Exploration of signature based on T cell-related genes in stomach adenocarcinoma by analysis of single cell sequencing data.

gastric cancer immune microenvironment immunotherapy prognosis single-cell sequencing

Journal

Aging
ISSN: 1945-4589
Titre abrégé: Aging (Albany NY)
Pays: United States
ID NLM: 101508617

Informations de publication

Date de publication:
25 Mar 2024
Historique:
received: 10 10 2023
accepted: 29 12 2023
medline: 27 3 2024
pubmed: 27 3 2024
entrez: 27 3 2024
Statut: aheadofprint

Résumé

Gastric cancer (GC) is a leading reason for the death of cancer around the world. The immune microenvironment counts a great deal in immunotherapy of advanced tumors, in which T cells exert an indispensable function. Single-cell RNA sequencing data were utilized to characterize the expression profile of T cells, followed by T cell-related genes (TCRGs) to construct signature and measure differences in survival time, enrichment pathways, somatic mutation status, immune status, and immunotherapy between groups. The complex tumor microenvironment was analyzed by scRNA-seq data of GC patients. We screened for these T cell signature expression genes and the TCRGs-based signature was successfully constructed and relied on the riskscore grouping. In gene set enrichment analysis, it was shown that pro-tumor and suppressive immune pathways were more abundant in the higher risk group. We also found different infiltration of immune cells in two groups, and that the higher risk samples had a poorer response to immunotherapy. Our study established a prognostic model, in which different groups had different prognosis, immune status, and enriched features. These results have provided additional insights into prognostic evaluation and the development of highly potent immunotherapies in GC.

Sections du résumé

BACKGROUND BACKGROUND
Gastric cancer (GC) is a leading reason for the death of cancer around the world. The immune microenvironment counts a great deal in immunotherapy of advanced tumors, in which T cells exert an indispensable function.
METHODS METHODS
Single-cell RNA sequencing data were utilized to characterize the expression profile of T cells, followed by T cell-related genes (TCRGs) to construct signature and measure differences in survival time, enrichment pathways, somatic mutation status, immune status, and immunotherapy between groups.
RESULTS RESULTS
The complex tumor microenvironment was analyzed by scRNA-seq data of GC patients. We screened for these T cell signature expression genes and the TCRGs-based signature was successfully constructed and relied on the riskscore grouping. In gene set enrichment analysis, it was shown that pro-tumor and suppressive immune pathways were more abundant in the higher risk group. We also found different infiltration of immune cells in two groups, and that the higher risk samples had a poorer response to immunotherapy.
CONCLUSION CONCLUSIONS
Our study established a prognostic model, in which different groups had different prognosis, immune status, and enriched features. These results have provided additional insights into prognostic evaluation and the development of highly potent immunotherapies in GC.

Identifiants

pubmed: 38536020
pii: 205687
doi: 10.18632/aging.205687
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Huimei Wang (H)

Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China.

Nan An (N)

Department of Gastric Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China.

Aiyue Pei (A)

Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China.

Yongxiao Sun (Y)

Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China.

Shuo Li (S)

Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China.

Si Chen (S)

Department of Colorectal and Anal Surgery, General Surgery Center, The First Hospital of Jilin University, Changchun, China.

Nan Zhang (N)

Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China.

Classifications MeSH