CN117589658A - Method for establishing immune thrombocytopenia bone marrow immune cell characteristic spectrum and application thereof - Google Patents

Abstract

The invention discloses a method for establishing a characteristic map of bone marrow immune cells in immune thrombocytopenia and its application. The present invention uses immune molecule markers and immunostaining methods to compare the proportion of bone marrow immune cells in immune thrombocytopenia patients and healthy control groups obtained through a mass spectrometry flow detection system and the content of co-signaling molecules in the bone marrow immune cells. The analysis included 32 immune molecular markers, identified the phenotypes of myeloid cells and T cell subsets, and focused on the expression of co-signaling molecules, such as CTLA4, to obtain different proportions and immune checkpoints of bone marrow immune cells at different stages. Immune cell profiles of immune thrombocytopenia patients with different expression patterns of molecules. It can be used to develop therapeutic targets for patients with immune thrombocytopenia and prepare related drugs or immunotherapy layered products.

Description

A method for establishing a characteristic map of bone marrow immune cells in immune thrombocytopenia and its application

Technical field

The invention belongs to the field of biomedicine, and specifically relates to a method for establishing a characteristic map of bone marrow immune cells in immune thrombocytopenia and its application.

Background technique

Immune thrombocytopenia (ITP), as an acquired autoimmune bleeding disorder, accounts for approximately 1/3 of the total number of bleeding disorders, with an annual incidence rate of 5 to 10/100,000 adults. Patients with ITP present with isolated thrombocytopenia in peripheral blood, with or without bleeding symptoms. Abnormal humoral immunity and cellular immunity jointly participate in the pathogenesis of ITP. Due to the complexity of the pathogenesis, a comprehensive and systematic analysis of immune cell characteristics will provide an important reference for fine grouping and personalized treatment of ITP patients. Mass cytometry (Cytometry of Time of Flight, CyTOF) technology is a new multi-parameter flow cytometry detection technology based on the principle of mass spectrometry, which has significantly higher resolution than traditional flow cytometry technology. CyTOF technology was used to establish an ITP bone marrow immune cell map and analyze the proportion of immune cell subpopulations and the expression of important immune checkpoint molecules on the cell surface, which will provide support for the realization of precise treatment of ITP in the future.

Co-signaling receptors are not antigen specific and are usually distributed near TCR and BCR in the form of auxiliary molecules. When lymphocytes interact with other immune cells, the auxiliary molecule gathers near the TCR or BCR to form an immune synapse and binds to the corresponding ligand to deliver activation or inhibitory signals to the immune cells. Therefore, this type of receptors is actually divided into two categories. One type initiates the transduction of activating signals, which is called co-stimulatory receptors (providing the second signal for T and B cell activation), and the other type initiates the transduction of inhibitory signals, called inhibitory receptors. sex receptors. The two antagonize each other, and the mechanism is that the intracellular segment of the receptor molecule contains an immunoreceptor tyrosine activation motif (ITAM) and an inhibitory motif (ITIM) respectively. Therefore, the ligand of the co-signaling receptor should be a cosignal molecule. Common signaling molecules include two superfamilies: TNF-TNFR superfamily and immunoglobulin superfamily.

Contents of the invention

The technical problem to be solved by the present invention is how to obtain the characteristic map of bone marrow immune cells in patients with immune thrombocytopenia and/or how to perform personalized treatment on patients with immune thrombocytopenia and/or how to develop or prepare anti-inflammatory drugs for immune thrombocytopenia. Products for stratification of immunotherapy.

In order to solve the above technical problems, the present invention first provides a method for obtaining the characteristic map of bone marrow immune cells in patients with immune thrombocytopenia, which is characterized in that: the method uses immune molecular markers and immunostaining methods to detect by mass spectrometry. Comparative analysis of the proportion of bone marrow immune cells and the content of co-signaling molecules in the bone marrow immune cells obtained from the system of immune thrombocytopenia patients and healthy control groups, to obtain the immune cell characteristic map of the immune thrombocytopenia patients step.

The above method may include the following steps:

A1) Obtain bone marrow mononuclear cells: Extract bone marrow mononuclear cells from bone marrow blood samples of patients with immune thrombocytopenia and healthy controls;

A2) Extracellular staining: The bone marrow mononuclear cells are extracellularly stained by immunostaining, so that the bone marrow immune cells in the bone marrow mononuclear cells and the co-signaling molecules in the bone marrow immune cells carry their corresponding Specific antibodies with chromogenic reagents bind to obtain immunostained bone marrow mononuclear cells;

A3) Flow cytometry mass spectrometry detection: perform flow cytometry mass spectrometry detection on the immunostained bone marrow mononuclear cells to obtain mass spectrometry flow detection data;

A4) Data analysis: Analyze the mass spectrometry flow detection data of the immune thrombocytopenia patient population and the healthy control population, and obtain the results of the immune thrombocytopenia patient population and the healthy control population. The bone marrow immune cells with different proportions and the co-signaling molecules with different expression patterns were used to obtain a characteristic map of bone marrow immune cells in patients with immune thrombocytopenia.

The above expression pattern may be expression level.

In the above method, the bone marrow immune cells may be classic type 1 dendritic cells (cDC1), classic type 2 dendritic cells (cDC2), plasmacytoid dendritic cells (pDC), or CD45RB-positive dendritic cells. (CD45RB ⁺ DC), classical mononuclear cell (classical mono), non-classical mononuclear cell (non-classical mono), intermediate mononuclear cell (intermediate mono), CD8 ⁺ T cell naive T cell (naive) subtype population, CD8 ⁺ T cell central memory T cell (CM) subset, CD8 ⁺ T cell effector memory T cell (EM) subset, CD8 ⁺ T cell effector cell (EF) subset, γδ T cell subset, CD4 ⁺ T Cell naive T cell (naive) subset, CD4 ⁺ T cell central memory T cell (CM) subset, CD4 ⁺ T cell effector memory T cell (EM) subset, CD4 ⁺ T cell effector cell (EF) subset, CD4 ⁺ T cell Tfh helper T cell subset, CD4 ⁺ T cell Th1 helper T cell subset, CD4 ⁺ T cell Th17 helper T cell subset and CD4 ⁺ T cell Treg helper T cell subset; the co-signaling molecule can For CD28, ICOS (inducible costimulatory molecule, CD278), HVEM (herpesvirus entry mediator, CD270), BTLA (B and T lymphocyte attenuation factor, CD272), CTLA4 (cytotoxic T lymphocyte-associated protein 4, CD152) , PD-1 (programmed death receptor 1, CD279), LAG3 (lymphocyte activating gene 3, CD223) and Tim-3 (T lymphocyte immunoglobulin mucin 3, CD366).

In the above method, the specific antibody carrying a chromogen described in A2) may be a specific antibody carrying a metal isotope.

In the above method, in step A4), Flowjo software can be used to analyze the mass spectrometry flow detection data.

The analysis may include a step of raw data normalization, which may be the use of calibration microspheres to correct the raw data of different batches of samples.

The patients with immune thrombocytopenia mentioned above may be Chinese people.

In order to solve the above technical problems, the present invention also provides the application of the method described above in developing or preparing drugs for the treatment, auxiliary treatment or personalized treatment of patients with immune thrombocytopenia.

In order to solve the above technical problems, the present invention also provides the application of the above-mentioned method in developing or preparing immunotherapy stratified products for patients with immune thrombocytopenia.

The application of the method described above in developing therapeutic targets for patients with immune thrombocytopenia also falls within the scope of the present invention.

In order to further analyze in detail the changes in bone marrow innate immune and adaptive immune cell subpopulations and important immune checkpoint molecules on cell surfaces in ITP patients, the present invention used mass spectrometry flow cytometry technology to draw an immune cell characteristic map of bone marrow cells in ITP patients.

The present invention describes the characteristic profile of bone marrow immune cells in ITP patients. The present invention uses mass spectrometry flow cytometry to analyze immune cells, identify myeloid cells and T cell subpopulations, and focus on the expression of important immune checkpoint molecules, such as CTLA4, ICOS, etc. Characteristic changes in the proportion of bone marrow immune cell subpopulations and expression patterns of immune checkpoint molecules in patients with active ITP provide a basis for precise treatment of ITP patients and can be used to develop or prepare related drugs for the treatment of patients with immune thrombocytopenia.

Description of drawings

Figure 1 shows the process of mass spectrometry flow cytometry data processing by Flowjo software. A is a scatter plot gated by 191Ir-labeled DNA1 and 193Ir-labeled DNA2. The abscissa is the expression level of 191Ir-labeled DNA1, and the ordinate is the expression level of 193Ir-labeled DNA2; B is a gated scatter plot based on 89Y-labeled CD45 and 194Pt-labeled cisplatin. , the abscissa is the expression level of 89Y-marked CD45, the ordinate is the expression level of 194Pt-marked cisplatin; C is a scatter plot gated by Event length and 194Pt-marked cisplatin, the abscissa is the Event length value, and the ordinate is the 194Pt-marked cisplatin Expression level; D is a scatter plot gated with 140Ce and 102Pd, the abscissa is the expression level of 140Ce, and the ordinate is the expression level of 102Pd; E is a scatter plot gated with 115In labeling CD3 and 142Nd labeling CD19/TCRgd, the abscissa is 115In marks the expression level of CD3, and the ordinate is the expression level of 142Nd marking CD19/TCRgd.

Figure 2 shows the process of visual analysis of changes in the proportion of bone marrow monocytes and dendritic cells using bioinformatics methods. A is a dot plot of dimensionality reduction data visualization obtained by T-distributed stochastic neighbor embedding (t-SNE) analysis on the surface molecule expression of bone marrow monocytes and dendritic cells; B is the identification of bone marrow monocytes and dendritic cells based on the cell surface molecule expression. Dendritic cell grouping results; C is the proportion of bone marrow monocytes and dendritic cell subpopulations between the HC group and ITP group, the ordinate is the proportion of each cell subpopulation in CD3-CD19- cells, and the horizontal axis is the proportion of each cell subpopulation in CD3-CD19- cells. The coordinates are the names of each cell subpopulation, * indicates that the p value obtained by the t test for the difference in cell proportions between the two groups is less than 0.05, and ** indicates that the p value obtained by the t test for the difference in cell proportions between the two groups is less than 0.01.

Figure 3 is the process of identifying and analyzing the proportion changes of bone marrow T cell subpopulations by flow cytometry gating method. A is the gating step of identifying bone marrow T cell subpopulations. The horizontal and vertical coordinates are the expression levels of cell surface molecules labeled with corresponding metal isotopes; B is the proportion of each bone marrow T cell subpopulation between the HC group and the ITP group. The ordinate is the CD8+ cell subpopulation in CD3+CD19-CD8+ cells, the CD4+ cell subpopulation in CD3+CD19-CD4+ cells or the γδ T cells in CD3+ The proportion of CD19- cells, the abscissa is the name of each T cell subpopulation, * indicates that the p value of the t test for the difference in cell proportion between the two groups is less than 0.05.

Figure 4 shows the expression changes of immune checkpoint molecules on the surface of bone marrow T cell subsets. ○ represents the healthy control group HC group, ● represents the ITP group, the ordinate is the average fluorescence intensity value of the indicated molecules, and the abscissa represents initial cells (naive), central memory cells (CM), effector memory cells (EM) and effector cells in order. (EF), * indicates that the p value of the t test on the difference in molecular expression on the cell surface between the two groups is less than 0.05.

Detailed ways

The present invention will be described in further detail below in conjunction with specific embodiments. The examples given are only for illustrating the present invention and are not intended to limit the scope of the present invention. The examples provided below can serve as a guide for those of ordinary skill in the art to make further improvements, and do not limit the present invention in any way.

The experimental methods in the following examples, unless otherwise specified, are all conventional methods and are carried out in accordance with the techniques or conditions described in literature in the field or in accordance with product instructions. Materials, reagents, etc. used in the following examples can all be obtained from commercial sources unless otherwise specified.

The experimental methods in the embodiments of the present invention are as follows:

Example 1. Obtaining the immune profile of ITP patients based on mass spectrometry flow detection data

1.Samples and data sources

A total of 40 patients in the ITP group were included in the mass spectrometry flow detection of the present invention, with an average age of 49 years old (range 23-71 years old, all patients were Chinese), including 19 males and 21 females, and the platelet count was (15-38)× 10 ⁹ /L, the median is 24×10 ⁹ /L. As a control, the bone marrow samples of the HC group were donated by 10 allogeneic hematopoietic stem cell transplant recipients, with an average age of 43.2 years (range 30-55 years old, all donors were Chinese), including 4 males and 6 females, and the platelet count was (121 -321)×10 ⁹ /L, the median is 227×10 ⁹ /L. This study was approved by the Ethics Committee of Peking University People's Hospital, and all subjects signed informed consent.

EDTA anticoagulated bone marrow blood samples were collected from all subjects, and bone marrow mononuclear cell extraction, cell staining, fixation, on-machine (flow mass spectrometer) detection, and mass spectrometry flow cytometry result data analysis were performed in sequence. Mass spectrometry flow cytometry result data is single-cell level proteomic data, which is used to identify the phenotypes of myeloid cells and T cell subsets in the sample, and focuses on the expression of immune checkpoint receptor molecules on the surface of T cells, such as CD28, ICOS, and HVEM. , BTLA, CTLA4, PD-1, LAG3 and Tim-3, etc.

The method for extracting bone marrow mononuclear cells is as follows:

Freshly collected EDTA anticoagulated bone marrow blood samples were centrifuged at 3000 rpm for 15 minutes at 4°C. After aspirating the upper plasma, PBS phosphate buffer (Gibco, Cat#10010023) was added to dilute the sample to 20 mL. Take a 50mL centrifuge tube, add 10mL of Ficoll-Paque PLUS separation solution (GE Healthcare, Cat#17-1440-03), absorb the diluted sample, slowly add the upper layer of Ficoll separation solution, and centrifuge at 400g for 15 minutes (the speed is increased to 1 ). After centrifugation, use a suction pump to suck away the waste liquid above the separated buffy coat layer, use a 1mL manual pipette to transfer the buffy coat layer to a new 50mL centrifuge tube, and repeat the pipetting until no obvious cells remain in the Ficoll layer. Add PBS to make up to 30mL, centrifuge at 400g for 10 minutes, aspirate and discard the supernatant, add 1mL of ACK red blood cell lysate (PLT, Cat#BS-01-05), mix by pipetting, and let stand for 1 to 2 minutes. Add PBS to the lysed cell suspension to make up to 10 mL, and centrifuge at 400g for 5 minutes. Aspirate and discard the supernatant, add 4 mL of PBS, pipet and resuspend, add 10 μL of cell suspension to trypan blue dye, dilute to an appropriate volume multiple, and count. Centrifuge and discard the supernatant to obtain mononuclear cell pellet.

The extracellular staining method is as follows:

Take the mononuclear cell pellet sample (containing 3×10 ⁶ cells) in a 1.5mL centrifuge tube, and add 100 μL of 194 Cisplatin live and dead stain (Cell-ID ^TM Cisplatin-194Pt, FLUIDIGM, Cat#201194) to each sample to a final concentration of 0.25μM, stain on ice for 5 minutes, add 1mL PBS to each sample, resuspend the cells, centrifuge at 400g for 5 minutes at 4°C, discard the supernatant. Add 50μL Block mix( Antibody Labeling Kit, FLUIDIGM, Cat#201300), resuspend the cells and block on ice for 20 minutes. According to the 32 antibody combinations in Table 1 (each antibody carries a metal isotope chromogen label and can specifically recognize 32 bone marrow cell surface protein molecules), prepare a surface antibody mixture, and directly add it to each antibody after blocking. Add 50 μL of antibody mixture to the sample, mix the cells by gentle pipetting, and stain on ice for 30 minutes. Add 1mL of PBS to each sample, resuspend the cells, centrifuge at 400g for 5 minutes at 4°C, discard the supernatant, repeat washing once, and wash with Fix andPermBuffer(/> Antibody Labeling Kit, FLUIDIGM, Cat#201300), prepare DNA staining solution (Cell-ID ^TM Intercalator-Ir, FLUIDIGM, Cat#201192B) with a final concentration of 250nM. Take 200μL of each sample to resuspend the cells and incubate at room temperature for 1 hour or Incubate overnight at 4°C to obtain immunostained bone marrow mononuclear cell pellets.

Table 1. 32 immune molecular markers and their corresponding metal isotope antibodies

Note: Among molecular markers, bone marrow immune cell grouping markers include: CD45, CD3, CD56, CD19, TCRgd, CD14, CD123, CD197, CD141, CD172, CD11c, CD25, CD1c, CD183, CD185, CD196, CD45RA, CD16, CD127 , HLA-DR, CD4, CD8, CD11b; co-signaling molecules include PD-L1, CD270, Tim3, ICOS, CTLA4, CD28, PD1, LAG3, CD272.

The method for mass spectrometry flow cytometry is as follows:

Add 1 mL of 1×Perm Buffer (ThermoFisher Scientific, Cat#00-8333-56) to each immunostained single cell pellet sample to wash the cells, centrifuge at 800 g for 5 minutes at 4°C, discard the supernatant, and repeat washing once. Add 1mL ddH ₂ O to each sample to resuspend the cells and transfer them to a 5mL flow tube with a filter using a pipette. Then add 1mL ddH ₂ O to a 1.5mL centrifuge tube to clean the tube wall and transfer all to a 5mL flow tube with a filter. style tube. Centrifuge at 800g for 5 minutes at 4°C and discard the supernatant. 20% calibration microspheres (EQ ^TM Four Element Calibration Beads, FLUIDIGM, Cat#201078) were added, cells were resuspended in 1 mL ddH ₂ O, and mass spectrometry flow cytometry data were obtained for on-machine detection using a Helios flow mass spectrometer (FLUIDIGM).

2. Analysis of mass spectrometry flow cytometry results

Mass spectrometry flow detection data were analyzed using Flowjo software (Figure 1).

The raw data off the machine are first corrected using calibration microspheres for different batches of samples, which contain 4 stable and constant concentrations of metal elements (FLUIDIGM, Cat#201078), which are spiked into each sample of different batches, based on Standardize the signals of these 4 metal elements. Then use Flowjo software (https://www.flowjo.com/) to preprocess to remove debris (191Ir ⁺ 193Ir ⁺ ) (A in Figure 1), remove dead cells (194Pt ^- ) (B in Figure 1), and remove sticky cells. Connect the cells (Eventlength <20) (C in Figure 1), remove the calibration microspheres (140Ce-) (D in Figure 1), select single, viable, and complete cells, and select lymphocytes through the CD3/CD19 circle gate. Cells and myeloid cells were initially distinguished (E in Figure 1). After obtaining the expression intensity of each molecular marker for each cell, after acrsinh data conversion (cofactor=5), t-SNE dimensionality reduction visualization was performed, and abnormal cell groups were screened after cell annotation. T cell subpopulations were identified through a flow cytometry gating strategy, and the expression intensity of CD28, BTLA, PD1, LAG3, Tim3, ICOS, and CTLA4 in each cell population was obtained for further analysis. The statistical test for comparing the differences in molecular expression between the two groups was performed using t test, and the statistical analysis was completed using R version 3.6.3.

Use Flowjo software to identify CD3 ⁺ CD19 ^- T lymphocyte population, CD3 ^- CD19 ^- myeloid cell population, CD3 ^- CD19 ⁺ B lymphocyte population and CD3 ⁺ TCRγδ ⁺ T cell population through CD3/CD19 circle gate.

An unsupervised clustering method was used to further analyze the CD3 ^- CD19 ^- myeloid cell population (A in Figure 2). After excluding the natural killer cell population, from the mononuclear cells of 50 bone marrow samples, according to CD1c, CD11c, CD14, CD16, Molecular expression patterns of CD45RB, CD141, CD123, CD272 and HLA-DR identified 7 myeloid cell subpopulations: classic type 1 dendritic cells (cDC1), classic type 2 dendritic cells (cDC2), plasmacytoid Dendritic cells (pDC), CD45RB-positive dendritic cells (CD45RB ⁺ DC), classical mononuclear cells (classical mono), non-classical mononuclear cells (non-classicalmono), intermediate mononuclear cells (intermediate mono) ) (B in Figure 2).

The CD3 ⁺ CD19 ^- T lymphocyte population was further analyzed using the flow cytometry gate method, and 13 T lymphocyte subpopulations were identified (B in Figure 3): CD8 ⁺ T cell naive T cell (naive) subpopulation, CD8 ⁺ T cell Central memory T cell (CM) subset, CD8 ⁺ T cell effector memory T cell (EM) subset, CD8 ⁺ T cell effector cell (EF) subset, γδ T cell subset, CD4 ⁺ T cell naive T cell (naive ) subset, CD4 ⁺ T cell central memory T cell (CM) subset, CD4 ⁺ T cell effector memory T cell (EM) subset, CD4 ⁺ T cell effector cell (EF) subset, CD4 ⁺ T cell Tfh helper T cell subsets, CD4 ⁺ T cell Th1 helper T cell subset, CD4 ⁺ T cell Th17 helper T cell subset, CD4 ⁺ T cell Treg helper T cell subset, and simultaneously obtain immune checkpoint molecules on the cell surface of each subpopulation. The expression level was expressed as the average fluorescence intensity value (Figure 4).

2.1 Compare the proportion of myeloid cell subpopulations in ITP group and HC group

The composition of immune cell subpopulations in the ITP group and the HC group (control group) was analyzed (Figure 2). The results showed that compared with the HC group, the proportion of plasmacytoid dendritic cells in the ITP group was significantly reduced (represented by pDC in C in Figure 2, p=0.0017), while the proportion of intermediate monocytes (represented by intermediate in C in Figure 2) There was a significant increase in the proportion (p=0.0447).

2.2 Compare the proportion of T cell subpopulations in the ITP group and the HC group

Comparative analysis of CD4 ⁺ T cells and CD8 ⁺ T cell subsets. Both CD4 ⁺ and CD8 ⁺ T cells include naive T cells (naive), central memory T cells (CM), effector memory T cells (EM) and effector cells (EF). ). In addition, CD4 ⁺ T cells also identified different helper T cell subsets, including Tfh, Th1, and Th17, as well as suppressor T cells (Treg) (Figure 3, B).

Comparing the proportion of T cell subpopulations in the ITP group and the HC group, the results show:

Compared with the HC control group, the proportion of naive T cells in the ITP group was significantly reduced (CD8 ⁺ : p = 0.0044; CD4 ⁺ : p = 0.0087). The proportions of CD8 ⁺ effector T cells (represented by CD8 ⁺ EF in B in Figure 3 ) and CD4 ⁺ effector memory T cells (represented by CD4 ⁺ EM in B in Figure 3 ) were significantly increased in ITP patients (CD8 ⁺ EF: p=0.0040 ; CD4 ⁺ EM: p=0.0038), while the proportion of Th17 cells in the helper T cell subset was significantly increased in ITP patients (p=0.0320).

2.3 Analyze the expression patterns of immune checkpoint molecules on the surface of T cells in the ITP group and HC group

Compared with the HC control group (represented by ○ in Figure 4), the expression of CD28 and ICOS in CD4 ⁺ central memory (CM) T cells increased in ITP patients (represented by ● in Figure 4) (left panel in Figure 4, CD28: p= 0.042; ICOS: p=0.012), HVEM expression was mainly increased in CD8 ⁺ central memory (CM) and effector (EF) T cells (right panel in Figure 4, CM: p=0.012; EF: p=0.045).

Among inhibitory costimulatory molecules, LAG3 expression was significantly increased in both CD4 ⁺ and CD8 ⁺ naive and effector memory (EM) T cells (Figure 4, CD4 ⁺ naive: p = 0.008; CD4 ⁺ EM: p=0.047; CD8 ⁺ naive: p=0.005; CD8 ⁺ EM: p=0.040).

Except for naive T cells, the expression of BTLA in other CD4 ⁺ and CD8 ⁺ T cell subsets was increased compared with the HC group, and the expression of CTLA4 was mainly reduced in effector memory (EM) and effector (EF) T cells.

Therefore, CTLA4 and HVEM in CD8 ⁺ effector T cells, and LAG3, BTLA, and CTLA4 in CD4 ⁺ effector memory T cells can be developed as immunotherapy targets for ITP patients.

The present invention has been described in detail above. For those skilled in the art, the present invention can be implemented in a wider range under equivalent parameters, concentrations and conditions without departing from the spirit and scope of the invention and without performing unnecessary experiments. Although specific embodiments of the present invention have been shown, it should be understood that further modifications can be made to the invention. In short, based on the principles of the present invention, this application is intended to include any changes, uses, or improvements to the present invention, including changes that depart from the scope disclosed in this application and are made using conventional techniques known in the art.

Claims (9)

1. A method for obtaining the characteristic map of bone marrow immune cells in patients with immune thrombocytopenia, characterized in that: the method uses immune molecular markers and immunostaining methods to detect immune thrombocytopenia patients obtained through a mass spectrometry flow detection system. Comparative analysis of the proportion of bone marrow immune cells and the content of co-signaling molecules in the bone marrow immune cells of the population and the healthy control population, and obtaining the immune cell characteristic map of the immune thrombocytopenia patient. 2. The method according to claim 1, characterized in that: the method includes the following steps: A1) Obtain bone marrow mononuclear cells: Extract bone marrow mononuclear cells from bone marrow blood samples of patients with immune thrombocytopenia and healthy controls; A2) Extracellular staining: The bone marrow mononuclear cells are extracellularly stained by immunostaining, so that the bone marrow immune cells in the bone marrow mononuclear cells and the co-signaling molecules in the bone marrow immune cells carry their corresponding Specific antibodies with chromogenic reagents bind to obtain immunostained bone marrow mononuclear cells; A3) Flow cytometry mass spectrometry detection: perform flow cytometry mass spectrometry detection on the immunostained bone marrow mononuclear cells to obtain mass spectrometry flow detection data; A4) Data analysis: Analyze the mass spectrometry flow detection data of the immune thrombocytopenia patient population and the healthy control population, and obtain the results of the immune thrombocytopenia patient population and the healthy control population. The bone marrow immune cells with different proportions and the co-signaling molecules with different expression patterns were used to obtain a characteristic map of bone marrow immune cells in patients with immune thrombocytopenia. 3. The method according to claim 1 or 2, characterized in that: the bone marrow immune cells are classic type 1 dendritic cells, classic type 2 dendritic cells, plasmacytoid dendritic cells, and CD45RB-positive trees. Process cells, classical monocytes, non-classical monocytes, intermediate monocytes, CD8 ⁺ T cell initial T cell subset, CD8 ⁺ T cell central memory T cell subset, CD8 ⁺ T cell effector memory T cell subsets, CD8 ⁺ T cell effector cell subsets, γδ T cell subsets, CD4 ⁺ T cell naïve T cell subsets, CD4 ⁺ T cell central memory T cell subsets, CD4 ⁺ T cell effector memory T cell subsets , CD4 ⁺ T cell effector cell subset, CD4 ⁺ T cell Tfh helper T cell subset, CD4 ⁺ T cell Th1 helper T cell subset, CD4 ⁺ T cell Th17 helper T cell subset, and CD4 ⁺ T cell Treg helper T Cell subpopulation; the co-signaling molecules are CD28, inducible co-stimulatory molecule ICOS, herpes virus entry mediator HVEM, B and T lymphocyte attenuation factor BTLA, cytotoxic T lymphocyte-associated protein 4CTLA4, programmed death receptor 1, Lymphocyte activating gene 3, CD223 and T lymphocyte immunoglobulin mucin 3. 4. The method according to any one of claims 1 to 3, characterized in that: the specific antibody carrying a chromogen described in A2) is a specific antibody carrying a metal isotope. 5. The method according to any one of claims 1-4, characterized in that: in A4), Flowjo software is used to analyze the mass spectrometry flow detection data. 6. The method according to any one of claims 1-5, characterized in that: the immune thrombocytopenia patients are Chinese people. 7. Application of the method according to any one of claims 1 to 6 in the development or preparation of drugs for the treatment, adjuvant treatment or personalized treatment of patients with immune thrombocytopenia. 8. Application of the method according to any one of claims 1 to 6 in the development or preparation of layered products for immunotherapy for patients with immune thrombocytopenia. 9. Application of the method according to any one of claims 1 to 6 in developing therapeutic targets for patients with immune thrombocytopenia.