Gastric cancer prognosis-related single nucleotide polymorphisms: a genome-wide association analysis

Abstract

ObjectiveTo explore the association of genome-wide single nucleotide polymorphisms (SNPs) with the prognosis of gastric cancer (GC) for identifying new prognostic biomarkers and developing personalized treatment strategies for GC. MethodsA follow-up study was conducted among 251 first diagnosed GC patients recruited in a county hospital of Fujian province from April 2013 to December 2017. Kaplan-Meier method was used to calculate 5-year survival rate of the patients and genome-wide SNPs loci of the patients were detected with whole-genome chip. Cox proportional hazards regression model was applied to analyze the association of SNPs loci with GC prognosis. Results Of all the patients, 218 (86.85%) completed the follow-up and were included in the analysis. The 1-, 3-, and 5-year survival rate of the patients were 61.5%, 40.8%, and 37.5%, respectively, and the median survival time was 22.0 months. Univariate Cox proportional hazards regression analysis showed that aged \begin{document}$\geqslant $\end{document} 65 years and at intermediate and advanced tumor node metastasis (TNM) stage were risk factors for poor prognosis of GC; while, undergoing surgery and chemotherapy were protective factors against poor prognosis. The genome-wide association study (GWAS) identified 165 genetic loci significantly associated with GC prognosis, which involved 33 functional regions corresponding to 55 functional genes. The function genes were mainly involved in growth factor response pathway, immune escape, and inflammation-related pathways and the expression of 7 of functional genes correlated significantly with GC prognosis based on the information from The Cancer Genome Atlas (TCGA) database. ConclusionThe SNPs are closely related to the prognosis of GC and the GC prognosis-related functional genes are widely involved in biological processes of cancer cell proliferation, immunity and inflammation.

Keywords

• gastric cancer
• prognosis
• genome-wide association analysis