Abstract

Although the role of T cells in tumor immunity and modulation of the tumor microenvironment (TME) has been extensively studied, their precise involvement in gastric adenocarcinoma remains inadequately explored. In this work, we analyzed the single-cell RNA sequencing data set in GSE183904 and identified 322 T cell marker genes using the “FindAllMarkers” method of the R package “Seurat”. STAD patients in the TCGA database were divided into high-risk and low-risk categories based on risk scores. The five-gene prediction signature based on T cell marker genes can predict the prognosis of gastric cancer patients with high accuracy. In the training cohort, the areas under the receiver operating characteristic (ROC) curve were 0.667, 0.73, and 0.818 at 1, 3, and 5 years. External validation of the predictive signature was also performed using multiple clinical subgroups and GEO cohorts. To help with practical application, a diagnostic model was created that shows values of 0.732, 0.752, and 0.816 for the relevant areas under the ROC curve at 1, 3, and 5 years. The T cell marker genes identified in this study may serve as potential therapeutic targets, and the developed predictive signatures and nomograms may aid in the clinical management of gastric cancer.

Details

Title
Identification and validation of a T cell marker gene-based signature to predict prognosis and immunotherapy response in gastric cancer
Author
Zhong, Jinlin 1 ; Pan, Rongling 1 ; Gao, Miao 1 ; Mo, Yuqian 1 ; Peng, Xin 1 ; Liang, Guoxiao 1 ; Chen, Zixuan 1 ; Du, Jinlin 1 ; Huang, Zhigang 2 

 Guangdong Medical University, Department of Epidemiology and Health Statistics, School of Public Health, Dongguan, People’s Republic of China (GRID:grid.410560.6) (ISNI:0000 0004 1760 3078) 
 Guangdong Medical University, Department of Epidemiology and Health Statistics, School of Public Health, Dongguan, People’s Republic of China (GRID:grid.410560.6) (ISNI:0000 0004 1760 3078); Key Laboratory of Noncommunicable Diseases Control and Health Data Statistics of Guangdong Medical University, Dongguan, People’s Republic of China (GRID:grid.410560.6) (ISNI:0000 0004 1760 3078) 
Pages
21357
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2897532386
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.