| Biomarker | EBV (Epstein-Barr virus) | Full name | Epstein-Barr virusMMMMMMMMM | Molecular Type | Viral nucleic acid (DNA/RNA) |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Diagnosis, prognosis, and prediction | ||
| Disease(or Constitution) | Gastric Cancer | Disease Subtypes | Ebv-associated gastric cancer | ||
| Organ | Stomach | Test Sample / Technology Platform | Tumor tissues (EBER in situ hybridization, NGS detection of EBV DNA), serum (EBV antibody detection) | ||
| Pathobiological Mechanisms | About 10% of gastric cancer is EBV-positive. After the viral genome is integrated into host cells, the NF-κB pathway is activated by the expression of EBER and LMP1 proteins, which promotes inflammatory response and immunosuppression (such as high expression of PD-L1) | ||||
| Clinical Availability Status | Clinically useful (subtype diagnosis/immunotherapy screening) : it is used for the diagnosis of EBV-associated gastric cancer and the prediction of immunotherapy efficacy | ||||
| Notes and Dynamics | As a specific diagnostic marker for EBV-associated gastric cancer, this subtype of patients has high PD-L1 expression rate, high tumor mutation burden (TMB), and significantly better response to ICIs treatment than other subtypes, which is a dominant population marker for immunotherapy | ||||
| Biomarker | MSI (microsatellite instability) /dMMR (mismatch repair deficiency) | Full name | Microsatellite Instability / Mismatch Repair Deficiency | Molecular Type | Genomic features (DNA) |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Diagnosis, prognosis, and prediction | ||
| Disease(or Constitution) | Gastric Cancer | Disease Subtypes | MSI-H/dMMR type gastric cancer | ||
| Organ | Stomach | Test Sample / Technology Platform | Tumor tissue (IHC for MMR protein, PCR for microsatellite loci, and NGS for TMB/MSI) | ||
| Pathobiological Mechanisms | Mutations or methylation of DNA mismatch repair genes (MLH1, MSH2, MSH6, PMS2) lead to dMMR, which in turn causes microsatellite sequence instability (MSI-H). Due to the accumulation of mutations, tumor cells produce a large number of neoantigens, which are easily recognized by the immune system and have a high response rate to ICIs treatment | ||||
| Clinical Availability Status | Clinically available (immunotherapy screening) : guidelines recommend ICIs treatment, and immunotherapy is recommended for MSI-H/dMMR patients | ||||
| Notes and Dynamics | As a "dominant population" marker for immunotherapy, MSI-H/dMMR patients have an objective response rate (ORR) of 30%-50% after ICIs treatment, which is significantly better than that of the general gastric cancer population. It can be used as a core indicator for first-line immunotherapy screening and is associated with a good prognosis | ||||
| Biomarker | PD-L1 (Programmed death ligand 1) | Full name | Programmed death-ligand 1 | Molecular Type | Proteins |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Prediction, prognosis | ||
| Disease(or Constitution) | Gastric Cancer | Disease Subtypes | Intestinal-type gastric cancer/diffuse gastric cancer | ||
| Organ | Stomach | Test Sample / Technology Platform | Tumor tissue (IHC, e.g. 28-8, SP142 antibody), circulating tumor cells (CTC, flow cytometry) | ||
| Pathobiological Mechanisms | The high expression of PD-L1 in gastric cancer cells binds to PD-1 on the surface of T cells to inhibit the killing function of T cells and achieve immune escape. The expression level of PD-L1 is positively correlated with the efficacy of immune checkpoint inhibitors (ICIs) | ||||
| Clinical Availability Status | Clinical usability (immunotherapy screening) : guidelines recommend it for screening patients with ICIs treatment, and the cutoff values of different antibodies (28-8 and SP142) are different | ||||
| Notes and Dynamics | Ebv-positive and MSI-H/dMMR gastric cancer are the core predictive markers of immunotherapy, the PD-L1 expression rate is higher, and the combination of CTLA-4 inhibitors can improve the efficacy. Dynamic monitoring of PD-L1 expression can guide the adjustment of immunotherapy course, which is the key indicator for accurate screening of immunotherapy in gastric cancer | ||||
| Biomarker | HER2 (human epidermal growth factor receptor 2) | Full name | Human epidermal growth factor receptor 2 (ERBB2) | Molecular Type | Protein/nucleic acid (DNA/RNA) |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Diagnosis, prognosis, and prediction | ||
| Disease(or Constitution) | Gastric Cancer | Disease Subtypes | Intestinal-type gastric cancer/diffuse gastric cancer | ||
| Organ | Stomach | Test Sample / Technology Platform | Tumor tissues (IHC, FISH, NGS), circulating tumor DNA (ctDNA, NGS) | ||
| Pathobiological Mechanisms | Tyrosine kinase receptor ERBB2 gene encoding across a cell membrane, stomach cancer is about 10% - 20% HER2 gene amplification or protein expression, by activating MAPK, PI3K/Akt pathway drive unlimited proliferation of tumor cells, inhibit apoptosis, is the core of the HER2 targeting treatment targets | ||||
| Clinical Availability Status | Clinical availability (targeted therapy screening) : the guideline-recommended first-line detection of gastric cancer, HER2-positive patients can use targeted drugs such as trastuzumab | ||||
| Notes and Dynamics | Tumor heterogeneity should be paid attention to in the detection of precise targeted therapy for gastric cancer. Combined chemotherapy can significantly prolong the survival of patients with HER2-positive advanced gastric cancer. The mechanisms of drug resistance (such as HER2 mutation and MET amplification) are current research hotspots | ||||
| Biomarker | AFP (alpha-fetoprotein) | Full name | Alpha-fetoprotein | Molecular Type | Protein |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Diagnosis, prognosis, prediction | ||
| Disease(or Constitution) | Gastric Cancer | Disease Subtypes | Intestinal-type gastric cancer/Diffuse gastric cancer (special subtype) | ||
| Organ | Stomach | Test Sample / Technology Platform | Serum (ELISA, chemiluminescence immunoassay), tumor tissue (IHC) | ||
| Pathobiological Mechanisms | Normally synthesized by fetal liver cells, gastric cancer cells (especially hepatoid adenocarcinoma subtypes) re-express due to cell dedifferentiation, and promote tumor proliferation, invasion and liver metastasis by activating PI3K/Akt pathway. Patients with high expression of PI3K/ AKT have poor response to chemotherapy and short survival time | ||||
| Clinical Availability Status | Clinical use (subtype diagnosis/prognosis evaluation) : It is used for the diagnosis and prognosis of a special subtype of gastric cancer (hepatoid adenocarcinoma), and is not the first choice in routine gastric cancer detection | ||||
| Notes and Dynamics | It has specific diagnostic value for hepatoid adenocarcinoma and yolk sac tumor-like subtype of gastric cancer, and can predict the risk of liver metastasis. Patients with high AFP level should be preferentially screened for liver metastasis. It is a key marker for gastric cancer subtype and individualized treatment | ||||
| Biomarker | CA72-4 (carbohydrate antigen 72-4) | Full name | Carbohydrate antigen 72-4 | Molecular Type | Protein |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Diagnosis, prognosis, and monitoring | ||
| Disease(or Constitution) | Gastric Cancer | Disease Subtypes | Intestinal-type gastric cancer/diffuse type gastric cancer/mixed type gastric cancer | ||
| Organ | Stomach | Test Sample / Technology Platform | Serum (ELISA, chemiluminescence immunoassay), tumor tissue (IHC) | ||
| Pathobiological Mechanisms | Mucin-associated antigens are rarely expressed in normal tissues, but highly expressed in gastric cancer cells due to abnormal gene regulation. Mucin-associated antigens promote tumor metastasis by enhancing abnormal intercellular adhesion. The specificity of mucin-associated antigens in the diagnosis of gastric cancer (> 90%) is higher than CEA and CA19-9 | ||||
| Clinical Availability Status | Clinical availability (auxiliary diagnosis/prognosis evaluation) : routine clinical tests have low sensitivity (18%-30%) when used alone, and are often used as one of the combined detection combinations | ||||
| Notes and Dynamics | The relative specific markers of gastric cancer have better diagnostic value for gastric adenocarcinoma than for squamous cell carcinoma, and the continuous increase after surgery indicates a high risk of recurrence. The combination of CEA and CA19-9 can increase the diagnostic sensitivity to 60%-70%, which is an important supplementary indicator for the accurate diagnosis of gastric cancer | ||||
| Biomarker | CA19-9 (carbohydrate antigen 19-9) | Full name | Carbohydrate antigen 19-9 | Molecular Type | Protein |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Diagnosis, prognosis, and monitoring | ||
| Disease(or Constitution) | Gastric Cancer | Disease Subtypes | Intestinal-type gastric cancer/diffuse type gastric cancer/mixed type gastric cancer | ||
| Organ | Stomach | Test Sample / Technology Platform | Serum (ELISA, chemiluminescence immunoassay), tumor tissue (IHC) | ||
| Pathobiological Mechanisms | Glucolipid antigens on the surface of cell membrane are secreted by pancreatic and gastrointestinal epithelial cells, and abnormally synthesized by gastric cancer cells, leading to elevated serum levels. They promote tumor proliferation, invasion and chemoresistance by participating in cell signal transduction. High expression of glucolipid antigens indicates strong invasion and poor prognosis | ||||
| Clinical Availability Status | Clinical usefulness (auxiliary diagnosis/prognosis evaluation) : the positive rate of routine clinical detection items in advanced gastric cancer (18%-44%) is higher than that in the early stage, and the sensitivity of liver metastasis monitoring is higher | ||||
| Notes and Dynamics | The diagnostic specificity of CEA for gastric cancer (85%-95%) is higher than that of CEA, but about 5%-10% of patients are false negative due to negative Lewis antigen. The combination of CEA and CA72-4 can reduce missed diagnosis and is one of the core indicators for the monitoring of advanced gastric cancer | ||||
| Biomarker | CEA (carcinoembryonic antigen) | Full name | Carcinoembryonic antigen | Molecular Type | Protein |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Diagnosis, prognosis, and monitoring | ||
| Disease(or Constitution) | Gastric Cancer | Disease Subtypes | Intestinal type gastric cancer/diffuse type gastric cancer/mixed type gastric cancer | ||
| Organ | Stomach | Test Sample / Technology Platform | Serum (ELISA, chemiluminescence immunoassay), tumor tissue (IHC) | ||
| Pathobiological Mechanisms | The glycoprotein expressed in embryonic stage is low in normal adult tissues and re-expressed in gastric cancer due to abnormal cell proliferation. It is involved in tumor cell adhesion, invasion and angiogenesis. Its level is positively correlated with tumor burden, lymph node metastasis and distant metastasis risk, and can reflect treatment response and recurrence | ||||
| Clinical Availability Status | Clinical availability (auxiliary diagnosis/prognostic evaluation) : Routine clinical tests, used alone, have limited diagnostic sensitivity (4.3%-30%) and specificity, and are often combined with other markers | ||||
| Notes and Dynamics | Classic broad-spectrum tumor markers, which are widely used in the efficacy monitoring and recurrence warning of gastric cancer, can significantly improve the diagnostic accuracy when combined with CA19-9 and CA72-4. They are one of the most basic auxiliary indicators in clinical practice, but their diagnostic value for early gastric cancer is low | ||||
| Biomarker | VIT | Full name | Vitamin D-binding protein (GC protein) / Vitamin transporter protein | Molecular Type | Protein |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Risk prediction, metabolic regulation | ||
| Disease(or Constitution) | Esophageal Carcinoma | Disease Subtypes | Esophageal squamous cell carcinoma (ESCC) | ||
| Organ | Esophagus | Test Sample / Technology Platform | Tissue/plasma (MR Analysis, IHC) | ||
| Pathobiological Mechanisms | It is involved in the regulation of vitamin metabolism and cell function, and its high expression increases the risk of ESCC and promotes disease progression by regulating metabolic reprogramming of tumor cells | ||||
| Clinical Availability Status | Clinical research stage: Mendelian randomization analysis confirms the causal relationship between ESCC and metabolic regulation mechanism needs to be clarified | ||||
| Notes and Dynamics | It is a potential metabolism-related marker of ESCC, which provides ideas for metabolic intervention combined with cancer therapy | ||||
| Biomarker | CTSF | Full name | Cathepsin F | Molecular Type | Protein |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Risk prediction, protease regulation | ||
| Disease(or Constitution) | Esophageal Carcinoma | Disease Subtypes | Esophageal squamous cell carcinoma (ESCC) | ||
| Organ | Esophagus | Test Sample / Technology Platform | Tissue/plasma (MR Analysis, Western blotting) | ||
| Pathobiological Mechanisms | It is a cysteine protease, and its high expression increases the risk of ESCC. It participates in multiple processes of tumor occurrence and development through proteolysis | ||||
| Clinical Availability Status | Clinical research stage: the causal relationship has been verified by MR Analysis, and the functional mechanism research is in the basic stage | ||||
| Notes and Dynamics | To provide a new target for ESCC protease targeted therapy, its clinical application value needs to be further verified | ||||
| Biomarker | PLA2R1 | Full name | Phospholipase A2 receptor 1 | Molecular Type | Protein |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Risk prediction, immune regulation | ||
| Disease(or Constitution) | Esophageal Carcinoma | Disease Subtypes | Esophageal squamous cell carcinoma (ESCC) | ||
| Organ | Esophagus | Test Sample / Technology Platform | Tissue/plasma (MR Analysis, qPCR) | ||
| Pathobiological Mechanisms | It is involved in the regulation of phospholipid metabolism and immune response, and its high expression increases the risk of ESCC and affects disease progression by regulating the inflammatory response of tumor microenvironment | ||||
| Clinical Availability Status | Clinical research stage: Mendelian randomization analysis confirmed the causal relationship between the tumor and ESCC, and the immune regulation mechanism needs further study | ||||
| Notes and Dynamics | It is a potential risk marker related to ESCC metabolism, which provides a new direction for multi-target combined therapy | ||||
| Biomarker | HSP90B1 | Full name | Heat shock protein 90 beta family member 1 | Molecular Type | Protein |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Risk prediction, protein folding regulation | ||
| Disease(or Constitution) | Esophageal Carcinoma | Disease Subtypes | Esophageal squamous cell carcinoma (ESCC) | ||
| Organ | Esophagus | Test Sample / Technology Platform | Tissue/plasma (MR Analysis, IHC) | ||
| Pathobiological Mechanisms | It is involved in protein folding and stability, high expression increases the risk of ESCC, and promotes disease progression by regulating tumor cell stress response and survival | ||||
| Clinical Availability Status | Clinical research phase: the causal relationship has been verified by MR Analysis, and related targeted inhibitors are being explored | ||||
| Notes and Dynamics | This study provides new ideas for the targeted molecular chaperone therapy of ESCC, which has certain clinical transformation potential | ||||
| Biomarker | MMP10 | Full name | Matrix metalloproteinase-10 | Molecular Type | Proteins |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Risk prediction, invasion and metastasis regulation | ||
| Disease(or Constitution) | Esophageal Carcinoma | Disease Subtypes | Esophageal squamous cell carcinoma (ESCC) | ||
| Organ | Esophagus | Test Sample / Technology Platform | Tissue/plasma (MR Analysis, Western blotting) | ||
| Pathobiological Mechanisms | It is involved in the degradation of extracellular matrix and tumor invasion and metastasis, and its high expression can increase the risk of ESCC and promote disease progression by regulating tumor microenvironment remodeling | ||||
| Clinical Availability Status | Clinical research stage: Mendelian randomization analysis confirmed its causal relationship with ESCC, and the mechanism was further studied | ||||
| Notes and Dynamics | It is a key marker related to ESCC invasion and metastasis, which provides a potential target for anti-metastatic therapy | ||||
| Biomarker | IGLV7-43 | Full name | Immunoglobulin lambda variable 7-43 | Molecular Type | Nucleic acid (immunoglobulin gene) |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Prognosis | ||
| Disease(or Constitution) | Esophageal Carcinoma | Disease Subtypes | Esophageal squamous cell carcinoma (ESCC) | ||
| Organ | Esophagus | Test Sample / Technology Platform | Tissues (qPCR, sequencing) | ||
| Pathobiological Mechanisms | It belongs to λ type immunoglobulin light chain. Its low expression is related to the poor prognosis of ESCC patients and participates in the regulation of tumor-specific immune response | ||||
| Clinical Availability Status | Clinical research stage: As an important part of the prognostic model, its immune regulatory mechanism needs to be further elucidated | ||||
| Notes and Dynamics | It provides new molecular markers for immune-related prognosis evaluation of ESCC and is expected to optimize the existing prognostic prediction system | ||||
| Biomarker | MAP3K8 | Full name | Mitogen-activated protein kinase kinase kinase 8 | Molecular Type | Protein |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Prognosis, immune regulation | ||
| Disease(or Constitution) | Prognosis, immune regulation | Disease Subtypes | Esophageal squamous cell carcinoma (ESCC) | ||
| Organ | Esophagus | Test Sample / Technology Platform | Tissue (qPCR, IHC) | ||
| Pathobiological Mechanisms | It is a serine/threonine kinase involved in immune checkpoint, chemokine and receptor regulation. High expression is associated with poor prognosis of ESCC patients. It participates in tumor-related inflammation through NF-κB and Toll-like receptor pathways | ||||
| Clinical Availability Status | Clinical research phase: immune-related prognostic models of ESCC have been incorporated to verify their correlation with immune infiltration | ||||
| Notes and Dynamics | It is a key prognostic marker related to ESCC inflammation, which provides potential targets for targeting inflammatory pathway therapy | ||||
| Biomarker | PD-L1 | Full name | Programmed death-ligand 1 | Molecular Type | Protein |
| Molecular Formula | Molecular Weight | Core Functional Dimensions | Prediction and diagnosis of immunotherapy efficacy | ||
| Disease(or Constitution) | Esophageal Carcinoma | Disease Subtypes | Esophageal squamous cell carcinoma (ESCC) | ||
| Organ | Esophagus | Test Sample / Technology Platform | Tissue (IHC, SP263 assay) | ||
| Pathobiological Mechanisms | Combined with PD-1, it inhibits the activation of T cells and induces their apoptosis, helping tumor cells to evade immune surveillance. Its expression level directly affects the therapeutic effect of immune checkpoint inhibitors | ||||
| Clinical Availability Status | Clinical application/guideline recommendation: CPS and TAP scores have been used as core markers for predicting the efficacy of immunotherapy in ESCC, and are commonly used evaluation criteria | ||||
| Notes and Dynamics | CPS and TAP score are the key biomarkers for ESCC immunotherapy, and their combination with other biomarkers can improve the accuracy of efficacy prediction | ||||