Application of CXCR6+PDCD1+TOX + T cell in predicting curative effect of hepatocellular carcinoma immunotherapy

Abstract

The invention provides an application of a CXCR6 + PDCD1 + TOX + T cell in predicting the curative effect of hepatocellular carcinoma immunotherapy. In particular, the present invention provides a new depleted T cell subset, called TEX3 cells (CXCR6 + PDCD1 + TOX + T cells). In HBV + HCC, the TEX3 cells become an effective tumor killer. In addition, the TEX3 cell shows that the TEX3 cell obviously interacts with macrophages rich in CXCL9 and PD-L1 in HBV + HCC, a stronger immunosuppression tumor environment is shown, and the TEX3 cell obviously exists in a patient, so that the TEX3 cell shows an obviously better treatment effect.

Description

Technical Field

[0001] The present invention relates to the field of biomedicine technology, and in particular to an application of CXCR6+PDCD1+TOX+T cells in predicting the efficacy of immunotherapy for hepatocellular carcinoma. Background Art

[0002] Globally, hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related mortality. Conventional treatment modalities, including surgical resection, liver transplantation, and radiotherapy, often have limited efficacy in many cases. In recent years, immunotherapy has become a topic of extensive research and application in various cancer types. However, its successful application in liver cancer still faces many challenges. Nivolumab and pembrolizumab, both PD-1-targeting antibodies, have been approved for the treatment of HCC. However, it is worth noting that the phase III clinical trials of these therapies did not meet the primary endpoint of improving overall survival. The basic principle of immunotherapy is to use the patient's immune system to fight tumor cells. As researchers have deepened their understanding of the complexity of immunotherapy for liver cancer, the key role of viral infection in this context has been recognized. It is worth noting that hepatitis B virus (HBV) infection is closely related to the occurrence and development of HCC and is an important global risk factor for HCC, which has a significant impact on its occurrence and development.

[0003] The impact of hepatitis virus infection on immunotherapy of liver cancer has always been a focus of debate. Studies have reported that HBV-infected HCC patients (HBV+HCC) respond better to immune checkpoint inhibitor therapy than non-viral HCC infected patients (NBNC). In contrast, other studies have shown that there is no significant difference in the response rate of checkpoint inhibitors in HCC patients with different viral infection backgrounds, and this difference may be related to the significant heterogeneity of the immune microenvironment in HBV+HCC patients.

[0004] Hepatitis virus-infected hepatocellular carcinoma patients may be affected in their responsiveness to immunotherapy; however, the exact mechanisms and specific effects are unclear, and there is still an unmet need for biomarker-based patient stratification to optimize treatment response and predict treatment efficacy. Summary of the invention

[0005] Based on this, the present invention provides an application of a reagent for detecting CXCR6+PDCD1+TOX+T cells in a sample in the preparation of a product for predicting the efficacy of immunotherapy for patients with hepatocellular carcinoma.

[0006] In one embodiment, the immunotherapy includes immune checkpoint inhibitor therapy, adoptive immunotherapy and cell therapy.

[0007] In one embodiment, the immune checkpoint inhibitors include PD-1 inhibitors, PD-L1 inhibitors and CTLA-4 inhibitors.

[0008] In one embodiment, the reagent is a reagent used for detecting CXCR6+PDCD1+TOX+T cells based on flow cytometry.

[0009] In one embodiment, the reagents include fluorescein-labeled CXCR6 antibody, PDCD1 antibody and TOX antibody.

[0010] In one embodiment, the fluorescein is selected from APC-Cy7, APC, PE-Cy7, PerCP-Cy5.5, FITC and PE.

[0011] In one embodiment, the product is a detection kit, a detection chip or a detection device.

[0012] In one embodiment, the detection kit further comprises PBS buffer and red blood cell lysis solution.

[0013] In one embodiment, the sample is a peripheral blood sample or a tissue sample.

[0014] The above solution of the present invention has the following beneficial effects: The present invention provides a new exhausted T cell subset, called TEX3 cells (CXCR6+PDCD1+TOX+T cells). In HBV+HCC, these TEX3 cells become effective tumor killers. In addition, TEX3 cells show significant interactions with CXCL9- and PD-L1-rich macrophages in HBV+HCC, indicating a stronger immunosuppressive tumor environment, and patients with significant presence of TEX3 cells show significantly better immunotherapy effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1The present invention is a comprehensive analysis of immunotherapy for hepatocellular carcinoma according to an embodiment of the present invention; wherein A is a schematic diagram of the workflow used in this study; B is a Kaplan-Meier survival curve describing the prognosis of patients receiving immunotherapy in the data set, analyzing and comparing HBV-infected patients (395 cases) and NBNC-infected patients (79 cases); C is a representative CT image of HBV+HCC patients with significant therapeutic effects after receiving targeted combined immunotherapy, in which the significant reduction in tumor size and the reduction in tumor activity are emphasized, the left side shows the situation before treatment, and the right side shows the results after treatment; D is a unified manifold approximation and projection (UMAP) diagram, which depicts the main cell types in the tumor microenvironment, with individual cells represented by dots and colors representing different cell populations, including myeloid cells, lymphoid cells, tumor cells and other cells, and subpopulations including DC (dendritic cells), MonoDC (monocytic dendritic cells), Mo-T cells, Mph (macrophages), Mono-like (monocyte-like) cells, mast cells, Neu (neutrophils), B cells, CD4+ T cells, CD8+ T cells, NK (natural killer cells), gdT (γ-δ T cells), tumor cells, Fb (fibroblasts) and EC (endothelial cells); E is a UMAP diagram showing the cell density distribution of HBV, HCV and NBNC groups; F is a stacked bar graph showing the distribution ratio of different cell types in the tumor microenvironment of HBV, HCV and NBNC groups; G is a representative scatter plot showing the proportion of CD8+ cells in HBV, HCV and NBNC cancer tissues relative to adjacent cancer tissues in TMA chip staining results (upper figure) and representative flow cytometry data of the proportion of CD8+ cells in the peripheral blood of HCC patients under different hepatitis virus backgrounds (lower figure); H is a representative immunohistochemistry image of CD8+ staining results of HCC patients under different hepatitis virus backgrounds; I is a diagram depicting the communication between different types of cells The point heat map of the pattern, the color intensity and dot size represent the scaled average, the red circle represents a statistically significant interaction, the row represents the receptor-ligand pair, and the column represents the sending cell type to the receiving cell type; J is a representative multi-color immunofluorescence image showing the spatial position and relationship of CD8+, CK8+ and CD68+ cells in different populations (HBV, HCV and NBNC); K is a scatter plot showing the results of the distance between CD8+ and CD68+ cells in liver cancer patients with different hepatitis backgrounds (HBV, HCV, NBNC). The data comes from multi-color immunofluorescence, each point represents a cell, the ordinate represents the CD8+ distance, and the CD68+ cell distance is 0~20μm and 20~40μm from bottom to top respectively; Figure 2The CD8 cell subtypes and molecular characteristics of hepatocellular carcinoma in an embodiment of the present invention; wherein A is a heat map depicting the expression of various molecular markers in different subtypes of CD8 cells, the color gradient from blue to red represents the increase in gene expression level, and the darker the color, the higher the expression level; B is a UMAP diagram showing that CD8 cell subtypes are separated into 7 different clusters; C is a stacked bar chart showing the differences in the distribution of CD8 cell subtypes in different individual patients, the columns represent single samples, different CD8 cell subtypes are coded with different colors, and are sorted from left to right according to the proportion of CD8+TEX (CD8+ T exhaustion) cells; D is a UMAP density map showing the distribution differences of CD8 cell subtypes in patients with different hepatitis backgrounds (HBV, HCV and NBNC), the color gradient from blue to red represents the density of each group of cells, and the dotted line emphasizes the density within the CD8+TEX position; E is a bar chart showing the specific distribution ratios of various CD8 cell subtypes in the HBV, HCV and NBNC groups; F is a CD8+PD1+ Representative flow cytometry data of B2M cell ratio; G is a representative scatter plot of the TMA chip staining results showing the proportion of PD1+CD8+ cells in HCC tissues and adjacent tissues of patients with different hepatitis backgrounds (HBV, HCV and NBNC), and each dot represents a cell; H is a representative figure of PDCD1 (PD1) immunohistochemical staining results of liver cancer patients with different hepatitis virus backgrounds, one representative image was selected from each group, and a total of 10 cases were analyzed, and each image had one cancer tissue field; I is a representative multicolor immunofluorescence image showing the levels of CD8+, CK8+ and PDCD1+ cells in different groups (HBV, HCV and NBNC) and their spatial locations and relationships; Figure 3 The present invention is an analysis of T cell function-related labels and differentiation trajectories of hepatocellular carcinoma under different hepatitis backgrounds in one embodiment of the present invention; wherein A is a bar graph showing significant differences in important T cell function-related labels between patients with different hepatitis virus backgrounds; B is a UMAP density map showing important T cell function-related labels, including inhibition, cytotoxicity, teff-related and tpex-related labels, with colors from blue to red indicating an increase in scores, and the darker the color, the higher the score (Tpex: precursor-exhausted T cells; TEFF: effector T cells); C is a UMAP density map depicting the expression of pseudo-time analysis in T cells; D is a density map showing the differentiation trajectories of T cells in patients with HBV, HCV and NBNC backgrounds, with the x-axis representing pseudo-time and the y-axis representing cell proportion; E is a line graph showing the differences in important T cell function-related labels at different pseudo-times in patients with HBV, HCV and NBNC backgrounds; Figure 4The figure is a characteristic of exhausted CD8 T cell subtypes and CXCR6 expression in hepatocellular carcinoma in an embodiment of the present invention; wherein A is a UMAP graph showing six different subtypes of exhausted CD8 T cells; B is a UMAP density map showing the difference in the distribution of CD8 T cell subtype exhaustion in patients with different hepatitis backgrounds (HBV, HCV and NBNC from left to right), the color gradient from blue to red represents the density of the origin cells in each group, and the dotted line represents the density within the TEX_3 (T3) position; C is a stacked bar graph showing the distribution difference of different exhausted CD8 T cell subtypes in different individual patients; D is a UMAP graph showing the expression level of CXCR6; E is a UMAP graph showing the inhibition and cytotoxicity scores; F is a box plot illustrating the differences in inhibition and cytotoxicity scores between different exhausted CD8 T cell subtypes, the statistical significance is as follows: ns (not significant, P>0.05), , , , ; G is a representative flow cytometry data of the proportion of CD3+CD8+PD1+CXCR6+ cells in the peripheral blood of HCC patients with different hepatitis virus backgrounds; H is a representative figure of CXCR6 immunohistochemical staining results of HCC patients in the HBV group, HCV group and NBNC group. One representative image was selected from each group, and a total of 10 cases were analyzed; I is a representative multicolor immunofluorescence image of different populations (HBV, HCV, NBNC), depicting the level, spatial distribution and interaction of CD8+, CK8+, TOX+, and PD1+ cells, and DAPI staining is represented by blue; J is a KM diagram showing the effect of CXCR6 expression on the prognosis of untreated HCC patients (TCGA data) and the response to immunotherapy, from left to right: TCGA, Gide_2019PD-1 / melanoma overall survival (OS), Gide_2019 PD-1 / melanoma progression-free survival (PFS), Nathanson2017_CTLA4 OS, melanoma PFS, and VanAllen2015_CTLA4 OS; Figure 5The macrophage subtypes, immune microenvironment and tumor immune cell interaction in hepatocellular carcinoma in one embodiment of the present invention; A is a UMAP diagram showing 9 different subtypes of macrophages; B is a stacked bar chart showing the distribution changes of different exhausted CD8 T cell subtypes in patients with different hepatitis backgrounds (HBV, HCV and NBNC); C is the CD274 of different subtypes of macrophages =Bar graph showing the difference in expression levels of PD-L1 (PD-L1); D is a representative scatter plot depicting the proportion of PDL1+CD68 cells in the TMA chip staining results, especially in HCC tissues of patients with different hepatitis backgrounds (HBV, HCV and NBNC), and each dot represents a single cell; E is a scatter plot of the distance between CD8+ and PDL1+CD68 cells, PDCD1+CD8+ and PDL1+CD68 cells in patients with different hepatitis backgrounds (HBV, HCV and NBNC), the data are derived from multi-color immunofluorescence, each dot represents a single cell, the y-axis is the distance between CD8+ and CK8+PDL1+ cells, from bottom to top is 0~20μm, 20~ 40μm; F is a chord diagram showing the inhibitory ligand-receptor interaction network between macrophages and exhausted T cells in the HBV group. The thickness of the chord represents the strength of communication, and different colors represent different ligand-receptor networks; G is a scatter plot showing the distance between CD8+PD1+ and PDL1+CD68+ cells in patients with different hepatitis backgrounds (HBV, HCV and NBNC); the data are derived from multicolor immunofluorescence, and each point represents a single cell; the y-axis is cdd8 The distance between CD8+PD1+ and CD68+PDL1+ cells, from bottom to top, ranges from 0 to 20 μm and 20 to 40 μm; H is a representative multicolor immunofluorescence image of the HBV, HCV, and NBNC groups, depicting the levels, spatial distribution, and interactions of CD8+PD1+CXCR6+ exhausted T cells, PD-L1+CD68 macrophages, and CK+ cancer cells in tumors and adjacent normal tissues, with DAPI staining indicated in blue; I is a representative multicolor immunofluorescence image of the HBV, HCV, and NBNC groups, showing the connections between CD8+PD1+CXCR6+ exhausted T cells, PD-L1+CD68 macrophages, and CK+ cancer cells; Figure 6The prognostic analysis and treatment response of hepatocellular carcinoma patients with different viral backgrounds in one embodiment of the present invention; wherein A is a KM curve showing the prognostic results of patients receiving immunotherapy in the data set, which are stratified according to the viral background, including HBV infection (395 cases), NBNC infection (79 cases) and HCV infection (27 cases); B is a representative CT image showing a significant treatment response after HBV+HCC patients received targeted combined immunotherapy, which shows that the tumor size and activity are significantly reduced, the left figure shows the situation before treatment, and the right figure shows the results after treatment; C is a stacked bar chart depicting the distribution ratio of different cell types in the tumor microenvironment under different clinical backgrounds, including cirrhosis group, gender and BCLC stage; D is a representative image of CD8 immunohistochemical staining of HCC patients classified according to the viral background (HBV, HCV and NBNC), one representative image was selected for each group, and a total of 10 cases were analyzed, each group had 5 cancerous tissue fields and 5 adjacent non-cancerous tissue fields; Figure 7 The present invention is a comprehensive analysis of cell interactions and immune cell distribution in hepatocellular carcinoma according to an embodiment of the present invention; wherein A is a circular diagram of the inhibitory receptor ligand interaction network of different types of cells in the HBV, HCV and NBNC groups, the thickness of the lines indicates the intensity of the communication, and different colors indicate different receptor networks; B is a representative multicolor immunofluorescence image, showing the levels of CD8+, CK8+, and CD68+ cells in different populations (HBV, HCV, NBNC) and their spatial positions and relationships; C is a representative multicolor immunofluorescence image, showing the levels of CD8+, CK8+, and CD68+ cells in different populations (HBV, HCV, NBNC) at high magnification and their spatial positions and relationships; D is a scatter plot of the distance results of CD8+ and CD68+ cells in liver cancer patient groups with different hepatitis backgrounds (HBV, HCV, NBNC), the data are derived from multicolor immunofluorescence, each point represents a cell, the ordinate represents the CD8+ distance, and the CD68+ cell distance is 0~20μm and 20~40μm from bottom to top, respectively; Figure 8The characteristics of CD8 cell subtypes in hepatocellular carcinoma in an embodiment of the present invention; wherein A is a UMAP diagram illustrating the expression levels of subtype-specific markers in 6 different CD8 cell subtypes, and the color spectrum ranges from blue to red, indicating an increase in gene expression levels, and the darker the color, the higher the expression; B is a UMAP diagram showing the distribution ratio of CD8 cell subtypes in different clinical information groups, including cancer type, viral infection status and Barcelona Clinic Livercancer stage; C is a bar graph showing the total cell counts of different CD8 cell subtypes; D is a heat map of the correlation between the 6 CD8 cell subtypes, red indicates a positive correlation, and the darker the color, the higher the gene expression level; E is a bar graph of the differences in the proportions of CD8+ cell subtypes among HBV, HCV and NBNC groups, and the statistical significance is as follows: ns (not significant, P>0.05), , , , ; Fig. 9 Figure 1 is the immune characteristics and spatial relationship of hepatocellular carcinoma in an embodiment of the present invention; A is a representative image of CD8+ immunohistochemical staining results of HCC patients in the HBV group, HCV group and NBNC group. One representative image was randomly selected from each group, and a total of 10 cases were analyzed. Five cancer tissue fields and five adjacent normal tissue fields were selected for PD1 staining on each slide; B is a representative multicolor immunofluorescence image of different populations (HBV, HCV and NBNC), depicting the level, spatial distribution and interaction of PD1, CK8+ and CD8+ cells; C is a TMA chip staining result. A representative scatter plot of the proportion of CK8+PDL1+ cells in the results, especially in HCC tissues of patients with different hepatitis backgrounds (HBV, HCV and NBNC), each dot represents a single cell; D is a scatter plot of the distance between CD8+ and CK8+PDL1+ cells in HCC patients with different hepatitis backgrounds (HBV, HCV and NBNC from left to right), the data are from multi-color immunofluorescence, each dot represents a cell, the y-axis is the distance between CD8+ and CK8+PDL1+ cells, from bottom to top, 0~20μm, 20~40μm; Fig.10The present invention is an analysis of exhausted T cell subsets and CXCR6 expression in hepatocellular carcinoma according to an embodiment of the present invention; wherein, A is a representative image of the immunohistochemical results of CXCR6 expression in liver cancer patients in the HBV group, HCV group and NBNC group, one representative image is randomly selected from each group, and each CXCR6 staining slide has 5 cancer tissue fields and 5 adjacent normal tissue fields; B is three points selected in the TMA chip to quantify the CD8+PDCD1+CXCR6+ and CD8+PDCD1+TOX+CXCR6+ cells in the HBV, HCV and NBNC groups, respectively; C is a representative multicolor immunofluorescence image of the expression level of CXCR6+PD1+TOX+CD8 cells in different populations (HBV, HCV and NBNC) and its spatial relationship with tumor cells (CK8+); Fig.11 The present invention is an analysis of macrophage subtypes and immune checkpoint expression in hepatocellular carcinoma according to an embodiment of the present invention; wherein, A is a UMAP diagram showing the distribution ratio of macrophage subtypes in different clinical information groups, including viral infection status, Barcelona Clinic Liver Cancer stage and cancer type; B is a bar graph showing the difference in CXCL12 expression levels of macrophages of different subtypes; C is a bar graph showing the difference in PDCD1LG2 (PDL2) expression levels of macrophages of different subtypes; D is a representative scatter plot of the proportion of CD68+ cells in liver cancer tissues and adjacent normal tissues in the HBV group and NBNC group, each dot represents a separate cell; E is a chord diagram showing the inhibitory receptor ligand interaction network between macrophages and CD8+ TEX cells in the HCV group and NBNC group, the thickness of the line represents the intensity of the communication, and different colors represent different ligand networks; F is a heat map showing the correlation between different macrophage subtypes and CD8+ T cell subtypes in the HBV, HCV and NBNC groups; G is a graph depicting the correlation between different macrophage subtypes and CD8 Heat map of intercellular communication patterns between T cell subtypes. Color intensity and dot size represent scaled averages. Red circles indicate statistically significant interactions. Rows represent receptor-ligand pairs, and columns represent sending cell types to receiving cell types. Fig.12The present invention is a spatial analysis of exhausted T cells and immune microenvironment in hepatocellular carcinoma according to an embodiment of the present invention; wherein A is a scatter plot of the distance between CD8+ and PDL1+CD68 cells in liver cancer tissues with different hepatitis backgrounds (HBV, HCV, NBNC), and the data are obtained by multicolor immunofluorescence, each point represents a single cell, the y-axis represents the distance of CD8+ cells, and the distances from bottom to top are 0~20µm and 20~40µm, respectively; B is a scatter plot of the distance between PD1+CD8+ and PDL1+CD68 cells in liver cancer tissues with different hepatitis backgrounds (HBV, HCV, NBNC), and the data are obtained by multicolor immunofluorescence, each point represents a single cell, the y-axis represents the distance of CK8+PDL1+ cells, and the distances from bottom to top are 0~20µm and 20~40µm, respectively; C is a scatter plot of the distance between CXCR6+PD1+CXCR6+ exhausted T cells, PD-L1+ Representative multicolor immunofluorescence images of differences in the interaction between CD68 macrophages and PD-L1+CK+ cancer cells. DETAILED DESCRIPTION

[0016] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other. The reagents and instruments used in the examples are conventionally selected in the art unless otherwise specified. The experimental methods without specific conditions in the examples are implemented according to conventional conditions, such as the conditions described in the literature, books or methods recommended by the manufacturer.

[0018] In the present invention, clinical prognosis data of 501 HCC patients with different hepatitis virus infection backgrounds (HBV, HCV and NBNC) were collected. The effect of hepatitis virus infection on HCC immunotherapy was evaluated by retrospective analysis and survival analysis, and single-cell data sets were collected from HCC tissues, representing hundreds of patients with different hepatitis virus infection backgrounds to date. Liver cancer samples from different patient populations were subjected to multicolor immunofluorescence staining, and the tumor microenvironment was studied in depth. In addition, flow cytometry was used to detect the differences in immune cell composition in fresh blood samples of liver cancer patients with different hepatitis virus infection backgrounds. The present invention aims to clarify the impact of HBV infection on the immune microenvironment of HCC patients and analyze the potential impact of this phenomenon on immunotherapy.

[0019] Example 1 HBV+ HCC exhibits enhanced immunotherapy response, likely due to increased inhibitory crosstalk between CD8 cells and macrophages: This study investigates the heterogeneity of the immune microenvironment of liver cancer under different viral infection environments ( Figure 1 A). Data from 501 patients with liver cancer were collected, and survival analysis showed that the median prognostic data of the HBV+HCC group was significantly improved compared with the non-viral infection group ( Figure 1 B and Figure 6 A; overall p value = 0.0073, HBV vs. NBNC p value = 0.0049). To validate these findings, CT data were collected from a subset of patients (including HBV, HCV, and non-viral infection groups) by performing CT scans before and after immunotherapy (2 to 4 months after treatment), confirming that HBV patients had the most significant tumor shrinkage ( Figure 1 C and Figure 6 B). To further investigate potential causes of these differences, single-cell RNA sequencing was performed on 160 samples from 124 patients. Cell subtypes were classified into lymphocytes, myeloid cells, tumor cells, and other types based on marker genes ( Figure 1 D). In addition, there were significant differences in clinical characteristics between the HBV group and the NBNC group, with a higher proportion of patients with cirrhosis and males in the HBV group. The proportion of patients in stage D was higher in the NBNC group, while the proportion of patients in stages C and D was the lowest in the HBV group ( Figure 6 C). Density plots and stacked bar graphs show significant heterogeneity of the tumor immune microenvironment under different viral infection backgrounds, especially the proportion of CD8+ T cells was the highest in the HBV group, while the proportion of lymphocytes was the lowest in the NBNC group, but the purity of tumor cells was the highest. In addition, the proportion of macrophages was significantly increased in the viral infection group ( Figure 1 EF). Tissue microarrays (TMA) were obtained from 90 confirmed HCC patients and subjected to multicolor immunofluorescence staining, and the results showed that the proportion of CD8+ cells in the HBV+ group was higher than that in the other two groups ( Figure 1 G top). In addition, the present application collected peripheral blood samples from 50 HCC patients and used flow cytometry to detect the content of peripheral blood immune cells. The results also showed that the proportion of CD8+ T cells in the HBV+ group was higher than that in the NBNC group ( Figure 1 G bottom). The paraffin-embedded specimens of 30 HCC patients who underwent surgical treatment were collected. Immunohistochemistry showed that the expression of CD8 in the HBV and HCV groups was higher than that in the NBNC group. There were differences in the proportion of CD8+ T cells in cancer tissues and adjacent tissues, with a higher expression near the portal area ( Figure 1 H and Figure 6 D).

[0020] Further cell communication analysis showed that the interactions between inhibitory cell receptors and ligands were more significant in the HBV group than in the NBNC group. Specifically, the strongest cell receptor-ligand interactions between CD8 cells and macrophages in HBV patients were identified, including NECTIN2-TIGIT, LGALS9 HAVCR2, FGL1-LAG3, CD86-CTLA4, CD80-CTLA4, CD274-PDCD1, and PDCD1LG2-PDCD1( Figure 1 I and Figure 7 A). TMA results further support more frequent interactions and closer proximity between CD8 cells and macrophages in the HBV tumor microenvironment ( Figure 1 J and Figure 7 BC). In HBV+HCC tumor tissues and adjacent normal tissues, it can be observed that the distance between CD8+ and CD68+ cells is closer ( Figure 1 K, Figure 7 D). These results highlight the importance of the crosstalk between CD8+ cells and macrophages in HBV+ HCC patients. In the context of HBV infection, enhanced cellular communication of immunosuppressive signals may directly lead to significant differences in CD8+ cell immunosuppression and exhaustion. Therefore, it is speculated that there may be significant differences in CD8 cell immunosuppression and exhaustion in different viral infection contexts, which may be the reason for the increased responsiveness to immunotherapy in HBV+ HCC.

[0021] Example 2 HBV+HCC showed the highest proportion of exhausted CD8+ T cells: CD8+ T cells play a crucial role in immunotherapy and are equally important in determining the prognosis, immune status, and treatment outcomes of patients with liver cancer. Therefore, CD8+ T cells were isolated and reconstituted to define different CD8+ T cell subsets using classical marker genes, including CD8+ central memory T cells (TCM), CD8+ effector memory T cells (TEM), CD8+ effector memory T cells that re-express CD45RA and CD27 (TEMRA_TEFF), CD8+ naïve T cells (TN), mucosal-associated invariant T cells (MAIT), CD8+ exhausted T cells (TEX), and mitotic ( Figure 2 AB and Figure 8 A). The distribution of these CD8+ T cell subtypes in liver cancer was elucidated, and the relationship between these CD8+ T cell subtypes was described using UMAP analysis combined with relevant clinical information ( Figure 8B). Subsequently, seven CD8+ T cell subsets were quantitatively analyzed. The most abundant subsets were CD8+TEM, CD8+TEMRA_TEFF, and CD8+TCM, followed by CD8+TEX, MAIT, MITO, and CD8+TN ( Figure 8 C). CD8+ T cell exhaustion is a common state of T cell dysfunction in chronic infection and tumors, and reactivating its activity has become a key strategy for enhancing anti-tumor responses in immunotherapy. Notably, two different CD8+ T cell subsets can be found, namely CD8+ TEX and Mitos. Mitos show characteristics associated with stem cell markers, and there are some similarities between these two cell populations ( Figure 8 B and Figure 8 DE). In addition, it can be observed that the proportions of these 7 CD8+ T cell subsets are significantly different in different liver cancer patients. Figure 2 As shown in Figure C, some patients with liver cancer have high levels of CD8+ TEX. One of the central goals of immunotherapy is to reverse the exhausted state of CD8+ T cells to eliminate tumor cells. Therefore, the level of CD8+ TEX is considered an important indicator for judging the response to immunotherapy.

[0022] The proportion of CD8+ TEX cells may be a key factor affecting the prognosis and immunotherapy response of HCC patients. To further explore the impact of different hepatitis virus infections on the distribution of CD8+ T cell subsets, UMAP density maps and stacked bar charts were used to illustrate the UMAP density distribution and CD8+ T cell subset proportion distribution in patients with different hepatitis virus infections. The results showed that there were significant differences in CD8+ T cell subsets in different patients. It is particularly noteworthy that the proportion of CD8+ T cell exhaustion subpopulations in HBV+HCC patients increased significantly, which is consistent with the Figure 1 The findings are consistent with ( Figure 2 DE). In addition, the present application also collected peripheral blood samples from patients with three different infection states (HBV, HCV and NBNC). Then, flow cytometry was used to evaluate CD8+ T cell subsets. The results showed that the proportion of CD8+ T cell exhaustion subsets in the blood of HBV+HCC patients was higher ( Figure 2 FG). HCC tissue samples from patients with three different infection statuses (HBV, HCV, and NBNC) were collected for CD8 and PDCD1 immunohistochemical staining. The results showed that the expression levels of CD8 and PDCD1 in tumor tissues of the HBV+HCC group were significantly higher than those in the HCV and non-viral infection groups, and this trend was also confirmed in adjacent normal tissues ( Figure 2 H and Fig. 9A). Multicolor immunofluorescence analysis further confirmed that the exhausted subset of CD8+ T cells (PDCD1+ CD8+ T cells) was more prevalent in tumor tissues of HBV+ HCC patients ( Figure 2 I and Fig. 9 B). In addition, it can be observed that the proportion of PD-L1+ tumor cells is higher in the tumor tissues of HBV+ HCC patients ( Fig. 9 C), in HBV+HCC patients, CD8+ T cells are closer to PD-L1+ tumor cells ( Fig. 9 D). This finding highlights the importance of the exhausted state of CD8+ T cells in HBV+ HCC and its potential impact on immunotherapy response.

[0023] Example 3 Exhausted CD8+ T cells from HBV+HCC patients exhibit cytotoxic potential: Compared with the NBNC group, the HBV group had higher scores of CD8+ T cells in "activation: effector function", "exhaustion", "TCR signaling", "cytotoxicity", "chemokines / chemokine receptors", and lower scores in "naïve". Notably, in HBV+HCC patients, the highest scores of CD8+ T cells in "TCR signaling", "stress response", "oxidative phosphorylation", "glycolysis", and "fatty acid metabolism" were observed ( Figure 3 A). Surprisingly, in HBV+ HCC patients, a population of CD8+ T cells could be found that, despite high immunosuppression scores, had a strong tumor-killing potential ( Figure 3 B). Under the intervention of immune checkpoint inhibitors (such as PDCD1 / CD274 inhibitors), these cells may be transformed from an exhausted state to effector T cells with cytotoxic capacity, a phenomenon that may help improve the efficacy of immunotherapy in HBV+ HCC patients.

[0024] We further explored why such a high proportion of CD8+ T cell exhaustion exists in HBV+HCC patients and how viral infection affects CD8+ T cell differentiation by analyzing the differentiation trajectory of HCC in different hepatitis backgrounds. The velocity pseudo-time plot showed that the TEX and mitotic subgroups had higher pseudo-times, indicating that the TEX and mitotic subgroups represent the end point of cell differentiation ( Figure 3C). Based on the differentiation trajectories of CD8+ T cells in different viral infection backgrounds drawn based on RNA velocity analysis, it can be seen that the differentiation trajectories of CD8+ T cell subtypes in liver cancer patients with different infection states are different. Although CD8+ T cell subtypes in liver cancer patients with different infection states eventually reach the end point of stem cell-like TEX and mitosis, in HBV+HCC patients, the proportion of these cells remains elevated for a considerable period of time ( Figure 3 D). In addition, the sources of exhausted T cells in the three groups of patients were different. The CD8+ T cells of HBV patients may be more derived from CD8+ TEM, and the proportion of early effector T cells was higher.

[0025] Interestingly, based on the differentiation trajectory of CD8+ T cells in different viral infection backgrounds, it can be seen that the proportion of mitosis at the starting point of the trajectory of HBV patients is higher. However, this proportion quickly drops to zero and rises again over time. It is speculated that in HCV-infected patients, CD8+ T cells have been exhausted, resulting in the infiltration of mitotic subsets of T cells into tumor tissues. Over time, these cells are reactivated and differentiated into different effector T cells, and then transformed into TEX cells under long-term stimulation of viruses and tumor antigens ( Figure 3 D). Plot the pseudo-time score changes among the HBV, HCV, and NBNC groups to depict the differences in differentiation trajectories among the three groups. In the HBV group, the chemokine receptor and exhaustion scores of CD8+ T cells peaked earlier and were higher ( Figure 3 E). In addition, a heat map was constructed to show the molecules that were highly expressed at different pseudo time points. These molecules that were highly expressed at the early pseudo time points may serve as drivers of T cell differentiation.

[0026] Example 4 The CXCR6+ TEX subpopulation in HBV+HCC patients increased significantly: UMAP plots showed significant differences in cell proportions even among exhausted T cells between patients with different viral infection backgrounds ( Figure 2 D). In addition, different exhausted T cells showed heterogeneity in their suppression and cytotoxicity scores ( Figure 3 B). Therefore, it was hypothesized that a specific TEX subtype existed in HBV+HCC patients. To test this hypothesis, the present invention reaggregated all exhausted T cells and identified 6 different exhausted T cell subsets, named TEX0-TEX5 ( Figure 4 A). Further analysis showed that the TEX3 subgroup (characterized by specific CXCR6 expression, CXCR6_TEX3) was significantly enriched in the HBV group compared with the other two groups ( Figure 4 BD and Fig.10 A).

[0027] The CXCR6_TEX3 subgroup showed higher inhibition and cytotoxicity scores ( Figure 4 EF). Flow cytometry further confirmed the presence of more CXCR6+ TEX cells in the blood of HBV patients ( Figure 4 G). Immunohistochemistry results also confirmed that the expression level of CXCR6 protein in tumor tissues and adjacent normal tissues of HBV patients was higher than that in the HCV group and NBNC group ( Figure 4 H and Fig.10 B). Multicolor immunofluorescence images also verified the presence of more CXCR6+ TEX in tumor tissues of HBV patients ( Figure 4 I and Fig.10 C). To explore the role of CXCR6 in liver cancer, this application analyzed the clinical survival data of TCGA-HCC and found that patients with high CXCR6 expression had a worse prognosis. Importantly, in the immunotherapy clinical cohorts of several cancer types, patients with high CXCR6 expression had a better prognosis ( Figure 4 J). Therefore, it is hypothesized that high expression of CXCR6_TEX3 may be an important reason why HBV+HCC patients respond better to immunotherapy.

[0028] Example 5 Enhanced interaction between exhausted T cells and PDL1+ macrophages in HBV+ HCC patients: To further study this area, this application isolated all macrophages and successfully defined 9 different macrophage subsets ( Figure 5 A). UMAP analysis was able to outline the correlation between these macrophage subsets and CD8+ T cells (see Fig.11 A). In the HBV group, it can be observed that the proportion of the Mph_06_CXCL9 subgroup was significantly higher than that of the other two groups ( Figure 5 B and Fig.11 B), and the expression levels of CD274 (PD-1) and PDCD1LG2 (PD-L2) were higher in the Mph_06_CXCL9 subgroup ( Figure 5 C and Fig.11 C). Analysis of multicolor immunofluorescence images further confirmed that the HBV group had more macrophages and PD-L1+ macrophages ( Fig.11 D and Figure 5 D). Cell communication analysis revealed that in HBV+HCC, the inhibitory cell receptor and ligand interactions between TEX cells and Mph_06_CXCL9 were stronger and the expression scores of inhibitory cell receptors and ligands were higher compared with the other two groups ( Figure 5 E and Fig.11EG). Spatial cell communication analysis further supported this observation. In HBV+HCC tumor tissues and adjacent normal tissues, it can be observed that CD68+PDL1 and CD8 cells are closer, and CD68+PDL1 and PDCD1+CD8 cells are also closer ( Figure 5 FG and Fig.12 AB). It can be observed that CD68+ PDL1 positive cells are closer to PDCD1+CD8 cells, and these two types of cells are in closer contact with tumor cells, which is more obvious in the HBV infection group than in the other two groups ( Figure 5 HI and Fig.12 C). These results highlight the specific interaction between TEX cells and Mph_06_CXCL9 and the close relationship between macrophages and CD8+ T cells in HBV+ HCC patients.

[0029] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. Application of a reagent for detecting CXCR6+PDCD1+TOX+T cells in a sample in the preparation of a product for predicting the efficacy of immunotherapy in patients with hepatocellular carcinoma.

2. The use according to claim 1, characterized in that: The immunotherapy includes immune checkpoint inhibitor therapy, adoptive immunotherapy and cell therapy.

3. The use according to claim 2, characterized in that: The immune checkpoint inhibitors include PD-1 inhibitors, PD-L1 inhibitors and CTLA-4 inhibitors.

4. The use according to claim 1, characterized in that: The reagent is a reagent used for detecting CXCR6+PDCD1+TOX+T cells based on flow cytometry.

5. The use according to claim 4, characterized in that: The reagents include fluorescein-labeled CXCR6 antibody, PDCD1 antibody and TOX antibody.

6. The use according to claim 5, characterized in that: The fluorescein is selected from APC-Cy7, APC, PE-Cy7, PerCP-Cy5.5, FITC and PE.

7. The use according to claim 1, characterized in that: The product is a detection kit, a detection chip or a detection device.

8. The use according to claim 7, characterized in that: The detection kit also includes PBS buffer and red blood cell lysis solution.

9. The use according to claim 1, characterized in that: The sample is a peripheral blood sample or a tissue sample.

Images