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

Wang, Guoguang; Zhan, Tian; Li, Fan; Shen, Jian; Gao, Xiang; Xu, Lei; Li, Yuan; Zhang, Jianping

doi:10.7150/jca.49658



International Journal of Biological Sciences

International Journal of Medical Sciences

Theranostics

Journal of Genomics

Nanotheranostics

Global reach, higher impact

Full Text | PDF

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

Research Paper

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

Guoguang Wang^1#, Tian Zhan^1#, Fan Li^1#, Jian Shen¹, Xiang Gao¹, Lei Xu¹, Yuan Li^2✉, Jianping Zhang^1✉

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.

Citation:

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. https://www.jcancer.org/v12p3344.htm

Other styles

Abstract

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

Citation styles

APA

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

ACS

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.

NLM

CSE

Wang G, Zhan T, Li F, Shen J, Gao X, Xu L, Li Y, Zhang J. 2021. The prediction of survival in Gastric Cancer based on a Robust 13-Gene Signature. J Cancer. 12(11):3344-3353.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.