构建胃癌中CD8+T细胞相关预后模型并筛选治疗药物OACSTPCD

Objective:Gastric cancer is a highly heterogeneous malignant tumor with a high mortality rate.Patients often present at advanced stages with poor prognosis.CD8+T cells play a crucial role in recognizing and eliminating tumor cells,significantly influencing cancer progression.This study aims to construct a prognostic model related to CD8+T cell infiltration to provide new biomarkers for prognostic assessment and objective evidence for drug therapy in gastric cancer patients. Methods:Data from 371 gastric cancer samples were downloaded from The Cancer Genome Atlas(TCGA)database as the training set,and data from 433 gastric cancer samples were downloaded from The Gene Expression Omnibus(GEO)database as the test set.The relative abundance of CD8+T cells in the training set gastric cancer samples was calculated,dividing samples into high and low CD8+T cell content groups.Kaplan-Meier analysis was used to compare the survival relationship between the 2 groups.Weighted gene co-expression network analysis(WGCNA)was conducted on the training set data to identify gene modules most correlated with CD8+T cells.Unifactor Cox regression analysis,least absolute shrinkage and selection operator(LASSO)regression analysis,and multi-factor Cox regression analysis were performed to select prognosis-related genes and construct a prognostic risk score model.The model was applied to calculate risk scores for patients in both the training set and the test set,categorizing patients into high and low-risk groups,and internally and externally tested.Validation of model genes was performed using the tumor immune single-cell hub 2(TISCH2)database and The Human Protein Atlas(HPA)database.Clinicopathological feature analysis,functional enrichment analysis,immune correlation analysis,and analysis of sensitivity to chemotherapeutic drugs were conducted in conjunction with the model. Result:Survival analysis indicated a poorer prognosis in the CD8+T cell low-content group.WGCNA analysis identified the Ebisque4 gene module as most correlated with CD8+T cells.9 independent prognostic genes were selected through Univariate Cox regression analysis,LASSO Logistic regression analysis,and multivariate Cox regression analysis to construct the prognostic risk score model.Internal and external testing demonstrated strong predictive capability of the model.Validation using the TISCH2 database showed differential expression patterns of model genes in the tumor microenvironment,while validation using the HPA database showed consistency in gene expression with the prognostic model.Clinicopathological feature analysis revealed a correlation between risk score and tissue infiltration depth.Functional enrichment analysis showed enrichment of molecular interaction pathways in the high-risk group and metabolic pathways in the low-risk group.Immune correlation analysis revealed differences in immune cells,immune functions,and immune checkpoints between high and low-risk groups.Sensitivity analysis of chemotherapeutic drugs indicated higher sensitivity of the high-risk group to pazopanib,and higher sensitivity of the low-risk group to cetuximab. Conclusion:CD8+T cell infiltration in the tumor microenvironment significantly influences the prognosis of gastric cancer patients.The prognostic model based on CD8+T cell-related genes demonstrates universality and clinical applicability,providing important guidance for drug therapy in gastric cancer patients.