TMP population decreased and the KLRG1 ^Hi T _EFF cell population increased (Fig. 2A). However, at both time points, the absolute numbers of _TMPs and T _EFFs increased approximately 2–10-fold due to the proliferative expansion of Fli1-deficient CD8 T cells (Fig. 2A). This bias towards T- _EFF -like T cell differentiation was also observed using CX3CR1 and CXCR3, ^with a significant enrichment of sgFli1 in the CX3CR1 ⁺ CXCR3 ^- T- _EFF subset compared to the early T _MEM subset (Fig. 2B). Although ^the number of C9P14 cells with increased cytotoxic potential (GzmB ⁺ TCF-1 ^- ) was also increased in the sgFli1 ⁺ group (Fig. 10B), the proportion of cells expressing T-bet or Eomes was similar between groups (Fig. 10C). Compared to the sgCtrl ⁺ group, the frequency of IFN-γ production by C9P14 cells in the sgFli1 ⁺ group after in vitro peptide stimulation was slightly lower, but the absolute number of cells producing IFN-γ or simultaneously producing multiple effector molecules was increased (Fig. 10D).

One concern with promoting T _EFF increase is preventing T _MEM formation. Therefore, the formation of Fli1-deficient T _MEM was examined at 1 month post-pi. Indeed, at day 29 post-pi, the number of KLRG1 ^Hi effector memory C9P14 cells remained high in the sgFli1 ⁺ C9P14 group compared to the sgCtrl ⁺ group. At this time, the number of CD127 ^Hi T _MEMs was similar between groups (Figs. 10E-10F), indicating that the robust increase in the KLRG1 ^Hi T _EFF population generated in the absence of Fli1 does not impair T _MEM formation. To further investigate the effect of Fli1 deficiency on T _MEM , the expression of pro-apoptotic and anti-apoptotic molecules Bcl-2, Bcl-XL, and Bim was examined. On day 15 of pi, compared with the sgCtrl ⁺ group, sgFli1 ⁺ C9P14 cells showed lower expression of both Bcl-2 and Bim, but no change in Bcl-XL expression (Fig. 10G-10H), resulting in a trend towards a higher BclXL/Bim ratio in the sgFli1 ⁺ C9P14 group (Fig. 10H). There were no differences in the expression of Bcl-2, Bcl-XL, or Bim in the T _EFF or T _MP subsets (Fig. 10I-10J), suggesting that the differences in the total C9P14 population partially reflect the different proportions of terminal T _EFFs and T _MPs . These observations are consistent with the finding that the Bcl-XL/Bim ratio is more important than the Bcl-2/Bim ratio in terminal T _EFF survival.

Fli1 expression was forced in WT LCMV-specific P14 cells using an RV-based overexpression (OE) system (Kurachi et al., (2017) Nature Protocols, 12:9 12, 1980–1998). Compared to the empty vector control, approximately a 5-fold reduction in responsive Fli1-OE-RV transduced P14 cells was observed at days 8 and 16 of pi (Fig. 2C). Furthermore, forced Fli1 expression induced _TMP differentiation in responsive P14 cells (Fig. 2D–Fig. 2E). In summary, these data reveal the role of Fli1 in inhibiting T _EFF differentiation and promoting _TMP development during acute infection.

Example 5: Fli1 antagonizes T _EFF -like differentiation during chronic infection

During chronic viral infection, CD8 T cell responses exhibit early fate divergence, with antiviral CD8 T cells either developing into terminal _TEFF- like cells or forming _TEX precursors, ultimately forming the mature _TEX population. Therefore, the role of Fli1 in this cell fate determination during early chronic infection was investigated. Similar to acute regressive infection, Fli1 gene perturbation biases virus-specific CD8 T cell responses toward the _TEFF pathway, defined as TCF-1 ^- GrzmB ⁺ or Ly108 ^- CD39 ⁺ cells (Fig. 3A). Due to a 5-10 fold increase in total Fli1-deficient cells, the number of both _TEFF- like and _TEX precursor cells was increased (Figs. 11A-11B). TF circuits known to be involved in early _TEX formation were also investigated. TCF-1 drives Eomes expression at this early time point; Eomes are another crucial TF for _TEX formation, and in fact, Eomes are reduced in the absence of Fli1 (Fig. 11C). T-bet, another type of T-box TF, showed similar expression between the sgCtrl ⁺ and sgFli1 ⁺ groups (Fig. 11C). Loss of Fli1 was also associated with low expression of the T- _EX master regulator Tox on day 15 of Cl13 pi, suggesting that Fli1 deficiency antagonizes T- _EX development and instead promotes T- _EFF -like differentiation (Fig. 11C). This shift towards T- _EFF fate was associated with increased expression of cytotoxic molecules (Fig. 3A) and a greater number of cells transforming into an increased number of cytokine-producing cells (Fig. 11D). Furthermore, Fli1 gene perturbation led to an increased proportion of CX3CR1 ⁺ and Tim3 ⁺ T _-EFF -like cells in chronic infection (Fig. 3B). Conversely, forced Fli1 expression had the opposite effect, resulting not only in a lower cell number (Fig. 11E) but also promoting the formation of Ly108 ^{+ CD39-} or TCF-1 ^{+ GrzmB-} T- _EX precursors and fewer CX3CR1 ⁺ cells (Fig. 11F–11H). Notably, PD-1 expression remained unchanged, unlike in acutely regressed infections, where KLRG1 expression was unaffected (Figure 3B).

To elucidate the underlying mechanisms, RNA-seq was performed on sorted sgCtrl ⁺ or sgFli1 ⁺ C9P14 cells on day 9 of Cl13 infection. Both sgRNAs targeting Fli1 produced similar transcriptional effects (Fig. 3C, Fig. 12A). sgFli1 ⁺ C9P14 cells differed transcriptionally from sgCtrl ⁺ C9P14 cells, with over 1400 differentially expressed genes between the two conditions (Fig. 3C, Fig. 12A). Effector-related genes such as Prf1, Gzmb, Cd28, Ccl3, and Prdm1 were robustly increased in sgFli1 ⁺ C9P14 cells, while sgCtrl ⁺ C9P14s were enriched in _TEX precursor genes such as Tcf7, Cxcr5, Slamf6, and Id3 (Fig. 3C). Gene set enrichment analysis also identified cell division-related and T cell activation-related pathways in sgFli1 ⁺ C9P14 cells (Fig. 3D), while sgCtrl ⁺ C9P14s were enriched in metabolic pathways, particularly nucleotide, nucleoside, and purine biosynthesis (Fig. 3E). Gene set enrichment analysis (GSEA) was used to examine the early stages of chronic infection when divergence occurred in differentiation into T _EFF- like or T _EX precursor cell fates. Indeed, T _EX precursor signatures were strongly enriched in sgCtrl ⁺ C9P14 cells compared to the sgFli1 ⁺ C9P14 population, while T _EFF gene signatures were strongly enriched in the sgFli1 ⁺ C9P14 population (Fig. 3F-Fig. 3G). Thus, Fli1 inhibits optimal T _EFF differentiation in both acute remission and chronic infection, while loss of Fli1 antagonizes T _EX cell development. However, although Fli1 gene perturbation drove increased expression of effector-related genes on day 9 of chronic infection, Tox, Tox2, and Cd28 were also increased. This effect suggests that while the loss of Fli1 may enhance _TEFF -like biology, this effect may not come at the expense of genes required to maintain responses in chronic infections that are necessary for cancer treatment.

Example 6: Fli1 remodels the epigenetic landscape of CD8 T cells and the expression of antagonistic T _EFF -related genes.

In acute myeloid leukemia, Fli1 co-localizes with the chromatin remodeler BRD4, and the EWS-FLI1 fusion oncoprotein driving Ewing's sarcoma can trigger de novo enhancer formation through chromatin remodeling and inactivate existing enhancers by replacing ETS family members. However, it remains unclear how Fli1 affects epigenetic landscape changes in developing _TEFF , _TMEM , or _TEX cells.

To examine the role of Fli1 in supporting the epigenetic landscape of CD8 T cells, ATAC-seq was performed on sgFli1 ⁺ and sgCtrl ⁺ C9P14 cells on day 9 of Cl13 pi. Chromatin accessibility was significantly altered in the sgFli1 ⁺ group compared to sgCtrl ⁺ C9P14 cells (Fig. 4A). More than 5000 open chromatin regions (OCRs) differed between the control and Fli1-perturbed groups, with roughly equal numbers of peaks gained or lost (Figs. 4B–4D). These changes were mostly located in introns or intergenic regions consistent with cis-regulatory or enhancer elements (Fig. 4C).

Each OCR was assigned to the nearest gene to estimate the genes that could be regulated by these cis-regulatory elements. T _EFF- related genes such as Ccl3, Ccl5, Cd28, Cx3cr1, and Prdm1 gained chromatin accessibility in the sgFli1 ⁺ group (Fig. 4D), consistent with RNA-seq data. In contrast, in the sgFli1 ⁺ group, chromatin accessibility near genes involved in T cell progenitor cell biology, such as Tcf7, Slamf6, Id3, and Cxcr5, decreased (Fig. 4D). Furthermore, accessibility at the Tox (and Tox2) loci was altered in sgFli1 ⁺ C9P14 cells, but these changes included both increases and decreases in accessibility at different peaks (Fig. 4D). These changes in chromatin accessibility corresponded to changes in gene expression, with approximately one-third of the genes altered in transcription associated with differentially accessible chromatin regions (402 out of 1467) (Fig. 4E). Overall, while increased accessibility is associated with increased transcription, there is a distinct regional subgroup where decreased accessibility corresponds to increased transcription (Fig. 4F).

Next, the Fli1-dependent accessibility-altering TF motifs in the OCR were defined. In the OCR with reduced accessibility in the absence of Fli1, the most enriched TF motifs were those of IRF1 and IRF2 (Fig. 4G), potentially linking Fli1 to downstream IRF1 and IRF2 in IFN signaling or to the regulation of the cell cycle by these TFs. In the OCR group with increased accessibility in the absence of Fli1, the ETS and RUNX motifs were highly enriched (Fig. 4G). The complex ETS:RUNX motif showed the greatest change to date, with an 18-fold enrichment (Fig. 4G). These observations suggest that Fli1 may limit the activity of other ETS family members (e.g., ETS1, ETV1, or ELK1) or alter accessibility at the ETS:RUNX binding site (Fig. 4G). Runx3 is a key driver of T _EFF differentiation, and its function is to directly regulate effector gene expression, coordinate and enable effector gene regulation through T-bet and Eomes, and antagonize TCF-1 expression. Therefore, the potential role of Fli1 in Runx3 biology will provide a mechanistic link between Fli1 loss and improved _TEFF differentiation.

Fli1 cut & run (Skene et al. (2017) Cdn. Elifesciences.org) was used to test how Fli1 genome binding relates to changes in chromatin accessibility and T _EFF biology. On day 9 of Cl13 pi, >90% of the identified Fli1 binding sites were included in the OCRs detected by ATAC-seq (Fig. 12B–Fig. 12D). Specifically, Fli1 binds to the OCRs of T _EFF- like genes such as Cx3cr1, Cd28, and Havcr2. Following Fli1 deletion, chromatin accessibility at these sites increased (Fig. 4H), leading to increased transcription (Fig. 3C) and protein expression (Fig. 3B and Fig. 4I). In contrast, no direct binding of Fli1 was observed for genes involved in progenitor cell biology, such as Tcf7 and Id3, whose expression was reduced in the absence of Fli1 (Fig. 12D), which may suggest that the primary role of Fli1 is to prevent overly robust T _EFF programs rather than directly enabling memory/progenitor cell biology. Furthermore, in the absence of Fli1, 78% of the Fli1 sites defined by cut & run showed increased chromatin accessibility, compared to decreased accessibility in 22% (Figure 4J), indicating that Fli1 primarily acts as a repressor of chromatin accessibility. Analysis of DNA-binding motifs in the Fli1 cut & run data revealed the expected Fli1 motif. However, SP2, NFY1, and RUNX1 motifs were also significantly enriched in the presence of Fli1 binding (Figure 4K). Combined with the increased ETS:RUNX motif observed in the aforementioned Fli1-deficient ATAC-seq results, these data support a model where Fli1 coordinates with RUNX family members to control T _EFF differentiation.

Example 7: Forced Runx3 expression and Fli1 deletion synergistically enhance the _TEFF response

Unlike T _EFF biology, the roles of Runx1 and Runx3 in T _EX development are unclear. Since T _EFFs and T _EXs have opposite fates in chronic infection, and the ETS:RUNX motif becomes more accessible in the absence of Fli1, it is hypothesized that the RUNX-Fli1 axis may influence T _EFF differentiation relative to T _EX . Therefore, it is necessary to test whether the expression of Runx1 or Runx3 in Fli1-deficient CD8 T cells affects T _EFF differentiation in early chronic infection.

On day 7 of Cl13 infection, forced expression of Runx1 in WT P14 cells reduced cell number (Fig. 12E). Furthermore, Runx1-OE promoted the formation of Ly108 ⁺ CD39 ^- _TEX precursors at the cost of a larger T _EFF -like Ly108 ^- CD39 ⁺ population (Fig. 12E). To investigate the effects of forced Runx1 expression in the absence of Fli1, a dual RV transduction approach was used, combining control or Fli1 sgRNA RV transduction with empty or Runx1-expressing RVs. VEX (targeting sgRNA) and mCherry were used to distinguish between single-transduced and dual-transduced cells. C9P14 cells were efficiently single-transduced or dual-transduced (Fig. 12F) and adoptively transferred to Cl13-infected mice, and dual-transduced (i.e., GFP ⁺ VEX ⁺ mCherry ⁺ ) C9P14 cells were analyzed on day 8 of pi (Fig. 5A). In the sgFli1 ⁺ Runx1 ^- OE group, the number of GFP ⁺ VEX ⁺ mCherry ⁺ C9P14 cells was reduced, while Ly108 ^- CD39 ⁺ cells were even fewer. In contrast, the GFP ⁺ VEX ⁺ mCherry ⁺ C9P14 cell population increased in the sgFli1 ⁺ empty-RV group, and these cells were tilted toward a Ly108 ^- CD39 ⁺ T _EFF -like fate (Fig. 5B-5D, Fig. 12G), as described above. However, in a Fli1-deficient environment with enhanced CD8 T cell expansion, Runx1 overexpression reduced the magnitude of the response and partially reversed the tilt toward a Ly108 ^- CD39 ⁺ T _EFF -like fate caused by Fli1 loss (Fig. 5B-5D).

In contrast to the effects of Runx1, forced expression of Runx3 alone (in the sgCtrl ⁺ group) moderately increased the magnitude of the CD8 T cell response, but robustly tilted the GGFP ⁺ VEX ⁺ mCherry ⁺ C9P14 population towards the CD39 ⁺ Ly108 ^- T _EFF -like population (Fig. 5A, Fig. 5E-Fig. 5G). In the sgFli1+Runx3-OE forced expression group, these effects were more pronounced in the absence of Fli1, with greater numerical amplification and even further tilt towards CD39+Ly108-T _EFF -like cells (Fig. 5E-Fig. 5G). Although the frequency of the T _EX precursor population was lower in the sgFli1 ⁺ Runx3-OE group, the absolute number of this population remained unchanged compared to the control (Fig. 5E, Fig. 5G, Fig. 12I). In summary, these data support a model in which the loss of Fli1 reveals the ETS:RUNX motif that Runx1 and/or Runx3 can utilize. However, while Runx3 drives increased T _EFF- like clusters—an effect amplified in the absence of Fli1—Runx1 appears to antagonize T _EFF production, consistent with the opposite functions of Runx1 and Runx3. Thus, Fli1 inhibits Runx3-mediated T _EFF -promoting activity by restricting genome access and protecting the ETS:RUNX binding site. These data reveal that Fli1, Runx3, and possibly Runx1 itself, are key regulators of fate selection between T _EFFs and T _EXs early after initial activation.

Example 8: Enhanced T _EFF cell response in the absence of Fli1 improves protective immunity against pathogens

The above data raised the question of whether the loss of Fli1 could improve infection control due to enhanced T _EFF differentiation. To test this idea, LCMV Cl13 was used to study protective immunity during chronic infection and two acute infection models, namely influenza virus (PR8) or Listeria monocytogenes (LM) (each expressing the LCMV _GP33-41 epitopes recognized by P14 cells (PR8 _GP33 and LM _GP33 )) (Figure 6A).

During Cl13 infection, adoptive transfer of sgCtrl ⁺ C9P14 cells provided moderate viral control compared to no transfer condition (NT, Fig. 6B). However, at approximately 2 weeks pi, sgFli1 ⁺ C9P14 cells provided significantly improved viral replication control compared to sgCtrl ⁺ C9P14 cells (Fig. 6B), demonstrating the benefit gained from the loss of Fli1 even in chronic viral infection—where exhaustion induction is a major barrier to effective protective immunity. Notably, in some experiments, sgFli1 ⁺ C9P14 mice, rather than sgCtrl ⁺ C9P14 recipient mice, experienced severe disease requiring euthanasia between piD7-D13 (Fig. 13A), suggesting that Fli1 can prevent excessive T _EFF -like differentiation and limit T cell-mediated immunopathology.

Next, the impact of Fli1 loss on the acute remission process was assessed. During influenza-PR8 _GP33 infection, mice receiving sgFli1 ⁺ C9P14 cells experienced less weight loss than control non-transferred mice or mice receiving sgCtrl ⁺ C9P14 cells (Fig. 6C). This reduced weight loss was associated with better control of viral replication in the lungs of mice receiving sgFli1 ⁺ C9P14 cells (Fig. 6D). In this context, the magnitude of sgFli1 ⁺ C9P14 amplification in the lungs after PR8GP33 infection varied (Fig. 13B–Fig. 13D). This heterogeneity in T-cell responses was associated with differences in viral control, with some mice nearly eliminating viral RNA by this time point (Fig. 6D) and recovering from weight loss. Indeed, in recovered mice, the overall magnitude of the C9P14 response was lower, consistent with prolonged viral replication and elevated antigen load driving increased T-cell amplification in uncontrolled infection mice (Fig. 13B–Fig. 13C). Notably, compared to only 1 out of 11 mice that received sgCtrl ⁺ C9P14, 6 out of 12 mice that received sgFli1 ⁺ C9P14 cells achieved disease control at this time point (Fig. 6D, Fig. 13C). In the group of mice still carrying viral RNA in their lungs, sgFli1 ⁺ C9P14 cells had expanded to a much higher number compared to sgCtrl ⁺ C9P14 cells (Fig. 13C). Similar differences in _TEFF cell expansion were also observed in the spleen (Fig. 13D).

Loss of Fli1 following LMGP33 infection also conferred a similar advantage. Although both sgCtrl ⁺ and sgFli1 ⁺ C9P14 cells showed increased survival after high-dose LMGP33 irritation (Fig. 6E), sgFli1 ⁺ C9P14 cells exhibited significantly better control over bacterial replication compared to sgCtrl ⁺ C9P14 cells at day 7 of pi (Fig. 6F). Consistent with the influenza virus model, this enhanced protective immunity was associated with a larger numerical expansion of sgFli1 ⁺ C9P14 cells compared to the sgCtrl ⁺ group (Fig. 13E). Therefore, Fli1 deficiency conferred substantial benefits for T _EFF cell expansion and protective immunity during chronic Cl13 infection, respiratory influenza virus infection, and systemic infection with intracellular bacteria.

Example 9: Loss of Fli1 in CD8 T cells enhances tumor immunity

Next, we investigated whether Fli1 deficiency enhances tumor control. A subcutaneous B16 _GP33 tumor model was used. On day 5 post-tumor inoculation (pt), tumor-bearing mice received the same number of sgCtrl ⁺ or sgFli1 ⁺ C9P14 cells (Fig. 7A). Rag2-/- receptor mice were used to separate the effect of sgCtrl ⁺ relative to sgFli1 ⁺ C9P14 cells (Fig. 7A). In this setting, sgFli1 ⁺ C9P14 cells robustly controlled tumor progression compared to non-metastatic mice or the sgCtrl ⁺ C9P14 group (Fig. 7B). Furthermore, at the endpoint, the tumor weight was significantly reduced in the sgFli1 ⁺ C9P14 group compared to either control group (Fig. 7C). Although there was no significant difference in C9P14 cell number/gram tumor, this tumor control was associated with a significant increase in Ly108 ^- CD39 ⁺ donor C9P14 in the sgFli1 ⁺ group, consistent with a greater T _EFF -like population (Figs. 7D-7E). However, in the spleen, the number of sgFli1 ⁺ C9P14 cells and the proportion of Ly108 ^- CD39 ⁺ cells were significantly increased compared to the sgCtrl ⁺ group (Fig. 7F-7G). These findings were extended to immunocompetent mice. Cas9+C57BL/6 recipient mice were used to prevent rejection of C9P14 donor cells and to allow for analysis of responses over extended time periods (Fig. 14A). In this setting, sgFli1 ⁺ C9P14 cells again demonstrated substantial benefits in tumor control compared to sgCtrl ⁺ C9P14 cells (Fig. 14B-14C). Furthermore, this improvement in tumor control was associated with an increase in the number of Ly108 ^- CD39 ⁺ _TEFF- like cells in the tumor, draining lymph nodes (dLN), and spleen, as well as an increase in the number of C9P14 cells in the dLN and spleen (Fig. 14D-14G). Therefore, Fli1 gene deletion provides substantial benefits for tumor control, indicating that Fli1 plays a central role in coordinating and suppressing the protective T _EFF response during tumor progression. In summary, these data suggest that Fli1 loss leads to enhanced protective immunity in systemic and local settings, acute regression and chronic infection, and tumor progression.

Example 10: Discussion

This study aims to improve immunotherapy for cancer and chronic infections by better understanding the biology of _TEX and T _EFF differentiation. An in vivo CRISPR screening method was used to specifically explore the mechanisms governing _TEX -to-T _EFF differentiation. Fli1 was identified as a key TF protecting transcriptional and epigenetic typing for complete T _EFF differentiation. Mechanistically, Fli1 restricts epigenetic access to the ETS:RUNX site, thereby preventing Runx3 from fully activating the effector program. Therefore, Fli1 deletion significantly improved protective immunity in multiple models of acute infection, chronic infection, and cancer, thus identifying Fli1 as a novel regulator of the T _EFF -to- _TEX differentiation program and a target for future immunotherapy strategies.

Recent advances in CRISPR-based screening methods have enabled the profiling of in vitro T cell activation and in vivo responses to infection and tumors. To better understand the fate determination of T _EFFs and T _EXs , this paper developed OpTICS. OpTICS is an in vivo CRISPR system that allows screening in mature CD8 T cells, among other things, using physiologically relevant T cell numbers that preserve disease pathogenesis and normal CD8 cell differentiation biology. In addition to identifying numerous known regulators of CD8 T cell responses, this method also identified several novel negative regulators of T _EFF differentiation, including Smad2, Erg, and Fli1. In fact, Fli1 gene loss enhances protective immunity in various settings, including acute or chronic infection and cancer. Furthermore, unlike the effects of loss of TF Tox, which drives T _EXs —where CD8 T cell responses cannot be sustained due to the loss of T _EX progenitors during chronic infection or cancer—Fli1 deficiency does not reduce the T _EX progenitor population.

Fli1 plays a role in hematopoietic stem cell differentiation and co-localizes with other TFs such as Gata1/2 and Runx1. In this study, we found that Fli1 gene perturbation significantly increased chromatin accessibility at the ETS:RUNX motif in antigen-specific CD8 T cell responses to viral infection. Furthermore, the effect of forced Runx3 expression was enhanced in the absence of Fli1. These observations suggest that Fli1 blocks access to the RUNX binding site, thereby limiting the activity of the effector-promoting TF Runx3. In addition, Runx3 can coordinate epigenetic changes at loci encoding other effector-promoting TFs. Although Runx1 may antagonize Runx3 (and vice versa), Runx3 appears to dominate in T cell-activated environments. The data in this study also suggest that Fli1 can collaborate with Runx1 to inhibit T _EFF differentiation, possibly through co-binding of Fli1 and Runx1 at the ETS-RUNX motif. In summary, these data demonstrate a model in which Fli1, in combination with Runx1, prevents efficient genomic accessibility or activity of Runx3, thereby suppressing the full-effects gene program involving positive feedforward effectors of Runx3 that promotes activity. Therefore, the deletion of Fli1 at least partially depresses T _EFF differentiation by creating opportunities for more efficient Runx3 activity.

Recent work has begun to define the transcriptional circuits that guide fate determination between terminal T _EFFs , T _MEMs , and T _EXs . Many of these transcriptional mechanisms that promote a cell fate directly repress opposite fates. For example, Tox represses T _EFFs while promoting T _EXs , TCF-1 promotes T _MEMs or T _EXs at the expense of T _EFFs , and Blimp-1, T-bet, Id2, etc., drive T _EFFs and repress T _MEMs . Fli1 has been identified as a genomic “protection” against over-stereotyping to effector differentiation, revealing several novel ideas. First, during chronic infection, the loss of TCF-1 or Tox results in the ability to maintain a response in the later stages of infection due to the stereotyping of terminally differentiated T _EFFs . These observations raise the question of whether the increase in T _EFF cell fate necessarily comes at the cost of losing the T _MEM or T _EX lineage. Fli1 represents a unique type of damper in otherwise robust feedforward effector transcriptional circuits. By suppressing the Runx3 node in the effector wiring, Fli1 moderates the central step that not only directly controls the expression of key effector genes but also actively enhances other co-effective TFs. However, unlike TCF-1 and Tox, Fli1 is not essential for progenitor cell biology, and the number of T _EFF cells and TMP (in acute regressive infection) or T _EX progenitor cells (in chronic infection) increases in the absence of Fli1. Therefore, it is possible to enhance the beneficial aspects of short-term protective immunity without impairing long-term immunity by blocking this "damper" in the circuit, rather than depriving the master switch for TMP or T _EX differentiation. Secondly, the data in this paper reveal a competitive mechanism for epigenetic realization between Fli1 and other factors that bind at the ETS:RUNX motif. These effects can be manifested because Fli1 occupies genomic sites that can be bound by ETS:RUNX family TFs, thereby catalyzing changes in chromatin accessibility. Alternatively, these effects may be caused by chromatin changes coordinated by Fli1 itself. For example, the EWS-FLI1 fusion recruits the BAF complex to initiate chromatin changes in cancer cells. Therefore, the role of Fli1 in CD8 T cells may involve a chromatin accessibility-based mechanism to suppress ETS:RUNX-driven effector biology, although other effects via IRF1/IRF2 may also exist.

Current research indicates that Fli1 loss has significant beneficial effects on protective immunity across various environments, including infection and cancer. Fli1 deficiency consistently enhances protective immunity in different models. Particularly relevant to immunotherapy is the improved control of tumor growth and chronic LCMV infection—where exhaustion induction typically limits immunity. Finally, given the potential for CRISPR-mediated gene manipulation in cell therapy settings, clinical benefits could be achieved by targeting Fli1 or related pathways.

Therefore, the OpTICS platform provides a highly robust in vivo platform for screening genes involved in regulating CD8 T cell differentiation, as it is relevant to tumor immunotherapy. This highly focused and optimized platform achieves 20-100-fold enrichment (enhancement) of sgRNA detection and considerable functional attainment screening resolution. Besides the novel role of Fli1 revealed here, many other potential targets can be explored through this screening. Furthermore, extending this focused TF biology to other areas of cell biology using OpTICS should provide a powerful platform for future discoveries.

List of implementation methods

The following implementation methods are provided, and their numbers should not be interpreted as indicating a level of importance.

Implementation 1 provides a modified immune cell or its precursor, comprising a modification at an endogenous locus encoding Fli1.

Implementation 2 provides the modified immune cells or precursors of Implementation 1, wherein the endogenous Fli1 gene or protein is disrupted.

Implementation 3 provides a modified immune cell or its precursor of Implementation 1 or 2, wherein the modification or disruption is performed by a method selected from: CRISPR system, antibody, siRNA, miRNA, antagonist, drug, small molecule inhibitor, PROTAC target, TALEN and zinc finger nuclease.

Embodiment 4 provides the modified immune cells or precursors thereof of Embodiment 3, wherein the CRISPR system comprises at least one sgRNA, the at least one sgRNA comprising any one of SEQ ID NO:152-156 or SEQ ID NO:676-713.

Implementation 5 provides an immune cell or its precursor from any of the foregoing implementations, wherein the cell is a human cell.

Implementation 6 provides an immune cell or its precursor from any of the foregoing implementations, wherein the cell is a T cell.

Embodiment 7 provides the immune cells or precursors of Embodiment 6, wherein the T cells are resistant to T cell exhaustion.

Embodiment 8 provides a pharmaceutical composition comprising an inhibitor of Fli1.

Embodiment 9 provides the pharmaceutical composition of Embodiment 8, wherein the inhibitor is selected from CRISPR systems, antibodies, siRNA, miRNA, antagonists, pharmaceuticals, small molecule inhibitors, PROTAC targets, TALENs, and zinc finger nucleases.

Example 10 provides the pharmaceutical composition of Example 9, wherein the CRISPR system comprises at least one sgRNA, the at least one sgRNA comprising any one of SEQ ID NO:152-156 or SEQ ID NO:676-713.

Embodiment 11 provides a method for treating a disease or disorder in a person in need, the method comprising administering to the person a cell of any one of Embodiments 1-7 or a composition of any one of Embodiments 8-10.

Implementation 12 provides the method of Implementation 11, wherein the disease or obstacle is an infection.

Implementation 13 provides the method of Implementation 11, wherein the disease is cancer.

Implementation 14 provides a method for screening T cells, the method comprising: i) introducing a Cas enzyme and an sgRNA library into activated T cells, ii) administering the T cells to an infected mouse, iii) isolating the T cells from the infected mouse, and iv) analyzing the T cells.

Implementation 15 provides the method of Implementation 14, wherein the sgRNA library contains multiple sgRNAs that target multiple transcription factors.

Implementation 16 provides the method of Implementation 15, wherein the plurality of transcription factors include any transcription factors listed in Table 1.

Implementation 17 provides the method of Implementation 15, wherein each sgRNA targets the DNA-binding domain of each transcription factor.

Implementation 18 provides the method of Implementation 14, wherein the sgRNA library contains at least one sequence selected from SEQ ID NO:1-675.

Implementation 19 provides the method of Implementation 14, wherein the sgRNA library consists of the nucleotide sequences listed in SEQ ID NO:1-675.

Implementation 20 provides the method of Implementation 14, wherein the screening assesses T cell exhaustion.

Implementation 21 provides the method of Implementation 14, wherein the analysis of the cells includes methods selected from sequencing, PCR, MACS and FACS.

Implementation 22 provides the method of Implementation 14, wherein the sequencing reveals a target of interest.

Implementation 23 provides the method of Implementation 22, wherein a drug is designed for the target of interest.

Implementation 24 provides the method of Implementation 22, wherein when the drug is administered to the T cells, at least one T cell response is increased.

Implementation 25 provides the method of Implementation 14, wherein 1 x ^10⁵ T cells are administered to the infected mouse.

Implementation 26 provides the method of Implementation 14, wherein the method identifies novel transcription factors that regulate the differentiation of _TEFF and _TEX cells.

The disclosure of each patent, patent application, and publication cited herein is hereby incorporated in its entirety. While the invention has been disclosed with reference to specific embodiments, it will be apparent to those skilled in the art that other embodiments and variations of the invention can be devised without departing from its true spirit and scope. The appended claims are intended to be construed as encompassing all such embodiments and equivalent variations.

Sequence List

<110> University of Pennsylvania Board of Trustees

E.J. Huili

Z. Chen

J. Stone

O•Kehan

J.R. Giles

S. Manny

<120> In vivo CRISPR screening system for discovering therapeutic targets in CD8 T cells

<130> 046483-7324WO1(02826)

<150> 63/153,191

<151> 2021-02-24

<160> 721

<170> PatentIn version 3.5

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<220>

<223> sgRNA

<400> 31

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<210> 32

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<210> 46

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<223> sgRNA

<400> 53

taatctgtgc ggtaacttgt                                     20

<210> 54

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 54

ttcttttcta ttaatctgtg                                 20

<210> 55

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 55

gagcaatgca ttcattaatt 20

<210> 56

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 56

tttggagaaa gcagtagtct                                     20

<210> 57

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 57

acaagaacag caacgagtac                                   20

<210> 58

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 58

caagaacagc aacgagtacc                                   20

<210> 59

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 59

acagcaacga gtaccgggta                                       20

<210> 60

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 60

gccgtgaact ggacacgctg                                                              

<210> 61

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 61

cgtgaactgg acacgctgcg                                   20

<210> 62

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 62

gtccaccgtc ttcttggcct                                 20

<210> 63

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 63

ggccaaggcc aagaagacgg                                                                                                                  

<210> 64

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 64

cagcttgtcc accgtcttct                               20

<210> 65

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 65

gctgcttgaa caagttccgc                                 20

<210> 66

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 66

ctgcttgaac aagttccgca                                         20

<210> 67

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 67

aatttcctcc gcctctcatc                                       20

<210> 68

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 68

aggacccaga tgagaggcgg                                     20

<210> 69

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 69

tgagaggcgg aggaaatttc                               20

<210> 70

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 70

cttctgtctg cagcgggtgg                                 20

<210> 71

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 71

ttaacaacaa ctgcttcagc                                     20

<210> 72

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 72

tttcgctttc aagtcgattt                           20

<210> 73

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 73

aagcgaaact tgagcgaagc                                 20

<210> 74

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 74

ggcattctct cgcactctgc                                 20

<210> 75

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 75

aaagctgagg taccagtact                                   20

<210> 76

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 76

tggtgcatgg caatggacca 20

<210> 77

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 77

cagaagaagc aactcgcaag                                     20

<210> 78

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 78

agaagaagca actcgcaagc                                     20

<210> 79

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 79

caactcgcaa gcgggggctg                                                                  

<210> 80

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 80

tgagagtcga gtcgcagtgc                                                                                                      

<210> 81

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 81

tcagaacaag aagcttatag                                                                                                                                    

<210> 82

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 82

tttggtggtc agatttagtg                             20

<210> 83

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 83

cagctccaag aagcgtttgg                                 20

<210> 84

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 84

tctgaccacc aaacgcttct                                                              

<210> 85

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 85

gatatgattc ttggacttct                                   20

<210> 86

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 86

agtccaagaa tcatatccag                                 20

<210> 87

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 87

acacgctatg acacgtcgct                             20

<210> 88

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 88

gacacgctat gacacgtcgc                                     20

<210> 89

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 89

cacgctatga cacgtcgctg                               20

<210> 90

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 90

gtccaaaaac aacatccagt                               20

<210> 91

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 91

agtccaaaaa caacatccag                                 20

<210> 92

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 92

acgcggtatg atacgtccct                                   20

<210> 93

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 93

acttcttggt gagcagaccg                               20

<210> 94

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 94

cttcttggtg agcagaccga                               20

<210> 95

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 95

tcctgagcca gtctcctgat                                   20

<210> 96

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 96

agtctaagaa caacgtccag                                 20

<210> 97

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 97

ggaggcgcag gacggcgtcc                                     20

<210> 98

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 98

ctgcagatac cttggctgtg                                                         

<210> 99

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 99

tgatatcacc aatgtcttag                                                        

<210> 100

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 100

gatatcacca atgtcttaga                             20

<210> 101

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 101

atcaattccc tctaagacat                                                                                                                                  

<210> 102

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 102

gtatgacatc accaatgtct                                                                                    

<210> 103

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 103

ttcgatgcca tccaagacat                                 20

<210> 104

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 104

tgtcttggat ggcatcgaac                                           20

<210> 105

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 105

ttgccacaaa actgggtgtt                                                              

<210> 106

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 106

caaaactggg tgttcggaag                                 20

<210> 107

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 107

cagatgtcgttattcacagc

<210> 108

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 108

tgtgaataac gacatctgcc                                                                

<210> 109

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 109

taacgacatc tgcctggacg                                         20

<210>  110

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 110

gctcctcggc cacctcgtcc                                   20

<210>  111

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 111

gggcccgtcc atttaaaagc                                                                                                                                                                                                                                           

<210> 112

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 112

ccttctgctgggcagggata                                                              

<210> 113

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 113

atcacaacct tctgctgggc                             20

<210> 114

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 114

tcacaacctt ctgctgggca                                                                  

<210> 115

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 115

gcgcttcctt tcgtcactcc                                                                   

<210> 116

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 116

agtttgccag gagtgacgaa                                   20

<210> 117

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 117

ggtccagcag caagtgcaag 20

<210> 118

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 118

gttcctcttg cacttgctgc                                   20

<210> 119

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 119

agatgaggtg ctcatgtttc                                     20

<210> 120

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 120

tggccacttc ttccgccttg                                                                           

<210>  121

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 121

gtacaagttc gtctctttcc                                 20

<210> 122

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 122

gctcattctg aggctcctgc                                     20

<210> 123

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 123

cagatcatgt gctcattctg                                 20

<210> 124

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 124

agaatgagca catgatctgc                                     20

<210> 125

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 125

cgtagtagtatcgcagggct

<210> 126

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 126

ctttacgtag tagtatcgca                             20

<210> 127

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 127

tgcacaggta gacgtgggcg                                                                  

<210> 128

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 128

cccacgtcta cctgtgcaac                                                                                                                  

<210> 129

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 129

ggaatttgag ccataggggc                                   20

<210> 130

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 130

tgatcatctc agtttggtgc                                   20

<210> 131

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 131

tgagatgatc atcaccaaac                                                                                                                                    

<210> 132

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 132

ggaactgcca cagctggatc 20

<210> 133

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 133

gtagtggcca gatccagctg                                 20

<210> 134

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 134

cgagcaggaa ctgccacagc                               20

<210> 135

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 135

cccgtggaag tcaaacttgt                                     20

<210> 136

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 136

cctacaagtt tgacttccac                                                              

<210> 137

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 137

caaaaatatc atccacaaga                                     20

<210> 138

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 138

aatatcatcc acaagacggc                                   20

<210> 139

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 139

aaatatcatc cacaagacgg                               20

<210> 140

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 140

agcgcttgcc cgccgtcttg                                 20

<210>  141

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 141

tctgcaggtc gcacacaaag                                     20

<210> 142

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 142

gaagcggacc aatccagttg                                   20

<210> 143

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 143

ccagctgatg aaagattgac                                                  20

<210> 144

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 144

cctgtcaatc tttcatcagc                                                                      

<210> 145

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 145

agcgcttgcc cgaagtcttg                                 20

<210> 146

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 146

tctgcaggtc acatacgaaa                                                                          

<210> 147

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 147

aggatccttc ataaaacaaa                         20

<210> 148

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 148

ggatccttca taaaacaaaa                             20

<210> 149

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 149

ttcataaaac aaaagggaaa                                 20

<210> 150

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 150

cttccttctg cagcagttcc                                   20

<210> 151

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 151

gctgccaggc gatgacatgg                                 20

<210> 152

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 152

cgctgtcgga cagtagttcc                                   20

<210> 153

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 153

acagctggcg ttggcgctgt                               20

<210> 154

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 154

ccaggtgata cagctggcgt                               20

<210> 155

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 155

tgaccaaagt gcatggcaaa                                       20

<210> 156

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 156

gccatggaag tcaaacttgt                                         20

<210> 157

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 157

aagagaaacg gagaatccga                                       20

<210> 158

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 158

ccatcttatt ccgttccctt                                                             

<210> 159

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 159

ctgcagccaa gtgccggaat                                   20

<210> 160

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 160

ttccttctct ttcagcagat                               20

<210> 161

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 161

ggaaaaactg gagtttattt                                   20

<210> 162

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 162

cagaagaaga agaaaagcga                             20

<210> 163

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 163

agcgaagggt tcgcagagag                                 20

<210> 164

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 164

tcgcagagag cggaacaagc                                 20

<210> 165

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 165

gatctgtcag ctccctccga                                     20

<210> 166

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 166

agcccggttt gtgggccacc                               20

<210> 167

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 167

aggagaagcg tcgaatccgg                                 20

<210> 168

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 168

agctagctgc agccaagtgt                             20

<210> 169

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 169

tctctgtcag ctcccggcga                                                  20

<210> 170

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 170

ggagctgaca gagaagctgc                                 20

<210> 171

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 171

cttctcctct tccagctcct                                                                   

<210> 172

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 172

atggccatat aagagtaggg                                   20

<210> 173

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 173

gaggccaccc tactcttata 20

<210> 174

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 174

atcatggcca tataagagta                               20

<210> 175

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 175

ccaagtgtag atgtccttca                                 20

<210> 176

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 176

ccaatggcaa ggtctccttc                                 20

<210> 177

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 177

tgatgaggtc ggcgtacgac                                             20

<210> 178

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 178

cttctcggct gagctctcga                               20

<210> 179

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 179

cgacagggtg agcctcttct                                                  20

<210> 180

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 180

ccctgtcgca gatctacgag                                 20

<210>  181

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 181

gaagagcgtg ccctacttca                                                            

<210> 182

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 182

ggcataggac aggttccccc                                                              

<210> 183

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 183

tgatcaggtc ggcataggac                                         20

<210> 184

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 184

gcgggtgatc aggtcggcat                                       20

<210> 185

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 185

gacaaagtga gccgtttgtc                                   20

<210> 186

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 186

gcacgggcaa gagctcttgg                                 20

<210> 187

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 187

ctgtggcggc gagatggtac                               20

<210> 188

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 188

ataaaatgaa tgggcagaac                               20

<210> 189

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 189

gcttgggctt gataaggggc                             20

<210> 190

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 190

ccttcgcttg ggcttgataa                                 20

<210> 191

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 191

acatcttccg gtttcgggtc                                   20

<210> 192

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 192

caagatgtga gctcacattg 20

<210> 193

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 193

aagatgtgag ctcacattgt                                     20

<210> 194

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 194

agatgtgagc tcacattgtg                                       20

<210> 195

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 195

ttgataaagc ttctgttatg                                 20

<210> 196

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 196

tctcacacgt aaataactga                             20

<210> 197

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 197

tcagagaggt aactcgttcc                                       20

<210> 198

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 198

ccaattatat actttcagag                               20

<210> 199

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 199

cctctctgaa agtatataat                               20

<210> 200

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 200

ataattggtt tgctaatcga                                 20

<210>  201

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  201

ttggtttgct aatcgacgga                               20

<210>  202

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 202

ctgcacgaag aaggcgtacg                                 20

<210>  203

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 203

cttcgtgcag acctgccgcg                                 20

<210>  204

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  204

gaagaagcat cccgactcgt                                                                                                          

<210>  205

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 205

gcgaagttca ccgacgagtc                                   20

<210>  206

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 206

ggcgaagttc accgacgagt                               20

<210>  207

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 207

gagcggcccc acggaggacc                                                                                                      

<210>  208

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 208

tctccacctg gtcctccgtg                                                                      

<210>  209

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 209

atctccacct ggtcctccgt                                                                    

<210>  210

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 210

cgatgaggca cagcgtggtg                                                               

<210>  211

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  211

gcagagtggc ggcggtcaga                                 20

<210>  212

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  212

ctactccaag ctcaaggaac                                                                                                                                  

<210>  213

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 213

tgtaatcgat gacgtgctgc                                       20

<210>  214

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  214

gcacgtcatc gattacatct                                 20

<210>  215

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 215

cttggacctg cagatcgccc                                                                

<210>  216

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 216

cgatagtggg atgcgagtcc                                 20

<210>  217

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 217

accactgcta ctcgcgcctg                                 20

<210>  218

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 218

ctcccggcac cagttcccgc                                                                      

<210>  219

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 219

ctggtgccgg gagtcccgcg                                                               

<210>  220

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  220

tggctaagct gagtgcctcg                               20

<210>  221

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 221

cacgctgcag gatttccacc                                 20

<210>  222

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  222

atctgtggga tcgtttgcat                                     20

<210>  223

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 223

tttgtgaacc atgagcacat                                         20

<210>  224

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 224

ccacactggt tgcactggaa                                       20

<210>  225

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 225

agcttcgctg tttatagctc                             20

<210>  226

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 226

taaacagcga agctctttag                                                  20

<210>  227

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 227

aagctccgca ctggtcag

<210>  228

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 228

gggtaaaaga agctccgcac                                 20

<210>  229

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 229

tctcagaagg ttgcccttct                                 20

<210>  230

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 230

gtctcagaag gttgcccttc                                 20

<210>  231

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 231

agaagaaggg acgctctcac                               20

<210>  232

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 232

aagatgaact gcgacgtgtg                                     20

<210>  233

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 233

agatgaactg cgacgtgtgc                                         20

<210>  234

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 234

caagacgttg aagctaatgc                               20

<210>  235

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 235

cgtcatatta aactgcacac                               20

<210>  236

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 236

gcgttccttg tgctcctcca                               20

<210>  237

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 237

gtctgcggca tggtctgcat                                       20

<210>  238

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 238

tctgcggcat ggtctgcatt                                         20

<210>  239

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 239

cttgtgtacc atgagcacat                                       20

<210>  240

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 240

cccccgagtg cagcttgatg                                                                  

<210>  241

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  241

cgccggcgtg acgcactcac                               20

<210>  242

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 242

cagcgtgctt ccatggaatc                               20

<210> 243

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 243

tgcttagcag cgtgcttcca                             20

<210>  244

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 244

tggaagcacg ctgctaagca                                 20

<210>  245

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 245

gcacgctgct aagcacggct                                 20

<210>  246

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 246

gaaggatcag agtaggaaca                                                                                                                          

<210>  247

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 247

ctttagccct ggtatcgtat                                   20

<210>  248

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 248

gccgagccgc atgcatccag                                                                 

<210>  249

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 249

ccagatcccc tggatgcatg                                                     

<210> 250

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 250

gtgccgagcc gcatgcatcc                                                                           

<210>  251

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 251

aaggacagaa gcataaagaa                               20

<210> 252

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 252

ctggacctgg ggcagctgga                                                              

<210> 253

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 253

gccgtaggccatgcttccac

<210> 254

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 254

tgccgtaggc catgcttcca                                     20

<210> 255

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 255

tcccgtggaa gcatggccta                                                                                                                

<210> 256

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 256

gttagctgct gacaatagca                                 20

<210> 257

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 257

gaacaagagc aatgactttg                                     20

<210> 258

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 258

gtggaaacac gcgggcaagc                                   20

<210> 259

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 259

gcaggactac aatcgtgagg                                                                                                                

<210>  260

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 260

tttaaaggca agttccgaga                                                                                                                    

<210>  261

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 261

acaagccaga tcctcctact                                     20

<210>  262

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 262

ccccaccacc ccgccgtgtg                                                     

<210>  263

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 263

gtactggcag ctgttcacct                                       20

<210>  264

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 264

gtgaacagct gccagtaccc                                       20

<210>  265

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 265

tgaacagctgccagtaccca

<210>  266

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 266

gcgcaggttg gccttccact                                   20

<210>  267

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 267

tgtgtagccagatgagacca

<210>  268

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 268

ctgtgtagcc agatgagacc                               20

<210>  269

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 269

ccaggggatc tggaagcgtt                               20

<210>  270

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 270

tggcatgttt ccaggggatc                                                             

<210>  271

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 271

cttgatgtac gatggcacca                                     20

<210>  272

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 272

tcagcagcgg ccagtacgag                                       20

<210> 273

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 273

gccactgcag cccctcgtac                                                                        

<210> 274

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 274

gccagtacga ggggctgcag                                                                                                                          

<210> 275

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 275

gcacagtctt ccgcgtaccc                                   20

<210>  276

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 276

ctgtgctgtg gagtgcacag                                                                   

<210>  277

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 277

cagaaatgtc cagctgggac                                                  20

<210>  278

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 278

atggctcaga aatgtccagc                                   20

<210>  279

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 279

tggctcagaaatgtccagct

<210>  280

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 280

tcagtcactt cttcaaaatc                                                            

<210>  281

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 281

agtgactgac cggtcccagc                                       20

<210>  282

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 282

ctgcatgcttccagggaatc                                                                 

<210> 283

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 283

cggattccct ggaagcatgc                                                                                                

<210>  284

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 284

ttgcttgcct gcatgcttcc                                       20

<210>  285

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 285

gcggagctgg atcgtggagc                                     20

<210>  286

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 286

gagctggatc gtggagcagg 20

<210>  287

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 287

aggagcggat caaggcagag                               20

<210>  288

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 288

ggcacttgga ggcggcaatg                                             20

<210>  289

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 289

cagcttccttttccggcact                                                                        

<210>  290

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 290

ggaagctgga gcggatcgct                                         20

<210>  291

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 291

gaaagcgcaa aactccgagc                                   20

<210>  292

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 292

ggcactaccg caaacacaca                               20

<210>  293

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 293

accgcaaaca cacagggcac                                                                                                          

<210>  294

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 294

acttctggca ctgaaagggc                             20

<210>  295

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 295

tcagtgccag aagtgtgaca                                       20

<210> 296

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 296

aaaaggcct gtcacacttc

<210>  297

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 297

20

<210>  298

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 298

tgcagctatc aaccagatcc                               20

<210> 299

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 299

ggcctgctct tcccgggaga                                                         

<210> 300

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 300

ccgtgctagt tcatagtatt                                       20

<210> 301

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 301

ctacacatgc agctttatcc                               20

<210> 302

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 302

cgtgaagcgc gtgtgccaga                                 20

<210> 303

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 303

gaagcgcgtg tgccagaagg                                 20

<210> 304

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 304

gcttctgcag ctcctccttc                                   20

<210> 305

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 305

cacgcgcttc acgcggcagc                               20

<210> 306

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 306

tctggcacac gcgcttcacg                                     20

<210> 307

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 307

ggagaatgcc agcatgaagc 20

<210> 308

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 308

atcgagctcc agcttcatgc                                   20

<210> 309

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 309

gttctgcagg gcctcgtact                                   20

<210> 310

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 310

ccagcttctc cacctcctgc                                                                         

<210> 311

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 311

ggaggtggag aagctggcct 20

<210> 312

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 312

atagagcttg tccagaaata                               20

<210> 313

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 313

gaaaacctcc tggacagaag                                         20

<210> 314

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 314

agcgtcactt ggggaaaact                           20

<210> 315

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 315

tgagaagctg aagaagctgg                                     20

<210> 316

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 316

tgatcttctt ctttggtcca                                                          

<210> 317

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 317

ggaagcagtg ccgtgagcgc                                           20

<210> 318

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 318

gctggaccga ggaggaagac                                   20

<210> 319

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 319

ggaagacagg atatctgtg

<210> 320

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 320

ctgtgaggcc cataaagtcc                                                                                                                

<210> 321

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 321

attgagttgg tcaagaagta                                     20

<210> 322

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 322

cggaggaaaa cgacaagagg                                     20

<210> 323

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 323

acaacgtctt ggaacgtcag                                   20

<210> 324

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 324

ttcagggatc tggtcacgca                                   20

<210> 325

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 325

tttcgttgtt ttccaattca                           20

<210> 326

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 326

tttgaggatc actaccttgg                                                            

<210> 327

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 327

acactgagga cgtgaccaag                                   20

<210> 328

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 328

gaagttatgg ttcttcctct                                   20

<210> 329

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 329

gaggaagaac cataacttct                                                                                                                

<210> 330

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 330

gaatacttgc aggctttggt                                   20

<210> 331

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 331

agaatacttg caggctttgg                                     20

<210> 332

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 332

tataactttg cctgtatcag                                           20

<210> 333

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 333

acatatattc ccactgatac                                                                     20

<210> 334

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 334

atatatgttg tgaccaatgc                                 20

<210> 335

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 335

tcagccattt acgtacactc                                         20

<210> 336

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 336

ggatccggag tgtacgtaaa                                           20

<210> 337

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 337

taatgaacca gtggtgttgc                                     20

<210> 338

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 338

acaaatacct gcaacaccac                                                                                                                                                                                                                                                                                              

<210> 339

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 339

agtggtgttg caggtatttg                                 20

<210> 340

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 340

attaactcga aaaaccaatc                               20

<210> 341

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 341

gttaatatca caaggaaaga                               20

<210> 342

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 342

atgagacgga aggcagccgg                                                                                                            

<210> 343

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 343

tgagacggaa ggcagccggg                                                                                                                  

<210> 344

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 344

aggcagccggggggctgtga

<210> 345

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 345

ccggacgctg tctctccagg                                                                   

<210> 346

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 346

cgatagggtt cgaggcccac

<210> 347

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 347

ctcatagtgg gcccggtgat                                                                                                            

<210> 348

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 348

cccggcccac tatgagacgg                                                                                                

<210> 349

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 349

ggcgctgtca aagccccaac                                 20

<210> 350

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 350

gcttgttctc catgtagccg                                   20

<210> 351

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 351

ctggggcttc agatcttcat                                 20

<210> 352

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 352

tgtaactgct gggttatgat                                       20

<210> 353

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 353

gcacggcaga tgtaactgct                                     20

<210> 354

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 354

tgcacggcag atgtaactgc                                         20

<210> 355

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 355

agcagttaca tctgccgtgc                                     20

<210> 356

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 356

tttatctttg caatggcaag                                       20

<210> 357

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 357

ggtaaaggcc agtctaatgg                                       20

<210> 358

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 358

gttggtaaag gccagtctaa                                 20

<210> 359

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 359

tggcctttac caactcactt                                                                                                      

<210> 360

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 360

atgaaactga aggtagccga 20

<210> 361

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 361

gtgcacatcc cacagcccag                                                                                      

<210> 362

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 362

tttagagtct ggcaggaagt                                   20

<210> 363

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 363

acaccacttt agagtctggc                                                            

<210> 364

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 364

cttcctgcca gactctaaag                                 20

<210> 365

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 365

tttacgtctc caatggacgg                                 20

<210> 366

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 366

actgcgcttc ctccgtccat                                 20

<210> 367

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 367

cgagctcact atgagactga                                   20

<210> 368

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 368

tcattggcac tgcagatgag                                                                                                                          

<210> 369

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 369

ctgcagatga gaggcctg

<210> 370

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 370

ggtagaaggc atggggccgc                                                      

<210> 371

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 371

cgggaaggtc gtgtctgtgc                                                                               

<210> 372

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 372

gaaaatggcg gagtttggga                               20

<210> 373

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 373

ggcggagttt gggaaggatt                                 20

<210> 374

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 374

gcggagtttg ggaaggattt                               20

<210> 375

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 375

cggagtttgg gaaggatttg                             20

<210> 376

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 376

ctgtctatga acatctgtgg                                       20

<210> 377

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 377

acttcatgtg actaagaaaa                               20

<210> 378

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 378

gaaaaaggta tttgaaacac                               20

<210> 379

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 379

tatttgaaac actggaagca 20

<210> 380

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 380

ggatgacagaggcgtgtatt

<210> 381

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 381

atcgttcagt tggtcacaaa                                   20

<210> 382

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 382

cattgaggtt cggttctatg                                   20

<210> 383

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 383

gagaatggat ggcaagcctt                                                                                                                      

<210> 384

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 384

gaatggatgg caagcctttg                                             20

<210> 385

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 385

agaatggatg gcaagccttt                                   20

<210> 386

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 386

tgtgggagag aagtccccaa                                                        

<210> 387

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 387

tgtaaccaag aagaacatga                                   20

<210> 388

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 388

caaggagctg aagaaagtca                             20

<210> 389

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 389

tcatggatct gagcattgta                                                                                                            

<210> 390

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 390

aggagccatc gctagctcga                             20

<210> 391

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 391

gtgggtcact gtgtgtcacc                                                              

<210> 392

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 392

aacagaatat ccagtacaaa                                                                                                                                

<210> 393

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 393

gttgcgattg atgcgaacga                                   20

<210> 394

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 394

20

<210> 395

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 395

acttcttgaa gcgacactgc                                 20

<210> 396

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 396

ttcaagaagt gtctctccgt                                   20

<210> 397

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 397

tggaacagttctcattcttc                                                                     

<210> 398

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 398

atgagaactg ttccatcatg                                       20

<210> 399

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 399

tttaagaagt gtctgtctgt                                       20

<210> 400

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  400

ctttaagaag tgtctgtctg 20

<210> 401

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  401

ttaagaagtg tctgtctgtg                                     20

<210> 402

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  402

gagggccgct gtgcagtctg                                                                                         

<210> 403

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  403

aatgcttcgt gtcagcacta                             20

<210> 404

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  404

tatggggtcc gcacctgtga                                       20

<210> 405

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  405

aagcgccaag tacatctgcc                                 20

<210> 406

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  406

ggcaaacaag gattgccctg                                     20

<210> 407

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  407

gacagtactg acaacgattt                             20

<210> 408

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  408

gaaatcgttg tcagtactgt                                     20

<210> 409

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  409

ttcagaagtg cctagctgtt                                 20

<210>  410

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  410

gaagtgccta gctgttggga                                       20

<210>  411

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  411

ctttaaccat cccaacagct                                                                                                              

<210> 412

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  412

tgcagtactg acatcggttt                                 20

<210> 413

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  413

gaaatctgca gtactgacat                                                                                        

<210>  414

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  414

tttcagaagt gtctcagtgt                                 20

<210> 415

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  415

gaagtgtctc agtgtcggga                               20

<210> 416

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  416

tctcagtgtc gggatggtta                                                                 

<210> 417

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  417

cagcttgtcc aactggtcgg                                       20

<210> 418

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  418

tgtgagccag gctgggtaga                                   20

<210> 419

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  419

gcctggctca cagtgtcaga                                                                                                                

<210> 420

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  420

cgaccagttg gacaagctgc                                 20

<210>  421

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  421

cggaggatct tatgctgaac                                                                                                                            

<210> 422

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  422

cccacagact cggcactcaa                                 20

<210> 423

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  423

gccattgagt gccgagtctg                                                                              

<210> 424

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  424

cattgagtgc cgagtctgtg                                 20

<210> 425

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  425

ataaataagc ttcaatcgga                               20

<210> 426

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  426

ggccgagaag gagaagctgt                                                  20

<210> 427

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  427

aatgtctgtg ccaagacgtt                           20

<210> 428

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  428

gtccacctga gagtgcacag                                                                      

<210> 429

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  429

ttgcaggtct ggcacttgaa                                     20

<210> 430

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  430

caagtagtgt ttctgcaggt                                 20

<210> 431

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 431

ttgtgctgct aaatctcttg                             20

<210> 432

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 432

caatgactcg agttctcc                                                                        

<210> 433

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 433

agtcattgtc atgaccacaa                                 20

<210> 434

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  434

tgtcatgacc acaaaggaag                                       20

<210> 435

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 435

gagtatgcgc tcaaagaata                                     20

<210> 436

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  436

ggacagccat gtagataaac                                   20

<210> 437

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  437

gctgcagaaa tgtttcgacg                               20

<210> 438

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  438

gtttgtcaag acaaatcatc                                 20

<210> 439

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  439

aaatcatccg gctaccacta                                                  20

<210> 440

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  440

20

<210> 441

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  441

aatcatccgg ctaccactat                                                                                                                  

<210> 442

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  442

caagccctgc ttcgtttgcc                                   20

<210> 443

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  443

cttgtcctgg caaacgaagc                                       20

<210> 444

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  444

ttgtcctggc aaacgaagca                                 20

<210> 445

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  445

ctgcagaagt gctttgaagt                                   20

<210> 446

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  446

cctgcagaag tgctttgaag                                     20

<210> 447

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  447

ggctttataga cccgaggagg                                                                                                                

<210> 448

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  448

catggcttat agacccgagg                                                                                                              

<210> 449

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  449

aagcatggct tatagacccg                               20

<210> 450

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 450

ttgtcattgc atacaaagca                               20

<210> 451

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 451

gtatgcaatg acaagtcttc                                 20

<210> 452

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  452

tattcggtgt gtaaagaaaa                             20

<210> 453

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 453

tgtccagcag ctgctgttca                                 20

<210> 454

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 454

atgtccagca gctgctgttc                                     20

<210> 455

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 455

attgggttag aaacaatggg                               20

<210> 456

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 456

ggatactatg aagcagaatt                                 20

<210> 457

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  457

tttcacggga ccaggctggg                                   20

<210> 458

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 458

ggaccaggct gggaggcacg 20

<210> 459

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 459

gagcctcgtg cctcccagcc                                                                            

<210> 460

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  460

atgcacatca gcttgagaaa                                   20

<210> 461

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  461

agctgatgtg catcggcaag                                     20

<210> 462

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  462

ccaggcttctgggccttatg                                                                                                                                                                                                                                               

<210> 463

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 463

tgttcgatga tctccacata                                 20

<210> 464

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  464

tcatcgaaca gccgaagcaa                                           20

<210> 465

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 465

atcgaacagc cgaagcaacg                                   20

<210> 466

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 466

ctgccgggat ggctactatg                                                     

<210> 467

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  467

tggtgttcag cacagcttcc                                   20

<210> 468

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  468

ggtgttcagc acagcttcct                               20

<210> 469

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  469

gaagtcggca cggccttccc                                 20

<210> 470

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  470

cacatcagcttgagagaagt

<210> 471

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  471

tctctcaagc tgatgtgcac                                                    

<210> 472

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  472

tcgagactgt ggcgggctgc                                 20

<210> 473

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 473

agactgtggc gggctgcggg                                                                         

<210> 474

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 474

ctgtggcggg ctgcgggga

<210> 475

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 475

gacggcgtgc ctggtgtgga                                 20

<210> 476

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 476

tgtcgtagac aggctcagag                                 20

<210> 477

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  477

tgtgagcaca gggcaggatg                                         20

<210> 478

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  478

agaagctgtg agcacagggc                                 20

<210> 479

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  479

ctgacagaag ctgtgagcac                                         20

<210> 480

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  480

tgacagaagc tgtgagcaca                                   20

<210> 481

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  481

tcatctgtag gcgacaaatg                                     20

<210> 482

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  482

ctgacgagga caggagtagg                                                                                                      

<210> 483

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  483

cttctgacga gcacaggagt                                                                    

<210> 484

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  484

acagttcttc tgacgaggac                               20

<210> 485

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  485

cacacgtaat gacaccataa                                     20

<210> 486

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  486

tatggtgtca ttacgtgtga                                 20

<210> 487

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  487

caggctgtcc cgctgcttct                               20

<210> 488

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  488

gcgggacagc ctgtatgctg                                     20

<210> 489

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  489

gcttctgcac ctcagcatac                                                                  

<210> 490

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  490

tacggagtca tcacgtgtga                                 20

<210> 491

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  491

gaggatgtcc aagaagcagc 20

<210> 492

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  492

atctgtgggg acaagtcatc                               20

<210> 493

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  493

cacaggtgat aaccccgtag                             20

<210> 494

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  494

tacggggtta tcacctgtga 20

<210> 495

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  495

ctacggggtt atcacctgtg                                     20

<210> 496

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  496

ctcgggacat gcccagcc

<210> 497

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  497

ttcaacgacc ttcgattcgt                               20

<210> 498

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  498

gttcaacgac cttcgattcg                                   20

<210> 499

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400>  499

cactgcggcc cacgaatcga                                 20

<210> 500

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 500

ttcgattcgt gggccgcagt                                 20

<210> 501

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 501

tgcgcacgag ctctcccgcg                                 20

<210> 502

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 502

gccacgaacc aaaatttccg                                     20

<210> 503

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 503

cagggcttcc acggaaattt                               20

<210> 504

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 504

aaaatttccg tggaagccct                                                              

<210> 505

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 505

cggtactacc ttaagcacca 20

<210> 506

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 506

tcagcttgcc atggtgctta                                     20

<210> 507

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 507

ctccactcgc ttatagtggt                                                                                                      

<210> 508

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 508

catcgccctg tttccaccca                               20

<210> 509

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 509

agggcgatga agaagagaaa                               20

<210> 510

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 510

ggccttctcc agctcttcca                                   20

<210> 511

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 511

tcagttcatg gtggctctgg                                     20

<210> 512

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 512

agaagtctct tcaccactgg                                                                                                      

<210> 513

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 513

ctgggatgga aaaaatcagc                                                                                                                

<210> 514

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 514

gggtctggag gagcaggtgg                                         20

<210> 515

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 515

tgaaaaagca gtgaaaagtc                               20

<210> 516

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 516

attgcaattc tgagtggtga                                     20

<210> 517

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 517

caggcgcttc acgatcgggg                             20

<210> 518

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 518

tcgtgaagcg cctgctgggt                               20

<210> 519

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 519

gaagggcgag cagaacgggc                                   20

<210> 520

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 520

cgagaaggcg gtcaagagct                               20

<210> 521

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 521

gctcaagaag acggggcagt                                                                                                                      

<210> 522

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 522

agttcattct tgtgtagatc                             20

<210> 523

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 523

acaacccgct catagtgata                             20

<210> 524

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 524

gaatccatat cactatgagc                                                                                                                  

<210> 525

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 525

tgatgtgtca tagacaaggt                                 20

<210> 526

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 526

tctatgcccg tctgtggagg                                                              

<210> 527

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 527

aggtgacgag gaagagaaat                                 20

<210> 528

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 528

ggaagagaaa tgggcagaaa                                 20

<210> 529

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 529

gaaaaagctg aagaagaaga                               20

<210> 530

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 530

gaagggtgct atggaggagc                                                                                                                                                                                                                            

<210> 531

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 531

tcgtgatggc tctgcaaatc                               20

<210> 532

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 532

ccgcgcgccg acctccgctt                               20

<210> 533

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 533

ctggccgccc aagcggaggt                                                                      

<210> 534

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 534

cgcgccgacc tccgcttggg                                     20

<210> 535

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 535

gagcagcagc tgcggtggcg                                                     

<210> 536

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 536

accacttcag ccggctctgc                                     20

<210> 537

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 537

ggactgcagg ctgggcccgg                                                                    

<210> 538

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 538

tggactgcag gctgggcccg                                                                      

<210> 539

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 539

gtaggacgag ggcggctgcg                                     20

<210> 540

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 540

cagcaggagg gggagcgagt                                                               

<210> 541

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 541

tctgaaggcg ctcacgcact                                     20

<210> 542

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 542

ccgggggcag cggcgtaaga                                                                                                                  

<210> 543

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 543

gatcagcaag cgcctgggcg                                   20

<210> 544

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 544

aaagtttcca ctccgcgccc                                                              

<210> 545

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 545

cgttcatcga cgaggccaag                                   20

<210> 546

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 546

gtgcagagcg cgcagccgct                               20

<210> 547

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 547

20

<210> 548

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 548

gtgcaccgca cgcagtcgct                                   20

<210> 549

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 549

cgaggccaag cgactgcgtg                                 20

<210> 550

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 550

actgcgtgcg gtgcacatga                                     20

<210> 551

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 551

ggtgcacatg aaggagtacc                                                                                

<210> 552

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 552

agaatccacc aacggaagtc                                 20

<210> 553

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 553

ctcagctgcc agacttccgt                                                                                                                    

<210> 554

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 554

ctgaaggaac agaaaaacgc                               20

<210> 555

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 555

tgaaggaaca gaaaaacgct                             20

<210> 556

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 556

ggtgcttctt aatgagctct                               20

<210> 557

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 557

aaaaccttga ccccggagga                                   20

<210> 558

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 558

ctggccctcc tccggggtca                                                                

<210> 559

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 559

ctgtctctgg ccctcctccg                                                                

<210> 560

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 560

gccagagaca gggcttaatt                                     20

<210> 561

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 561

gctggacaaa attctggagc                                 20

<210> 562

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 562

gcagctggac acacgctacc                                                                                                                    

<210> 563

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 563

gtacagcgac agcttcccca                                                              

<210> 564

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 564

gactctcaat ccaaggtgcc                                     20

<210> 565

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 565

gagattatga aacaccaacg                                         20

<210> 566

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 566

agaggacatt ggactcttgc                                                                                                              

<210> 567

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 567

attaccacag ctacatgcat                                                                                                            

<210> 568

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 568

cttcagtttc tgaaagacaa                               20

<210> 569

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 569

ctatgatgac aactttccta                                 20

<210> 570

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 570

tccggcatct gctagctcag                                       20

<210> 571

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 571

aatacaattg gatgaacagt                               20

<210> 572

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 572

ggacgataac gaccacaggg 20

<210> 573

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 573

gacgataacg acccaggga                                                                                                              

<210> 574

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 574

catggacgat aacgaccaca                                   20

<210> 575

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 575

gcagtggttc gacggggtga                               20

<210> 576

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 576

gtggttcgac ggggtgatgg                                   20

<210> 577

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 577

ccgtgcgcct gctggtgggg                                     20

<210> 578

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 578

agacctcttg attcgtttca                                   20

<210> 579

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 579

cagacctctt gattcgtttc                                 20

<210> 580

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 580

actttctggc agtggtttga                                                                    

<210> 581

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 581

gcagtggttt gatggcgtga                               20

<210> 582

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 582

ctaagcctgg cccaggggcc                                       20

<210> 583

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 583

taagcctggc ccaggggccc                                                                  

<210> 584

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 584

aggagagatc atgaacaaca 20

<210> 585

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 585

agaaaataaa gcgctgtgag                                 20

<210> 586

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 586

tccggagaca gcgtttggtg                                   20

<210> 587

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 587

tgaacttgga ccacaacagg                                                        

<210> 588

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 588

tagtgatgat catctctgtc                                 20

<210> 589

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 589

ccacggtgaa ggacaggaat                                       20

<210> 590

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 590

tggagcccac aagcattac                               20

<210> 591

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 591

tggtggacca gcaccactgg                                                                                            

<210> 592

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 592

agccagactt ggacgggggg                                       20

<210> 593

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 593

tgcagccaga cttggacggg                                                

<210> 594

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 594

ttccaccccc cgtccaagtc                               20

<210> 595

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 595

tcgataggtg cagccagact                                   20

<210> 596

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 596

catcactcaa ctccagtctg                                 20

<210> 597

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 597

cggagcggga gaaggagcgc                                                                                                          

<210> 598

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 598

ggagcgggag aaggagcgcc                                                                              

<210> 599

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 599

gcgggagaag gagcgccggg                                                  20

<210> 600

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 600

gcgggtccgc gacatcaatg                                                                  

<210> 601

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 601

gcacctgctg ctccaggctg                                                                

<210> 602

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 602

ttgaggggtt tcttgatgac                                 20

<210> 603

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 603

taaagcatga acgcattgag                                                                                                          

<210> 604

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 604

gtaaagcatg aacgcattga                                       20

<210> 605

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 605

tcaaccagat cctgggtcgc                                                                   

<210> 606

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 606

atacccgggc tggtccgcgc                                                                       

<210> 607

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 607

atacaacatg aaggcattca                                         20

<210> 608

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 608

tacaacatga aggcattcag                                                                                                          

<210> 609

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 609

tatacaacat gaaggcattc                                   20

<210>  610

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 610

taatggctgc actttccttc                                                                  

<210> 611

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 611

atagttgtcc cgggctgacc                                     20

<210> 612

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 612

acaggcttct ggggctcatt                               20

<210> 613

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 613

taggcagaca caggcttctg                               20

<210> 614

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 614

tttgttcttt cgtgataccc                               20

<210> 615

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 615

caaaagtagc atttggattc                             20

<210> 616

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 616

cgaagattgt ggcatcaatg                                                                

<210> 617

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 617

actggcttct gtggctcatt                                                                        

<210> 618

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 618

taggccgaca ctggcttctg                                 20

<210> 619

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 619

tgagccacag aagccagtgt                                     20

<210> 620

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 620

tgtaggccgc caaggctttc                               20

<210> 621

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 621

ggagtacctg aaagccttgg                                     20

<210> 622

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 622

agacgtgccc tgtgcagttg                                                                    

<210> 623

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 623

gtgctgtgac ttcttgtaga                                 20

<210> 624

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 624

caagaagtca cagcacatga 20

<210> 625

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 625

ctgtacggcg gtctctccca                               20

<210> 626

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 626

tctgtacggc ggtctctccc                                                    

<210> 627

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 627

ccacttatgc cattactgtg                                                                 

<210> 628

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 628

caaagcgctccccacagtaa                                                                                                                          

<210> 629

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 629

gtgttgtctc aggttacttc                                                            

<210> 630

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 630

ggtgttgtct caggttatactt                                                               

<210> 631

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 631

gggtatggag gtgttgtctc                                   20

<210> 632

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 632

ttgcttccgt cgatgaccac                                   20

<210> 633

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 633

ggtcatcgac ggaagcaatg                                         20

<210> 634

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 634

agaagacttc cttgttccca                                 20

<210> 635

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 635

ggctgttcct tcctccaaga                                   20

<210> 636

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 636

cgaaggaagt tgtccaggct                                                                                                                                                                                                                                                                          

<210> 637

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 637

aagaggccat aaagatatca                             20

<210> 638

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 638

tcctggtatt cacaccatca                                                                                                      

<210> 639

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 639

cacaccatca cggcgtgtcc                             20

<210> 640

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 640

acaccatcac ggcgtgtcca                               20

<210> 641

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 641

ctcagaaaat tatccagact                                   20

<210> 642

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 642

cgagtgtgga atctgtagaa                                 20

<210> 643

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 643

atcatttgat tgagcacatg 20

<210> 644

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 644

gcacatgcgg ctgcactctg                                       20

<210> 645

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 645

ccacacttgt cacattgata                                                                                                

<210> 646

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 646

gtgattcatg tgttgagagt                                     20

<210> 647

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 647

acagacatgt ggtccttgta                                     20

<210> 648

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 648

agcatactat gctatgaaca                                       20

<210> 649

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 649

ttcagcagtt catcagagtt                                 20

<210> 650

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 650

ctgaggaagg cccacagcaa                                                                       

<210> 651

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 651

ctcaggaatt tgtgaaggaa                                       20

<210> 652

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 652

tccactgtgt atcctctgat                                       20

<210> 653

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 653

ctccactgtg tatcctctga                                 20

<210> 654

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 654

acccatcaga ggatacacag 20

<210> 655

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 655

gaggtttgaa ttcagactga                                                                  

<210> 656

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 656

ggattctttg atgtctttg                                 20

<210> 657

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 657

aggatctgtc ccaggctcct                           20

<210> 658

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 658

gacttggcag gatctgtccc

<210> 659

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 659

ggaatgatga cagacttggc                                                                                                    

<210> 660

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 660

agcttccctt taaggccttc                               20

<210> 661

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 661

gcatgtaggg gatgtaggac                                                                                                                

<210> 662

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 662

gggcccggtg gctgagccca                                                        

<210> 663

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 663

aattccatgg gctcagccac                                   20

<210> 664

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 664

attccatggg ctcagcccac

<210> 665

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 665

cagccaccgg gcccctccct                                                                      

<210> 666

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 666

gacagcaaac cggaagctga                               20

<210> 667

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 667

aggacttcgg acttcttcta                               20

<210> 668

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 668

gaagaagtcc gaagtcctat 20

<210> 669

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 669

ctagctgacc gataggactt                                 20

<210> 670

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 670

atactgaaac agttgataaa                                 20

<210> 671

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 671

ctcaaagact gatccttctg                                                            

<210> 672

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 672

ggacagaaaa atccagcctt                                                                                                                                                                                                                                                                                

<210> 673

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 673

gagtagaaga gggagcaaat                                                                                                                

<210> 674

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 674

atttgctccc tcttctactc                                                  

<210> 675

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 675

ctactcaggt gaaaaagcaa                             20

<210> 676

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 676

gaagcgggca gatccagctg                                 20

<210> 677

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 677

ccaggaggaa ttgccacagc                                 20

<210> 678

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 678

ccagctgtgg caattcctcc                                                             

<210> 679

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 679

tgtcggagag cagctccagg                                   20

<210> 680

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 680

cgctgtcgga gagcagctcc                                   20

<210> 681

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 681

acagctggcg ttggcgctgt                               20

<210> 682

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 682

ccaggtgata cagctggcgt                               20

<210> 683

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 683

ccaacgccag ctgtatcacc                                                            

<210> 684

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 684

cccctcccag gtgatacagc                                                                   

<210> 685

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 685

caacgccagc tgtatcacct 20

<210> 686

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 686

cgccagctgt atcacctggg                                   20

<210> 687

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 687

gccagctgta tcacctggga 20

<210> 688

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 688

ccagctgtat cacctggggag                                                                

<210> 689

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 689

ctccccgttg gtcccctccc                                                            

<210> 690

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 690

atcacctggg aggggaccaa                                 20

<210> 691

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 691

tcacctggga ggggaccaac                                                                                                              

<210> 692

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 692

cacctgggag gggaccaacg                                                                                                      

<210> 693

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 693

cgtcattttg aactccccgt                                   20

<210> 694

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 694

caacggggag ttcaaaatga                                 20

<210> 695

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 695

caaaatgacg gaccccgatg                                                  20

<210> 696

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 696

aatgacggac cccgatgagg                                   20

<210> 697

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 697

agcgcctggc cacctcatcg                                     20

<210> 698

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 698

cggaccccga tgaggtggcc                                                                                      

<210> 699

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 699

cagcgcctgg ccacctcatc                                                                

<210> 700

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 700

ccagcgcctg gccacctcat                                                                   

<210> 701

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 701

ccgatgaggt ggccaggcgc                                                                   

<210> 702

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 702

cgatgaggtg gccaggcgct                                 20

<210> 703

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 703

gatgaggtgg ccaggcgctg                                   20

<210> 704

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 704

tttccgctcg ccccagcgcc                                     20

<210> 705

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 705

tggccaggcg ctggggcgag                                                  20

<210> 706

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 706

agcttgtcgt aattcatgtt                                 20

<210> 707

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 707

catagtaata acggagggcc                                     20

<210> 708

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 708

tttatcatag taataacgga                           20

<210> 709

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 709

ttttatcata gtaataacgg                                     20

<210> 710

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 710

tgtttttatc atagtaataa                               20

<210> 711

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 711

aacattatga ccaaagtgca                           20

<210> 712

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 712

atatcttttg ccgtgcactt                                     20

<210> 713

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 713

gcttacaaatttgacttcca

<210> 714

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 714

agtggaagcc attgctctcg                                 20

<210> 715

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 715

aatggcaact ggtccccttc                                 20

<210> 716

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 716

gaagatgggc gggagtcttc                               20

<210> 717

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 717

cagcttgtcc aactggtcgg                                       20

<210> 718

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 718

ccaaagccac catsgcaaag

<210> 719

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 719

gaacatcggc tacagccagg                                 20

<210> 720

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 720

cgctgtcgga cagtagttcc                                   20

<210> 721

<211>  20

<212> DNA

<213> Artificial sequence

<220>

<223> sgRNA

<400> 721

gccatggaag tcaaacttgt                                         20

Claims (26)

1. Modified immune cells or their precursors, containing modifications at an endogenous locus encoding Fli1. 2. Modified immune cells or their precursors, wherein the endogenous Fli1 gene or protein is disrupted. 3. The modified immune cell or its precursor according to claim 1 or 2, wherein the modification or disruption is performed by a method selected from: CRISPR system, antibody, siRNA, miRNA, antagonist, drug, small molecule inhibitor, PROTAC target, TALEN and zinc finger nuclease. 4. The modified immune cell or its precursor according to claim 3, wherein the CRISPR system comprises at least one sgRNA, the at least one sgRNA comprising any one of SEQ ID NO:152-156 or SEQ ID NO:676-713. 5. The modified immune cell or its precursor according to any one of the preceding claims, wherein the cell is a human cell. 6. The modified immune cell or its precursor according to any one of the preceding claims, wherein the cell is a T cell. 7. The modified immune cell or its precursor according to claim 6, wherein the T cell is resistant to T cell exhaustion. 8. A pharmaceutical composition comprising an inhibitor of Fli1. 9. The pharmaceutical composition according to claim 8, wherein the inhibitor is selected from CRISPR systems, antibodies, siRNA, miRNA, antagonists, drugs, small molecule inhibitors, PROTAC targets, TALENs, and zinc finger nucleases. 10. The composition of claim 9, wherein the CRISPR system comprises at least one sgRNA, the at least one sgRNA comprising any one of SEQ ID NO:152-156 or SEQ ID NO:676-713. 11. A method for treating a disease or disorder in a person in need, the method comprising administering to the person the cells of any one of claims 1-7 or the composition of any one of claims 8-10. 12. The method of claim 11, wherein the disease or obstacle is an infection. 13. The method of claim 11, wherein the disease is cancer. 14. A method for screening T cells, the method comprising: i) Introduce the Cas enzyme and sgRNA library into activated T cells. ii) The T cells were administered to the infected mice. iii) Isolate the T cells from the infected mice, and iv) Analyze the T cells. 15. The method of claim 14, wherein the sgRNA library comprises multiple sgRNAs targeting multiple transcription factors. 16. The method of claim 15, wherein the plurality of transcription factors includes any of the transcription factors listed in Table 1. 17. The method of claim 15, wherein each sgRNA targets the DNA-binding domain of each transcription factor. 18. The method of claim 14, wherein the sgRNA library comprises at least one sequence selected from SEQ ID NO:1-675. 19. The method of claim 14, wherein the sgRNA library comprises the nucleotide sequences listed in SEQ ID NO:1-675. 20. The method of claim 14, wherein the screening assesses T cell exhaustion. 21. The method of claim 14, wherein the analysis of the cells comprises a method selected from sequencing, PCR, MACS, and FACS. 22. The method of claim 14, wherein the sequencing reveals the target of interest. 23. The method of claim 22, wherein the drug is designed for the target of interest. 24. The method of claim 22, wherein when the drug is administered to the T cells, at least one T cell response is increased. 25. The method of claim 14, wherein 1 x ^10⁵ T cells are administered to the infected mouse. 26. The method of claim 14, wherein the method identifies novel transcription factors that regulate T _EFF and T _EX cell differentiation.