Scientific Reports (Dec 2023)

Identification and validation of a T cell marker gene-based signature to predict prognosis and immunotherapy response in gastric cancer

  • Jinlin Zhong,
  • Rongling Pan,
  • Miao Gao,
  • Yuqian Mo,
  • Xin Peng,
  • Guoxiao Liang,
  • Zixuan Chen,
  • Jinlin Du,
  • Zhigang Huang

DOI
https://doi.org/10.1038/s41598-023-48930-8
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 12

Abstract

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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.