Biomarkers for diagnosing gvhd and uses thereof

Abstract

The application provides a biomarker for diagnosing GVHD and application thereof. The application proves by experiments that the Ki67 positive proportion, Granzyme B positive proportion and TEM cell proportion in donor-derived T cells can be used as biomarkers for distinguishing GVHD patients from non-GVHD patients, and when the T cells cannot be distinguished from the donor and the recipient, the Ki67 positive proportion, Granzyme B positive proportion and TEM cell proportion in the T cells can still be used as biomarkers for distinguishing GVHD patients from non-GVHD patients. The method for diagnosing GVHD by using the biomarker provided by the application has the advantages of immune subpopulation specific quantification, low cell amount adaptability, short time efficiency, low cost and the like.

Description

Technical Field

[0001] This invention belongs to the field of biomedicine, specifically relating to biomarkers for diagnosing GVHD and their applications. Background Technology

[0002] Graft-versus-host disease (GVHD) is a serious immune complication that threatens the survival of transplant recipients, typically occurring after hematopoietic stem cell transplantation. In liver transplantation, although the incidence of GVHD is only 0.5-2%, its pathological progression exhibits significant unique characteristics: insidious onset and rapid progression. By the time patients develop typical clinical symptoms, including skin rashes, fever, and pancytopenia, the disease has often progressed to the terminal stage, resulting in a mortality rate as high as 85-90%.

[0003] Donor immune cell chimerism is a core diagnostic marker for GVHD, and its quantitative results are crucial for early intervention. Currently, the short tandem repeat (STR)-PCR technology, which is widely used in clinical practice, amplifies donor-recipient specific STRs and calculates the chimerism rate in postoperative biological samples based on DNA length polymorphism, making it the mainstream method for clinical chimerism quantification. However, STR-PCR technology has many defects and shortcomings: 1) Limitations in quantifying the chimeric proportion of immune cell subsets: After liver transplantation, the peripheral blood immune cell subset ratio of GVHD patients is significantly imbalanced, usually dominated by recipient-derived granulocytes, while the number of pathogenic lymphocytes (especially donor-derived T cells) is drastically reduced. Conventional STR technology extracts DNA from all cells in the sample for STR polymorphism analysis. Under the pathological state of extremely low lymphocyte proportion, the detection signal is easily diluted by the DNA of other immune cells (such as granulocytes), leading to an underestimation of the T cell donor chimeric proportion, resulting in false negative diagnostic results and seriously affecting the accuracy of clinical decision-making; 2) The contradiction between the required cell quantity for quantification and the disease state of trilineage reduction: The number of peripheral blood lymphocytes in liver transplantation GVHD is drastically reduced. Under these conditions, if STR technology is needed to detect T cell chimerism (requiring a large initial DNA detection amount), a large amount of peripheral blood needs to be collected for T cell isolation, which is difficult to operate clinically and has low patient compliance; 3) Low clinical timeliness: The multi-step operation process of STR testing technology, including cell sorting, DNA purification, amplification, and STR polymorphism quantification, is time-consuming and relies on fully manual operation by experienced technicians. Operational deviations can easily lead to distorted results, significantly increasing the difficulty of quality control and the risk of result bias. If the T cell chimerism ratio needs to be detected, an additional cell sorting step is required, and the entire testing cycle can take more than 48 hours. In addition, due to the limitations of equipment and personnel requirements, most medical institutions need to send samples to professional institutions for testing, which further prolongs the testing cycle, ultimately extending the testing cycle to 5-6 days. The timeliness is difficult to match the rapid progression of GVHD pathological characteristics, resulting in delayed test results during the golden intervention window and delaying clinical decision-making. 4) High cost: STR testing requires the use of various professional meristem testing equipment, and the cost of a single test exceeds 1,000 yuan. If T cells need to be sorted, additional costs for sorting reagents and special instruments are required, further pushing the overall cost to more than 3,000 yuan, which is difficult to meet the needs of long-term dynamic clinical monitoring.

[0004] Therefore, there is a need to develop new biomarkers and methods for diagnosing GVHD. Summary of the Invention

[0005] In view of this, in order to overcome the shortcomings of the prior art, the present invention is proposed.

[0006] The first aspect of this invention provides for any of the following applications:

[0007] (1) Application of substances that detect Ki67 and / or Granzyme B in T cells of test samples in the preparation of diagnostic GVHD products;

[0008] (2) The application of detecting Ki67 and / or Granzyme B and HLA substances in T cells of the test sample in the preparation of diagnostic GVHD products.

[0009] In this invention, GVHD refers to graft-versus-host disease (GVHD), which includes acute GVHD and chronic GVHD. Based on the time of occurrence after transplantation, GVHD occurring within 100 days is termed acute GVHD, and GVHD occurring after 100 days is termed chronic GVHD.

[0010] In some implementations, the GVHD is acute GVHD.

[0011] In some implementations, the causes of GVHD include, but are not limited to, allogeneic bone marrow transplantation, organ transplantation, and blood transfusion.

[0012] In some implementations, the cause of GVHD is liver transplantation.

[0013] In this invention, Ki67 is a core marker of cell proliferation. It is a non-histone protein that exists in the cell nucleus, and the gene encoding it is located on chromosome 10q25.

[0014] In this invention, Granzyme B is a serine protease stored in the cytoplasmic granules of cytotoxic cells, and is also referred to as GranB below.

[0015] In this invention, HLA stands for Human Leukocyte Antigen, a group of genes located on the short arm of human chromosome 6 that encodes the Major Histocompatibility Complex (MHC). The HLA system plays a crucial role in the immune system, primarily responsible for recognizing self and non-self and participating in the regulation of immune responses. HLA genes are divided into three classes: 1. HLA class I molecules: including HLA-A, HLA-B, and HLA-C. These are present on the surface of almost all nucleated cells. Their main function is to present intracellular antigens (such as viral proteins and tumor antigens) to CD8+ T cells (cytotoxic T cells), triggering a cellular immune response. 2. HLA class II molecules: including HLA-DP, HLA-DQ, and HLA-DR. These are mainly present on the surface of antigen-presenting cells (such as dendritic cells, macrophages, and B cells). Their main function is to present extracellular antigens (such as bacteria and parasites) to CD4+ T cells (helper T cells), triggering a humoral immune response. 3. HLA class III molecules: including complement components (such as C2, C4, and factor B) and cytokines (such as tumor necrosis factor TNF). They are mainly involved in inflammatory responses and immune regulation.

[0016] In some implementations, the HLA is used to distinguish between donor and recipient-derived T cells.

[0017] In some embodiments, the substance used to detect Ki67 and / or Granzyme B in the T cells of the test sample includes, but is not limited to, a binder capable of binding to Ki67 and / or Granzyme B.

[0018] In some implementations, substances that detect Ki67 and / or Granzyme B, as well as HLA, in the T cells of the test sample include, but are not limited to, binders capable of binding to Ki67 and / or Granzyme B, as well as HLA.

[0019] In some implementations, the binding agent includes, but is not limited to, protein binding agents of Ki67 and Granzyme B, and nucleic acid binding agents.

[0020] In some implementations, the binding agent includes, but is not limited to, HLA protein binding agents and nucleic acid binding agents.

[0021] In some implementations, the protein binding agent includes, but is not limited to, antibodies or antibody fragments, peptide mimics, and nucleic acid aptamers.

[0022] In some implementations, the nucleic acid binding agent includes, but is not limited to, probes and primers.

[0023] In some implementations, GVHD is diagnosed by detecting the expression levels of Ki67 and / or Granzyme B in T cells of the test sample.

[0024] In some implementations, GVHD is diagnosed by detecting the expression levels of Ki67 and / or Granzyme B in donor-derived T cells of the test sample.

[0025] In some implementations, GVHD is diagnosed by detecting the proportion of Ki67 and / or Granzyme B-positive cells.

[0026] In some implementations, the T cells include CD3+ T cells.

[0027] In some implementations, GVHD is diagnosed by the proportion of Ki67-positive cells among CD3+ T cells in the test sample and / or the proportion of Granzyme B-positive cells among CD3+ T cells in the test sample.

[0028] In some implementations, the CD3+ T cells are total T cells, which include CD4+ T cells and CD8+ T cells.

[0029] In some implementations, the proportion of Ki67-positive cells among CD4+ T cells in the sample to be tested is used.

[0030] In some implementations, GVHD is diagnosed by the proportion of Ki67-positive cells among CD8+ T cells in the test sample and / or the proportion of Granzyme B-positive cells among CD8+ T cells in the test sample.

[0031] In some embodiments, the CD3+ T cells include CD3+ TEM cells. CD3+ TEM cells are CD3+ effector memory T cells.

[0032] In some implementations, GVHD is diagnosed by the proportion of Ki67-positive cells to CD3+ TEM cells in the test sample and / or the proportion of Granzyme B-positive cells to CD3+ TEM cells in the test sample.

[0033] In some embodiments, the CD3+TEM cells include CD3+CCR7-CD45RA-TEM cells, that is, CD3+TEM cells are T cells that express CD3 but do not express CCR7 or CD45RA.

[0034] In some implementations, the CD4+ T cells include CD4+ TEM cells.

[0035] In some implementations, the proportion of Ki67-positive cells to CD4+ TEM cells in the test sample is used.

[0036] In some embodiments, the CD4+TEM cells include CD4+CCR7-CD45RA-TEM cells, that is, CD4+TEM cells are T cells that express CD4 but do not express CCR7 or CD45RA.

[0037] In some implementations, the CD8+ T cells include CD8+ TEM cells.

[0038] In some implementations, GVHD is diagnosed by the proportion of Ki67-positive cells to CD8+TEM cells in the test sample and / or the proportion of Granzyme B-positive cells to CD8+TEM cells in the test sample.

[0039] In some embodiments, the CD8+TEM cells include CD8+CCR7-CD45RA-TEM cells, that is, CD8+TEM cells are T cells that express CD8 but do not express CCR7 or CD45RA.

[0040] In some implementations, the use of substances that detect Ki67 and / or Granzyme B, as well as HLA, in the preparation of diagnostic GVHD products refers to the use of substances that detect Ki67 and HLA in the T cells of the test sample in the preparation of diagnostic GVHD products, or the use of substances that detect Granzyme B and HLA in the T cells of the test sample in the preparation of diagnostic GVHD products, or the use of substances that detect Ki67, Granzyme B, and HLA in the T cells of the test sample in the preparation of diagnostic GVHD products.

[0041] In some implementations, GVHD is diagnosed by detecting the proportion of Ki67-positive cells in donor-derived CD3+ T cells of the test sample, i.e., obtaining the proportion of Ki67-positive cells in donor-derived CD3+ T cells of the test sample relative to donor-derived CD3+ T cells.

[0042] In some implementations, GVHD is diagnosed by detecting the proportion of Ki67-positive cells in donor-derived CD3+ TEM cells of the test sample, i.e., the proportion of Ki67-positive cells in donor-derived CD3+ TEM cells of the test sample to the proportion of donor-derived CD3+ TEM cells.

[0043] In some implementations, GVHD is diagnosed by detecting the proportion of Ki67-positive cells in donor-derived CD4+ T cells of the test sample, i.e., obtaining the proportion of Ki67-positive cells in donor-derived CD4+ T cells of the test sample relative to donor-derived CD4+ T cells.

[0044] In some implementations, GVHD is diagnosed by detecting the proportion of Ki67-positive cells in donor-derived CD4+ TEM cells of the test sample, i.e., obtaining the proportion of Ki67-positive cells in donor-derived CD4+ TEM cells of the test sample to the proportion of donor-derived CD4+ TEM cells.

[0045] In some implementations, GVHD is diagnosed by detecting the proportion of Ki67-positive cells in donor-derived CD8+ T cells of the test sample, i.e., the proportion of Ki67-positive cells in donor-derived CD8+ T cells of the test sample relative to donor-derived CD8+ T cells.

[0046] In some implementations, GVHD is diagnosed by detecting the proportion of Ki67-positive cells in donor-derived CD8+ TEM cells of the test sample, i.e., the proportion of Ki67-positive cells in donor-derived CD8+ TEM cells of the test sample to the proportion of donor-derived CD8+ TEM cells.

[0047] In some implementations, GVHD is diagnosed by detecting the proportion of Granzyme B-positive cells in donor-derived CD3+ T cells of the test sample, i.e., the proportion of Granzyme B-positive cells in donor-derived CD3+ T cells of the test sample to the proportion of donor-derived CD3+ T cells.

[0048] In some implementations, GVHD is diagnosed by detecting the proportion of Granzyme B-positive cells in donor-derived CD3+ TEM cells of the test sample, i.e., the proportion of Granzyme B-positive cells in donor-derived CD3+ TEM cells of the test sample to the proportion of donor-derived CD3+ TEM cells.

[0049] In some implementations, GVHD is diagnosed by detecting the proportion of Granzyme B-positive cells in donor-derived CD8+ T cells of the test sample, i.e., by detecting the proportion of Granzyme B-positive cells in donor-derived CD8+ T cells of the test sample to donor-derived CD8+ T cells.

[0050] In some implementations, GVHD is diagnosed by detecting the proportion of Granzyme B-positive cells in CD8+ TEM cells from the donor of the test sample, i.e., the proportion of Granzyme B-positive cells in CD8+ TEM cells from the donor of the test sample to the proportion of CD8+ TEM cells from the donor cells.

[0051] In some implementations, GVHD is diagnosed by detecting the proportion of Ki67 and Granzyme B positive cells in donor-derived CD3+ T cells of the test sample. In other words, GVHD is diagnosed by obtaining the proportion of Ki67 positive cells in donor-derived CD3+ T cells to donor-derived CD3+ T cells and the proportion of Granzyme B positive cells to donor-derived CD3+ T cells.

[0052] In some implementations, GVHD is diagnosed by detecting the proportion of Ki67 and Granzyme B positive cells in donor-derived CD3+ TEM cells of the test sample. That is, by obtaining the proportion of Ki67 positive cells in donor-derived CD3+ TEM cells of the test sample to the proportion of donor-derived CD3+ TEM cells and Granzyme B positive cells to the proportion of donor-derived CD3+ TEM cells.

[0053] In some implementations, GVHD is diagnosed by detecting the proportion of Ki67 and Granzyme B positive cells in donor-derived CD8+ T cells of the test sample. In other words, GVHD is diagnosed by obtaining the proportion of Ki67 positive cells in donor-derived CD8+ T cells and the proportion of Granzyme B positive cells in donor-derived CD8+ T cells of the test sample.

[0054] In some implementations, GVHD is diagnosed by detecting the proportion of Ki67 and Granzyme B positive cells in donor-derived CD8+ TEM cells of the test sample. That is, by obtaining the proportion of Ki67 positive cells in donor-derived CD8+ TEM cells of the test sample to the proportion of donor-derived CD8+ TEM cells and Granzyme B positive cells to the proportion of donor-derived CD8+ TEM cells.

[0055] In some implementations, the substances used to detect Ki67, Granzyme B, or HLA in the T cells of the test sample include, but are not limited to, one or more of the reagents, kits, and detection devices used in flow cytometry or single-cell sequencing.

[0056] In some embodiments, the reagents or kits used in the flow cytometry include Ki67 antibody, Granzyme B antibody, or HLA antibody.

[0057] In some embodiments, the reagents or kits used in the flow cytometry also include antibodies that identify T cell subsets of the sample to be tested.

[0058] In some implementations, the antibodies that identify T cell subsets of the sample to be tested include, but are not limited to, one or more of CD3 antibodies, CD4 antibodies, CD8 antibodies, CCR7 antibodies, and CD45RA antibodies.

[0059] In some implementations, the HLA antibody needs to be screened based on the preoperative HLA typing results of organ transplantation to identify specific HLA sites that show significant differences between the donor and recipient, and then the applicable HLA antibody is determined.

[0060] In some embodiments, the reagents or kits used for flow cytometry also include common components. These components include, but are not limited to, one or more of the following: fluorescent dyes, buffers, washing solutions, lysis buffers, negative controls, positive controls, standards, quality controls, and blank controls. These components may also be present in the reagents or kits used for flow cytometry described below in this application.

[0061] The second aspect of this invention provides the application of a substance for detecting the proportion of TEM cells in T cells of a test sample in the preparation of diagnostic GVHD products.

[0062] In some implementations, the detection of the proportion of TEM cells in the T cells of the test sample refers to the detection of the proportion of TEM cells among the T cells in the test sample.

[0063] In some embodiments, the TEM cells include CD3+ TEM cells.

[0064] In some implementations, the detection of the proportion of TEM cells in the T cells of the test sample refers to the detection of the proportion of total CD3+ TEM cells in the test sample to total T cells, without distinguishing the donor and recipient sources of CD3+ TEM cells and T cells in the test sample.

[0065] In some implementations, the detection of the proportion of TEM cells in the T cells of the test sample refers to the detection of the proportion of donor CD3+ TEM cells to donor T cells in the test sample.

[0066] In some embodiments, the CD3+TEM cells include CD4+TEM cells and CD8+TEM cells.

[0067] In some implementations, the detection of the proportion of TEM cells in the T cells of the test sample refers to the proportion of total CD4+ TEM cells in the test sample to total T cells, without distinguishing the donor and recipient sources of CD4+ TEM cells and T cells in the test sample.

[0068] In some implementations, the detection of the proportion of TEM cells in the T cells of the test sample refers to the detection of the proportion of donor CD4+ TEM cells to donor T cells in the test sample.

[0069] In some implementations, the detection of the proportion of TEM cells in the T cells of the test sample refers to the proportion of total CD8+ TEM cells in the test sample to total T cells, without distinguishing the donor and recipient sources of CD8+ TEM cells and T cells in the test sample.

[0070] In some implementations, the proportion of TEM cells in the T cells of the test sample refers to the proportion of donor CD8+ TEM cells to donor T cells in the test sample.

[0071] In some implementations, the substance used to detect the proportion of TEM cells in the T cells of the sample to be tested includes one or more of the reagents, kits, and detection devices used in flow cytometry or single-cell sequencing.

[0072] In some embodiments, the reagents or kits used in the flow cytometry include one or more of CD3 antibodies, CD4 antibodies, CD8 antibodies, CCR7 antibodies, and CD45RA antibodies.

[0073] A third aspect of the present invention provides a product for diagnosing GVHD, the product comprising substances for detecting Ki67 and / or Granzyme B in T cells of a test sample.

[0074] In some embodiments, the explanation of the substance for detecting Ki67 and / or Granzyme B in T cells of the test sample is as described in the first aspect of the invention for detecting Ki67 and / or Granzyme B in T cells of the test sample.

[0075] In some implementations, the Granzyme B antibody is manufactured by Biolegend, with catalog number 372216.

[0076] In some implementations, the Ki-67 antibody is manufactured by Biolegend, with catalog number 350522.

[0077] In some implementations, the CD3 antibody is manufactured by eBioscience, with catalog number 58-0038-42.

[0078] In some implementations, the CD4 antibody is manufactured by BD Biosciences, catalog number 740161.

[0079] In some implementations, the CD8 antibody is manufactured by Biolegend, with catalog number 301037.

[0080] In some implementations, the CCR7 antibody is manufactured by Biolegend, with catalog number 353212.

[0081] In some implementations, the CD45RA antibody is manufactured by Biolegend, with catalog number 304156.

[0082] In some embodiments, the product further includes a substance for detecting HLA in the sample to be tested. For an explanation of the substance for detecting HLA in the sample to be tested, please refer to the substance for detecting HLA in the sample to be tested described in the first aspect of this invention.

[0083] A third aspect of the invention also provides another product for diagnosing GVHD, the product comprising a substance for detecting the proportion of TEM cells in T cells of a test sample.

[0084] In some embodiments, the TEM cells include CD3+ TEM cells.

[0085] In some embodiments, the CD3+TEM cells include CD4+TEM cells and CD8+TEM cells.

[0086] In some implementations, the substance used to detect the proportion of TEM cells in the T cells of the sample to be tested includes one or more of the reagents, kits, and detection devices used in flow cytometry or single-cell sequencing.

[0087] In some embodiments, the reagents or kits used in the flow cytometry include one or more of CD3 antibodies, CD4 antibodies, CD8 antibodies, CCR7 antibodies, and CD45RA antibodies.

[0088] In some implementations, the product includes, but is not limited to, one or more of reagents, kits, and testing devices.

[0089] In some implementations, the kit also includes instructions.

[0090] In some implementations, the kit includes, but is not limited to, a flow cytometry kit.

[0091] In some implementations, the detection device includes, but is not limited to, a flow cytometer.

[0092] In some embodiments, the flow cytometer is a full-spectrum flow cytometer and / or a conventional multifluorescence flow cytometer.

[0093] A fourth aspect of the present invention provides a method for diagnosing GVHD, the method being performed by a computer and comprising the following steps:

[0094] Acquire T cell-related data of the sample to be tested, including one or more of the following: Ki67 positive rate data, Granzyme B positive rate data, and TEM cell rate data.

[0095] Based on the T cell-related data of the sample to be tested, a classification prediction is performed to obtain a classification result indicating the risk of developing GVHD.

[0096] If the proportion of Ki67 positivity in T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Ki67 positivity in T cells is lower than the threshold, the risk of GVHD is low.

[0097] If the proportion of Granzyme B positivity in T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Granzyme B positivity in T cells is lower than the threshold, the risk of GVHD is low.

[0098] If the proportion of TEM cells in the T cells is higher than the threshold, the risk of GVHD is high; if the proportion of TEM cells in the T cells is lower than the threshold, the risk of GVHD is low.

[0099] In some implementations, the method includes acquiring donor-derived T cell-related data for the sample to be tested, wherein the donor-derived T cell-related data includes one or more of the following: Ki67 positivity rate data, Granzyme B positivity rate data, and TEM cell proportion data in the donor-derived T cells;

[0100] Based on the donor-derived T cell data of the test sample, classification and prediction are performed to obtain classification results indicating the high or low risk of GVHD.

[0101] If the proportion of Ki67 positivity in donor-derived T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Ki67 positivity in donor-derived T cells is lower than the threshold, the risk of GVHD is low.

[0102] If the proportion of Granzyme B positivity in donor-derived T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Granzyme B positivity in donor-derived T cells is lower than the threshold, the risk of GVHD is low.

[0103] If the proportion of TEM cells in the donor-derived T cells is higher than the threshold, the risk of GVHD is high; if the proportion of TEM cells in the donor-derived T cells is lower than the threshold, the risk of GVHD is low.

[0104] A fourth aspect of the present invention provides another method for diagnosing GVHD, wherein the steps described above, performed by a human, are computer-generated.

[0105] In some implementations, when a person performs the steps described above that are computer-generated, the step of acquiring the T-cell related data of the test sample includes either directly acquiring the T-cell related data of the test sample that has already been tested, or it includes a step of a person performing the test of the T-cell related data of the test sample.

[0106] A fifth aspect of the present invention provides a system for diagnosing GVHD, the system comprising:

[0107] Acquisition module: Acquires T cell-related data of the sample to be tested, including one or more of the following: Ki67 positive rate data, Granzyme B positive rate data, and TEM cell rate data.

[0108] Prediction module: Based on the T cell-related data of the sample to be tested, it performs classification prediction to obtain the classification result of the risk of GVHD.

[0109] Output module: Used to output classification results;

[0110] If the proportion of Ki67 positivity in T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Ki67 positivity in T cells is lower than the threshold, the risk of GVHD is low.

[0111] If the proportion of Granzyme B positivity in T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Granzyme B positivity in T cells is lower than the threshold, the risk of GVHD is low.

[0112] If the proportion of TEM cells in the T cells is higher than the threshold, the risk of GVHD is high; if the proportion of TEM cells in the T cells is lower than the threshold, the risk of GVHD is low.

[0113] In some implementations, the acquisition module can acquire donor-derived T cell-related data for the sample to be tested, including one or more of the following: Ki67 positivity rate data, Granzyme B positivity rate data, and TEM cell proportion data in the donor-derived T cells.

[0114] A fifth aspect of the present invention also provides an apparatus for diagnosing GVHD, the apparatus comprising a first computing device including a memory and a processor. The memory is used to store program instructions. The processor is used to invoke the program instructions, which, when executed, implement the steps of the method for diagnosing GVHD described in the fourth aspect of the present invention.

[0115] The fifth aspect of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for diagnosing GVHD as described in the fourth aspect of the present invention.

[0116] The fifth aspect of the present invention also provides a computer program that, when executed by a processor, implements the steps of the method for diagnosing GVHD as described in the fourth aspect of the present invention.

[0117] The advantages and beneficial effects of this invention are as follows:

[0118] This invention provides biomarkers for diagnosing GVHD and their applications. The method for diagnosing GVHD using the biomarkers provided by this invention has the following advantages:

[0119] (1) It has the ability to quantify immune subpopulations specifically: In response to the limitations of STR-PCR technology in quantifying the chimeric proportion of immune cell subpopulations, a combination of multicolor antibodies and scattered light parameters (SSC / FSC) are used to simultaneously complete the analysis of immune cell subpopulations during the chimeric quantification process, avoiding additional time-consuming steps;

[0120] (2) Low cell quantity adaptation: To address the contradiction between the cell quantity requirements of STR-PCR technology and the reduction of disease state by three-lineage PCR, this invention requires a small number of cells for detection, with a total cell quantity >10. 4 -10 5 It can detect and be adapted to the patient's disease state;

[0121] (3) Timeliness advantage: In view of the low clinical timeliness of STR-PCR technology, the first antibody verification and chimeric quantification of this invention takes about 4 hours, and subsequent continuous chimeric detection takes about 2 hours, which greatly shortens the detection time and meets the needs of rapid clinical diagnosis and timely intervention.

[0122] (4) Cost control advantage: In view of the high cost of STR-PCR technology, the reagents involved in this invention include immune cell extraction, antibodies, and flow cytometry staining reagents, which involve the use of flow cytometry equipment. The total cost is about RMB 500-600 per sample, which greatly reduces the cost of using the technology and is more suitable for multiple dynamic monitoring scenarios. Attached Figure Description

[0123] Figure 1This is an example diagram of HLA matching using donor-receptor specific distinguishing sites.

[0124] Figure 2 This is a flow cytometry result of HLA-DR / CD38 / CD137 / CD25 / CD69, markers of T cell activation in peripheral blood of GVHD and non-GVHD patients.

[0125] Figure 3 These are flow cytometry results for Ki67 and Granzyme B. Figure A shows representative flow cytometry data of GranB in peripheral blood T cells from GVHD and non-GVHD patients, with significantly higher GranB expression in GVHD patients compared to non-GVHD patients. Figure B shows representative flow cytometry data of Ki67 in peripheral blood T cells from GVHD and non-GVHD patients, with significantly higher Ki67 expression in GVHD patients compared to non-GVHD patients.

[0126] Figure 4 These are flow cytometry results for TIGIT, PD-1, and CD57. Figure A shows a representative flow cytometry graph of peripheral blood T cells from GVHD and non-GVHD patients with TIGIT; Figure B shows a representative flow cytometry graph of peripheral blood T cells from GVHD and non-GVHD patients with PD-1; and Figure C shows a representative flow cytometry graph of peripheral blood T cells from GVHD and non-GVHD patients with CD57.

[0127] Figure 5 The images show examples of HLA-specific antibody replacement. In Figure A, the selected HLA-specific antibody cannot effectively distinguish between donor and recipient immune cells; in Figure B, the HLA-specific antibody can effectively distinguish between donor and recipient immune cells after replacement.

[0128] Figure 6 This is a diagram showing the dynamic monitoring results of CD3, CD4, and CD8 positive T cell chimeras in peripheral blood of GVHD patients after transplantation using the method of this invention.

[0129] Figure 7 This is a diagram showing the dynamic changes of donor-derived chimeric CD4 and CD8 in two patients with GVHD after liver transplantation, detected using the experimental method of this invention.

[0130] Figure 8 This is a graph showing the dynamic monitoring results of the expression levels of total CD3 T cells and donor / recipient CD4-positive T cells and CD8-positive T cells (Ki67 protein, a marker of proliferation) in peripheral blood of GVHD patients after transplantation using the method of this invention.

[0131] Figure 9 This is a graph showing the dynamic monitoring results of the expression level of Ki67 protein, a proliferation marker of peripheral blood donor-derived TEM cells, in GVHD patients after transplantation using the method of this invention.

[0132] Figure 10 This is a graph showing the dynamic monitoring results of the expression levels of granzyme B protein, a cytotoxic marker of total CD3 T cells and donor / recipient CD4-positive T cells and CD8-positive T cells in the peripheral blood of GVHD patients after transplantation, using the method of the present invention.

[0133] Figure 11 This is a graph showing the dynamic monitoring results of Gran B protein expression, a TEM cytotoxicity marker derived from donor peripheral blood in GVHD patients after transplantation, using the method of this invention.

[0134] Figure 12 This is a graph showing the monitoring results of peripheral blood supply, recipient-derived CD3 total T cells (A and B), CD4 (C and D), and CD8 positive T cell (E and F) subsets Naive (CD45RA+CCR7+), TCM (CD45RA-CCR7+), TEM (CD45RA-CCR7-), and TEMRA (CD45RA+CCR7-) in GVHD patients after transplantation using the method of this invention.

[0135] Figure 13 This is a representative flow cytometry plot of the proportion of donor-derived T cells (TEM) (CD45RA-CCR7-) in peripheral blood of GVHD and non-GVHD patients. The proportion of CD3 T cells (A), CD8 T cells (B), and CD4 T cells (C) in TEM is significantly higher in GVHD patients than in non-GVHD patients.

[0136] Figure 14 This is a representative flow cytometry plot showing the proportion of Ki67 expression in donor T cells from peripheral blood in GVHD and non-GVHD patients. The Ki67 expression in CD3 T cells (A), CD3 TEM (B), CD8 T cells (C), CD8 TEM (D), CD4 T cells (E), and CD4 TEM (F) in GVHD patients was significantly higher than that in non-GVHD patients.

[0137] Figure 15 This is a representative flow cytometry plot showing the proportion of Granzyme B expression in peripheral blood donor T cells from GVHD and non-GVHD patients. Granzyme B expression in CD3 T cells (A), CD3 TEM (B), CD8 T cells (C), and CD8 TEM (D) was significantly higher in GVHD patients than in non-GVHD patients.

[0138] Figure 16 The ROC curve is used to diagnose GVHD by the proportion of TEM (AC), Ki67 (DI), and Granzyme B (JM) of peripheral blood donor T cells.

[0139] Figure 17 This is a graph showing the monitoring results of the dynamic changes in Ki67 expression in total CD3 T cells, CD4 and CD8 T cells in peripheral blood of GVHD patients after transplantation using the method of this invention;

[0140] Figure 18 This is a graph showing the monitoring results of the dynamic changes in Gran B expression in peripheral blood CD3 T cells, CD4 and CD8 T cells of GVHD patients after transplantation using the method of this invention;

[0141] Figure 19 The purpose of this invention is to monitor the dynamic changes of peripheral blood CD3 T cells, CD4 and CD8 T cell subsets Naive (CD45RA+CCR7+), TCM (CD45RA-CCR7+), TEM (CD45RA-CCR7-) and TEMRA (CD45RA+CCR7-) in GVHD patients after transplantation using the method of this invention.

[0142] Figure 20 This invention is used to monitor the dynamic changes in Ki67 expression in peripheral blood CD3 T cells, CD4 and CD8 T cells of GVHD patients after transplantation using the method of this invention.

[0143] Figure 21 This is a graph showing the monitoring results of the dynamic changes in Gran B expression in peripheral blood TEM cells of GVHD patients after transplantation using the method of this invention;

[0144] Figure 22 This is a flow cytometry diagram representing Ki67 expression in peripheral blood T cells from GVHD and non-GVHD patients. Ki67 expression in CD3, CD8, and CD4 T cells was significantly higher in GVHD patients than in non-GVHD patients (AC); Ki67 expression in CD3, CD8, and CD4 T cells was significantly higher in GVHD patients than in non-GVHD patients (DF).

[0145] Figure 23 These are representative flow cytometry images of Granzyme B expression in peripheral blood T cells from GVHD and non-GVHD patients. Granzyme B expression in CD3 and CD8 T cells was significantly higher in GVHD patients than in non-GVHD patients (A, B); Granzyme B expression in CD3 and CD8 T cells was significantly higher in GVHD patients than in non-GVHD patients (CD).

[0146] Figure 24 This is a flow cytometry plot representing the proportion of peripheral blood T cells in GVHD and non-GVHD patients. The proportion of TEM in CD3 (A), CD4 (B), and CD8 T (C) cells is significantly higher in GVHD patients than in non-GVHD patients.

[0147] Figure 25The ROC curves of the proportion of Ki67 (AF), Granzyme B (GJ), and TEM (KN) T cells in peripheral blood that can be used to diagnose GVHD are shown.

[0148] Figure 26 The peripheral blood sample taken at the onset of GVHD was tested for chimerism using STR-PCR technology. The results indicated that the chimerism rate of donor cell DNA in the patient's peripheral blood was 0.

[0149] Figure 27 The results of HLA flow cytometry analysis are shown in the following figures: A represents the donor chimerism rate of CD3+ T cells (91.5%); B represents the donor chimerism rate of lymphocytes (42.1%); C represents the differentiation phenotype analysis of recipient T cells, including naive T cells (20.2%), central memory T cells (7.10%), effector memory T cells (60.1%), and terminally differentiated T cells (12.6%); D represents the differentiation phenotype of donor T cells, mainly effector memory T cells (99.1%); E represents the KI67 positivity rate of donor T cells (96.3%); and F represents the Granzyme B positivity rate of donor T cells (78.5%).

[0150] Figure 28 The results of STR chimerism detection were obtained after flow cytometry sorting of lymphocytes.

[0151] Figure 29 The method of this invention is used to detect lymphocyte chimerism in this peripheral blood sample;

[0152] Figure 30 This is a schematic flowchart of a method for diagnosing GVHD provided in an embodiment of this application;

[0153] Figure 31 This is a schematic flowchart of another method for diagnosing GVHD provided in an embodiment of this application;

[0154] Figure 32 This is a schematic diagram of a system for diagnosing GVHD provided in an embodiment of this application;

[0155] Figure 33 This is a schematic diagram of a device for diagnosing GVHD provided in an embodiment of this application. Detailed Implementation

[0156] The present invention will be further described below with reference to embodiments. The following description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any other way. Any person skilled in the art may make equivalent modifications to the disclosed technical content to create equivalent embodiments. Any simple modifications or equivalent changes made to the following embodiments based on the technical essence of the present invention without departing from the scope of the invention are all within the protection scope of the present invention.

[0157] Example 1: Screening of donor-receptor specific site-specific antibodies based on HLA typing

[0158] 1. Experimental Materials

[0159] Phosphate-buffered saline (PBS), lymphocyte separation medium (Stemcell, made in Canada, catalog number: #07861), and the corresponding antibodies required for flow cytometry (HLA-BW6, Miltenyi Biotec, made in Germany, catalog number: 130-123-264, HLA-ABC, Biolegend, made in the USA, catalog number: 311436, 7-AAD, BD Biosciences, made in the USA, catalog number: 559925).

[0160] 2. Experimental Methods

[0161] HLA-matched donor-receptor specific distinguishing sites screening

[0162] Based on preoperative HLA typing results for organ transplantation, specific HLA loci with significant differences between donors and recipients are first screened out, for example, as shown in the figure. Figure 1 As shown, in this example, recipient-specific HLA-A2 antibody and donor-specific HLA-BW6 antibody can be used as alternative antibodies to distinguish the cell origins of donors and recipients.

[0163] HLA antibody distinguishing efficacy test

[0164] To verify the discriminative efficacy of donor-specific HLA antibodies, the following detection protocol was used:

[0165] (1) Cell resuscitation: The frozen donor and recipient immune cells were placed in a 37 ℃ water bath to thaw until a little ice remained in the tube, and the cells were washed 1-2 times with 1640 medium preheated at 37 ℃.

[0166] (2) Resuspend the cell pellet in PBS, count the cells, and mix the donor and recipient immune cells in flow cytometry tubes at ratios of 1:2, 1:4, 1:8, 1:16, 1:32, 1:64, and 1:128 to ensure the ability of the selected HLA-specific antibody to distinguish between donor and recipient cells. Reserve donor and recipient cells as controls. The cell suspension volume should be controlled at 50–100 μL, and the cell count at 0.5–1.0 × 10⁻⁶ cells / mL. 6 ;

[0167] (3) Add candidate HLA-specific antibodies, pan-HLA-ABC antibodies, and PBS to the flow cytometry tube to adjust the staining system to 100 μL for cell surface staining; shake well and incubate at 4 ℃ in the dark for 30 min.

[0168] (4) Add 1 mL PBS to wash the cells, 450 g, 5 min, 4 ℃;

[0169] (5) Discard the supernatant, add 7-AAD to remove dead cells, and then perform the test.

[0170] Data were acquired using flow cytometry and analyzed using flow cytometry software such as FlowJo. This method can systematically evaluate the specificity and sensitivity of HLA antibodies in cell tracing (accurate detection of less than 1%), thereby confirming their reliability and accuracy in differentiating peripheral blood immune cell origins (donor or recipient).

[0171] Example 2: Establishment of a Multicolor Flow Cytometry Detection Scheme

[0172] 1. Experimental Materials

[0173] Phosphate-buffered saline (PBS), lymphocyte separation medium (stemcell, made in Canada, catalog number: #07861), erythrocyte lysis buffer (Solarbio, made in China, catalog number R1010), and the corresponding antibodies required for flow cytometry: CD4 (BD Biosciences, made in the USA, catalog number 740161), CD8 (Biolegend, made in the USA, catalog number 301038), CD45RA (Biolegend, made in the USA, catalog number 304156), CD3 (eBioscience, made in the USA, catalog number 58-0038-42), CCR7 (Biolegend, made in the USA, catalog number 353212), HLA-specific antibodies (to be selected according to donor and recipient HLA typing, available from companies such as Biolegend in the USA, BD Biosciences, and Miltenyi Biotec in Germany), Granzyme. B (Biolegend, USA, catalog number 372216), Ki-67 (Biolegend, USA, catalog number 350522), eBioscience™ Foxp3 / transcription factor flow cytometry fixation and permeabilization buffer (eBioscience, USA, catalog number 00-5523-00).

[0174] 2. Experimental Methods

[0175] Currently, some literature (Zuber J, Rosen S, Shonts B, et al. Macrochimerism in Intestinal Transplantation: Association With Lower Rejection Rates and Multivisceral Transplants, Without GVHD [J]. Am J Transplant, 2015, 15(10):2691-703.) reports that an increased chimerism rate after organ transplantation does not completely predict the impending occurrence of GVHD. We searched for other GVHD pathological phenotypes: Initially, we attempted to perform flow cytometry experiments on T cell activation-related markers combined with specific HLA to observe whether certain T cell activation markers could serve as immunomarkers for the diagnosis of GVHD. The main antibodies included (HLA-DR / CD38 / CD137 / CD25 / CD69), but the experimental results ( Figure 2 The results showed that these T-cell activation markers did not differ significantly between GVHD and non-GVHD patients, and therefore could not provide a good reference for the diagnosis of GVHD.

[0176] Based on our findings, we shifted our focus to immune markers related to T cell proliferation, cytotoxicity, and cellular senescence. Therefore, we added the detection of proliferation-related antibody Ki67, cytotoxicity-related granzyme B, and cellular senescence and exhaustion-related antibodies CD57, TIGIT, and PD-1. We also upgraded our flow cytometer from a traditional low-parameter (BDLSRFortessa) to a full-spectrum flow cytometer (Cytek Aurora), enabling simultaneous detection of multiple parameters. The results showed that Ki67 and Granzyme B positivity rates were abnormally elevated in donor-derived T cells from liver transplant recipients with GVHD, significantly higher than in recipient-derived T cells. This characteristic is a specific phenotype of donor T cells after GVHD surgery. Such high levels of Ki67 and Granzyme B were not observed in patients without GVHD after surgery. Figure 3 However, the expression levels of aging and depletion markers CD57, TIGIT, and PD-1 did not show a generally significant increase. Figure 4 It does not have the ability to assist in the diagnosis of GVHD.

[0177] Screening of specific antibodies

[0178] For antibody screening, the same antibody may have multiple clone numbers and fluorescence types. Certain clone numbers and fluorescence types may lead to poor detection results. For example, in screening HLA-specific antibodies, we initially used HLA-A2, A11, BW4, and BW6 from One Lambda. However, during subsequent HLA-specific antibody validation, HLA-A2, BW4, and BW6 antibodies performed poorly, sometimes failing to detect antibody expression. Only HLA-A11 showed good results and is currently still used for chimeric detection. To solve this problem, we tried changing antibody suppliers to find antibodies with better staining effects. After repeated experimental verification, we changed the HLA-A2 antibody supplier to BD Biosciences (USA), and HLA-BW4 and BW6 to Miltenyi (Germany), and added HLA-A3 and A9. The changed antibodies performed well, and we could basically select the corresponding HLA-specific antibody for chimeric detection based on the donor and recipient HLA typing information. An example result of changing HLA-specific antibodies is shown in the figure below. Figure 5 As shown in Figure A, the selected HLA-specific antibody cannot effectively distinguish between donor and recipient immune cells; Figure B shows that after changing to an HLA-specific antibody, it can effectively distinguish between donor and recipient immune cells.

[0179] To explore antibody staining protocols for immune markers related to T cell differentiation, proliferation, cytotoxicity, cell exhaustion, and cell senescence, and to select the final HLA-specific antibody, the antibodies used are shown in Table 1. This protocol was performed using a Cytek Aurora full-spectrum flow cytometer.

[0180] Table 1. Antibody staining protocols and final HLA-specific antibody selection for exploring immune markers related to T cell differentiation, proliferation, cytotoxicity, cell exhaustion, and cellular senescence.

[0181]

[0182] Traditional flow cytometry uses lasers to excite fluorescent dyes bound to cells, and then separates and collects signals at different wavelengths using filters and photomultiplier tubes (PMTs). Spectroscopic flow cytometry, on the other hand, uses prisms or gratings to disperse the fluorescence signal into a continuous spectrum, and acquires the complete spectral information using multi-channel detectors (such as PMT arrays or CCDs). Both methods must consider the interference between fluorescence labeled with different antibodies, as well as the overlap between fluorescence values. This overlap can cause false positives or false negatives in subsequent result interpretation. The more complex the staining protocol, the more pronounced this overlap between different fluorescence values ​​becomes. Therefore, antibody combinations must fully consider this situation to ensure the accuracy of the results. After repeated iterations of antibody combinations, we finally determined the current staining protocol, as shown in Table 2.

[0183] Identification of peripheral blood immune cell subsets and chimerism after transplantation:

[0184] (1) Isolation and purification of peripheral blood mononuclear cells (PBMCs)

[0185] ① Pour 15 mL of whole blood into a 50 mL centrifuge tube, and at the same time add 15 mL of PBS to the centrifuge tube and mix thoroughly to dilute the whole blood;

[0186] ② Add 15 mL of lymphocyte separation solution to another 50 mL centrifuge tube, and slowly add the diluted whole blood to the top layer of the lymphocyte separation solution using a Pasteur tube;

[0187] ③ PBMCs were separated using a horizontal centrifuge and a brakeless density gradient centrifugation method. Centrifugation conditions: 800 g, room temperature, 25 min.

[0188] ④ After centrifugation, carefully aspirate the middle white film layer into a 15 mL centrifuge tube using a 5 mL Pasteur tube, add PBS to 15 mL, incubate at 450 g, 4 ℃, for 6 min, and wash twice with PBS.

[0189] ⑤ Resuspend the cell pellet in PBS and take 1~5×10⁻⁶ cells. 5Cells were collected and the cell suspension was controlled at 15-20 μL, then transferred to flow cytometry tubes for subsequent flow cytometry staining.

[0190] (2) Quantitative identification of chimeras and immune cells by surface staining using flow cytometry:

[0191] ① When extracting PBMCs by centrifugation, the antibody mixture should be prepared simultaneously according to the antibody information in Table 2. HLA-specific antibodies should be selected based on the HLA typing report and after the standardized verification in Experiment 1 above. The prepared antibody mixture should be placed in a 4 ℃ refrigerator for later use.

[0192] ② Staining: Add the pre-prepared antibody mixture (surface antibody) to the cell suspension, and add Zombie NIR live / dead dye to eliminate the influence of dead cells. Shake well and incubate at 4 ℃ in the dark for 30 min.

[0193] ③ Wash cells with PBS, 450g, 4 ℃, 6 min;

[0194] ④ Discard the supernatant and perform intracellular antibody staining;

[0195] ⑤ Mix 1 part of fixation / permeabilization concentrate with 3 parts of fixation / permeabilization diluent to prepare a fresh fixation / permeabilization working solution;

[0196] ⑥ Mix 1 part of 10× concentrate with 9 parts of distilled water to prepare 1× working solution for membrane breaking;

[0197] ⑦ Fixation: Add 1 mL of the prepared fixation / membrane rupture working solution to the flow cytometer and vortex thoroughly. Incubate at 4 °C in the dark for 30-60 min.

[0198] ⑧ Add 2 mL of 1× membrane rupture buffer, centrifuge at 450 g for 8 min at room temperature, and discard the supernatant (repeat once);

[0199] ⑨ Add the above intracellular staining antibody mixture and incubate at room temperature in the dark for 30 min;

[0200] ⑩ Add 2 mL of 1× membrane rupture solution to each tube, centrifuge at 500 g for 8 min at room temperature, and discard the supernatant;

[0201] ⑪ On-machine testing.

[0202] Table 2 Antibody Information

[0203]

[0204] Example 3: Establishment of a high-dimensional flow cytometry scheme for multi-parameter detection in postoperative peripheral blood.

[0205] Based on validated HLA-specific antibodies, we established a high-dimensional flow cytometry protocol for multi-parameter detection of peripheral blood after surgery, used for chimerism quantification and immunophenotypic analysis. The specific method is as follows:

[0206] 1. Collect peripheral blood from patients after surgery and separate peripheral blood mononuclear cells (PBMCs) using density gradient centrifugation.

[0207] 2. Prepare a multicolor antibody mixture containing: 1) surface markers (CD3 / CD14 / CD33 / CD19 / CD56 / CD4 / CD8 / CCR7 / CD45RA / HLA-ABC / HLA specific antibodies) and live cell dyes (Zombie NIR); 2) intracellular markers (Ki67 / Granzyme B) specific antibodies.

[0208] 3. After completing the staining process according to the standardized procedure, data were collected using a Cytek flow cytometer and analyzed using FlowJo.

[0209] Detection of GVHD and non-GVHD patients

[0210] The method of this invention was used to dynamically monitor the CD3, CD4, and CD8-positive T-cell chimerism in peripheral blood of patients with post-transplant GVHD. The experimental data came from a clinical case of GVHD after liver transplantation. This patient developed a rash and fever 20 days post-transplantation, underwent a skin biopsy on day 21, and was diagnosed with GVHD on day 24. Figure 6 It was observed that on postoperative day 21, the percentages of peripheral blood CD3, CD4, and CD8 T cell chimeras increased from 1.14%, 1.53%, and 1.45% on postoperative day 18 to 20.1%, 3.23%, and 39.4%, respectively, and further increased to 30.7%, 6.12%, and 67.6% on postoperative day 24.

[0211] The experimental method of this invention was used to detect the dynamic changes of donor-derived chimeric CD4 and CD8 in two patients with GVHD after liver transplantation. Figure 7Observations revealed the following: Case 1 developed a rash and fever 20 days post-surgery, underwent a skin biopsy on day 21, and was diagnosed with GVHD on day 24. Before GVHD, the proportion of donor-derived CD4 T cells was higher than that of donor-derived CD8 T cells; however, after GVHD occurred (day 21 and thereafter), donor-derived T cells became predominantly CD8 T cells. Case 2 developed a fever 20 days post-surgery, developed a rash on day 23, underwent a skin biopsy, and was diagnosed with GVHD on day 27. Again, before GVHD, the proportion of donor-derived CD4 T cells was higher than that of donor-derived CD8 T cells; however, after GVHD occurred (day 20 and thereafter), donor-derived T cells became predominantly CD8 T cells.

[0212] This invention was used to dynamically monitor the expression levels of total CD3 T cells and Ki67 protein (a marker of proliferation of donor and recipient CD4-positive and CD8-positive T cells) in the peripheral blood of patients with post-transplant GVHD. The experimental data came from a clinical case of GVHD following liver transplantation. This patient developed rash and fever 20 days post-transplantation, underwent a skin biopsy on day 21, and was diagnosed with GVHD on day 24. Figure 8 It was observed that: (A) On postoperative day 21, overall CD3 T cell Ki67 expression increased from 5.76% on postoperative day 18 to 24.6%, and then increased to 30.5% on postoperative day 24; (B) On postoperative day 21, donor CD3 T cell Ki67 expression increased from 16.7% on postoperative day 18 to 95.0%, and then decreased to 83.5% on postoperative day 24; (C) On postoperative day 21, recipient CD3 T cell Ki67 expression increased from 5.75% on postoperative day 18 to 6.87%, and then decreased to 5.16% on postoperative day 24; (D) On postoperative day 21, donor CD4 T cell Ki67 expression increased from 0% on postoperative day 18 to 92.3%, and then decreased to 62.5% on postoperative day 24; (E) On postoperative day 21, recipient CD4 T cell Ki67 expression decreased from 3.3% on postoperative day 18 to 3.08%, and then decreased to 2.10% on postoperative day 24; (F) On postoperative day 21, donor CD8 Ki67 expression on T cells increased from 16.7% to 95.6% on postoperative day 18; (G) Ki67 expression on receptor CD8 T cells increased from 7.19% to 9.39% on postoperative day 18 and to 12.9% on postoperative day 24.

[0213] The method of this invention was used to dynamically monitor the expression level of Ki67 protein, a proliferation marker of TEM cells derived from peripheral blood donors, in patients with post-transplant GVHD. The experimental data came from a clinical case of GVHD following liver transplantation. This patient developed rash and fever 20 days post-transplantation, underwent a skin biopsy on day 21, and was diagnosed with GVHD on day 24. Figure 9 The experimental results showed that: (A) Ki67 expression in donor CD3+ TEM cells increased from 16.7% on day 18 to 95.9% on day 21 post-surgery, and decreased to 87.9% on day 24 post-surgery; (B) Ki67 expression in donor CD4+ TEM cells increased from 0% on day 18 to 100% on day 21 post-surgery, and decreased to 75% on day 24 post-surgery; (C) Ki67 expression in donor CD8+ TEM cells increased from 33.3% on day 18 to 96.0% on day 21 post-surgery, and decreased to 88.9% on day 24 post-surgery.

[0214] This invention was used to dynamically monitor the expression levels of granzyme B protein, a cytotoxic marker of total CD3 T cells and donor / recipient CD4-positive and CD8-positive T cells, in the peripheral blood of patients with post-transplant GVHD. The experimental data came from a clinical case of GVHD following liver transplantation. This patient developed rash and fever 20 days post-transplantation, underwent a skin biopsy on day 23, and was diagnosed with GVHD on day 26. Figure 10 The experimental results showed that: (A) the overall expression of GranB in CD3 T cells increased in GVHD after surgery; (B) the proportion of donor CD3 T cells expressing GranB remained above 70% after surgery; (C) the proportion of recipient CD3 T cells expressing GranB continued to decrease after surgery; (D) although the proportion of donor CD4 T cells expressing GranB increased, the increase was limited; (E) the proportion of recipient CD4 T cells expressing GranB continued to decrease; (F) the proportion of donor CD8 T cells expressing GranB remained above 70%, and was significantly higher than that of recipient CD8 T cells at the onset of GVHD (G).

[0215] The method of this invention was used to dynamically monitor the expression level of GranB protein, a TEM cytotoxic marker derived from donor peripheral blood, in patients with post-transplant GVHD. The experimental data came from a clinical case of GVHD following liver transplantation. This patient developed rash and fever 20 days post-transplantation, underwent a skin biopsy on day 21, and was diagnosed with GVHD on day 24. Figure 11The experimental results showed that: (A) On day 21 post-surgery, the Gran B expression in donor CD3+ TEM cells increased from 66.7% on day 18 post-surgery to 91.7%, and decreased to 90.9% on day 24 post-surgery; (B) On day 21 post-surgery, the Gran B expression in donor CD4+ TEM cells increased from 0 on day 18 post-surgery to 9.09%, and decreased to 8.33% on day 24 post-surgery; (C) On day 21 post-surgery, the Gran B expression in donor CD8+ TEM cells remained above 90% from day 18 post-surgery onwards.

[0216] The above experimental results show that, in terms of the proportion of TEM expression and the expression of Ki67 and GranB in chimeric, donor-recipient CD3, CD4 and CD8 T cells, the expression of Ki67 and GranB in chimeric and donor-derived CD8 cells can diagnose GVHD.

[0217] The method of this invention was used to improve peripheral blood supply and total CD3 T cells of recipient-derived cells in GVHD patients after transplantation. Figure 12 A and B), CD4 ( Figure 12 C and D) and CD8-positive T cells (C and D) and CD8-positive T cells Figure 12 Dynamic changes in naive (CD45RA+CCR7+), TCM (CD45RA-CCR7+), TEM (CD45RA-CCR7-), and TEMRA (CD45RA+CCR7-) subgroups E and F were monitored. This experimental data comes from a case of GVHD following a clinical liver transplant. This patient developed a rash and fever 20 days post-transplantation, underwent a skin biopsy on day 21, and received a diagnosis of GVHD on day 24. Figure 12 The experimental results showed that during GVHD, the donor-derived CD3 total T cells, CD4 and CD8 positive T cell subsets were mainly TEM, while the donor-derived CD3 total T cells and CD8 TEM remained above 75%.

[0218] Validation of diagnostic efficacy of immune markers

[0219] Representative flow cytometry images of the proportion of donor-derived T cells (TEM 45RA-CCR7-) in peripheral blood from GVHD and non-GVHD patients are shown below. Figure 13 As shown, the proportion of CD3 T cells (A), CD8 T cells (B), and CD4 T cells (C) in GVHD patients was significantly higher than that in non-GVHD patients.

[0220] Representative flow cytometry images of the proportion of Ki67 expression in peripheral blood donor T cells from GVHD and non-GVHD patients are shown below. Figure 14As shown, the expression of Ki67 in CD3 T cells (A), CD3 TEM (B), CD8 T cells (C), CD8 TEM (D), CD4 T cells (E), and CD4 TEM (F) was significantly higher in GVHD patients than in non-GVHD patients.

[0221] Representative flow cytometry images of the proportion of Granzyme B expression in peripheral blood donor T cells from GVHD and non-GVHD patients are shown below. Figure 15 As shown, the expression of Granzyme B in CD3 T cells (A), CD3 TEM (B), CD8 T cells (C), and CD8 TEM (D) was significantly higher in GVHD patients than in non-GVHD patients.

[0222] Eight patients with gastrointestinal vascular disease (GVHD) after clinical liver transplantation were selected. A frequency-matched method was used to select control patients (non-GVHD group) from the same year as the GVHD patients, with a ratio of 1:4. Peripheral blood samples from the control group within 60 days post-transplantation were analyzed using the method of this invention. The efficacy of donor-derived CD3 TEM cell percentage, CD4 TEM cell percentage, CD8 TEM cell percentage, CD3 T cell Ki67 positivity rate, CD4 T cell Ki67 positivity rate, CD8 T cell Ki67 positivity rate, CD8 TEM cell Ki67 positivity rate, CD3 T cell GranB positivity rate, CD3 TEM cell GranB positivity rate, CD8 T cell GranB positivity rate, and CD8 TEM cell GranB positivity rate in distinguishing between GVHD and non-GVHD patients was verified. The experimental results are as follows: Figure 16 As shown in Table 2, the specific data is as follows.

[0223] Table 2. Cut-off value, sensitivity, specificity, 95% confidence interval, Youden index, area under the curve, and p-value of ROC curves for immune indicators that can be used to diagnose GVHD.

[0224]

[0225]

[0226] In summary, based on cut-off values ​​and clinical experience, the proportions of total CD3 T cells, CD4 T cells, and CD8 T cells in donors, as well as the effector memory T cell ratios (CD3+CCR7-CD45RA->60%; CD8+CCR7-CD45RA->70%; CD4+CCR7-CD45RA->50%), Ki67 positivity rates (CD3+Ki67+>45%; CD8+Ki67+>55%; CD4+Ki67+>20%; CD3+CCR7-CD45RA-KI67+>50%; CD8+CCR7-CD45RA-KI67+>60%; CD4+CCR7-CD45RA-KI67+>15%), and Granzyme B positivity rates (CD3+Gran B+>45%; CD8+Gran B+>70%; CD3+CCR7-CD45RA-Gran B+>15%), are considered to be positive for these factors. B+>77%; CD8+CCR7-CD45RA-Gran B+>85%) can diagnose GVHD.

[0227] Example 3: Establishment of a diagnostic method for GVHD in the absence of HLA-specific antibodies that can be used to distinguish between donor and recipient immune cell origins.

[0228] This invention further analyzes that when there are no available HLA-specific antibodies to distinguish between donor and recipient immune cells, i.e., when it is impossible to diagnose GVHD after liver transplantation by detecting chimerism, GVHD can be diagnosed by T cell TEM expression, Ki67 positivity rate, and GranB positivity rate.

[0229] The method of this invention was used to monitor the dynamic changes in Ki67 expression in total CD3 T cells, CD4 and CD8 T cells in the peripheral blood of patients with post-transplant GVHD. The experimental data came from a clinical case of GVHD after liver transplantation. This patient developed rash and fever 20 days post-transplantation, underwent a skin biopsy on day 23, and was diagnosed with GVHD on day 26. Figure 17 The experimental results showed that: (A) the overall expression of Ki67 in CD3 T cells increased from 3.41% on day 20 to 91% on day 23 after surgery; (B) the proportion of CD4 T cells expressing Ki67 increased from 4.40% on day 20 to 77.8% on day 23 after surgery; and (C) the proportion of CD8 T cells expressing Ki67 increased from 3.01% on day 20 to 96.2% on day 23 after surgery.

[0230] The method of this invention was used to monitor the dynamic changes in Gran B expression in peripheral blood CD3 T cells, CD4 and CD8 T cells of patients with post-transplant GVHD. The experimental data came from a clinical case of GVHD after liver transplantation. This patient developed rash and fever 20 days post-transplantation, underwent a skin biopsy on day 23, and was diagnosed with GVHD on day 26. Figure 18 The experimental results showed that: (A) the overall expression rate of Gran B in CD3 T cells continued to increase after surgery; (B) the expression rate of Gran B in CD4 T cells did not change significantly after surgery; and (C) the expression rate of Gran B in CD8 T cells continued to increase after surgery.

[0231] The method of this invention was used to monitor the dynamic changes of peripheral blood CD3 T cells, CD4 and CD8 T cell subsets Naive (CD45RA+CCR7+), TCM (CD45RA-CCR7+), TEM (CD45RA-CCR7-), and TEMRA (CD45RA+CCR7-) in patients with post-transplant GVHD. The experimental data came from a clinical case of GVHD after liver transplantation. This patient developed rash and fever 20 days post-transplantation, underwent a skin biopsy on day 23, and was diagnosed with GVHD on day 26. Figure 19 The experimental results show that in the early stages of GVHD, CD3, CD4, and CD8 T cell subsets gradually develop into cells dominated by TEM.

[0232] The method of this invention was used to monitor the dynamic changes in Ki67 expression in peripheral blood CD3 T cells, CD4 and CD8 T cells after liver transplantation in patients with post-transplant GVHD. The experimental data came from a clinical case of GVHD after liver transplantation. This patient developed rash and fever 20 days post-transplantation, underwent a skin biopsy on day 21, and was diagnosed with GVHD on day 24. Figure 20 It can be observed that in the early stage of GVHD, the expression of Ki67 in CD3+ TEM cells, CD8+ TEM cells, and CD4+ TEM cells is significantly increased.

[0233] The method of this invention was used to monitor the dynamic changes in Gran B expression in peripheral blood TEM cells of patients with post-transplant GVHD. The experimental data came from a clinical case of GVHD after liver transplantation. This patient developed rash and fever 20 days post-transplantation, underwent a skin biopsy on day 23, and was diagnosed with GVHD on day 26. Figure 21 The experimental results showed that: (A) the overall expression rate of Gran B in CD3 TEM cells continued to increase after surgery; (B) the expression rate of Gran B in CD4 TEM cells did not change significantly after surgery; and (C) the expression rate of Gran B in CD8 TEM cells continued to increase after surgery.

[0234] Validation of diagnostic efficacy of immune markers

[0235] Representative flow cytometry images of Ki67 expression in peripheral blood T cells from GVHD and non-GVHD patients are shown below. Figure 22 As shown, the expression of Ki67 in CD3, CD8, and CD4 T cells was significantly higher in GVHD patients than in non-GVHD patients (AC); the expression of Ki67 in CD3, CD8, and CD4 TEM cells was significantly higher in GVHD patients than in non-GVHD patients (DF).

[0236] Representative flow cytometry images of Granzyme B expression in peripheral blood T cells from GVHD and non-GVHD patients are shown below. Figure 23 As shown, the expression of CD3 and CD8 T cell Granzyme B in GVHD patients was significantly higher than that in non-GVHD patients (AB); the expression of CD3 and CD8 TEM Granzyme B in GVHD patients was significantly higher than that in non-GVHD patients (CD).

[0237] Representative flow cytometry images of the peripheral blood T cell percentages in GVHD and non-GVHD patients are shown below. Figure 24 As shown, the proportion of TEM in CD3, CD4, and CD8 T cells was significantly higher in GVHD patients than in non-GVHD patients.

[0238] Eight patients with gastrointestinal hypertension (GVHD) after clinical liver transplantation were selected. A frequency-matched method was used to select control patients (GVHD patients from the same year as the GVHD patients) at a ratio of 1:4. Peripheral blood samples from the control group within 60 days post-transplantation were analyzed using the method of this invention. The efficacy of immune markers in distinguishing between GVHD and non-GVHD patients was verified. The experimental results are as follows: Figure 25 As shown in Table 3, the specific data is as follows.

[0239] Table 3. Cut-off value, sensitivity, specificity, 95% confidence interval, Youden index, area under the curve, and p-value of ROC curves for immune indicators that can be used to diagnose GVHD.

[0240]

[0241] In summary, when donor-recipient HLA typing results do not yield available HLA-specific antibodies or effective antibodies to distinguish donor-recipient immune cells, i.e., when chimerism cannot be detected for post-liver transplant GVHD diagnosis, based on cut-off values ​​and clinical experience, the Ki67 positivity rate of T cells (CD3+Ki67+>20%; CD3+CCR7-CD45RA-KI67+>50%; CD8+KI67+>30%; CD8+CCR7-CD45RA-KI67+>50%; CD4+KI67+>10%; CD4+CCR7-CD45RA-KI67+>10%), and T cell Granzyme... The positive rate of B (CD3+GranzB+>50%; CD8+GranzB+>70%; CD3+CCR7-CD45RA-GranzB+>65%; CD8+CCR7-CD45RA-GranzB+>75%) and the proportion of TEM cells (CD3+CCR7-CD45RA->40%; CD8+CCR7-CD45RA->45%; CD4+CCR7-CD45RA->20%) can diagnose GVHD.

[0242] Example 4: An example where STR is not well-suited for detecting GVHD chimerism in liver transplant recipients.

[0243] A 52-year-old male presented with fever and rash 23 days post-surgery. Bacterial, viral, fungal, and tuberculosis tests were all negative, and liver function was normal. GVHD was clinically suspected. 15 ml of peripheral blood was drawn from the patient, and one pre-operative peripheral blood sample each from the donor and recipient were obtained from the biobank. Post-operatively, 10 ml of the blood was sent for STR-PCR, and 5 ml was used to isolate PBMCs for HLA flow cytometry analysis.

[0244] STR-PCR results ( Figure 26 The results showed that the donor cell DNA chimerism rate was 0, which does not support the diagnosis of GVHD.

[0245] Application of HLA flow cytometry analysis:

[0246] Based on the preoperative HLA typing information of the donor and recipient, HLA-BW6 was selected as the donor-specific HLA antibody and HLA-A2 as the recipient-specific HLA antibody. Preoperative sample validation confirmed that these antibodies can be used to detect donor-recipient chimeras.

[0247] HLA flow cytometry analysis ( Figure 27The study found that in the patient's peripheral blood T cells, 91.5% were donor-derived and 8.01% were recipient-derived (A). In lymphocytes, 42.1% were donor-derived and 56.2% were recipient-derived (B). The proportion of recipient effector memory T cells was 60.1% (C). Among donor T cells, TEM cells accounted for 99.1% (D), the KI67 positivity rate of donor T cells reached 96.3% (E), and the GranzB positivity rate reached 78.5% (F), exhibiting a significant GVHD pathological immunophenotype, supporting the diagnosis of GVHD.

[0248] To analyze the reasons for the failure of STR-PCR in detecting chimeras, we reviewed the patient's complete blood count and found that the patient's CD3 T cell count was severely reduced, while the peripheral blood contained a large number of receptor granulocytes. We concluded that the reduction in target cells was the main reason for the test failure.

[0249] We combined multiple peripheral blood PBMC samples from this patient after the onset of illness, accumulating the total cell count to 1.0 × 10⁻⁶. 6 Subsequently, T cells were pre-acquired through flow cytometry sorting and then subjected to STR-PCR detection again. However, the cell count still could not reach 10-1. 5 Therefore, the amount of DNA obtainable will be lower than the monitoring threshold. Later, the method was changed to sorting lymphocytes (3.0 × 10⁻⁶). 5 Afterwards, DNA was extracted according to the instructions of the micro-DNA extraction kit, and STR-PCR chimerism detection was performed again. The results showed that the donor cell DNA chimerism rate was 54.3%. Figure 28 The lymphocyte chimerism rate detected by flow cytometry was 58.7%. Figure 29 ), supports GVHD diagnosis.

[0250] Example 5: Methods, systems, and equipment for diagnosing GVHD

[0251] Figure 30 This is a schematic flowchart of a method for diagnosing GVHD provided in an embodiment of this application. Specifically, the method includes the following steps:

[0252] 101: Obtain T cell-related data of the sample to be tested, wherein the T cell-related data includes one or more of the following: Ki67 positive rate data, Granzyme B positive rate data, and TEM cell rate data.

[0253] 102: Based on the T cell-related data of the sample to be tested, classification and prediction are performed to obtain the classification results of the risk of GVHD.

[0254] 103: If the proportion of Ki67 positivity in the T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Ki67 positivity in the T cells is lower than the threshold, the risk of GVHD is low.

[0255] If the proportion of Granzyme B positivity in T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Granzyme B positivity in T cells is lower than the threshold, the risk of GVHD is low.

[0256] If the proportion of TEM cells in the T cells is higher than the threshold, the risk of GVHD is high; if the proportion of TEM cells in the T cells is lower than the threshold, the risk of GVHD is low.

[0257] In some implementations, the T cells include CD3+ T cells.

[0258] In some implementations, the CD3+ T cells are total T cells, which include CD4+ T cells and CD8+ T cells.

[0259] In some embodiments, the CD3+ T cells include CD3+ TEM cells. CD3+ TEM cells are CD3+ effector memory T cells.

[0260] In some implementations, the CD4+ T cells include CD4+ TEM cells.

[0261] In some implementations, the CD8+ T cells include CD8+ TEM cells.

[0262] In some implementations, the method includes acquiring donor-derived T cell-related data for the sample to be tested, wherein the donor-derived T cell-related data includes one or more of the following: Ki67 positivity rate data, Granzyme B positivity rate data, and TEM cell proportion data in the donor-derived T cells;

[0263] Based on the donor-derived T cell data of the test sample, classification and prediction are performed to obtain classification results indicating the high or low risk of GVHD.

[0264] If the proportion of Ki67 positivity in donor-derived T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Ki67 positivity in donor-derived T cells is lower than the threshold, the risk of GVHD is low.

[0265] If the proportion of Granzyme B positivity in donor-derived T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Granzyme B positivity in donor-derived T cells is lower than the threshold, the risk of GVHD is low.

[0266] If the proportion of TEM cells in the donor-derived T cells is higher than the threshold, the risk of GVHD is high; if the proportion of TEM cells in the donor-derived T cells is lower than the threshold, the risk of GVHD is low.

[0267] In some implementations, the donor T cells for the test sample are determined using HLA data.

[0268] Figure 31 This is a schematic flowchart of a method for diagnosing GVHD provided in an embodiment of this application. Specifically, the method includes the following steps:

[0269] 201: Obtain the HLA data of the sample to be tested, and determine whether there is a usable HLA antibody that can distinguish the donor and recipient cell origins. If there is, proceed to steps 202-204; otherwise, proceed to steps 205-207.

[0270] 202: Obtain donor-derived T cell-related data for the sample to be tested, wherein the donor-derived T cell-related data includes one or more of the following: Ki67 positivity rate data, Granzyme B positivity rate data, and TEM cell proportion data in the donor-derived T cells;

[0271] 203: Based on the donor-derived T cell-related data of the test sample, classification and prediction are performed to obtain the classification results of the risk of GVHD.

[0272] 204: If the Ki67 positivity rate in the donor-derived T cells is higher than the threshold, the risk of GVHD is high; if the Ki67 positivity rate in the donor-derived T cells is lower than the threshold, the risk of GVHD is low.

[0273] If the proportion of Granzyme B positivity in donor-derived T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Granzyme B positivity in donor-derived T cells is lower than the threshold, the risk of GVHD is low.

[0274] If the proportion of TEM cells in the donor-derived T cells is higher than the threshold, the risk of GVHD is high; if the proportion of TEM cells in the donor-derived T cells is lower than the threshold, the risk of GVHD is low.

[0275] 205: Obtain T cell-related data of the sample to be tested, wherein the T cell-related data includes one or more of the following: Ki67 positive rate data, Granzyme B positive rate data, and TEM cell rate data;

[0276] 206: Based on the donor-derived T cell-related data of the test sample, classification and prediction are performed to obtain the classification results of the risk of GVHD.

[0277] 207: If the proportion of Ki67 positivity in the T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Ki67 positivity in the T cells is lower than the threshold, the risk of GVHD is low.

[0278] If the proportion of Granzyme B positivity in T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Granzyme B positivity in T cells is lower than the threshold, the risk of GVHD is low.

[0279] If the proportion of TEM cells in the T cells is higher than the threshold, the risk of GVHD is high; if the proportion of TEM cells in the T cells is lower than the threshold, the risk of GVHD is low.

[0280] In steps 202-203, when performing classification prediction based on the Ki67 positivity rate data of donor-sourced T cells, the T cells refer to CD3+ T cells, wherein CD3+ T cells may include CD4+ T cells and CD8+ T cells, CD3+ T cells include CD3+ TEM cells, CD4+ T cells include CD4+ TEM cells, and CD8+ T cells include CD8+ TEM cells.

[0281] In steps 202-203, when performing classification prediction based on the proportion of TEM cells in the donor-sourced T cells, the T cells refer to CD3+ T cells, wherein CD3+ T cells may include CD4+ T cells and CD8+ T cells, CD3+ T cells include CD3+ TEM cells, CD4+ T cells include CD4+ TEM cells, and CD8+ T cells include CD8+ TEM cells.

[0282] In steps 202-203, when performing classification prediction based on the Granzyme B positivity rate data of the donor-sourced T cells, the T cells refer to CD3+ T cells, wherein CD3+ T cells may include CD8+ T cells, CD3+ T cells may include CD3+ TEM cells, and CD8+ T cells may include CD8+ TEM cells.

[0283] In steps 204-205, the T cells include CD3+ T cells, wherein CD3+ T cells may include CD4+ T cells and CD8+ T cells, CD3+ T cells may include CD3+ TEM cells, CD4+ T cells may include CD4+ TEM cells, and CD8+ T cells may include CD8+ TEM cells.

[0284] In this invention, the Ki67 positivity rate data and Granzyme B positivity rate data in T cells refer to the proportion of Ki67-positive cells or Granzyme B-positive cells in a specific T cell population. Taking the Ki67 positivity rate data in CD3+ T cells as an example, it refers to the proportion of Ki67-positive cells in CD3+ T cells, and the Ki67 positivity rate data in CD3+ TEM cells refers to the proportion of Ki67-positive cells in CD3+ TEM cells.

[0285] In this invention, the TEM cell proportion data refers to the proportion of TEM cells to T cells. The TEM cell proportion data includes the proportion of CD3+ TEM cells to T cells, the proportion of CD4+ TEM cells to T cells, and the proportion of CD8+ TEM cells to T cells.

[0286] In some implementations, determining whether there are available HLA antibodies that distinguish between donor and recipient cell origins includes the following steps: based on preoperative HLA typing results for organ transplantation, screening for specific HLA sites that show significant differences between donor and recipient, and then determining the available HLA antibodies.

[0287] In some implementations, determining whether there are available HLA antibodies that can differentiate between donor and recipient cell sources also includes testing the HLA antibody differentiation efficacy of the identified available HLA antibodies.

[0288] Figure 32 This is a schematic diagram of a system for diagnosing GVHD provided in an embodiment of this application. The system includes:

[0289] 301 Acquisition Module: Acquires T cell-related data of the sample to be tested, including one or more of the following: Ki67 positive rate data, Granzyme B positive rate data, and TEM cell rate data.

[0290] 302 Prediction Module: Based on the T cell-related data of the sample to be tested, it performs classification prediction to obtain the classification result of the risk of GVHD.

[0291] 303 Output Module: Used to output classification results;

[0292] If the proportion of Ki67 positivity in T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Ki67 positivity in T cells is lower than the threshold, the risk of GVHD is low.

[0293] If the proportion of Granzyme B positivity in T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Granzyme B positivity in T cells is lower than the threshold, the risk of GVHD is low.

[0294] If the proportion of TEM cells in the T cells is higher than the threshold, the risk of GVHD is high; if the proportion of TEM cells in the T cells is lower than the threshold, the risk of GVHD is low.

[0295] In some implementations, the acquisition module can acquire donor-derived T cell-related data for the sample to be tested, including one or more of the following: Ki67 positivity rate data, Granzyme B positivity rate data, and TEM cell proportion data in the donor-derived T cells.

[0296] Figure 33 This is a schematic diagram of a device for diagnosing GVHD according to an embodiment of this application. The device includes a first computing device, which includes a memory and a processor. The memory is used to store program instructions. The processor is used to invoke the program instructions, and when the program instructions are executed, they implement the steps of the method for diagnosing GVHD according to the fourth aspect of this invention.

[0297] In some implementations, the device further includes one or more of the following: a T-cell related data detection device, a user interface device, and a user interface device.

[0298] In some implementations, the T-cell related data detection device, the user interface device, and the user interface device are each communicatively coupled to the first computing device.

[0299] In this invention, the communication coupling refers to the ability of coupled components to exchange data signals with each other, such as electrical signals via a conductive medium, electromagnetic signals via air, and optical signals via an optical waveguide.

[0300] In some implementations, the T-cell-related data detection device includes, but is not limited to, a flow cytometer.

[0301] In some embodiments, the flow cytometer is a full-spectrum flow cytometer and / or a conventional multifluorescence flow cytometer.

[0302] In some implementations, the user interface device allows users to input data related to T cells in the sample to be tested.

[0303] In some implementations, the user interface device supports receiving results from T-cell related data detection devices.

[0304] In some implementations, the user interface device displays the results of the received T-cell related data detection device to the user.

[0305] In some implementations, the user interface device displays the prediction results to the user.

[0306] In some implementations, the user interface device includes, but is not limited to, a local computing device (e.g., a desktop computer, tablet, smartphone, etc.) or a remote computing device (e.g., a cloud computing device).

[0307] In some implementations, the user interface device is communicatively coupled to the first computing device. The user inputs relevant data of the T cells of the sample to be tested through the user interface device, which is then transmitted to the first computing device. After processing by the first computing device, the prediction results are displayed by the user interface device.

[0308] In some implementations, the T-cell related data detection device is communicatively coupled to a user interface device, and the user interface device is communicatively coupled to a first computing device. The T-cell related data detection device detects T-cell related data in the sample to be tested. The detection results are received by the user interface device and then transmitted to the first computing device. After being processed by the first computing device, the prediction results are displayed by the user interface device.

[0309] The above description of the embodiments is only for understanding the method and core ideas of the present invention. It should be noted that those skilled in the art can make various improvements and modifications to the present invention without departing from the principles of the invention, and these improvements and modifications will also fall within the protection scope of the claims of the present invention.

Claims

1. The application of a substance that detects Ki67 in T cells of a test sample in the preparation of a product for diagnosing GVHD after liver transplantation, characterized in that, The T cells include one or more of CD3+ T cells, CD8+ T cells, and CD4+ T cells.

2. The application according to claim 1, characterized in that, The CD3+ T cells include CD3+ TEM cells, the CD8+ T cells include CD8+ TEM cells, and the CD4+ T cells include CD4+ TEM cells.

3. The application of substances that detect Ki67 and Granzyme B in T cells of the test sample in the preparation of products for diagnosing GVHD after liver transplantation, characterized in that, The T cells include one or more of CD3+ T cells, CD8+ T cells, and CD4+ T cells.

4. The application according to claim 3, characterized in that, The CD3+ T cells include CD3+ TEM cells, the CD8+ T cells include CD8+ TEM cells, and the CD4+ T cells include CD4+ TEM cells.

5. The application of a substance that detects Granzyme B in T cells of a test sample in the preparation of a product for diagnosing GVHD after liver transplantation, characterized in that, The T cells include one or more types of CD3+ T cells and CD8+ T cells.

6. The application according to claim 5, characterized in that, The CD3+ T cells include CD3+ TEM cells, and the CD8+ T cells include CD8+ TEM cells.

7. The application of substances that detect Ki67 and HLA in T cells of the test sample in the preparation of products for diagnosing GVHD after liver transplantation, characterized in that, The T cells include one or more of CD3+ T cells, CD8+ T cells, and CD4+ T cells.

8. The application according to claim 7, characterized in that, The CD3+ T cells include CD3+ TEM cells, the CD8+ T cells include CD8+ TEM cells, and the CD4+ T cells include CD4+ TEM cells.

9. The application of substances that detect Ki67, Granzyme B, and HLA in T cells of the test sample in the preparation of products for diagnosing GVHD after liver transplantation, characterized in that, The T cells include one or more of CD3+ T cells, CD8+ T cells, and CD4+ T cells.

10. The application according to claim 9, characterized in that, The CD3+ T cells include CD3+ TEM cells, the CD8+ T cells include CD8+ TEM cells, and the CD4+ T cells include CD4+ TEM cells.

11. The application of substances that detect Granzyme B and HLA in T cells of test samples in the preparation of products for diagnosing GVHD after liver transplantation, characterized in that, The T cells include one or more types of CD3+ T cells and CD8+ T cells.

12. The application according to claim 11, characterized in that, The CD3+ T cells include CD3+ TEM cells, and the CD8+ T cells include CD8+ TEM cells.

13. The application according to any one of claims 1-12, characterized in that, The substances used to detect Ki67 and / or Granzyme B in T cells of the test sample include one or more of the reagents, kits, and detection devices used in flow cytometry.

14. The application according to claim 13, characterized in that, The reagents or kits used in the flow cytometry include Ki67 and / or Granzyme B antibodies.

15. The application according to claim 13, characterized in that, The reagents or kits used in the flow cytometry also include antibodies that identify T cell subsets of the sample to be tested.

16. The application according to claim 15, characterized in that, The antibodies that identify T cell subsets of the sample to be tested include one or more of the following: CD3 antibody, CD4 antibody, CD8 antibody, CCR7 antibody, and CD45RA antibody.

17. The application according to claim 13, characterized in that, The reagents or kits used in the flow cytometry also include one or more of the following: fluorescein, buffer, washing solution, lysis buffer, negative control, positive control, standard, quality control, and blank control.

18. The application according to any one of claims 7-12, characterized in that, The substances used to detect HLA in the sample include one or more of the reagents, kits, and detection equipment used in flow cytometry.

19. The application according to claim 18, characterized in that, The reagents or kits used in the flow cytometry include HLA antibodies.

20. The application according to claim 18, characterized in that, The reagents or kits used in the flow cytometry also include one or more of the following: fluorescein, buffer, washing solution, lysis buffer, negative control, positive control, standard, quality control, and blank control.

21. The application of a substance for detecting the proportion of TEM cells in T cells of a test sample in the preparation of a product for diagnosing GVHD after liver transplantation, characterized in that, The TEM cells in the T cells include one or more of the following: CD3+ TEM cells, CD4+ TEM cells, and CD8+ TEM cells.

22. The application according to claim 21, characterized in that, The substances used to detect the proportion of TEM cells in T cells of the sample to be tested include one or more of the reagents, kits, and detection equipment used in flow cytometry.

23. The application according to claim 22, characterized in that, The reagents or kits used in the flow cytometry include one or more of the following: CD3 antibody, CD4 antibody, CD8 antibody, CCR7 antibody, and CD45RA antibody.

24. The application according to claim 22, characterized in that, The reagents or kits used in the flow cytometry also include one or more of the following: fluorescein, buffer, washing solution, lysis buffer, negative control, positive control, standard, quality control, and blank control.

25. A method for diagnosing GVHD after liver transplantation, characterized in that, The method is performed by a computer and includes the following steps: Obtain T cell-related data from the sample to be tested, including one or more of the following: Ki67 positivity rate in T cells, Granzyme B positivity rate in T cells, and TEM cell proportion in T cells. Based on the T cell-related data of the sample to be tested, a classification prediction is performed to obtain a classification result indicating the risk of developing GVHD. If the proportion of Ki67 positivity in T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Ki67 positivity in T cells is lower than the threshold, the risk of GVHD is low. If the proportion of Granzyme B positivity in T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Granzyme B positivity in T cells is lower than the threshold, the risk of GVHD is low. If the proportion of TEM cells in the T cells is higher than the threshold, the risk of GVHD is high; if the proportion of TEM cells in the T cells is lower than the threshold, the risk of GVHD is low. The Ki67 positivity rate data in T cells is one or more of the following: Ki67 positivity rate data in CD3+ T cells, Ki67 positivity rate data in CD8+ T cells, and Ki67 positivity rate data in CD4+ T cells. The Granzyme B positivity rate data in T cells is one or more of the Granzyme B positivity rate data in CD3+ T cells and the Granzyme B positivity rate data in CD8+ T cells. The proportion of TEM cells in the T cells is one or more of the following: CD3+ TEM cell proportion, CD4+ TEM cell proportion, and CD8+ TEM cell proportion.

26. The method according to claim 25, characterized in that, The method includes acquiring donor-derived T cell-related data for the sample to be tested, wherein the donor-derived T cell-related data includes one or more of the following: Ki67 positivity rate data, Granzyme B positivity rate data, and TEM cell proportion data in the donor-derived T cells; Based on the donor-derived T cell data of the test sample, classification and prediction are performed to obtain classification results indicating the high or low risk of GVHD. If the proportion of Ki67 positivity in donor-derived T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Ki67 positivity in donor-derived T cells is lower than the threshold, the risk of GVHD is low. If the proportion of Granzyme B positivity in donor-derived T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Granzyme B positivity in donor-derived T cells is lower than the threshold, the risk of GVHD is low. If the proportion of TEM cells in the donor-derived T cells is higher than the threshold, the risk of GVHD is high; if the proportion of TEM cells in the donor-derived T cells is lower than the threshold, the risk of GVHD is low.

27. The method according to claim 26, characterized in that, The donor T cells for the test sample were determined using HLA data.

28. A system for diagnosing GVHD following liver transplantation, characterized in that, The system includes: Acquisition module: Acquires T cell-related data of the sample to be tested, including one or more of the following: Ki67 positive rate data, Granzyme B positive rate data, and TEM cell rate data. Prediction module: Based on the T cell-related data of the sample to be tested, it performs classification prediction to obtain the classification result of the risk of GVHD. Output module: Used to output classification results; If the proportion of Ki67 positivity in T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Ki67 positivity in T cells is lower than the threshold, the risk of GVHD is low. If the proportion of Granzyme B positivity in T cells is higher than the threshold, the risk of GVHD is high; if the proportion of Granzyme B positivity in T cells is lower than the threshold, the risk of GVHD is low. If the proportion of TEM cells in the T cells is higher than the threshold, the risk of GVHD is high; if the proportion of TEM cells in the T cells is lower than the threshold, the risk of GVHD is low. The Ki67 positivity rate data in T cells is one or more of the following: Ki67 positivity rate data in CD3+ T cells, Ki67 positivity rate data in CD8+ T cells, and Ki67 positivity rate data in CD4+ T cells. The Granzyme B positivity rate data in T cells is one or more of the Granzyme B positivity rate data in CD3+ T cells and the Granzyme B positivity rate data in CD8+ T cells. The proportion of TEM cells in the T cells is one or more of the following: CD3+ TEM cell proportion, CD4+ TEM cell proportion, and CD8+ TEM cell proportion.

29. A device for diagnosing GVHD after liver transplantation, characterized in that, The device includes a first computing device, which includes a memory and a processor; the memory is used to store program instructions; the processor is used to invoke the program instructions, which, when executed, implement the steps of the method for diagnosing GVHD after liver transplantation as described in any one of claims 25-27.

30. The device according to claim 29, characterized in that, The device also includes one or more of the following: T-cell related data detection device, user interface device, and user interface device.

31. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method for diagnosing post-liver transplantation GVHD as described in any one of claims 25-27.

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