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 immune thrombocytopenia bone marrow immune cells and application thereof. The invention uses immune molecular markers to compare and analyze the proportion of the immune cells of the immune thrombocytopenia patient population and healthy control population obtained by a mass spectrometry flow type detection system and the content of common signal molecules in the immune cells of the bone marrow, comprises 32 immune molecular markers, identifies the phenotype of myeloid cells and T cell subsets, focuses the expression of common signal molecules, such as CTLA4 and the like, and obtains the immune cell characteristic map of the immune thrombocytopenia patient comprising different proportions of the immune cells of different stages and different expression modes of immune checkpoint molecules. Can be applied to the development of therapeutic targets of patients suffering from immune thrombocytopenia and the preparation of related medicaments or immunotherapeutic layered products.

Description

Method for establishing immune thrombocytopenia bone marrow immune cell characteristic spectrum and application thereof

Technical Field

The invention belongs to the field of biological medicine, and in particular relates to a method for establishing an immune thrombocytopenia bone marrow immune cell characteristic map and application thereof.

Background

Immune thrombocytopenia (Immune thrombocytopenia, ITP) is an acquired autoimmune hemorrhagic disease, accounting for about 1/3 of the total number of hemorrhagic disease, and the annual incidence rate of adults is 5-10/100000. ITP patients manifest peripheral blood isolated thrombocytopenia with or without bleeding symptoms. Humoral immunity and cellular immune abnormalities are commonly involved in the pathogenesis of ITP. Because of the complexity of pathogenesis, a comprehensive systematic analysis of immune cell characteristics would provide an important reference for fine grouping and personalized treatment of ITP patients. The mass spectrum flow cytometry (Cytometry of Time of Flight, cyTOF) technology is a novel multiparameter flow cytometry detection technology based on the mass spectrum principle, and has high resolution capability which is remarkably higher than that of the traditional flow cytometry technology. And (3) establishing an ITP bone marrow immune cell map by using a CyTOF technology, analyzing the proportion of immune cell subsets and the expression of important immune checkpoint molecules on the cell surface, and providing support for the realization of future ITP accurate treatment.

Co-signaling receptors are not antigen specific and are typically distributed in the vicinity of TCR and BCR in the form of accessory molecules. When lymphocytes interact with other immune cells, the accessory molecules aggregate near the TCR or BCR, forming an immune synapse, and bind to the corresponding ligand, delivering an activation or inhibition signal to the immune cell. Thus, such receptors are actually classified into two classes, one that initiates transduction of activation signals, known as co-stimulatory receptors (providing a second signal for T, B cell activation), and the other that initiates transduction of inhibitory signals, inhibitory receptors. The two are opposed by the fact that the intracellular segment of the receptor molecule carries an Immunoreceptor Tyrosine Activation Motif (ITAM) and an inhibition motif (ITIM), respectively. Thus the ligand for the co-signaling receptor should be a co-signaling molecule (cosignal molecule). Co-signaling molecules include two superfamilies: TNF-TNFR superfamily and immunoglobulin superfamily.

Disclosure of Invention

The invention aims to solve the technical problems of how to obtain the bone marrow immune cell characteristic map of an immune thrombocytopenia patient and/or how to carry out personalized treatment on the immune thrombocytopenia patient and/or how to develop or prepare a product for carrying out immune treatment layering on the immune thrombocytopenia.

In order to solve the technical problems, the invention firstly provides a method for acquiring a bone marrow immune cell characteristic map of an immune thrombocytopenia patient, which is characterized in that: the method comprises the step of comparing and analyzing the ratio of the bone marrow immune cells of the patient suffering from the immune thrombocytopenia and the healthy control group obtained by a mass spectrometry flow detection system and the content of common signal molecules in the bone marrow immune cells by using an immune molecular marker and adopting an immune staining method to obtain an immune cell characteristic map of the patient suffering from the immune thrombocytopenia.

The method may comprise the steps of:

a1 Bone marrow mononuclear cell acquisition: extracting bone marrow mononuclear cells from bone marrow blood samples of patients suffering from immune thrombocytopenia and healthy control people;

a2 Extracellular staining: extracellular staining is carried out on the marrow mononuclear cells by an immunostaining method, so that marrow immune cells in the marrow mononuclear cells and co-signal molecules in the marrow immune cells are combined with corresponding specific antibodies carrying color developing agents, and the immunostained marrow mononuclear cells are obtained;

a3 Flow mass spectrometry detection: performing flow mass spectrometry detection on the immunostained bone marrow mononuclear cells to obtain mass spectrometry detection data;

a4 Data analysis: analyzing the mass spectrometry detection data of the immune thrombocytopenia patient population and the healthy control population to obtain the common signal molecules with different proportions of the bone marrow immune cells and different expression patterns in the immune thrombocytopenia patient population and the healthy control population, and obtaining the bone marrow immune cell characteristic map of the immune thrombocytopenia patient.

The expression pattern may be an expression level.

In the above method, the bone marrow immune cell may be classical type 1 dendritic cell (cDC 1), classical type 2 dendritic cell (cDC 2), plasmacytoid dendritic cell (pDC), CD45RB positive dendritic cell (CD 45 RB) ⁺ DC), classical (classical mono), non-classical (non-classical mono), intermediate (intermediate mono), CD8 ⁺ T cell naive T cell (naive) subpopulations, CD8 ⁺ T cell central memory T Cell (CM) subpopulations, CD8 ⁺ T cell effector memory T cell (EM) subpopulations, CD8 ⁺ T cell effector cell (EF) subpopulations, γδ T cell subpopulations, CD4 ⁺ T cell naive T cell (naive) subpopulations, CD4 ⁺ T cell central memory T Cell (CM) subpopulations, CD4 ⁺ T cell effector memory T cell (EM) subpopulations, CD4 ⁺ T cell effector cell (EF) subpopulations, CD4 ⁺ T cell Tfh helper T cell subpopulation, CD4 ⁺ T cell Th1 helper T cell subpopulation, CD4 ⁺ T cell Th17 helper T cell subpopulations and CD4 ⁺ T cell Treg helper T cell subpopulations; the co-signaling molecules may be CD28, ICOS (inducible co-stimulatory molecule, CD 278), HVEM (herpes virus entry mediator, CD 270), BTLA (B and T lymphocyte attenuation factor, CD 272), CTLA4 (cytotoxic T lymphocyte-associated protein 4, CD 152), PD-1 (programmed death receptor 1, CD 279), LAG3 (lymphocyte activating gene 3, CD 223) and Tim-3 (T lymphocyte immunoglobulin mucin 3, CD 366).

In the above method, the specific antibody carrying a color developing agent in A2) may be a specific antibody carrying a metal isotope.

In the above method, the mass spectrometry detection data may be analyzed in A4) using Flowjo software.

The analysis may include a step of raw data normalization, which may be the correction of raw data for different batches of samples using calibration microspheres.

The above-described patients with immune thrombocytopenia may be the chinese population.

In order to solve the technical problems, the invention also provides application of the method in developing or preparing medicines for treating, assisting in treating or individualizing patients suffering from immune thrombocytopenia.

In order to solve the technical problems, the invention also provides application of the method in development or preparation of an immune thrombocytopenia patient immunotherapy layered product.

The application of the method in developing therapeutic targets for patients with immune thrombocytopenia is also within the scope of the invention.

In order to analyze the changes of marrow innate immunity and adaptive immune cell subpopulations and cell surface important immune checkpoint molecules in ITP patients in further detail, the invention uses mass spectrometry flow technology to perform immune cell characteristic map drawing on the marrow cells of the ITP patients.

The invention describes the bone marrow immune cell characteristic map of ITP patients. The present invention uses mass spectrometry to perform immune cell analysis, identify myeloid cells and T cell subsets, and focus the expression of important immune checkpoint molecules, such as CTLA4, ICOS, etc. The characteristic changes of the bone marrow immune cell subset proportion and the immune checkpoint molecular expression pattern of the active ITP patient provide basis for the accurate treatment of the ITP patient, and can be applied to the development or preparation of related medicaments for treating the immune thrombocytopenia patient.

Drawings

Fig. 1 is a Flowjo software process mass flow data flow. A is a gate scatter diagram set by using 191Ir marked DNA1 and 193Ir marked DNA2, the abscissa is 191Ir marked DNA1 expression quantity, and the ordinate is 193Ir marked DNA2 expression quantity; b is a gate scatter diagram of cisplatin marked with 89Y marks CD45 and 194Pt, the abscissa is the expression quantity of the 89Y marks CD45, and the ordinate is the expression quantity of cisplatin marked with 194 Pt; c is a gate scatter diagram of cisplatin marked by Event length and 194Pt, the abscissa is Event length value, and the ordinate is cisplatin expression quantity marked by 194 Pt; d is a scatter diagram with 140Ce and 102Pd, the abscissa is 140Ce expression level, and the ordinate is 102Pd expression level; e is a gate scatter plot with 115In marks CD3 and 142Nd marks CD19/TCRgd, the abscissa is 115In marks CD3 expression level, and the ordinate is 142Nd marks CD19/TCRgd expression level.

FIG. 2 is a process for bioinformatics method visualization of the change in the ratio of bone marrow mononuclear cells to dendritic cells. A is a visual point diagram of dimension reduction data obtained by T distribution random neighbor embedding (T-SNE) analysis of the molecular expression quantity of the surfaces of bone marrow mononuclear cells and dendritic cells; b is the result of identifying the bone marrow mononuclear cells and dendritic cells according to the expression level of the cell surface molecules; c is the ratio of each subgroup of bone marrow mononuclear cells and dendritic cells between HC group and ITP group, the ordinate is the ratio of each subgroup of cells in CD3-CD 19-cells, the abscissa is the name of each subgroup of cells, the p value obtained by t test of cell ratio difference between two groups is less than 0.05, and the p value obtained by t test of cell ratio difference between two groups is less than 0.01.

FIG. 3 is a flow gate method for identifying and analyzing the ratio change of the bone marrow T cell subgroup, wherein A is the gate identifying step of the bone marrow T cell subgroup, and the abscissa is the cell surface molecular expression amount corresponding to the metal isotope label; b is the proportion of each subgroup of bone marrow T cells between HC group and ITP group, the ordinate is the proportion of CD8+ cell subgroup in CD3+CD19-CD8+ cells, CD4+ cell subgroup in CD3+CD19-CD4+ cells or gamma delta T cells in CD3+CD19-cells, the abscissa is the name of each T cell subgroup, and the p value obtained by T-test of cell proportion difference between the two groups is less than 0.05.

FIG. 4 shows the change in expression of a bone marrow T cell subset surface immune checkpoint molecule. The ∈ is represented by the healthy control group HC, the ∈ is represented by the ITP group, the ordinate represents the average fluorescence intensity value of the molecules shown, the abscissa represents the initial cell (naive), the central memory Cell (CM), the effector memory cell (EM) and the effector cell (EF) in order, and the p value obtained by t-test, which represents the difference in the molecular expression level of the cell surface between the two groups, is less than 0.05.

Detailed Description

The following detailed description of the invention is provided in connection with the accompanying drawings that are presented to illustrate the invention and not to limit the scope thereof. The examples provided below are intended as guidelines for further modifications by one of ordinary skill in the art and are not to be construed as limiting the invention in any way.

The experimental methods in the following examples, unless otherwise specified, are conventional methods, and are carried out according to techniques or conditions described in the literature in the field or according to the product specifications. Materials, reagents and the like used in the examples described below are commercially available unless otherwise specified.

The experimental method in the embodiment of the invention is as follows:

example 1 obtaining an immune profile of an ITP patient based on mass flow detection data

1. Sample and data sources

The mass spectrometry detection of the invention is carried out on 40 ITP patients, the average age is 49 years (the range is 23-71 years, all patients are Chinese people), wherein 19 men and 21 women have the platelet count of (15-38) x 10 ⁹ L, median 24×10 ⁹ and/L. The control HC group marrow samples were donated by transplantation of 10 allogeneic hematopoietic stem cells, with an average age of 43.2 years (ranging from 30 to 55 years, all donors being Chinese population), 4 men, 6 women, and platelet count (121-321). Times.10 ⁹ L, median 227×10 ⁹ and/L. The study was approved by the ethics committee of the civil hospital at Beijing university, and all subjects signed informed consent.

EDTA anticoagulation bone marrow blood samples of all subjects are collected, and bone marrow mononuclear cell extraction, cell staining, fixation, on-machine (flow type mass spectrometer) detection and mass spectrometry flow type result data analysis are sequentially carried out. The mass spectrometry results data are single cell level proteomic data used to identify phenotypes of sample myeloid cells and T cell subsets and focus the expression of T cell surface immune checkpoint receptor molecules such as CD28, ICOS, HVEM, BTLA, CTLA, PD-1, LAG3, tim-3, and the like.

The extraction method of the bone marrow mononuclear cells comprises the following steps:

freshly collected EDTA anticoagulated bone marrow samples were centrifuged at 3000rpm for 15 min at 4℃and after aspiration of the upper plasma, the samples were diluted to 20mL with PBS phosphate buffer (Gibco, cat # 10010023). A50 mL centrifuge tube was taken, 10mL of Ficoll-Paque PLUS separation (GE Healthcare, cat#17-1440-03) was added, the diluted sample was aspirated, the top layer of Ficoll separation was slowly added, and 400g was centrifuged for 15 minutes (1 for ramp-up and ramp-down). After centrifugation, the waste liquid above the separated white membrane layer is sucked by a suction pump, the white membrane layer is transferred to a new 50mL centrifuge tube by a 1mL manual pipette, and suction is repeated until the Ficoll layer has no obvious cell residue. Adding PBS to fill 30mL, centrifuging 400g for 10 min, removing supernatant, adding 1mL of ACK erythrocyte lysate (PLT, cat#BS-01-05), blowing, mixing, and standing for 1 to 2 min. PBS was added to the lysed cell suspension to 10mL and centrifuged at 400g for 5 min. The supernatant was aspirated, resuspended by addition of 4mL PBS and 10. Mu.L of the cell suspension was diluted to the appropriate volume by trypan blue dye and counted. Centrifuging, and discarding the supernatant to obtain mononuclear cell sediment.

The extracellular staining method is as follows:

mononuclear cell pellet samples (containing 3×10) ⁶ Cells) in a 1.5mL centrifuge tube, 100. Mu.L 194 cisplatin dead-living stain (Cell-ID) was added to each sample ^TM Cisplatin-194Pt, FLUIDIGGM, cat#20194) to a final concentration of 0.25. Mu.M, stained on ice for 5min, 1mL PBS was added to each sample, the cells were resuspended, and 400g centrifuged at 4℃for 5min, and the supernatant was discarded. 50 mu L of Block mix was added to each sampleAntibody Labeling Kit, FLUIDIGM, cat # 201300), cells were resuspended and blocked on ice for 20 min. According to the 32 antibody combinations in Table 1 (each antibody carries a metal isotope color reagent mark and can specifically recognize 32 bone marrow cell surface protein molecules), a surface antibody mixed solution is prepared, 50 mu L of the antibody mixed solution is directly added into each sample after the end of sealing, uniformly mixed cells are gently blown, and the mixture is stained on ice for 30 minutes. 1mL of PBS was added to each sample, the cells were resuspended, 400g centrifuged at 4℃for 5 minutes, the supernatant discarded, and the washing repeated 1 time with Fix and PermBuffer (>Antibody Labeling Kit DNA stain (Cell-ID) was formulated at a final concentration of 250nM in Fluidigm, cat #201300 ^TM Intercaster-Ir, FLUIDIGM, cat# 201192B) dye liquor,200. Mu.L of resuspended cells were taken for each sample, incubated at room temperature for 1 hour or at 4℃overnight to obtain immunostained bone marrow mononuclear cell pellets.

TABLE 1.32 immune molecular markers and corresponding metal isotope antibodies thereto

Note that: among the molecular markers, the 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 mass spectrometry method is as follows:

1mL of 1 XPerm Buffer (Thermo Fisher Scientific, cat # 00-8333-56) was added to each immunostained single cell pellet sample to wash the cells, and the supernatant was discarded and washing was repeated 1 time at 800g for 5 minutes at 4 ℃. 1mL ddH was added to each sample ₂ O cells were resuspended and transferred to a 5mL flow tube with filter by pipette gun and 1mL ddH was added to a 1.5mL centrifuge tube ₂ O the tube wall was cleaned and transferred in its entirety into a 5mL flow tube with screen. Centrifuging at 4deg.C for 5min at 800g, and discarding supernatant. Incorporation of 20% calibration microspheres (EQ ^TM Four Element Calibration Beads，FLUIDIGM，Cat#201078)，1mL ddH ₂ O resuspended cells, and the mass spectrometry detection data are obtained by on-machine detection by a Helios flow mass spectrometer (FLUIDIGM).

2. Mass flow type result analysis

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

The original data of the machine is first corrected for different batches of samples by using calibration microspheres, wherein 4 stable and constant concentrations are carried outMetallic elements (FLUIDIGM, cat# 201078) were incorporated into each sample of the different batches, based on normalization with these 4 metallic element signals. The fragments (191 Ir) were then removed using Flowjo software (https:// www.flowjo.com /) pre-treatment ⁺ 193Ir ⁺ ) (A in FIG. 1), removal of dead cells (194 Pt ^- ) (FIG. 1B), removal of adherent cells (Event length < 20) (FIG. 1C), removal of calibrated microspheres (140 Ce-) (FIG. 1D), round selection of single, viable, intact cells, and preliminary differentiation of lymphocytes from myeloid cells by CD3/CD19 round gate (FIG. 1E). After the expression intensity of each molecular marker of each cell is obtained, t-SNE dimension reduction visualization is carried out after acrsinh data conversion (cofactor=5), and abnormal cell populations are screened after cell annotation. The T cell subpopulations were identified by flow gate-loop strategy and the expression intensities of the individual cell populations CD28, BTLA, PD1, LAG3, tim3, ICOS and CTLA4 were obtained for further analysis. Comparison of molecular expression differences between the two groups statistical tests were performed using t-test, and statistical analysis was performed using R version 3.6.3.

Identification of CD3 through CD3/CD19 loop gate using Flowjo software ⁺ CD19 ^- T lymphocyte population, CD3 ^- CD19 ^- Myeloid cell populations, CD3 ^- CD19 ⁺ B lymphocyte population and CD3 ⁺ TCRγδ ⁺ A T cell population.

Further analysis of CD3 using unsupervised clustering ^- CD19 ^- Myeloid cell populations (a in fig. 2), after depletion of the natural killer cell population, from mononuclear cells of 50 bone marrow samples, 7 myeloid cell subsets were identified based on the molecular expression patterns of CD1c, CD11c, CD14, CD16, CD45RB, CD141, CD123, CD272 and HLA-DR: classical type 1 dendritic cells (cDC 1), classical type 2 dendritic cells (cDC 2), plasmacytoid dendritic cells (pDC), CD45RB positive dendritic cells (CD 45 RB) ⁺ DC), classical monocytes (classical monoo), non-classical monocytes (non-classical monoo), intermediate monocytes (intermediate mono) (B in fig. 2).

Further analysis of CD3 using the flow gate method ⁺ CD19 ^- T lymphocyte populations, 13T lymphocyte subpopulations were identified (B in fig. 3):CD8 ⁺ t cell naive T cell (naive) subpopulations, CD8 ⁺ T cell central memory T Cell (CM) subpopulations, CD8 ⁺ T cell effector memory T cell (EM) subpopulations, CD8 ⁺ T cell effector cell (EF) subpopulations, γδ T cell subpopulations, CD4 ⁺ T cell naive T cell (naive) subpopulations, CD4 ⁺ T cell central memory T Cell (CM) subpopulations, CD4 ⁺ T cell effector memory T cell (EM) subpopulations, CD4 ⁺ T cell effector cell (EF) subpopulations, CD4 ⁺ T cell Tfh helper T cell subpopulation, CD4 ⁺ T cell Th1 helper T cell subpopulation, CD4 ⁺ T cell Th17 helper T cell subpopulation, CD4 ⁺ T cell tregs assist in T cell subsets and simultaneously obtain the expression levels of cell surface immune checkpoint molecules for each subset, expressed as mean fluorescence intensity values (fig. 4).

2.1 comparing the proportion of myeloid cell subsets in ITP and HC groups

The immune cell subpopulations of ITP and HC groups (control group) were analyzed for composition (fig. 2). As a result, it was found that the proportion of ITP group plasmacytoid dendritic cells was significantly reduced (represented by pDC at C in fig. 2, p=0.0017), while the proportion of intermediate monocytes (represented by inter-media at C in fig. 2) was significantly increased (p= 0.0447) relative to HC group.

2.2 comparison of T cell subset ratios of ITP group and HC group

Comparative analysis of CD4 ⁺ T cells and CD8 ⁺ T cell subpopulations, 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 T helper cell subsets, including Tfh, th1 and Th17, as well as suppressor T cells (tregs) (B in fig. 3).

Comparing the T cell subset ratios of ITP and HC groups, the results showed that:

relative to the HC control group, the proportion of naive T cells in ITP group was significantly reduced (CD 8 ⁺ ：p＝0.0044；CD4 ⁺ ：p＝0.0087)。CD8 ⁺ Effector T cells (CD 8 of B in FIG. 3) ⁺ EF) and CD4 ⁺ Effector memory T cells (CD 4 of B in fig. 3 ⁺ EM representative) ratio was significant in ITP patientsIncrease (CD 8) ⁺ EF：p＝0.0040；CD4 ⁺ EM: p=0.0038), whereas the proportion of Th17 cells in the T helper cell subpopulation increases significantly in ITP patients (p=0.0320).

2.3 analysis of expression patterns of ITP group and HC group T cell surface immune checkpoint molecules

CD28 and ICOS in CD4 in ITP patients (represented by ≡in FIG. 4) relative to HC control group (represented by ≡in FIG. 4) ⁺ Increased expression in Central Memory (CM) T cells (left panel in fig. 4, CD28: p=0.042; icos: p=0.012), HVEM is predominantly at CD8 ⁺ Increased expression in Central Memory (CM) and Effector (EF) T cells (right panel in fig. 4, CM: p=0.012; EF: p=0.045).

In the inhibitory co-stimulatory molecule, LAG3 is in CD4 ⁺ And CD8 ⁺ Expression in both naive and Effector Memory (EM) T cells was significantly increased (fig. 4, cd4 ⁺ naive：p＝0.008；CD4 ⁺ EM：p＝0.047；CD8 ⁺ naive：p＝0.005；CD8 ⁺ EM：p＝0.040)。

In addition to naive T cells, BTLA is found on other CD4 ⁺ And CD8 ⁺ Expression in T cell subsets was increased over HC groups, and CTLA4 expression was reduced mainly in Effector Memory (EM) and Effector (EF) T cells.

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

The present invention is described in detail above. It will be apparent to those skilled in the art that the present invention can be practiced in a wide range of equivalent parameters, concentrations, and conditions without departing from the spirit and scope of the invention and without undue experimentation. While the invention has been described with respect to specific embodiments, it will be appreciated that the invention may be further modified. In general, this application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains.

Claims (9)

1. A method for obtaining a bone marrow immune cell profile of a patient suffering from immune thrombocytopenia, comprising the steps of: the method comprises the step of comparing and analyzing the ratio of the bone marrow immune cells of the patient suffering from the immune thrombocytopenia and the healthy control group obtained by a mass spectrometry flow detection system and the content of common signal molecules in the bone marrow immune cells by using an immune molecular marker and adopting an immune staining method to obtain an immune cell characteristic map of the patient suffering from the immune thrombocytopenia.

2. The method according to claim 1, characterized in that: the method comprises the following steps:

a1 Bone marrow mononuclear cell acquisition: extracting bone marrow mononuclear cells from bone marrow blood samples of patients suffering from immune thrombocytopenia and healthy control people;

a2 Extracellular staining: extracellular staining is carried out on the marrow mononuclear cells by an immunostaining method, so that marrow immune cells in the marrow mononuclear cells and co-signal molecules in the marrow immune cells are combined with corresponding specific antibodies carrying color developing agents, and the immunostained marrow mononuclear cells are obtained;

a3 Flow mass spectrometry detection: performing flow mass spectrometry detection on the immunostained bone marrow mononuclear cells to obtain mass spectrometry detection data;

a4 Data analysis: analyzing the mass spectrometry detection data of the immune thrombocytopenia patient population and the healthy control population to obtain the common signal molecules with different proportions of the bone marrow immune cells and different expression patterns in the immune thrombocytopenia patient population and the healthy control population, and obtaining the bone marrow immune cell characteristic map of the immune thrombocytopenia patient.

3. The method according to claim 1 or 2, characterized in that: the bone marrow immune cells are classical type 1 dendritic cells, classical type 2 dendritic cells, plasmacytoid dendritic cells, CD45RB positive dendritic cells, and classical single dendritic cellsNuclear cells, non-classical monocytes, intermediate monocytes, CD8 ⁺ T cell primary T cell subpopulations, CD8 ⁺ T cell central memory T cell subpopulations, CD8 ⁺ T cell effector memory T cell subpopulations, CD8 ⁺ T cell effector cell subpopulation, γδ T cell subpopulation, CD4 ⁺ T cell primary T cell subpopulations, CD4 ⁺ T cell central memory T cell subpopulations, CD4 ⁺ T cell effector memory T cell subpopulations, CD4 ⁺ T cell effector cell subpopulations, CD4 ⁺ T cell Tfh helper T cell subpopulation, CD4 ⁺ T cell Th1 helper T cell subpopulation, CD4 ⁺ T cell Th17 helper T cell subpopulations and CD4 ⁺ T cell Treg helper T cell subpopulations; the co-signal 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. A method according to any one of claims 1-3, characterized in that: a2 The specific antibody carrying the color developing agent is a specific antibody carrying a metal isotope.

5. The method according to any one of claims 1-4, wherein: a4 Flowjo software is used to analyze the mass flow detection data.

6. The method according to any one of claims 1-5, wherein: the patients with the immune thrombocytopenia are Chinese people.

7. Use of the method of any one of claims 1-6 for developing or preparing a medicament for the treatment, co-treatment or personalized treatment of an immunocytopenic patient.

8. Use of the method of any one of claims 1-6 for developing or preparing an immunotherapeutic layered product for an immunocompromised patient.

9. Use of the method of any one of claims 1-6 for developing a therapeutic target for an immune thrombocytopenia patient.