Glycolysis-Based Genes Associated with the Clinical Outcome of Pancreatic Ductal Adenocarcinoma Identified by The Cancer Genome Atlas Data Analysis
Guangwei Tian, Guang Li, Peipei Liu, Zihui Wang, Nan Li
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the deadly tumors in digestive tract tumors. Although there has been advancement in PDAC treatment, its prognosis still remains unsatisfactory, mainly because of dismal diagnosis. This article aims to develop new prognostic factors related to energy metabolism in PDAC and to use these genes for novel risk stratification. Hundred fifty messenger RNA (mRNA) expression profiles and clinicopathological data of PDAC were downloaded from The Cancer Genome Atlas dataset. The glycolysis pathway was the significant pathway based on the gene set enrichment analysis. We chose the glycolysis pathway-related 176 genes for further analysis. Multivariate Cox regression analysis and forward stepwise Cox regression model established a novel three-gene glycolytic signature (including MET, B3GNT3, and SPAG4) for PDAC patients' prognosis prediction. All 150 patients were classified into two groups by the median risk score. High-risk group had a worse outcome compared to the low-risk group. The risk score was also significantly correlated with age and radiotherapy. A nomogram, including the glycolytic gene signature, has shown some clinical net benefit for overall survival prediction. We also validated the validity and reliability in the Puleo dataset. This novel gene expression signature may be involved in the pathophysiology and used for risk stratification and prognosis prediction in PDAC.