J Cancer 2021; 12(11):3344-3353. doi:10.7150/jca.49658

Research Paper

The prediction of survival in Gastric Cancer based on a Robust 13-Gene Signature

Guoguang Wang1#, Tian Zhan1#, Fan Li1#, Jian Shen1, Xiang Gao1, Lei Xu1, Yuan Li2✉, Jianping Zhang1✉

1. Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
2. Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center For Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China.
#These authors contributed equally to this work.

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Wang G, Zhan T, Li F, Shen J, Gao X, Xu L, Li Y, Zhang J. The prediction of survival in Gastric Cancer based on a Robust 13-Gene Signature. J Cancer 2021; 12(11):3344-3353. doi:10.7150/jca.49658. Available from https://www.jcancer.org/v12p3344.htm

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Gastric cancer represents a major public health problem. Owing to the great heterogeneity of GC, conventional clinical characteristics are limited in the accurate prediction of individual outcomes and survival. This study aimed to establish a robust gene signature to predict the prognosis of GC based on multiple datasets. Initially, we downloaded raw data from four independent datasets of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and performed univariate Cox proportional hazards regression analysis to identify prognostic genes associated with overall survival (OS) from each dataset. Thirteen common genes from four datasets were screened as candidate prognostic signatures. Then, a risk score model was developed based on this 13‑gene signature and validated by four independent datasets and the entire cohort. Patients with a high-risk score had poorer OS and recurrence-free survival (RFS). Multivariate regression and stratified analysis revealed that the 13-gene signature was not only an independent predictive factor but also associated with recurrence when adjusting for other clinical factors. Furthermore, in the high-risk group, gene set enrichment analysis (GSEA) showed that the mTOR signaling pathway and MAPK signaling pathway were significantly enriched. The present study provided a robust and reliable gene signature for prognostic prediction of both OS and RFS of patients with GC, which may be useful for delivering individualized management of patients.

Keywords: drug resistance, gastric cancer, Kyoto Encyclopedia of Genes and Genomes pathway, recurrence, prognostic signature