The predictive effect of immune therapy and chemotherapy under T cell-related gene prognostic index for Gastric cancer

Abstract

Background: Gastric cancer (GC) is one of the most common malignancies in the human digestive tract. CD4+T cells can eliminate tumor cells directly through the mechanism of cytolysis, they can also indirectly attack tumor cells by regulating the tumor TME. A prognostic model of CD4+T cells is urgently needed to improve treatment strategies and explore the specifics of this interaction between CD4+T cells and gastric cancer cells. Methods: The detailed data of GC samples were downloaded from the Cancer Genome Atlas (TCGA), GSE66229, and GSE84437 datasets. CD4+ T cell-related genes were identified to construct a risk-score model by using the Cox regression method and validated with the Gene Expression Omnibus (GEO) dataset. In addition, postoperative pathological tissues of 139 gastric cancer patients were randomly selected for immunohistochemical staining, and their prognostic information were collected for external verification. Immune and molecular characteristics of these samples and their predictive efficacy in immunotherapy and chemotherapy were analysed.Results: The training set and validation set had consistent results, with GC patients of high PROC and SERPINE1 expression having poorer prognosis. In order to improve their clinical application value, we constructed a risk scoring model and established a high-precision nomogram. Low-risk patients had a better overall survival (OS) than high-risk patients, consistent with the results from the GEO cohort. Furthermore, the risk-score model can predict infiltration of immune cells in the tumor microenvironment of GC, as well as the response of immunotherapy. Correlations between the abundance of immune cells with PROC and SERPINE1 genes were shown in the prognostic model according to the training cohort. Finally, sensitive drugs were identified for patients in different risk subgroup.Conclusion: The risk model not only provides a basis for better prognosis in GC patients, but also is a potential prognostic indicator to distinguish the molecular and immune characteristics of the tumor, and its response to immune checkpoint inhibitor (ICI) therapy and chemotherapy.

Unravelling diagnostic clusters and immune landscapes of disulfidptosis patterns in gastric cancer through bioinformatic assay

“…Previous studies have shown that abundant immune cells are infiltrated in the tumor microenvironment of GC, and the number and phenotype of immune cell subpopulations in GC tissues are closely correlated with the development and prognosis of GC patients [ 35 ]. CD4 T cells are a special type of T cells targeting tumor cells in various ways, which can directly eliminate tumor cells through cytolysis, or indirectly kill tumor cells by increasing the number of B Cells and CTL (Cytotoxic T Lymphocytes) responses [ 36 , 37 ]. Existing study reveals that DNA damage repair and immunogenic tumor microenvironment in GC could be characterized by activated subsets of CD4 T cells [ 38 ].…”

Unravelling infiltrating T‐cell heterogeneity in kidney renal clear cell carcinoma: Integrative single‐cell and spatial transcriptomic profiling

“…The progression of renal clear cell carcinoma (RCCC) is intricately linked to the immune system, with a particular emphasis on the distribution and function of T cells within the tumour microenvironment, exerting a direct influence on RCCC's growth and dissemination. 9 , 10 , 11 However, the heterogeneity within these T‐cell populations remains a subject warranting more comprehensive exploration.…”

A tumor-associated endothelial signature score model in immunotherapy and prognosis across pan-cancers

“…Glypican-3 expression in cancer-associated fibroblasts is a critical prognostic biomarker for PD-1 blockage therapy in GC ( Li et al, 2023 ). The T-cell-related gene prognostic index is a potential prognostic indicator used to distinguish the response to immune checkpoint inhibitor (ICI) therapy ( Chen J. et al, 2023 ). The neutrophil-to-lymphocyte ratio is an effective biomarker used for evaluating the prognosis of GC patients who received ICI therapy ( Li and Pan, 2023 ).…”