ArticleScientific reports2023
Identification and validation of a T cell marker gene-based signature to predict prognosis and immunotherapy response in gastric cancer.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 9 citations in OpenAlex.
- The immune signatures predict gastric/gastroesophageal junction cancer response to first-line anti-PD-1 blockade or chemotherapy.BMC cancer · 2025Trial
- sigNATURE maps cohort-specific T-cell states to reproducible programs of ICI response.bioRxiv : the preprint server for biology · 2026Article
- Transcriptomic Analysis Reveals the Role ofHuman mutation · 2026Article
- Identification ofEndocrine, metabolic & immune disorders drug targets · 2026Article
- Endothelial-specific genes TMTC1, RPS6KA2, and F8 are downregulated in hypertrophic cardiomyopathy.European journal of medical research · 2025Article
- Identification of prognostic biomarkers associated with T and melanoma cell subpopulations in melanoma through integrating machine learning and multiomics.Discover oncology · 2025Article
- Pyroptosis drives tumor progression and immune evasion in Hepatocellular Carcinoma: a single-cell and spatial transcriptomic study.Discover oncology · 2025Article
- Prognostic development and validation of a prediction model based on major histocompatibility complex-related differentially expressed genes in stomach adenocarcinoma.Translational cancer research · 2025Article
- Single-cell RNA-sequencing and genome-wide Mendelian randomisation along with abundant machine learning methods identify a novel B cells signature in gastric cancer.Discover oncology · 2025Article
- Application and progress of nomograms in gastric cancer.Frontiers in medicine · 2025Review
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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