Biomarker group of b cells and use thereof

Abstract

The present invention relates to a biomarker group of B cells and a use thereof. According to the present invention, a single-cell transcriptome analysis technology is used, and by analyzing single-cell gene expression profiles of B cells in cancerous and adjacent non-cancerous tissues of cancer patients, B cell subsets capable of reflecting a body's tumor immune status, namely, naïve B cells expressing genes Cd83 and Irs2, are isolated and characterized. Moreover, further studies identified that new characteristic genes Cd83 and Irs2 expressed by the cell subsets and the relationship between the proportion of naïve B cells and tumor prognosis can be used for diagnosis and monitoring of tumor prognosis, and as novel targets for tumor immunotherapy.

Description

A B cell biomarker panel and its application Technical Field

[0001] The present invention belongs to the field of biotechnology, and particularly relates to a B cell biomarker panel and applications thereof. Background Art

[0002] Liver cancer is a highly prevalent malignant tumor in China, with the second highest mortality rate among all malignant tumors. Hepatocellular carcinoma (HCC) accounts for approximately 90% of all liver cancer cases (Forner A, Reig M, Bruix J. Hepatocellular carcinoma. Lancet. 2018 Mar 31;391(10127):1301-1314). Although the five-year survival rate for liver cancer patients has gradually increased globally, it remains less than 10% in my country. Common treatment options for liver cancer—surgery, targeted therapy, transcatheter arterial chemoembolization, and ablation—are very limited in effectiveness for advanced liver cancer. Difficulty in early diagnosis, poor prognosis, and rapid progression are the main challenges in liver cancer prevention and treatment. Approximately 70% of liver cancer patients are diagnosed at an advanced stage. Surgical resection and chemoradiotherapy are currently the mainstays of treatment, but recurrence rates are high.

[0003] Immunotherapy is a broad-spectrum anti-tumor treatment that uses immune agents to dynamically modulate the body's immune system. By activating immune cells and enhancing the body's anti-tumor immune response, it specifically eliminates tiny residual tumor lesions, inhibits tumor growth, and breaks immune tolerance. Early immunotherapy primarily involved injections of vaccines and antiserum to prevent and treat chronic diseases. With the increasing demand for organ transplantation and tumor treatment, immunotherapy has now been widely used to treat immunodeficiency disorders, autoimmune diseases, viral diseases, tumors, and allergic diseases. Studies have shown that cancer immunotherapy has a significant impact on clinical outcomes in some patients with colon cancer, lung cancer, breast cancer, liver cancer, and melanoma (De Simone M, Arrigoni A, Rossetti G, et al. Transcriptional Landscape of Human Tissue Lymphocytes Unveils Uniqueness of Tumor-Infiltrating T Regulatory Cells. Immunity. 2016;45(5):1135-1147; Plitas G, Konopacki C, Wu K, Bos PD, Morrow M, Putintseva EV, Chudakov DM, Rudensky AY. Regulatory T Cells Exhibit Distinct Features in Human Breast Cancer. Immunity. 2016 Nov 15;45(5):1122-1134; Prieto J , Melero I , Sangro B . Immunological landscape and immunotherapy of hepatocellular carcinoma[J]. Nat Rev Gastroenterol Hepatol, 2015.). However, the types, numbers, and activities of immune cells in the HCC tumor microenvironment (TME) remain largely unknown.

[0004] B lymphocytes, pluripotent stem cells derived from the bone marrow, are crucial cellular components of the body's immune response, primarily responsible for humoral immunity. They participate in the immune cell response to antigens through various mechanisms, including producing immunoglobulins, acting directly as antigen-presenting cells (APCs), or indirectly influencing APCs to produce autoantibodies and secrete cytokines. While B cells possess a powerful defense against invading foreign enemies, abnormalities in their morphology and function can also contribute to a variety of diseases, including B cell tumors, autoimmune diseases, and type 1 diabetes. In recent years, the role of B lymphocytes in immunotherapy has been extensively studied. The adaptive immune response, in which B lymphocytes participate, is one of the body's primary pathways against tumor cells. Studies have found that patients with high B cell levels in tumor tissue are more likely to respond well to immunotherapy ( Petitprez F, de Reyniès A, Keung EZ, et al. B cells are associated with survival and immunotherapy response in sarcoma. Nature. 2020;577(7791):556-560; Helmink BA, Reddy SM, Gao J, et al. B cells and tertiary lymphoid structures promote immunotherapy response. Nature. 2020;577(7791):549-555.). Immunotherapies targeting B lymphocytes can achieve superior therapeutic effects compared to traditional therapies in the treatment of some diseases, such as the autoimmune disease systemic lupus erythematosus and melanoma ( Harvey PR, Gordon C. B-cell targeted therapies in systemic lupus erythematosus: successes and challenges. BioDrugs. 2013;27(2):85-95; Cabrita R, Lauss M, Sanna A, et al. Tertiary lymphoid structures improve immunotherapy and survival in melanoma [published correction appears in Nature. 2020 Apr;580(7801):E1]. Nature. 2020;577(7791):561-565. )

[0005] Early screening, diagnosis, and treatment of malignant tumors are crucial for improving patient survival. Tumor marker testing will become a new clinical diagnostic and treatment approach, providing crucial insights for disease screening, disease monitoring, and assessing prognosis, chemotherapy sensitivity, and recurrence after treatment.

[0006] The recent rise of single-cell sequencing technology has overcome the problem of conventional transcriptomic methods detecting the average of all cells in a sample, allowing for focused research on a single cell of interest. Using single-cell sequencing to deeply analyze the molecular signatures of liver cancer at different stages could provide new insights into early diagnosis, personalized treatment, and precise adjuvant therapy for prognosis. Technical issues

[0007] Conventional transcriptomic methods measure the average of all cells in a sample. The rise of single-cell sequencing technology allows for focused research on specific cells of interest. Using single-cell sequencing to deeply analyze the molecular signatures of liver cancer at different stages could provide new insights into early diagnosis, personalized treatment, and precise adjuvant therapy for prognosis. Technical Solutions

[0008] The purpose of the present invention is to provide a B cell biomarker panel and its application in response to the problems existing in the prior art.

[0009] The inventors of the present invention used single-cell transcriptome analysis technology to analyze the single-cell gene expression profiles of B cells in cancer tissues by comparing cancer and adjacent tissues, isolated and characterized B cell subpopulations that can reflect the body's tumor immune status, and further studied and determined the new characteristic genes expressed by this cell subpopulation, as well as the relationship between these characteristic genes and tumor prognosis, and completed the present invention on this basis.

[0010] Thus, the present invention is broadly directed to a series of markers, methods, compounds, compositions and articles of manufacture that can be used to identify or characterize, and optionally to isolate, compartmentalize, separate or enrich for, B cell subsets associated with tumor immunity.

[0011] More specifically, the inventors of the present application have discovered a series of markers that can be used independently or collectively to accurately identify, sort, enrich, and / or characterize B cell subsets from tumors. Using selected biochemical techniques, by associating the markers of the present invention with B cells in tumor tissue, B cell subsets that reflect the immune status of the tumor can be enriched, isolated, or purified.

[0012] The markers disclosed in this invention can identify or characterize tumor-derived B cell subsets, constituting a universal characterization of these tumor immune cells. These markers can be used to elucidate therapeutic targets and screen for drug compounds. Furthermore, they can be used in both clinical and non-clinical settings for the diagnosis, prognosis, classification, monitoring, and management of tumor patients, as well as for the provision of related kits or other manufactured products.

[0013] The purpose of the present invention can be achieved by the following solutions:

[0014] A first aspect of the present invention provides:

[0015] A use of a naïve B cell biomarker panel in the preparation of a kit for diagnosing or monitoring the naive state of B cells, or for diagnosing or monitoring the prognosis of liver cancer, wherein the biomarker panel comprises the genes Cd83 and Irs2, or proteins or protein fragments expressed by the genes.

[0016] A biomarker panel for naïve B cells for diagnosis or monitoring comprises genes Cd83 and Irs2, or proteins or protein fragments expressed by said genes.

[0017] Preferably, the biomarker panel further comprises at least one of the genes Ms4a4d, Cxcr4, Ccr7, Srebf1, or a protein or protein fragment expressed by the at least one gene.

[0018] For example, the biomarker panel comprises genes Cd83, Irs2, and Ms4a4d, or proteins or protein fragments expressed by the genes; or, the biomarker panel comprises genes Cd83, Irs2, and Cxcr4, or proteins or protein fragments expressed by the genes; or, the biomarker panel comprises genes Cd83, Irs2, and Ccr7, or proteins or protein fragments expressed by the genes; or, the biomarker panel comprises genes Cd83, Irs2, and Srebf1, or proteins or protein fragments expressed by the genes;

[0019] Alternatively, the biomarker panel comprises genes Cd83, Irs2, Ms4a4d, and Cxcr4, or proteins or protein fragments expressed by said genes; alternatively, the biomarker panel comprises genes Cd83, Irs2, Ms4a4d, and Ccr7, or proteins or protein fragments expressed by said genes; alternatively, the biomarker panel comprises genes Cd83, Irs2, Ms4a4d, and Srebf1, or proteins or protein fragments expressed by said genes;

[0020] Alternatively, the biomarker panel comprises genes Cd83, Irs2, Cxcr4, and Ccr7, or proteins or protein fragments expressed by said genes; Alternatively, the biomarker panel comprises genes Cd83, Irs2, Cxcr4, and Srebf1, or proteins or protein fragments expressed by said genes;

[0021] Alternatively, the biomarker panel comprises genes Cd83, Irs2, Ccr7, and Srebf1, or proteins or protein fragments expressed by said genes;

[0022] Alternatively, the biomarker panel comprises genes Cd83, Irs2, Ms4a4d, Cxcr4, and Ccr7, or proteins or protein fragments expressed by said genes; alternatively, the biomarker panel comprises genes Cd83, Irs2, Ms4a4d, Cxcr4, and Srebf1, or proteins or protein fragments expressed by said genes; alternatively, the biomarker panel comprises genes Cd83, Irs2, Cxcr4, Ccr7, and Srebf1, or proteins or protein fragments expressed by said genes;

[0023] or the proteins or protein fragments expressed by the genes; or, the biomarker panel comprises genes Cd83, Irs2, Ms4a4d, Cxcr4, Ccr7 and Srebf1, or the proteins or protein fragments expressed by the genes.

[0024] Most preferably, the biomarker panel comprises genes Cd83, Irs2, Ms4a4d, Cxcr4, Ccr7 and Srebf1, or proteins or protein fragments expressed by said genes.

[0025] The diagnosis or monitoring can be the diagnosis or monitoring of the immature state of B cells. The diagnosis or monitoring can be the diagnosis or monitoring of the prognosis of a tumor.

[0026] Compared with B cells in normal tissues or peripheral blood of the patient, the expression or increased expression of at least one of the above five genes indicates that the B cells are in an immature state, and further indicates a poor prognosis for the patient.

[0027] In one embodiment of the present invention, the tumor comprises liver cancer.

[0028] This study utilizes single-cell transcriptome analysis to analyze the gene expression profiles of B cells from both cancerous and adjacent tissues of tumor patients. This study isolated and characterized a B cell subset that reflects the body's tumor immunity status, namely, naive B cells expressing the genes Cd83 and Irs2. Further research identified the relationship between the expression of the novel signature genes Cd83 and Irs2 in this cell subset, as well as the proportion of naive B cells, and tumor prognosis. A higher proportion indicates a better prognosis, suggesting potential applications in the diagnosis and monitoring of tumor prognosis, as well as as a novel target for tumor immunotherapy.

[0029] A second aspect of the present invention provides:

[0030] A kit for diagnosing or monitoring tumor prognosis, comprising a binding agent capable of binding to the B cell gene Cd83 or a protein or protein fragment expressed thereby, and a binding agent capable of binding to the B cell gene Irs2 or a protein or protein fragment expressed thereby.

[0031] Preferably, the kit further comprises a binding agent capable of binding to the gene Ms4a4d of B cells or a protein or protein fragment expressed therefrom, and / or a binding agent capable of binding to the gene Cxcr4 of B cells or a protein or protein fragment expressed therefrom.

[0032] A binding agent that binds to, and / or a binding agent that can bind to the B cell gene Ccr7 or the protein or protein fragment expressed therefrom, and / or a binding agent that can bind to the B cell gene Srebf1 or the protein or protein fragment expressed therefrom.

[0033] Most preferably, the kit comprises a binding agent that can bind to the gene Cd83 of B cells or a protein or protein fragment expressed therefrom, a binding agent that can bind to the gene Irs2 of B cells or a protein or protein fragment expressed therefrom, a binding agent that can bind to the gene Ms4a4d of B cells or a protein or protein fragment expressed therefrom, a binding agent that can bind to the gene Cxcr4 of B cells or a protein or protein fragment expressed therefrom, a binding agent that can bind to the gene Ccr7 of B cells or a protein or protein fragment expressed therefrom, and a binding agent that can bind to the gene Srebf1 of B cells or a protein or protein fragment expressed therefrom.

[0034] In a preferred embodiment of the present invention, the tumor comprises liver cancer.

[0035] A third aspect of the present invention provides:

[0036] Disclosed is a use of an inhibitor in the preparation of a tumor therapeutic drug, wherein the inhibitor inhibits the expression of a target gene or a protein expressed by the target gene, wherein the genes include Cd83 and Irs2.

[0037] In a preferred embodiment of the present invention, the tumor comprises liver cancer.

[0038] Since the expression or high expression of Cd83 or Irs2 will cause the corresponding B cells to be in an immature state, upregulating the expression of these genes or upregulating the activity of the expressed proteins will be beneficial to maintaining the activity of immature B cells, thereby achieving the effect of treating tumors.

[0039] A fourth aspect of the present invention provides:

[0040] A method for screening drugs, the method comprising the following steps:

[0041] mixing the test chemical with the gene or the protein expressed by it, or mixing the test chemical with B cells expressing the gene;

[0042] Detecting changes in the activity of the expressed protein, or whether the test chemical substance binds to the gene or the protein expressed by it, or changes in the activity of the cell, or changes in the expression level of the gene in the cell;

[0043] The gene is selected from the group consisting of: Cd83 and Irs2.

[0044] In a preferred embodiment of the present invention, the drug is used to treat tumors. In an embodiment of the present invention, the tumor includes liver cancer.

[0045] A fifth aspect of the present invention provides:

[0046] A subset of B cells that express the genes Cd83 and Irs2.

[0047] The B cell subset may further express at least one of the genes Ms4a4d, Cxcr4, Ccr7 and Srebf1.

[0048] For example, the B cell subpopulation expresses genes Cd83, Irs2 and Ms4a4d; or, the B cell subpopulation expresses genes Cd83, Irs2 and Cxcr4; or, the B cell subpopulation expresses genes Cd83, Irs2 and Ccr7; or, the B cell subpopulation expresses genes Cd83, Irs2 and Srebf1;

[0049] Alternatively, the B cell subpopulation expresses genes Cd83, Irs2, Ms4a4d, and Cxcr4; alternatively, the B cell subpopulation expresses genes Cd83, Irs2, Ms4a4d, and Ccr7; alternatively, the B cell subpopulation expresses genes Cd83, Irs2, Ms4a4d, and Srebf1;

[0050] Alternatively, the B cell subpopulation expresses genes Cd83, Irs2, Cxcr4, and Ccr7; Alternatively, the B cell subpopulation expresses genes Cd83, Irs2, Cxcr4, and Srebf1; Alternatively, the B cell subpopulation expresses genes Cd83, Irs2, Ccr7, and Srebf1;

[0051] Alternatively, the B cell subpopulation expresses genes Cd83, Irs2, Ms4a4d, Cxcr4, and Ccr7; Alternatively, the B cell subpopulation expresses genes Cd83, Irs2, Ms4a4d, Cxcr4, and Srebf1; Alternatively, the B cell subpopulation expresses genes Cd83, Irs2, Cxcr4, Ccr7, and Srebf1;

[0052] Alternatively, the B cell subpopulation expresses the genes Cd83, Irs2, Ms4a4d, Cxcr4, Ccr7 and Srebf1.

[0053] The B cell subset is naive. Through comparative studies, the inventors of the present invention discovered for the first time that B cells expressing the genes Cd83 and Irs2 are in a naive state. A greater proportion of these B cell subsets among tumor-infiltrating B cells indicates a more naive state of the patient's tumor-infiltrating B cells and a better prognosis. Furthermore, the more genes of the six genes (Cd83, Irs2, Ms4a4d, Cxcr4, Ccr7, and Srebf1) expressed by these B cell subsets, the more accurate the diagnosis of the patient's tumor immune status and the more accurate the prognosis.

[0054] In a preferred embodiment of the present invention, the two T cell subsets are both derived from tumors. In a specific embodiment of the present invention, the tumor is liver cancer, in particular hepatocellular carcinoma.

[0055] A sixth aspect of the present invention provides:

[0056] The method for enriching the B cell subpopulation described in the fifth aspect.

[0057] The method comprises the following steps: contacting a population of immune cells infiltrating a tumor with a binding agent that binds to at least one of the above-mentioned genes or proteins or protein fragments expressed therein; and sorting the immune cells bound to the binding agent to provide an enriched B cell subpopulation.

[0058] The binding agents include nucleic acids, ligands, enzymes, substrates, and antibodies.

[0059] As one embodiment of the present invention, a method for enriching a B cell subpopulation includes the following steps: contacting an immune cell population infiltrating a tumor with a binding agent that binds to a target gene or a protein or protein fragment expressed by the target gene; and sorting the immune cells bound to the binding agent to provide an enriched CD8+T cell subpopulation.

[0060] The target genes include Cd83 and Irs2. Preferably, the target genes further include at least one of Ms4a4d, Cxcr4, Ccr7 and Srebf1.

[0061] In a preferred embodiment of the present invention, the sorting step comprises fluorescence activated cell sorting, magnetic assisted cell sorting, substrate assisted cell sorting, laser mediated cutting, fluorimetry, flow cytometry or microscopy.

[0062] In a preferred embodiment of the present invention, the tumor is liver cancer, in particular hepatocellular carcinoma.

[0063] A seventh aspect of the present invention provides:

[0064] A method of diagnosis or evaluation, comprising the steps of:

[0065] 1) classifying a sample of immune cells infiltrating into a tumor obtained from a subject into B cells; and,

[0066] 2) contacting the separated B cells with at least one binding agent that binds to a target gene or a protein or protein fragment expressed by the target gene, wherein the target gene includes Cd83 and Irs2;

[0067] The binding agents include nucleic acids, ligands, enzymes, substrates, and antibodies.

[0068] Preferably, in step 2), the target gene further comprises at least one of Ms4a4d, Cxcr4, Ccr7 and Srebf1.

[0069] In a preferred embodiment of the present invention, the tumor is liver cancer, in particular hepatocellular carcinoma.

[0070] In one embodiment of the present invention, the method is performed before the patient receives treatment. In other embodiments, the method can be performed after the subject receives treatment, such as after chemotherapy, radiotherapy, or surgery.

[0071] In one embodiment of the present invention, the method is used to determine the prognosis of a subject, and the higher the B cell ratio, the better the prognosis.

[0072] The genes used in the present invention are expressed to varying degrees in various cells of liver cancer tissue. For example, gene Cd83 is expressed in multiple cells of liver cancer tissue, including B cells, DC cells, and endothelial cells. As shown in FIG13 , the expression level in DC cells is close to that in B cells. Therefore, the measurement of a single gene cannot reflect the proportion of B cells or even the exact cell type. Even the conventional combination of existing genes cannot accurately reflect the proportion of B cells.

[0073] This study more accurately reflects B cell proportions by detecting genes Cd83 and Irs2, which are more closely associated with the naive state of B cells. Furthermore, the study further analyzes the expression of related genes Ms4a4d, Cxcr4, Ccr7, and Srebf1 in B cells. Combinations of one or more of these genes, particularly Ms4a4d, combined with Cd83 and Irs2, can further improve accuracy, enabling a more precise assessment of a subject's prognosis based on B cell proportions. Beneficial effects

[0074] (1) The present invention uses single-cell transcriptome analysis technology to analyze the single-cell gene expression profile of B cells in cancer tissues and discovers new B cell genes that can reflect the body's tumor immune status.

[0075] (2) The present invention discovered that B cells express genes Cd83 and Irs2, which means that the B cells are in an immature state. Genes Cd83 and Irs2 are genes related to the immature state of B cells discovered for the first time by the present invention, and there is a correlation between B cells expressing genes Cd83 and Irs2 and tumor prognosis.

[0076] On this basis, the Cd83 and Irs2 genes of B cells can become functional molecules of B cells, upregulating the expression of the genes or the activity of their expressed proteins, and can be used for tumor immunotherapy.

[0077] In addition, the Cd83 and Irs2 genes of B cells can also be used as a diagnostic marker group for tumor prognosis.

[0078] Description of terms in this invention:

[0079] CD83, also known as HB15, encodes a single-pass type I membrane protein and a member of the immunoglobulin receptor superfamily. It may play an important role in antigen presentation or cell-cell interactions following lymphocyte activation.

[0080] IRS2 is a protein-coding gene. Diseases associated with IRS2 include type 2 diabetes and fatty liver disease. Pathways involved include the IL-9 signaling pathway and the insulin receptor signaling cascade. The gene product is phosphorylated by the insulin receptor tyrosine kinase upon receptor stimulation, as well as by the interleukin-4 receptor-associated kinase.

[0081] Ms4a4d, also known as MS4A4A, is a protein-coding gene associated with diseases including Alzheimer's disease and chromophobia-induced renal cell carcinoma. As a component of a multimeric receptor complex, this protein may be involved in signal transduction.

[0082] CXCR4, encoding a specific CXC chemokine receptor for stromal cell-derived factor-1, has seven transmembrane regions and is located on the cell surface. It works with the CD4 protein to support HIV entry into cells and is highly expressed in breast cancer cells.

[0083] The protein encoded by the Ccr7 gene is a member of the G protein-coupled receptor family. This receptor is expressed in various lymphoid tissues and activates B and T lymphocytes. It can also control the migration of memory T cells to inflamed tissues and stimulate the maturation of dendritic cells.

[0084] Srebf1, a protein-coding gene, is implicated in diseases including mucosal epithelial dysplasia, hereditary dysplasia, and Ifap syndrome 2. Its associated pathways include steroid metabolism and gene expression (transcription).

[0085] CD38 is a protein-coding gene. Diseases associated with CD38 include prolymphocytic leukemia, leukemia, and chronic lymphocytic leukemia 2. Pathways involved in CD38 include NAD metabolism, water-soluble vitamins, and cofactor metabolism. It can serve as a prognostic marker for patients with B-cell chronic lymphocytic leukemia.

[0086] CD20, also known as MS4A1, encodes a member of the transmembrane 4A gene family. Members of this newly discovered protein family display unique expression patterns in hematopoietic cells and non-lymphoid tissues. This gene also encodes a B lymphocyte surface molecule that plays a role in the development and differentiation of B cells into plasma cells.

[0087] The basic information of the above genes is shown in Table 1 (gene names are based on HGNC, and NG, NM, and NP numbers are based on the RefSeq database):

[0088] Table 1

[0089] Gene name Full name DNA number mRNA number Protein number CD83CD83 MoleculeNC_000006.12NM_001040280.3NP_001035370.1IRS2Insulin Receptor Substrate 2NC_000013.11NM_003749.3NP_001074681.1Ms4a4dMembrane Spanning 4-Domains A4ANC_000011.10NM_001243266.2NP_683876CD38CD38 MoleculeNC_000004.12NM_001775.4NP_001766.2CXCR4C-XC Motif Chemokine Receptor 4NC_000002.12NM_001008540.2NP_001008540.1Ccr7C-C Motif Chemokine Receptor 7NC_000017.11NM_001301714.2NP_001288643.1Srebf1Sterol Regulatory Element Binding Transcription Factor 1NC_000017.11NM_001005291.3NP_001005291.1CD20Membrane Spanning 4-Domains A1NC_000011.10NM_021950.4NP_068769.2. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0091] Figure 1 shows flow cytometry analysis of CD45+ immune cells. The upper left image shows a flow cytometry analysis of a CD45-negative control tumor tissue, the upper right image shows a flow cytometry analysis of a CD45-positive tumor tissue, the lower left image shows a flow cytometry analysis of a CD45-negative control paracancerous tissue, and the lower right image shows a flow cytometry analysis of a CD45-positive paracancerous tissue.

[0092] Figure 2 shows examples of qualified single-cell cDNA. The left figure shows the fragment distribution of cDNA products after reverse transcription of CD45-positive cells from cancer tissue using the 10x Genomics platform. The right figure shows the fragment distribution of cDNA products after reverse transcription of CD45-positive cells from adjacent adjacent tissue using the 10x Genomics platform.

[0093] Figure 3 shows an example of a qualified library. The left figure shows the fragment distribution of CD45-positive cells in cancer tissue after library construction; the right figure shows the fragment distribution of CD45-positive cells in adjacent tissue after library construction.

[0094] Figure 4 is a heat map of B cell gene expression;

[0095] Figure 5 is a cluster analysis diagram of three B cell subsets;

[0096] Figure 6 shows the distribution (left) and expression (right) of Cd83 in different cell subsets;

[0097] Figure 7 shows the distribution (left) and expression (right) of Irs2 in different cell subsets;

[0098] Figure 8 shows the distribution (left) and expression (right) of Ms4a4d in different cell subsets;

[0099] Figure 9 shows the distribution (left) and expression (right) of Cxcr4 in different cell subsets;

[0100] Figure 10 shows the distribution (left) and expression (right) of Ccr7 in different cell subsets;

[0101] Figure 11 shows the distribution (left) and expression (right) of Srebf1 in different cell subsets;

[0102] FIG12 is a Kaplan Meier curve showing the correlation between the expression of naive B cell signature genes and the survival of liver cancer patients. The signature genes are Cd83, Irs2, Ms4a4d, Cxcr4, Ccr7, and Srebf1.

[0103] Figure 13 shows the distribution (top and middle) and expression (bottom) of Cd83 in different cells. Modes for Carrying Out the Invention

[0104] The present invention is further described below with reference to the following examples.

[0105] It should be noted that the embodiments cannot be used to limit the scope of protection of the present invention. Those skilled in the art understand that any improvements and changes made on the basis of the present invention are within the scope of protection of the present invention.

[0106] The chemical reagents used in the following examples are all conventional reagents and can be obtained commercially.

[0107] The analysis software used and its sources are as follows:

[0108] GSNAP(http: / / researchpub.gene.com / gmap / );

[0109] Statistical software R (https: / / www.r project.org / );

[0110] TCGA data: cBioportal (http: / / www .cbioportal .org / ) and (https: / / gdc.cancer.gov / ). Example

[0111] Taking liver cancer patients as an example, a single-cell transcriptome information analysis method of B cells was carried out

[0112] 1. Clinical sample collection

[0113] From August 2017 to June 2018, surgical tissue and peripheral blood (3 ml) were collected from patients at Zhongshan Hospital, Fudan University. These patients had hepatocellular carcinoma and had not received preoperative adjuvant radiotherapy or chemotherapy. This study adhered to the medical ethics standards of the Declaration of Helsinki and was reviewed by the ethics committees of Fudan University and Shanghai Jiao Tong University.

[0114] Blood samples were collected before surgery in EDTA-anticoagulant tubes and temporarily stored on ice. Cancerous and adjacent normal tissue samples were collected during surgery, with necrotic tissue removed from the cancerous tissue; adjacent normal tissue was defined as normal tissue at least 5 cm away from the cancerous tissue. Within 30 minutes of ex vivo removal, both cancerous and adjacent normal tissues were placed on ice in RNAlater (Qiagen) solution, and single-cell isolation was completed the same day.

[0115] 2. Preparation of Single Cell Suspension

[0116] For cancer and adjacent tissues, single cells were isolated by enzymatic hydrolysis and red blood cell lysis: the tissues were first rinsed 2–3 times with DMEM (Thermo Fisher, 11965118) containing 10% FBS (Thermo Fisher, 26140079). The erosion-like areas and blood clot areas were cut with scissors, and the medium was removed. The tissues were then cut into 1 mm squares. 3sized fragments; add 5 mL of DMEM solution containing 0.2% collagenase 2 (Sigma-Aldrich, C2-28-100MG), transfer the tissue fragments to a centrifuge tube, and enzymatically hydrolyze at 80-100 rpm in a 37°C water bath shaker for 10-15 minutes; after the enzymatic hydrolysis is completed, remove the supernatant of the lysate, filter it through a 70 μm filter, and replenish it with pre-cooled DMEM medium containing 10% FBS; all the filtrates are centrifuged at 300 g, 4°C for 6-10 minutes, remove the supernatant, and use 1-3 mL of red blood cell lysis buffer (Thermo Fisher, 599451) to lyse at room temperature for 3 minutes to remove red blood cells; after the red blood cell lysis is completed, replenish 5-10 mL of ice-cold DMEM medium and centrifuge again at 300 g, 4°C for 6-10 minutes; after the centrifugation, replenish it with 10 mL of pre-cooled DMEM medium and then centrifuge for 4 minutes. The cells were washed by centrifugation at 4°C for 6-10 minutes, and resuspended in 2-3 mL PBS (Thermo Fisher, 10010-049) to obtain a single-cell suspension.

[0117] 3. Single-cell analysis and sorting of target immune cells

[0118] The target cells for isolation are live CD45+ cells, i.e., cells that are positive for CD45 antibody labeling and negative for PI staining. Figure 1 shows flow cytometry analysis of immune cells (CD45+). The upper left image shows a flow cytometry analysis of a CD45-negative control tumor tissue; the upper right image shows a flow cytometry analysis of a CD45-positive tumor tissue; the lower left image shows a flow cytometry analysis of a CD45-negative control adjacent to the cancer; and the lower right image shows a flow cytometry analysis of a CD45-positive adjacent to the cancer tissue.

[0119] Single-cell suspensions were counted using a cell counter and adjusted to a concentration of 5,000 to 10,000 cells per microliter. Cells were fluorescently labeled with CD45 antibodies (BioLegend, 103108) and further labeled with PI dye (Biolegend, 421301) before flow cytometry. Dead cells were removed by flow cytometry, and CD45+ immune cells were isolated from cancer and adjacent tissues, respectively.

[0120] 4. Sequencing library construction and sequencing

[0121] The sorted CD45+ cells from cancerous and paracancerous tissues were washed and centrifuged to obtain a cell pellet, which was then resuspended in PBS at a concentration of 700-1200 cells per microliter. Cell viability was assessed using trypan blue (Thermo Fisher). A cell viability of 70% or higher met the standard for subsequent experiments. The cells were then transferred to the 10x Genomics Chromium System for oil droplet encapsulation and reverse transcription, with a target cell harvest of 8,000 cells. After demulsification and recovery, the reverse transcription product was eluted and amplified using 11 cycles of cDNA amplification. The cDNA was then used for library construction and paired-end sequencing on the NovaSeq 6000. Figure 2 shows the Agilent 2100 quality assurance results for qualified single-cell cDNA (left: from tumor tissue; right: from paracancerous tissue), and Figure 3 shows the quality assurance results for qualified libraries (left: from tumor tissue; right: from paracancerous tissue). Example

[0122] Bioinformatics analysis

[0123] 1. Data comparison and quality control

[0124] The raw fastq data from sequencing was first processed using the fastp software package to obtain quality-controlled fastq data. The data was then filtered using the count function in the Cellranger software package to obtain gene expression counts. Low-quality reads were filtered if they met any of the following criteria: containing more than 10% unknown bases (N); having an average Phred quality score below 10; being less than 16 bases in length; or retaining only one read with identical sequence and position.

[0125] 2. Cell type identification

[0126] The obtained expression matrix was integrated and filtered using the Seurat software package. Cells with gene expression exceeding 300, mitochondrial gene expression exceeding 20%, and hemoglobin gene expression exceeding 3% were first filtered out. Samples from different batches were then merged using the canonical correlation analysis (CCA) algorithm to remove batch effects. Unsupervised dimensionality reduction clustering was then performed on the cells using the UMAP algorithm. The Wilcox Rank Sum test was used to identify differentially expressed genes in each population, and the cells were annotated based on these differentially expressed genes.

[0127] Table 2 Genes expressed by B cells in liver cancer tissues

[0128] Gene name avg_logFCp_val_adjCd79a0.6236122.71E-258Cd830.4594776.65E-209Irs20.3979256.87E-203Mef2c0.3310628.43E-162Ebf10.4345581.45E-148Cd740.2512448.76E-143Ccr70.4416812.38E-117Ly6d0.3971282.16E-55

[0129] Through our research, we discovered that Cd83 and Irs2 are new genes characteristically expressed in naive B cells.

[0130] Figure 4 is a heat map of B cell gene expression; Figure 5 is a cluster analysis of three B cell subsets, clustered into three types based on gene expression, with cluster 0 representing naive B cells. Figures 6 through 11 show the expression levels of Cd83, Irs2, Ms4a4d, Cxcr4, Ccr7, and Srebf1 in different cell subsets: distribution (left) and expression (right).

[0131] 3. Utility in prognosis

[0132] The characteristic genes of the B cell functional groups identified above were analyzed for their usefulness in patient disease prognosis. The dataset used was the TCGA (The Cancer Genome Atlas) liver cancer (LIHC, hepatocellular carcinoma) data, as this study collected and collated patient follow-up information. Patient cancer tissue gene expression data were downloaded from UCSC Xena (http: / / xena.ucsc.edu / ), and patient follow-up (survival) information was downloaded from the GDC Data Portal (https: / / gdc portal.nci.nih.gov / ).

[0133] To eliminate the possibility of interference from the expression of specific genes in non-tumor-associated B cells, we averaged the z-score-converted gene expression values ​​for each sample obtained from the TCGA database for the signature genes of naive B cells identified in the previous study. The average was then divided by the Cd38 expression value for each sample to reflect the degree of B cell infiltration in cancer tissue.

[0134] To maximize the ability to differentiate patient prognoses, signature genes were analyzed individually and in random combinations. For individual genes, patients were divided into high and low expression groups, with the median value used as the grouping factor. For combined genes, the expression levels within a group were first averaged, then further divided into high and low expression groups, with the median value used as the grouping factor.

[0135] The candidate gene range is determined by the analysis in step 2 above, which identified genes specifically highly expressed in naive B cells. Kaplan-Meier curves were used to visualize patient survival differences (Figure 12), and the log-rank test was used to determine if the differences were significant (P < 0.01). This indicates that HCC patients with high expression of Cd83 and Irs2 in naive B cells have shorter survival times, which is of great significance in the prognosis of HCC patients. The gene panel containing Cd83 and Irs2 expressed by naive B cells can be used for prognostic diagnosis of HCC patients.

[0136] Table 3 Statistical values ​​of characteristic expression genes of naive B cells in the prognostic difference of patient survival

[0137] Gene combination P value Hazard ratio Cd83, Irs2, Ms4a4d, Cxcr4, Ccr7, Srebf1 0.0018 20.5802 Cd83, Irs2 0.039 0.8901 Cd83, Irs2, Ms4a4d 0.0065 0.6352 Cd83, Irs2, Cxcr4 0.01 0.8092 Cd83, Irs2, Ccr7 0.008 0.8123 Cd83, Irs2, Srebf1 0.009 0.8621 Cd83, Irs2, Ms4a4d, Cxcr4 0.005 40.6173 Cd83, Irs2, Ms4a4d, Ccr7 0.005 0.625 3Cd83, Irs2, Ms4a4d, Srebf10.00420.6098Cd83, Irs2, Cxcr4, Ccr70.0070.7223Cd83, Irs2, Cxcr4, Srebf10.00860.7462Cd83, Irs2, Ccr7, Srebf10 .00780.7623Cd83, Irs2, Ms4a4d, Cxcr4, Ccr70.0030.6001Cd83, Irs2, Ms4a4d, Cxcr4, Srebf10.0020.5982Ms4a4d, Cxcr4, Ccr7, Srebf10.050.8992

[0138] As can be seen from the above table, liver cancer patients whose naïve B cells highly express Ms4a4d, Cxcr4, Ccr7, and Srebf1 have a long survival time, which is of great significance in the prognosis diagnosis of liver cancer patients. The gene combination expressed by naïve B cells containing Ms4a4d, Cxcr4, Ccr7, and Srebf1 can be used for the prognosis diagnosis of liver cancer patients.

[0139] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art may make various variations or modifications within the scope of the claims, which do not affect the essence of the present invention. Industrial Applicability

[0140] Drug development: By analyzing B cell markers, the efficacy and safety of candidate drugs can be screened and evaluated, accelerating the drug development process.

[0141] Diagnostic testing: Develop B cell-related detection methods that can be used for early diagnosis, prognosis assessment, and treatment monitoring of diseases, improving diagnostic accuracy and personalized treatment.

[0142] Immunotherapy: B cell markers are used to identify and isolate B cells with specific functions, such as plasma cells with strong antibody-producing ability, to conduct cell therapy and immunotherapy research.

[0143] Disease Research: Further investigation of the functions and regulatory mechanisms of B cell markers can increase understanding of immune diseases, autoimmune diseases, and tumor immune escape, and promote research progress in related fields. Sequence Listing Free Content

[0144] Type your sequence listing free description paragraph here.

Claims

1. Use of a biomarker panel of naïve B cells in the preparation of a kit for diagnosing or monitoring the naïve state of B cells, or for diagnosing or monitoring the prognosis of liver cancer, Characterized in that, The biomarker panel comprises the genes Cd83 and Irs2, or the proteins or protein fragments expressed by said genes.

2. The use according to claim 1, Characterized in that, The biomarker panel further comprises at least one of the genes Ms4a4d, Cxcr4, Ccr7, Srebf1, or the proteins or protein fragments expressed by said at least one gene.

3. The use according to claim 2, Characterized in that, The biomarker panel is the genes Cd83, Irs2, Ms4a4d, Cxcr4, Ccr7 and Srebf1, or the proteins or protein fragments expressed by said genes.

4. The use according to any one of claims 1-3, Characterized in that, The liver cancer is hepatocellular carcinoma.

5. Use of a binder in the preparation of a kit for diagnosing or monitoring the naïve state of naïve B cells, or diagnosing or monitoring the prognosis of liver cancer, Characterized in that, The binder comprises a binder capable of binding to the gene Cd83 of naïve B cells or the protein or protein fragment expressed thereby, and a binder capable of binding to the gene Irs2 of CD8+ T cells or the protein or protein fragment expressed thereby.

6. The use according to claim 5, Characterized in that, The kit further comprises a binder capable of binding to the gene Ms4a4d of B cells or the protein or protein fragment expressed thereby, and / or a binder capable of binding to the gene Cxcr4 of B cells or the protein or protein fragment expressed thereby, and / or a binder capable of binding to the gene Ccr7 of B cells or the protein or protein fragment expressed thereby, and / or a binder capable of binding to the gene Srebf1 of B cells or the protein or protein fragment expressed thereby.

7. The use according to claim 5, Characterized in that, The kit comprises a binder capable of binding to the gene Cd83 of B cells or the protein or protein fragment expressed thereby, a binder capable of binding to the gene Irs2 of B cells or the protein or protein fragment expressed thereby, a binder capable of binding to the gene Ms4a4d of B cells or the protein or protein fragment expressed thereby, a binder capable of binding to the gene Cxcr4 of B cells or the protein or protein fragment expressed thereby, a binder capable of binding to the gene Ccr7 of B cells or the protein or protein fragment expressed thereby, and a binder capable of binding to the gene Srebf1 of B cells or the protein or protein fragment expressed thereby.

8. The use according to any one of claims 5-7, Characterized in that, The binder comprises one or more of nucleic acids, ligands, enzymes, substrates, antibodies.

9. A kit for diagnosing or monitoring tumor prognosis, Characterized in that, The kit contains a binder that can bind to the gene Cd83 or the protein or protein fragment expressed by B cells, and a binder that can bind to the gene Irs2 or the protein or protein fragment expressed by B cells.

10. Use of an inhibitor in the preparation of a tumor therapeutic drug, characterized in that the inhibitor inhibits the expression of a target gene or the protein expressed by the target gene, and the genes include Cd83 and Irs2; the tumor includes hepatocellular carcinoma.

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