T cell subset and application thereof in diagnosis and treatment of chronic obstructive pulmonary disease

Abstract

The invention relates to the technical field of disease diagnosis markers, in particular to a T cell subset and application thereof in diagnosis and treatment of chronic obstructive pulmonary diseases. The flow phenotype of the T cell subgroup disclosed by the invention is CD45 + CD3 + MThhigh. The early-warning cell of the early-stage chronic obstructive pulmonary disease is found by describing a single cell transcriptome map of a patient with the early-stage chronic obstructive pulmonary disease, and the early-warning cell is a T cell subset (marked as MT-high T cell). The feasibility of the MT-high T cell as the novel diagnostic marker of the chronic obstructive pulmonary disease is verified by a peripheral blood flow type detection method of a patient with the chronic obstructive pulmonary disease. The invention provides a new technical support for clarifying an immunological mechanism of early occurrence of the chronic obstructive pulmonary disease, analyzing the heterogeneity reason of the chronic obstructive pulmonary disease and formulating a corresponding early diagnosis and intervention treatment strategy, and brings good social and economic benefits for prevention and control of the chronic obstructive pulmonary disease.

Description

Technical Field

[0001] The present invention relates to the technical field of disease diagnostic markers, and particularly to T cell subsets and their applications in the diagnosis and treatment of chronic obstructive pulmonary disease. Background Art

[0002] Chronic obstructive pulmonary disease (COPD), also known as chronic obstructive lung disease, is mainly clinically characterized by chronic respiratory symptoms and airflow limitation, and is a chronic respiratory disease that seriously endangers public health. The Global Burden of Disease (GBD) study shows that there are approximately 392 million COPD patients worldwide, and at least 3.3 million people die from COPD every year. COPD can be induced by a variety of risk factors including smoking, biomass fuels, environmental air pollution, and occupational pollutants, and thus exhibits high heterogeneity, manifested as the complexity of phenotypes and endotypes as well as the complexity of immunological mechanisms. Currently, the ratio of the forced expiratory volume in one second (FEV1) to the forced vital capacity (FVC) measured by a spirometer less than 0.7 is the gold standard for clinical diagnosis. However, the definition of chronic obstructive pulmonary disease based solely on the measurement standard of vital capacity has many defects, because early airway changes and emphysematous destruction cannot be effectively converted into measurable airflow limitation. Due to the lack of obvious respiratory symptoms in the early stage of the disease and the lack of biomarkers for evaluating early changes in lung health, the diagnosis of COPD is currently at a stage where pathological changes are irreversible. Therefore, there is an urgent need for a biomarker that can be used for the early diagnosis and treatment of COPD to adopt targeted preventive strategies to slow down or even stop the progression of COPD. Summary of the Invention

[0003] To solve the above problems, the present invention provides T cell subsets and their applications in the diagnosis and treatment of chronic obstructive pulmonary disease. The T cell subsets provided by the present invention are a novel type of T cell subsets, which can be used as novel diagnostic markers for COPD and have important clinical significance for the early diagnosis of the disease, prediction of treatment response, prognosis evaluation, and individualized treatment.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] The present invention provides a T cell subset, and the flow cytometry phenotype of the T cell subset is CD45 + CD3 + MT high .

[0006] The present invention provides an antibody composition, comprising: a membrane marker antibody composition and an intracellular marker antibody;

[0007] The membrane-labeled antibody composition includes: an anti-CD45 antibody and an anti-CD3 antibody;

[0008] The intracellular-labeled antibody includes an anti-MT antibody.

[0009] Preferably, the anti-MT antibody includes an anti-MT2A antibody.

[0010] Preferably, the antibodies in the antibody composition are fluorescently labeled antibodies;

[0011] The fluorescent labels of the anti-CD45 antibody, anti-CD3 antibody, and anti-MT antibody are AF700, PerCP, and PE, respectively.

[0012] The present invention provides the use of the antibody composition described in the above technical solution in one or more of the following:

[0013] 1) Preparation of a diagnostic product for chronic obstructive pulmonary disease; 2) Preparation of a product for evaluating the risk of suffering from chronic obstructive pulmonary disease; 3) Preparation of a product for evaluating the prognosis of chronic obstructive pulmonary disease.

[0014] The present invention provides a system for evaluating the risk of suffering from chronic obstructive pulmonary disease, including a detection module and an analysis module;

[0015] The detection module is used to detect the antigen expression level of a test sample by flow cytometry, including the antibody composition described in the above technical solution;

[0016] The analysis module is used to analyze the detection results of the detection module.

[0017] The present invention provides the use of the T cell subset described in the above technical solution in the preparation of a product for treating chronic obstructive pulmonary disease.

[0018] The present invention provides an antibody composition for sorting the T cell subset described in the above technical solution, including: an anti-CD45 antibody, an anti-CD3 antibody, and an anti-SLC30A1 antibody.

[0019] Preferably, the antibodies in the antibody composition are fluorescently labeled antibodies;

[0020] The fluorescent labels of the anti-CD45 antibody, anti-CD3 antibody, and anti-SLC30A1 antibody are AF700, PerCP, and PE, respectively.

[0021] The present invention provides the use of the antibody composition described in the above technical solution in sorting the T cell subset described in the above technical solution.

[0022] Beneficial effects:

[0023] The present invention provides a T cell subset, and the flow cytometry phenotype of the T cell subset is CD45 + CD3 + MT high . By depicting the single-cell transcriptome atlas of early chronic obstructive pulmonary disease (COPD) patients, the present invention discovers warning cells for early COPD, which are a type of T cell subset (denoted as MT-high T cells). The feasibility of MT-high T cells as a new diagnostic marker for COPD is verified by flow cytometry detection of the peripheral blood of COPD patients. The present invention provides new technical support for clarifying the immunological mechanism of early occurrence of COPD, analyzing the reasons for the heterogeneity of COPD, and formulating corresponding early diagnosis and intervention treatment strategies, bringing good social and economic benefits to the prevention and control of COPD. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments.

[0025] Figures 1 to 5 is the whole cell type atlas of 14 COPD patients depicted by single-cell transcriptome sequencing; among them Figure 1 is the figure of 26 annotated cell types; Figure 2 is the cell type atlas among different patients; Figure 3 is the gene mapping diagram of the expression of immune (PTPRC), epithelial (EPCAM), endothelial (CLDN5), and stromal (COL1A2) cell marker genes; Figure 4 is the expression of marker genes of different clustered cells, and the maximum scale is 25 μm; Figure 5 is the change in the cell proportion of each cell subset among patients in different groups;

[0026] Figures 6 to 8 is the UMAP result of T cells in the control group and COPD patients at different stages and the change results of the proportion of each subset among different groups; among them, Figure 6 is the annotated UMAP diagram of T cells; Figure 7 in A is the change result of the proportion of each T cell subset among different groups; Figure 7 in B is the spatial mapping change result of cells in clusters 5 and 12 among patients in different groups; Figure 8 is the spatial mapping change result of cells in clusters 5 and 12 among single patient samples;

[0027] Figures 9 to 11 is the volcano diagram of differential genes of each T cell subset and the GO enrichment result of differential genes in clusters 5 and 12; among them, Figure 9 is the volcano diagram of differential genes of each T cell subset; Figure 10 is the GO enrichment result of upregulated differential genes in clusters 5 and 12; Figure 11GO enrichment results of differentially expressed genes down-regulated in clusters 5 and 12;

[0028] Figures 12 to 14 Expression of metallothionein-related genes in public datasets and co-staining results of MT2A and T cells in paraffin sections of human lung tissues; among them, Figure 12 For metallothionein in normal human lung whole cells [1] Expression; Figure 13 For metallothionein in normal human thymus T cells [2] Expression; Figure 14 Immunofluorescence staining results of paraffin sections of normal human lung tissues, scale bar is 25μm;

[0029] Figures 15 to 17 Co-immunofluorescence staining results of MT2A and T cells and flow cytometry detection results in human peripheral blood PBMC smears; among them, Figure 15 Immunofluorescence staining results of normal human peripheral blood PBMC smear cells; Figure 16 and Figure 17 Flow cytometry staining results of peripheral blood PBMCs of patients in different groups;

[0030] Figures 18 to 21 Analysis results of cell communication intensity between T cell subsets and ligand-receptor pair interaction intensity; among them, Figure 18 Analysis results of signal intensity sent and received by T cell subsets; Figures 19 to 21 Analysis results of ligand-receptor pair interaction between T cell subsets;

[0031] Figure 22 Immunofluorescence staining results of MT-high T cells and CD8 + T cells in paraffin sections of control group lung tissues. Specific implementation mode

[0032] The present invention provides a T cell subset, and the flow cytometry phenotype of the T cell subset is CD45 + CD3 + MT high .

[0033] By depicting the single-cell transcriptome atlas of early chronic obstructive pulmonary disease (COPD) patients, the present invention has discovered a warning cell for early COPD, which is a subset of T cells (denoted as MT-high T cells). Single-cell sequencing results show that there is an imbalance in the subset of T cells in early COPD. As a novel subset of T cells that exerts immune regulation, the continuous decrease in the proportion of MT-high T cells with disease progression may lead to persistent irreversible inflammatory responses and small airway damage in COPD. MT-high T cells can be used as a novel diagnostic marker for COPD in peripheral blood. Additionally, by transfusing MT-high T cells, the function of MT-high T cells in regulating CD8 + T cells can be used to treat COPD, which has important clinical significance for the early diagnosis, prediction of treatment response, prognosis assessment, and individualized treatment of chronic obstructive pulmonary disease.

[0034] The present invention provides an antibody composition for detecting the subset of T cells described in the above technical solution, including: a membrane-labeled antibody composition and an intracellular-labeled antibody;

[0035] The membrane-labeled antibody composition includes: an anti-CD45 antibody and an anti-CD3 antibody;

[0036] The intracellular-labeled antibody includes an anti-MT antibody.

[0037] As an embodiment, the anti-MT antibody includes an anti-MT2A antibody.

[0038] As an embodiment, the antibodies in the antibody composition are fluorescently labeled antibodies;

[0039] The fluorescent labels of the anti-CD45 antibody, anti-CD3 antibody, and anti-MT antibody are AF700, PerCP, and PE, respectively.

[0040] The antibody composition provided by the present invention can detect the subset of T cells described in the above technical solution by flow cytometry, and thus can be used for the early diagnosis, prediction of treatment response, prognosis assessment, and individualized treatment of chronic obstructive pulmonary disease.

[0041] Based on the above advantages, the present invention provides the application of the antibody composition described in the above technical solution in one or more of the following:

[0042] 1) Preparing a diagnostic product for chronic obstructive pulmonary disease; 2) Preparing a product for assessing the risk of suffering from chronic obstructive pulmonary disease; 3) Preparing a product for assessing the prognosis of chronic obstructive pulmonary disease.

[0043] As an embodiment, the product includes a kit. As another embodiment, the kit is a kit for detection by flow cytometry.

[0044] The present invention provides a system for evaluating the risk of suffering from chronic obstructive pulmonary disease, comprising a detection module and an analysis module;

[0045] The detection module is used to detect the antigen expression level of a sample to be tested by flow cytometry, including the antibody composition described in the above technical solution;

[0046] The analysis module is used to analyze the detection result of the detection module.

[0047] As an implementation manner, when the proportion of MT-high T in peripheral blood of the sample to be tested in CD3 + T cells is lower than 2%, then the sample to be tested has a risk of suffering from chronic obstructive pulmonary disease.

[0048] Based on the above advantages, the present invention provides the application of the T cell subsets described in the above technical solution in the preparation of products for treating chronic obstructive pulmonary disease. The present invention finds that, compared with the control group, the pulmonary function is improved, airway inflammation is weakened, and pulmonary emphysema is alleviated in the mouse model of chronic obstructive pulmonary disease with tail vein infusion of MT-high T cells.

[0049] Based on the above advantages, the present invention provides an antibody composition for sorting the T cell subsets described in the above technical solution, which is characterized by comprising: an anti-CD45 antibody, an anti-CD3 antibody, and an anti-SLC30A1 antibody.

[0050] As an implementation manner, the antibodies in the antibody composition are fluorescently labeled antibodies;

[0051] The fluorescent labels of the anti-CD45 antibody, the anti-CD3 antibody, and the anti-SLC30A1 antibody are AF700, PerCP, and PE in sequence.

[0052] The antibody composition provided by the present invention for sorting the T cell subsets described in the above technical solution can sort the T cell subsets described in the above technical solution from peripheral blood, so as to be used for the treatment of chronic obstructive pulmonary disease or the preparation of products for treating chronic obstructive pulmonary disease.

[0053] Based on the above advantages, the present invention provides the application of the antibody composition described in the above technical solution in sorting the T cell subsets described in the above technical solution.

[0054] To further illustrate the present invention, the T cell subsets provided by the present invention and their applications in the diagnosis and treatment of chronic obstructive pulmonary disease will be described in detail below in conjunction with the accompanying drawings and embodiments, but they should not be construed as limiting the protection scope of the present invention.

[0055] The references in the examples are as follows:

[0056] [1]BISCHOFF P, TRINKS A, OBERMAYER B, et al. Single-cell RNA sequencing reveals distinct tumor microenvironmental patterns in lung adenocarcinoma[J]. Oncogene, 2021, 40(50): 6748 - 58.

[0057] [2]PARK J E, BOTTING R A, DOMINGUEZ CONDE C, et al. A cell atlas of human thymic development defines T cell repertoire formation[J]. Science, 2020, 367(6480).

[0058] [3]ZHANG L, YU X, ZHENG L, et al. Lineage tracking reveals dynamic relationships of T cells in colorectal cancer[J]. Nature, 2018, 564(7735): 268 - 72.

[0059] [4]WANG X M, ZHANG J Y, XING X, et al. Global transcriptomic characterization of T cells in individuals with chronic HIV-1 infection[J]. Cell Discov, 2022, 8(1): 29.

[0060] [5] A B, JAIN D, JEONG Y, et al. Activation of CD8+ T Cells in Chronic Obstructive Pulmonary Disease Lung[J]. American Journal of Respiratory and Critical Care Medicine, 2023, 208(11): 1177 - 95.

[0061] [6]HE J, ZHANG X, WEI Y, et al. Low-dose interleukin-2 treatment selectively modulates CD4(+) T cell subsets in patients with systemic lupus erythematosus[J]. Nat Med, 2016, 22(9): 991-3.

[0062] Example 1

[0063] The present invention performed single-cell sequencing on 14 patient lung tissue samples. Among them, the control non-smoking group (4 cases), early chronic obstructive pulmonary disease (COPD) (5 cases), stable stage of COPD (5 cases), and the lung tissue samples were subjected to 10×Genomics single-cell transcriptome sequencing by BGI Genomics. The clinical information of each patient is shown in Table 1.

[0064] Table 1 Clinical information of 14 patients who have completed single-cell sequencing of lung tissue samples

[0065]

[0066]

[0067] After the high-throughput sequencing was completed, the original FASTQ-format files were obtained. The Cell Ranger software was used to align the original file data with the reference genome (GRCh38), and the unqualified data was initially filtered, followed by UMI and cell counting to generate a cell gene expression matrix.

[0068] Next, the Seurat software was used to perform quality control on the obtained data. To remove cells with poor quality, cells with less than 7500 and more than 500 unique features and less than 10% mitochondrial genes were filtered. The filtered data was normalized using the SCTransfrom method and then subjected to dimensionality reduction clustering analysis. To more intuitively display the global structure and retain local structure information, the UMAP method was used in the present invention for dimensionality reduction clustering analysis and the results were visualized.

[0069] After clustering, a total of 128,536 cells were obtained in the control non-smoking (Control) group (40,834 cells), the pre-chronic obstructive pulmonary disease (pre-COPD) group (47,802 cells), and the chronic obstructive pulmonary disease (COPD) group (39,900 cells). According to the reported [3] classical cell population marker genes in the literature, a total of 26 types of cells were annotated. The results are shown in Figure 1 and Figure 2 , specifically as follows:

[0070] Epithelial cells: type I alveolar (AT1), type II alveolar (AT2), mixed alveolar cells (AT2 / AT1), club cells, ciliated cells.

[0071] Endothelial cells: lymphatic endothelial cells, venous endothelial cells, capillary endothelial cells, aortic endothelial cells, aerocytes.

[0072] Stromal cells: smooth muscle cells (SMC), fibroblasts, pericytes, mesothelial cells.

[0073] Immune cells: T cells, natural killer cells (NK), B cells, plasma cells (B Plasma), alveolar macrophages, interstitial macrophages, myeloid dendritic cells (mDC), plasmacytoid dendritic cells (pDC), classical monocytes (cMonocyte), non-classical monocytes (ncMonocyte), neutrophils, basophils.

[0074] In addition to the common cell types, various subsets of mononuclear macrophages and rare transitioning AT2 / AT1 cells were also observed, demonstrating that the resolution and cell numbers were sufficient to support subsequent analysis of subgroup heterogeneity. To explore whether there were differences in various cell types at different time points, the proportions of each cell type at different time points were calculated, and the results are shown in Figures 3 to 5 . From the overall results, compared with the control group, among epithelial cells, AT2 tended to increase in patients with pre-COPD, suggesting that the lung repair mechanism still exists in patients with pre-COPD. T cells were the cell type with the largest proportion, showing a decreasing trend from the normal group to the early stage of COPD and then to the stable stage of COPD.

[0075] Example 2

[0076] Next, further clustering analysis was performed on the T cells with the highest proportion, including: extracting T cells expressing CD3D from the whole cells of patients in different groups, and performing re-dimensionality reduction clustering analysis and annotation. The results are shown in Figures 6 to 8 . Through literature reports [4]The T cell subset marker gene expression distribution map and bubble plot were used to further determine cell types. A total of 7 clusters of known T cells were annotated: effector CD4 + T (Effector CD4T), effector memory CD4 + T (Effector memory CD4T), central memory CD4 + T (Central memory CD4T), exhausted CD4 + T (Exausted CD4T), effector CD8 + T (Effector CD8T), proliferating T (ProlifratingT) and NK. And 2 clusters of CD4 and CD8 double-negative T cells with unclear markers, clusters 5 and 12 ( Figure 6 ). In terms of cell proportion, effector CD4 + T, effector memory CD4 + T, central memory CD4 + T and effector CD8 + T all showed an upward trend in early-stage COPD patients, which was relatively consistent with the existing literature reports [5] ( Figure 7 A). Clusters 5 and 12 are T cell subsets that have not been reported in the literature. They were significantly reduced in early-stage and stable-stage COPD patients and were relatively consistent within the patient population: in the 4 control groups, their proportions and subsets were obvious, but in early-stage and stable-stage COPD patients, there was a tendency to decrease significantly or even disappear with disease progression ( Figure 7 B and Figure 8 ).

[0077] To better define cluster 5 and cluster 12, the FindAllMarekers function of the Seurat package was used to find genes highly specifically expressed in each subset relative to other subsets, and the top 10 genes significantly expressed in each subset were shown in a volcano plot. The results are shown in Figure 9The results showed that both Cluster 5 and Cluster 12 highly expressed metallothionein-related genes, such as MT1X, MT1E, MT1F, and MT2A. Metallothionein (MT) is the main controller of intracellular zinc concentration. MT1 is ubiquitously expressed, preferentially expressed in fibroblasts, epithelial cells, and endothelial cells, expressed in the cytoplasm, and plays a role in heavy metal detoxification. MT2 is ubiquitously expressed in the nucleus and cytoplasm of various cells and plays a role in cell proliferation and apoptosis. Zn is crucial for the balance between different T cell subsets and the production of cytokines. Its deficiency reduces the production of type 1 cytokines (IFN-γ, IL-2, and TNF-α) by T cells, while type 2 cytokines (IL-4, IL-6, and IL-10) are less affected. MT regulates the phosphorylation levels of transcription factors STAT1 and STAT3 and is essential for T cell survival and expansion. The binding of Zn to MT may disrupt the phosphorylation process, leading to an increase in the level of IL-10.

[0078] In the present invention, functional enrichment analysis was performed on the differential genes of the two subsets to further understand the functions of the two subsets. GO functional enrichment was performed on the differential gene sets of the two subsets, and significant enrichment was defined as qvalue (padj) less than 0.05. The differentially expressed genes highly expressed in Cluster 5 and 12 were mainly enriched in biological processes such as protein folding, inorganic compound detoxification, and stress response to metal ions, which was consistent with the physiological role of MT. In addition, there were also upregulations of T cell activation and cytokine-mediated signaling pathways, suggesting that the cells in Cluster 5 and 12 were activated T cells ( Figure 10 ). The differentially expressed genes with low expression were mainly enriched in the downregulation of pathways related to the positive regulation of T cells, suggesting that Cluster 5 and 12 had the ability of negative regulation of T cells ( Figure 11 ). Therefore, Cluster 5 and 12 were combined and annotated as MT-high T cells.

[0079] Example 3 Verification of MT-high T cells in a public single-cell sequencing dataset, human lung tissue specimens, and peripheral blood

[0080] To verify the MT-high T cells discovered in the single-cell sequencing data of human lung tissue in the present invention, next, a public single-cell sequencing dataset [1] (https: / / codeocean.com / capsule / 8321305 / tree / v1) and paraffin sections of human lung tissue were used for verification, including: reclustering and dimensionality reduction of two public single-cell sequencing datasets of human lungs, mapping metallothionein-related genes and T cell marker genes; performing CD3 and MT2A immunofluorescence staining on paraffin sections of normal human lung tissue. First, the two public datasets [1,2] ( Figure 12 and Figure 13) A T cell population with high expression of MT1X, MT1E, MT1G, and MT2A was visible. Additionally, the present invention also performed immunofluorescence staining on paraffin sections of normal human lung tissue, and it was visible from Figure 14 that there was spatial co-localization of MT2A (green fluorescence) and CD3 (red fluorescence). Thus, it was confirmed that MT-high T cells indeed exist in normal human lung tissue.

[0081] The results of single-cell sequencing data showed that MT-high T was significantly reduced in the pre-COPD stage and further decreased with disease progression. This result suggested the potential of MT-high T as an early diagnostic target for chronic obstructive pulmonary disease. To explore its changes in human peripheral blood, the present invention intended to collect 20 cases each from a healthy control group (NC, source: volunteers), healthy smokers (CS, source: volunteers), pre-chronic obstructive pulmonary disease patients (pre-COPD, source: COPD cohorts of China-Japan Friendship Hospital and Peking University Third Hospital), and stable chronic obstructive pulmonary disease patients (COPD, source: COPD cohorts of China-Japan Friendship Hospital and Peking University Third Hospital). Currently, 9 cases of NC, 14 cases of CS, 11 cases of pre-COPD, and 23 cases of COPD have been enrolled. Take 1 mL of peripheral blood and centrifuge at 2000 rpm for 10 min to separate the plasma. Make up the remaining blood after taking the plasma to the original volume with PBS, mix well by inverting up and down, and slowly add it to the upper layer of 4 mL lymphocyte separation solution. Centrifuge at 2000 rpm for 20 min at room temperature with a speed increase of gear 9 and a speed decrease of gear 4 (density gradient centrifugation). Aspirate the peripheral blood mononuclear cell layer (PBMCs), add it to 8 mL of PBS, mix well, and centrifuge at 1500 rpm for 10 min at room temperature to wash away the lymphocyte separation solution. Resuspend with PBS for standby (2 mL) to make the cell suspension concentration approximately 1×10 6 cell / mL. Take 1×10 6The cells were stained by flow cytometry, and the peripheral blood smears of normal human peripheral blood PBMC were stained by immunofluorescence for CD3 and MT2A; PBMC were isolated from the peripheral blood of the non-smoking control group (NC), the smoking control group (CS), the pre-COPD group, and the COPD group, and stained by flow cytometry. The color-matching scheme was as follows: 1 μL of CD45-AF700 (BioLegend 304024), 1 μL of CD3-PerCP (BioLegend 300326). After vortexing the antibody, mix well and let stand at room temperature in the dark for 15 min, add 2 mL of PBS, vortex at 1200 rpm for 5 min and then discard the liquid. Fix the cells with 100 μL of Reagent A in the permeabilization kit (BD IntraSure kit 641776) for 5 min. Add 2 mL of PBS, vortex at 1200 rpm for 5 min and then discard the liquid. Then, permeabilize the cells with 50 μL of Reagent B for 20 min. Add 2 mL of PBS, vortex at 1200 rpm for 5 min and then discard the liquid. Then add 1.5 μL of MT2A-PE (Affinity DF6755), vortex the antibody, mix well and let stand at room temperature in the dark for 30 min. Add 2 mL of PBS, vortex at 1200 rpm for 5 min and then discard the liquid. Resuspend and add 200 - 300 μL of PBS, and detect by flow cytometry. Define the flow cytometry phenotype of MT-high T cells as CD45 + CD3 + MT high . In addition, the present invention also verified the existence of MT-high T cells in normal human peripheral blood through immunofluorescence staining of peripheral blood smear cells of normal human PBMC. The results are shown in Figures 15 to 17 and Table 2.

[0082] Table 2 Proportion of MT-high T cells in different groups (unit: %)

[0083]

[0084]

[0085] The flow cytometry results of different groups showed that: in the NC group, MT-high T cells accounted for 8.89% of T cells, in the CS group, MT-high T cells accounted for 7.68% of T cells, in pre-COPD, MT-high T cells accounted for 2.00% of T cells, and in the COPD group, MT-high T cells accounted for 1.43% of T cells. In the pre-COPD and COPD groups, MT-high T cells in CD3 +This result is consistent with the results of single-cell transcriptome analysis of lung tissue in patients with COPD, indicating that MT-high T can be used as a diagnostic target for early COPD. + When the proportion of T cells is less than or equal to 2%, the patient is at risk of COPD.

[0086] Example 4 MT-high T cells are T cells that play an immune regulatory role

[0087] The Cellchat tool was used to analyze the intensity of cell communication and ligand-receptor pairs between T subgroups. The results are shown in Figures 18 to 21 .

[0088] Figures 10 to 11 GO enrichment analysis results show that MT-high T cells may be T cells that play an immune regulatory role. Cell communication analysis can reveal the interactions between various cells, explore the immune microenvironment of diseases, and tap into potential therapeutic targets for diseases. Therefore, the present invention analyzes the cell communication analysis between MT-high T cells and other immune cells and epithelial cells. Figures 18 to 21 The results showed that MT-high T cells can interact with cells of different T cell subsets, and CD8 + T cells are the main receivers of signals.

[0089] The present invention also used lung tissue paraffin sections of the healthy control group for immunofluorescence staining to explore the relationship between MT-high T cells and CD8 + Spatial colocalization of T cells. Antibody color scheme and concentration are as follows: CD3 (abcam, ab318146-488), 1:50; MT2A (affinity, DF6755-594), 1:100; CD8 (abcam, ab245118-650), 1:200. Results are shown in Figure 22 The results showed that MT-high T cells (CD3 + MT2A + ) is spatially closely surrounding CD8 + T(CD3 + CD8 + ) cells, there is spatial co-localization. This result shows that MT-high T cells regulate CD8 + The possibility of MT-high T cells confirms the findings in the single-cell data. It can be seen that MT-high T cells have potential immunoregulatory functions and can regulate CD8 through cytokines such as macrophage migration inhibitory factor (MIF). +T cell proliferation function, so MT-high T cells can be used as potential target cells for the treatment of chronic obstructive pulmonary disease. In addition, there is a relatively specific GZMA-F2R ligand-receptor pair between MT-high T and epithelial cells, indicating that MT-high T can exert its function by secreting granzyme A.

[0090] In the next experiment of the present invention, the method of tail vein infusion of MT-high T cells sorted by the aforementioned method (the fluorochrome labels of anti-CD45 antibody (eBioscience 11-0032-82), anti-CD3 antibody (BioLegend 100220) and anti-SLC30A1 antibody (Invitrogen PA5-37463) are FITC, Pecy7 and PE respectively) was used to treat the chronic obstructive pulmonary disease model mice to verify its therapeutic effect. The methods for evaluating the therapeutic effect are as follows:

[0091] ① Pulmonary function evaluation: a. Inspiratory capacity: Measure the lung volume of the mice after maximum inspiration, which reflects the expansion ability of the lungs. b. Lung tissue compliance: Detect the lung compliance of each group of mice through the airway resistance and lung compliance detection system (RC system) of the small animal respiratory lung function instrument. A decrease in lung compliance indicates a decrease in lung tissue elasticity, which is an important feature of chronic obstructive pulmonary disease. c. Lung tissue elasticity: Evaluate the elastic recoil ability of the lung tissue by measuring the elastic modulus of the lung tissue.

[0092] ② Airway inflammation evaluation: a. Differential cell count of inflammatory cells in bronchoalveolar lavage fluid: Analyze the bronchoalveolar lavage fluid (BALF) to detect the number and type of inflammatory cells, such as macrophages, eosinophils, etc. An increase in inflammatory cells indicates the presence of airway inflammation. b. Inflammation score of lung tissue and airway: Perform HE staining on lung tissue and main airway sections to evaluate the degree of inflammatory cell infiltration and conduct an inflammation score.

[0093] ③ Emphysema evaluation: Through microscopic observation of lung tissue sections, measure the mean linear intercept of the alveolar wall to evaluate the degree of emphysema. Emphysema is manifested as the destruction of the alveolar wall and the expansion of the alveolar cavity, with an increase in the mean linear intercept.

[0094] The results showed that compared with the control group, the pulmonary function was improved, the airway inflammation was weakened, and the emphysema was alleviated in the chronic obstructive pulmonary disease model mice treated with tail vein infusion of MT-high T cells.

[0095] In summary, the single-cell sequencing results of the present invention show that T cell subset imbalance appears in early chronic obstructive pulmonary disease (COPD). As a novel T cell subset that plays an immune regulatory role, the continuous decrease in the proportion of MT-high T cells with disease progression may lead to persistent and irreversible inflammatory responses and small airway damage in COPD. Using MT-high T cells as a novel diagnostic marker for peripheral blood in COPD has important clinical significance for the early diagnosis, prediction of treatment response, prognosis evaluation, and individualized treatment of the disease.

[0096] Although the above embodiments have described the present invention in detail, they are only a part of the embodiments of the present invention, not all embodiments. People can also obtain other embodiments based on these embodiments without creative efforts, and these embodiments all fall within the protection scope of the present invention.

Claims

1. A T cell subset, characterized in that, The flow cytometry phenotype of the T cell subset is CD45 + CD3 + MT high .

2. An antibody composition, characterized in that, Comprising: A membrane-labeled antibody composition and an intracellular-labeled antibody; The membrane-labeled antibody composition comprises: an anti-CD45 antibody and an anti-CD3 antibody; The intracellular-labeled antibody comprises an anti-MT antibody.

3. The antibody composition according to claim 2, wherein The anti-MT antibody comprises an anti-MT2A antibody.

4. The antibody composition according to claim 2 or 3, characterized in that, The antibodies in the antibody composition are fluorescently labeled antibodies; The fluorescent labels of the anti-CD45 antibody, anti-CD3 antibody and anti-MT antibody are in sequence: AF700, PerCP and PE.

5. Use of the antibody composition according to any one of claims 2 to 4 in one or more of the following: 1) Preparing a diagnostic product for chronic obstructive pulmonary disease; 2) Preparing a product for assessing the risk of suffering from chronic obstructive pulmonary disease; 3) Preparing a product for assessing the prognosis of chronic obstructive pulmonary disease.

6. A system for evaluating the risk of suffering from chronic obstructive pulmonary disease, characterized in that, Comprising a detection module and an analysis module; The detection module is used to detect the antigen expression level of a sample to be tested by flow cytometry, and comprises the antibody composition according to any one of claims 2 to 4; The analysis module is used to analyze the detection result of the detection module.

7. Use of the T cell subset according to claim 1 in preparing a product for treating chronic obstructive pulmonary disease.

8. An antibody composition for sorting the T cell subsets according to claim 1, characterized in that, Comprising: An anti-CD45 antibody, an anti-CD3 antibody and an anti-SLC30A1 antibody.

9. The antibody composition according to claim 8, wherein, The antibodies in the antibody composition are fluorescently labeled antibodies; The fluorescent labels of the anti-CD45 antibody, anti-CD3 antibody and anti-SLC30A1 antibody are in sequence: AF700, PerCP and PE.

10. Use of the antibody composition according to claim 8 or 9 in sorting the T cell subset according to claim 1.

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