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Advances in Immunotherapy for Cancer: From Molecular Basis to Novel Biomarkers and Therapeutic Targets

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Oncology".

Deadline for manuscript submissions: 20 October 2024 | Viewed by 10212

Special Issue Editors


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Guest Editor
Department of Science and Technological Innovation DISIT, University of Eastern Piedmont, 15121 Alessandria, Italy
Interests: malignant melanoma; metabolic reprogramming; tumor microenvironment; metabolic cross-talk; NAD; NAMPT; immunotherapy; biomarker; therapy resistance
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Molecular Biotechnology Center "Guido Tarone", Department of Molecular Biotechnology and Health Sciences, University of Torino, 10126 Torino, Italy
Interests: breast cancer; cancer vaccines; cancer immunotherapy; tumor microenvironment; microbiota; cancer stem cells; tumor antigens

Special Issue Information

Dear Colleagues,

We are delighted to announce that the Special Issue entitled “Advances in Immunotherapy for Cancer: From Molecular Basis to Novel Biomarkers and Therapeutic Targets” is now open to receiving proposals.

Despite remarkable advances in the field of immunotherapy have improved patient survival, cancer mortality due to therapy resistance and metastatic spread still represents an unsolved problem. Current studies demonstrate that a deeper understanding of molecular, metabolic, functional cross-talk between cancer and immune cells within the tumor microenvironment would be central to ameliorating patients’ outcomes.

To this aim, in this Special Issue for IJMS, we will focus on the most recent advances in the field of cancer immunotherapy, with a focus on the discovery of new targets and biomarkers and on tumor microenvironment, addressing how alterations to its molecular and metabolic features impact the response to immunotherapy. Such knowledge could represent the basis for the rational design of new immunotherapeutic and combined strategies for cancer patients’ treatment and for the identification of novel predictive biomarkers to monitor patients’ immune responses.

For IJMS's paper, nontargeted syntheses and studies with no molecular aspects are out of the scope. Clinical trials and animal and cell testings are eligible only if they are strongly needed to support hypotheses or theories concerning structure–function correlations and are not suitable if no molecular aspects are considered.

We invite basic and clinical investigators to present their valuable work either as original articles or reviews to this Special Issue. We would be very grateful for your contributions and consider it a pleasure to receive your manuscripts.

Potential topics include, but are not limited to:

  • Mechanisms of immunesuppression and immune escape;
  • Fuctional cross-talk between tumor and immune cells within tumor microenvironment: metabolic signals, soluble molecules;
  • Novel agents that regulate immune response;
  • Immunotherapy: clinical and biological effects and limits;
  • Metabolic and molecular mechanisms of resistance to immunotherapy;
  • Future perspective for immune checkpoint inhibitors;
  • Novel predictive biomarkers of therapy response;
  • Novel targets to be used in combination with immunotherapy;
  • Cancer vaccination;
  • Tumor antigens.

Dr. Valentina Audrito
Dr. Laura Conti
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • tumor microenvironment
  • immune suppression
  • metabolic and molecular mechanisms of resistance to therapy
  • tumor immune escape
  • immunotherapy
  • immune checkpoint inhibitors
  • cancer vaccination
  • tumor-infiltrating cells
  • biomarkers
  • tumor antigens
  • cancer metabolism

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Published Papers (5 papers)

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Research

Jump to: Review

22 pages, 4953 KiB  
Article
Macrophage Profiling in Head and Neck Cancer to Improve Patient Prognosis and Assessment of Cancer Cell–Macrophage Interactions Using Three-Dimensional Coculture Models
by Nour Mhaidly, Fabrice Journe, Ahmad Najem, Louis Stock, Anne Trelcat, Didier Dequanter, Sven Saussez and Géraldine Descamps
Int. J. Mol. Sci. 2023, 24(16), 12813; https://doi.org/10.3390/ijms241612813 - 15 Aug 2023
Cited by 2 | Viewed by 1660
Abstract
Tumor-associated macrophages are key components of the tumor microenvironment and play important roles in the progression of head and neck cancer, leading to the development of effective strategies targeting immune cells in tumors. Our study demonstrated the prognostic potential of a new scoring [...] Read more.
Tumor-associated macrophages are key components of the tumor microenvironment and play important roles in the progression of head and neck cancer, leading to the development of effective strategies targeting immune cells in tumors. Our study demonstrated the prognostic potential of a new scoring system (Macroscore) based on the combination of the ratio and the sum of the high and low densities of M1 (CD80+) and M2 (CD163+) macrophages in a series of head and neck cancer patients, including a training population (n = 54) and a validation population (n = 19). Interestingly, the Macroscore outperformed TNM criteria and p16 status, showing a significant association with poor patient prognosis, and demonstrated significant predictive value for overall survival. Additionally, 3D coculture spheroids were established to analyze the crosstalk between cancer cells and monocytes/macrophages. Our data revealed that cancer cells can induce monocyte differentiation into protumoral M2 macrophages, creating an immunosuppressive microenvironment. This coculture also induced the production of immunosuppressive cytokines, such as IL10 and IL8, known to promote M2 polarization. Finally, we validated the ability of the macrophage subpopulations to induce apoptosis (M1) or support proliferation (M2) of cancer cells. Overall, our research highlights the potential of the Macroscore as a valuable prognostic biomarker to enhance the clinical management of patients and underscores the relevance of a spheroid model in gaining a better understanding of the mechanisms underlying cancer cell–macrophage interactions. Full article
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<p>Immunohistochemical representation of CD163 expression with a high (<b>A</b>) and low (<b>B</b>) density as well as CD80 high (<b>C</b>) and low (<b>D</b>) expression in head and neck carcinomas (scales = 250 µm).</p>
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<p>Kaplan–Meier curves of the OS of HNC patients according to the macrophages ratio score (<b>A</b>), the total amount of macrophages M1 and M2 infiltrating the tumor and stroma (<b>B</b>), and the Macroscore combining the ratio and quantity of macrophages (<b>C</b>). X axes are time in months.</p>
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<p>Kaplan–Meier curves of the OS of HNC patients (validation cohort, <span class="html-italic">n</span> = 19) according to the Macroscore defined using the training population. X axis is time in months.</p>
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<p>Coculture of FaDu cells and macrophages in spheroids. (<b>A</b>) Photographs of spheroids containing cancer cells with or without macrophages. (<b>B</b>) Quantification of spheroid volumes for the different coculture conditions (scale = 250 μm). (<b>C</b>) Comparison of Ki-67 proliferation marker expression by immunofluorescence in the different coculture conditions on day 7. (<b>D</b>) Quantitative data of Ki-67 expression performed with QuPath. Mean + SD, ANOVA one-way, and Tukey’s post hoc test (* <span class="html-italic">p</span> ≤ 0.05; ** <span class="html-italic">p</span> ≤ 0.01; *** <span class="html-italic">p</span> ≤ 0.001), <span class="html-italic">n</span> = 8.</p>
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<p>Evaluation of apoptosis in coculture spheroids. (<b>A</b>) Graphs showing raw data from flow cytometer assessing annexin V staining vs. cell viability. (<b>B</b>) Quantification of the number of apoptotic cells within spheroids of the different coculture conditions using the annexin V/dead cell marker assay. Mean ± SD, ANOVA one-way and Tukey’s post hoc test (* <span class="html-italic">p</span> ≤ 0.05), <span class="html-italic">n</span> = 3.</p>
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<p>Effect of cancer cells on monocyte polarization. (<b>A</b>) Evaluation of the expression of macrophage phenotypic markers: CD68, CD86, and CD206 on day 7 in the different coculture conditions (scale = 50 μm); M1–FaDu and M2–FaDu were used as positive control. (<b>B</b>,<b>C</b>) FACS analyses to quantify the percentage of M1 and M2 markers in FaDu–monocyte dissociated spheroids. Dot plots of CD206 expressed on FaDu spheroids, used as a negative control (no macrophage), and in monocytes–FaDu spheroids.</p>
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<p>mRNA relative expression (2<sup>−ΔCt</sup>) to characterize macrophage phenotype using (<b>A</b>) M1 markers (CD80, CD86) and (<b>B</b>) M2 markers (IL10, CD206). The analyses by RT-qPCR and the normalization with 18S expression were conducted on dissociated FaDu and monocytes–FaDu, M1–FaDu, and M2–FaDu spheroids. Mean + SD, <span class="html-italic">t</span>-test, * = <span class="html-italic">p</span> ≤ 0.05, *** <span class="html-italic">p</span> ≤ 0.001.</p>
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<p>mRNA relative expression (2<sup>−ΔCt</sup>) to characterize EMT markers (E-cadherin and Vimentin). The analyses by RT-qPCR and the normalization with 18S expression were performed on dissociated FaDu and monocytes–FaDu spheroids. Mean + SD, <span class="html-italic">t</span>-test, * = <span class="html-italic">p</span> ≤ 0.05.</p>
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<p>Human Cytokine Array Membrane (<b>A</b>,<b>B</b>) of supernatant of FaDu cancer cell spheroids and monocytes–FaDu spheroids on day 7. (<b>A</b>) Membranes. (<b>B</b>) Quantification showing the mean signal intensity (<span class="html-italic">n</span> = 3) normalized to positive control (Ctrl+). mRNA relative expression (2<sup>−ΔCt</sup>) of CCL2 and IL8 cytokines (<b>C</b>,<b>D</b>). Analyses by RT-qPCR and normalization with 18S expression on dissociated FaDu and monocytes–FaDu spheroids. Mean + SD, <span class="html-italic">t</span>-test, * = <span class="html-italic">p</span> ≤ 0.05, *** <span class="html-italic">p</span> ≤ 0.001.</p>
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17 pages, 1372 KiB  
Article
Exome-Based Genomic Markers Could Improve Prediction of Checkpoint Inhibitor Efficacy Independently of Tumor Type
by Lorraine Dalens, Julie Lecuelle, Laure Favier, Cléa Fraisse, Aurélie Lagrange, Courèche Kaderbhai, Romain Boidot, Sandy Chevrier, Hugo Mananet, Valentin Derangère, Caroline Truntzer and François Ghiringhelli
Int. J. Mol. Sci. 2023, 24(8), 7592; https://doi.org/10.3390/ijms24087592 - 20 Apr 2023
Cited by 2 | Viewed by 1741
Abstract
Immune checkpoint inhibitors (ICIs) have improved the care of patients in multiple cancer types. However, PD-L1 status, high Tumor Mutational Burden (TMB), and mismatch repair deficiency are the only validated biomarkers of efficacy for ICIs. These markers remain imperfect, and new predictive markers [...] Read more.
Immune checkpoint inhibitors (ICIs) have improved the care of patients in multiple cancer types. However, PD-L1 status, high Tumor Mutational Burden (TMB), and mismatch repair deficiency are the only validated biomarkers of efficacy for ICIs. These markers remain imperfect, and new predictive markers represent an unmet medical need. Whole-exome sequencing was carried out on 154 metastatic or locally advanced cancers from different tumor types treated by immunotherapy. Clinical and genomic features were investigated using Cox regression models to explore their capacity to predict progression-free survival (PFS). The cohort was split into training and validation sets to assess validity of observations. Two predictive models were estimated using clinical and exome-derived variables, respectively. Stage at diagnosis, surgery before immunotherapy, number of lines before immunotherapy, pleuroperitoneal, bone or lung metastasis, and immune-related toxicity were selected to generate a clinical score. KRAS mutations, TMB, TCR clonality, and Shannon entropy were retained to generate an exome-derived score. The addition of the exome-derived score improved the prediction of prognosis compared with the clinical score alone. Exome-derived variables could be used to predict responses to ICI independently of tumor type and might be of value in improving patient selection for ICI therapy. Full article
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<p>Genomic landscape of genes associated with response to immune checkpoint inhibitors. Tumor samples are sorted by cancer type and ascending order for TMB score. TMB: Tumor Mutational Burden, TCR: T-Cell Receptor.</p>
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<p>TMB score and outcome: (<b>A</b>) Boxplots showing TMB score according to RECIST criteria for each cancer. (<b>B</b>) Barplots representing frequency of TMB<sup>High</sup> and TMB<sup>Low</sup> patients dichotomized according to the standard cut-off and optimal cut-off for each cancer (cut-off in brackets). (<b>C</b>–<b>F</b>) Kaplan–Meier curves with patients stratified according to TMB status (optimal cut-off) for progression-free survival for (<b>C</b>) non-small-cell lung cancer, (<b>D</b>) colorectal cancer, (<b>E</b>) breast cancer, and (<b>F</b>) other cancers. ns: not significant.</p>
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<p>Association between progression-free survival and clinical variables: (<b>A</b>) Forest plots representing hazard ratios and confidence intervals for univariate (gray) and multivariate (purple) Cox models for progression-free survival estimated using clinical variables in the training cohort. *: Log-rank test <span class="html-italic">p</span>-value ≤ 0.1. (<b>B</b>,<b>C</b>) Kaplan–Meier curves with patients stratified according to the clinical model dichotomized by training median (High vs. Low) for progression-free survival for training cohort (<b>B</b>) and validation cohort (<b>C</b>). ICI: Immune Checkpoint Inhibitor; PD-L1: Programmed Death-Ligand 1; PD-1; Programmed cell Death protein-1; CTLA-4: Cytotoxic T Lymphocyte-Associated protein 4; WHO: World Health Organization.</p>
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<p>Association between progression-free survival and exome-derived variables: (<b>A</b>) Forest plots representing hazard ratios and confidence intervals for univariate (gray) and multivariate (purple) Cox models for progression-free survival estimated using exome-derived variables in the training cohort. *: Log-rank test <span class="html-italic">p</span>-value ≤ 0.1. (<b>B</b>,<b>C</b>) Kaplan–Meier curves with patients stratified according to the exome model dichotomized by optimal cut-off (High vs. Low) for progression-free survival for the training cohort (<b>B</b>) and validation cohort (<b>C</b>). TMB: Tumor Mutational Burden; MSI: Microsatellite Instability; MSS: Microsatellite Stable; CNV: Copy Number Variant; TCR: T-Cell Receptor; BCR: B-cell Receptor; WT: Wild-Type.</p>
Full article ">Figure 5
<p>Association between progression-free survival and clinical and exome-derived variables. Kaplan–Meier curves with patients stratified according to dichotomized linear predictors obtained from the combined model for progression-free survival in (<b>A</b>) training cohort and (<b>B</b>) validation cohort. (<b>C</b>) Barplots of time-dependent AUC (Area Under the Curve) for clinical, exome, and combined (clinical and exome) models for progression-free survival. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001. Kaplan–Meier curves with patients stratified according to clinical and exome models for progression-free survival for the (<b>D</b>) training cohort and (<b>E</b>) validation cohort.</p>
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Review

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23 pages, 5564 KiB  
Review
Innate Immune Cells in Melanoma: Implications for Immunotherapy
by Marialuisa Trocchia, Annagioia Ventrici, Luca Modestino, Leonardo Cristinziano, Anne Lise Ferrara, Francesco Palestra, Stefania Loffredo, Mariaelena Capone, Gabriele Madonna, Marilena Romanelli, Paolo Antonio Ascierto and Maria Rosaria Galdiero
Int. J. Mol. Sci. 2024, 25(15), 8523; https://doi.org/10.3390/ijms25158523 - 5 Aug 2024
Cited by 1 | Viewed by 783
Abstract
The innate immune system, composed of neutrophils, basophils, eosinophils, myeloid-derived suppressor cells (MDSCs), macrophages, dendritic cells (DCs), mast cells (MCs), and innate lymphoid cells (ILCs), is the first line of defense. Growing evidence demonstrates the crucial role of innate immunity in tumor initiation [...] Read more.
The innate immune system, composed of neutrophils, basophils, eosinophils, myeloid-derived suppressor cells (MDSCs), macrophages, dendritic cells (DCs), mast cells (MCs), and innate lymphoid cells (ILCs), is the first line of defense. Growing evidence demonstrates the crucial role of innate immunity in tumor initiation and progression. Several studies support the idea that innate immunity, through the release of pro- and/or anti-inflammatory cytokines and tumor growth factors, plays a significant role in the pathogenesis, progression, and prognosis of cutaneous malignant melanoma (MM). Cutaneous melanoma is the most common skin cancer, with an incidence that rapidly increased in recent decades. Melanoma is a highly immunogenic tumor, due to its high mutational burden. The metastatic form retains a high mortality. The advent of immunotherapy revolutionized the therapeutic approach to this tumor and significantly ameliorated the patients’ clinical outcome. In this review, we will recapitulate the multiple roles of innate immune cells in melanoma and the related implications for immunotherapy. Full article
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<p>Melanoma is a malignant tumor, which develops from an alteration in epidermal melanocytes. One of the main risk factors is overall lifetime exposure to solar light and sunburn frequency. Unprotected exposure to UVA and UVB rays damages the DNA of skin cells, causing genetic defects or mutations that can lead to skin cancer and premature aging (<b>a</b>). Increasing data suggest that innate immunity has a role in affecting the tumor microenvironment (TME) and cancer patients’ clinical outcomes. Innate immune cells exhibit amazing adaptability, acquiring both pro- and anti-tumorigenic roles depending on different factors present in the TME (<b>b</b>). The primary treatment option for cutaneous melanoma is surgery. Among the treatments used against melanoma, it is also possible to find chemotherapy and radiotherapy. Melanoma cells are particularly sensitive to radiation. Until a few years ago, chemotherapy was the only weapon available in advanced disease but, today, it plays a minor role. In recent years, targeted and immunotherapies have shown promise in treating advanced melanomas. Despite these considerable gains, most people become resistant. Understanding the methods by which melanomas gain resistance is critical for developing customized medicines that take into account each patient’s unique genetic and immunological features (<b>c</b>).</p>
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<p>The innate immune system, composed of MDSCs, macrophages, neutrophils, DCs, MCs, basophils, eosinophils, and ILCs, is the first line of defense. Innate immune cells are characterized by a surprising plasticity and can release both pro- and antitumorigenic molecules depending on factors present in the TME. Arrows indicate protumorigenic (red ones) or antitumorigenic (green ones) effects and molecules produced by melanoma or innate immune cells within the TME.</p>
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<p>Immune cells respond to different immunogens in a dynamic and specialized manner because of their developmental diversity and phenotypic flexibility. Patrolling monocytes increase NK cell resistance to metastasis by releasing IL-15, which induces IFN-γ production. They also maintain NK cell activation by maintaining high levels of NK-cell-activating receptors and low levels of NK cell inhibitory receptors. Macrophages can activate and recruit NK cells, thus increasing their resistance to metastases. Neutrophils release neutrophils extracellular traps (NETs), which prevents the migration of tumor cells and promotes cytotoxicity towards neoplastic cells. Additionally, neutrophils promote metastasis by preventing NK cell activation basophils and eosinophils can produce various protumor signals through the release of angiogenic molecules such as vascular endothelial growth factor (VEGF) A and B. Eosinophils also display antitumorigenic activity. MDSCs are essential for the development of tumors. The interaction of CCL5 with CCR5 stimulates the growth, invasion, angiogenesis, and recruitment of immune cells into the TME. The known mediators of the immunosuppressive actions of MDSC are ARG-1, ROS, PD-L1, and NO. MCs can also produce a range of cytokines, such as TNF-α, IL-1, IL-4, IL-8, IL-6, MCP-3, and MCP-4, which can help suppress the growth of tumors by triggering apoptosis. Tumor vascularization can be promoted by MCs by the secretion of angiogenic molecules such as VEGF-A, IL-8, FGF-2, VEGF-C, MMP-2, and MMP-9.</p>
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<p>ILC and DCs cross-talk in melanoma microenvironment. Proinflammatory cytokines expressed by DCs trigger the production of PDGF and GM-CSF by ILC1 cells, which, in turn, promotes tumor angiogenesis. ILC2 induces the recruitment of eosinophils to the lung metastatic niche, through the production of IL-5. Melanoma secretes IL-12, which causes endothelial cells to upregulate ICAM and VCAM, thus attracting NKp46+ ILC3 to the tumor bed and activating the vasculature. By promoting leukocyte infiltration through endothelial activation, NKp46+ ILC3 act against melanoma. Melanoma secreting CCL21 attracts CCR6<sup>+</sup> (CD4<sup>+</sup>) ILC3, which interact with fibroblastic reticular cells (FRC) to produce lymphoid-like stroma, generating a tolerogenic tumor environment. ILC3 are activated by DC-derived IL-23, through the expression of RORγt. Thus, when DC-derived IL-23 is produced in the melanoma microenvironment, ILC3s are activated and contribute to the protection against melanoma.</p>
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17 pages, 1633 KiB  
Review
The Role of the Toll-like Receptor 2 and the cGAS-STING Pathways in Breast Cancer: Friends or Foes?
by Chiara Cossu, Antonino Di Lorenzo, Irene Fiorilla, Alberto Maria Todesco, Valentina Audrito and Laura Conti
Int. J. Mol. Sci. 2024, 25(1), 456; https://doi.org/10.3390/ijms25010456 - 29 Dec 2023
Cited by 1 | Viewed by 1779
Abstract
Breast cancer stands as a primary malignancy among women, ranking second in global cancer-related deaths. Despite treatment advancements, many patients progress to metastatic stages, posing a significant therapeutic challenge. Current therapies primarily target cancer cells, overlooking their intricate interactions with the tumor microenvironment [...] Read more.
Breast cancer stands as a primary malignancy among women, ranking second in global cancer-related deaths. Despite treatment advancements, many patients progress to metastatic stages, posing a significant therapeutic challenge. Current therapies primarily target cancer cells, overlooking their intricate interactions with the tumor microenvironment (TME) that fuel progression and treatment resistance. Dysregulated innate immunity in breast cancer triggers chronic inflammation, fostering cancer development and therapy resistance. Innate immune pattern recognition receptors (PRRs) have emerged as crucial regulators of the immune response as well as of several immune-mediated or cancer cell-intrinsic mechanisms that either inhibit or promote tumor progression. In particular, several studies showed that the Toll-like receptor 2 (TLR2) and the cyclic GMP–AMP synthase (cGAS)–stimulator of interferon genes (STING) pathways play a central role in breast cancer progression. In this review, we present a comprehensive overview of the role of TLR2 and STING in breast cancer, and we explore the potential to target these PRRs for drug development. This information will significantly impact the scientific discussion on the use of PRR agonists or inhibitors in cancer therapy, opening up new and promising avenues for breast cancer treatment. Full article
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Figure 1
<p>Schematic representation of TLR2 dimers and their signaling pathway. Like other TLRs, TLR2 forms homo- or heterodimers that allow for activation and signaling upon ligand binding. TLR2 islocalized in the outer cell membrane, and mainly dimerizes with TLR1 and TLR6. TLR2 uses the canonical MyD88 pathway to transduce a signal that, through the IRAK–TRAF6 complex, induces the activation of NF-κB and MAPK. NF-κB is responsible for the transcription of several pro-inflammatory cytokines. The MAPK pathway induces the epithelial to mesenchymal transition, promoting cancer cell invasion and metastasis. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 22 December 2023).</p>
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<p>TLR2-mediated protumoral mechanisms. Cancer cells actively or passively release DAMPs, especially following cell death induced by chemo- or radiotherapy. In addition, alterations in the microbiota due to antibiotic therapies, chemotherapies, or other factors can foster the proliferation of bacterial species that exert protumoral activity, releasing PAMPs in the TME. These endogenous and exogenous TLR2 ligands activate its signaling, promoting tumor progression in a cancer cell-intrinsic manner (on the left). TLR2 signaling activates NF-κB, which subsequently transcribes protumoral cytokines such as IL-6, TGF-β and VEGF. This stimulates cancer cell survival, angiogenesis and resistance to therapies. Additionally, TLR2 triggers the MAPK pathway, inducing EMT and promoting metastasis. Moreover, TLR2 is expressed by immune cells, where it exerts immunosuppressive effects favoring tumor progression in a cancer cell-extrinsic manner (on the right). TLR2 induces the differentiation of T and B regulatory cells, as well as of MDSCs from bone marrow precursors. MDSCs contribute to immunosuppression through several mechanisms, including the reprogramming of macrophages into the M2 phenotype. These processes collectively result in the production of cytokines that inhibit CD8<sup>+</sup> T cells and their activity, promoting tumor immune evasion. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 10 November 2023).</p>
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<p>cGAS-STING antitumoral and protumoral mechanisms. This graphical representation illustrates the antitumoral and protumoral roles played by the cGAS-STING signaling pathway. In tumor cells, the activation of the cGAS-STING pathway is predominantly triggered by CIN or DNA damage induced by chemo- and radiotherapy. Upon activation, double-stranded DNA fragments bind to cGAS, leading to the synthesis of cGAMP. Subsequently, cGAMP binds to STING dimers in the endoplasmic reticulum (ER) membrane, activating STING and causing its trafficking to an ER-Golgi intermediate compartment. In this compartment, TBK1 is recruited to phosphorylate STING, and this phosphorylation, in turn, recruits IRF3. Phosphorylated IRF3 can form dimers, translocate to the nucleus, and activate the transcription of target genes, including type I IFNs, that are released by tumor cells, recruiting antitumor immune cell populations. Conversely, a chronically low production of type I IFNs activates PARP12, whose overexpression is associated with poor prognosis in breast cancer patients. Furthermore, dysregulated cGAS-STING signaling can activate the transcription factor NF-κB, leading to chronic inflammation and tumor-promoting effects. This includes the activation of the IL-6-STAT3 axis, promoting pro-survival effects, tumor cell proliferation, and PD-L1 expression, resulting in immune escape. Mutated forms of p53 play a role in the transition from the canonical cGAS-STING-TBK1-IRF3 signaling to the cGAS-STING-NF-κB signaling, contributing to the tumor-promoting effects of the cGAS-STING pathway. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 14 November 2023).</p>
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<p>Approaches to PRR-targeted therapies for breast cancer. Schematic representation of the therapeutic approaches proposed in this review. Left panel: The cGAS-STING pathway exhibits alterations in various tumors, including breast cancer. The pathological shift of this signaling, from an immunostimulatory state to a protumoral one, can be reversed by utilizing STING agonists combined with agents that restore canonical NF-κB and IRF3 pathways, hindering cancer progression (left circle). The proposed combination of STING agonists with the drug APR-246, known for reactivating the tumor suppressor P53 in P53-mutated tumors, is suggested here. The efficacy of these therapies could potentially be enhanced through combination with ICB immunotherapies, such as anti-PD-L1 antibodies. Right panel: Conflicting data exist in the current literature concerning the role of TLR2 in cancer. Consequently, the use of agonists or inhibitors must be carefully evaluated based on the specific context. TLR2 agonists appear promising in enhancing antigen presentation when coupled with anticancer vaccines (right upper circle). However, considering the protumoral roles of TLR2 as described in this review, TLR2 inhibition might serve as an alternative strategy, particularly in tumor subtypes where TLR2 correlates with poor prognosis. Furthermore, TLR2 inhibition has shown promising outcomes when combined with chemotherapies inducing immunogenic cell death, thereby releasing DAMPs capable of activating TLR2 signaling and its described protumoral effects. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 14 November 2023).</p>
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21 pages, 409 KiB  
Review
Virus-like Particle (VLP) Vaccines for Cancer Immunotherapy
by Francesca Ruzzi, Maria Sofia Semprini, Laura Scalambra, Arianna Palladini, Stefania Angelicola, Chiara Cappello, Olga Maria Pittino, Patrizia Nanni and Pier-Luigi Lollini
Int. J. Mol. Sci. 2023, 24(16), 12963; https://doi.org/10.3390/ijms241612963 - 19 Aug 2023
Cited by 7 | Viewed by 3521
Abstract
Cancer vaccines are increasingly being studied as a possible strategy to prevent and treat cancers. While several prophylactic vaccines for virus-caused cancers are approved and efficiently used worldwide, the development of therapeutic cancer vaccines needs to be further implemented. Virus-like particles (VLPs) are [...] Read more.
Cancer vaccines are increasingly being studied as a possible strategy to prevent and treat cancers. While several prophylactic vaccines for virus-caused cancers are approved and efficiently used worldwide, the development of therapeutic cancer vaccines needs to be further implemented. Virus-like particles (VLPs) are self-assembled protein structures that mimic native viruses or bacteriophages but lack the replicative material. VLP platforms are designed to display single or multiple antigens with a high-density pattern, which can trigger both cellular and humoral responses. The aim of this review is to provide a comprehensive overview of preventive VLP-based vaccines currently approved worldwide against HBV and HPV infections or under evaluation to prevent virus-caused cancers. Furthermore, preclinical and early clinical data on prophylactic and therapeutic VLP-based cancer vaccines were summarized with a focus on HER-2-positive breast cancer. Full article
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