Five gene signatures were identified in the prediction of overall survival in resectable pancreatic cancer

Chao Wu,Zuowei Wu,Bole Tian

doi:10.1186/s12893-020-00856-y

Chao Wu, Zuowei Wu + Show 1 more

Open Access

https://doi.org/10.1186/s12893-020-00856-y

Copy DOI

Abstract

BackgroundAlthough genes have been previously detected in pancreatic cancer (PC), aberrant genes that play roles in resectable pancreatic cancer should be further assessed.MethodsMessenger RNA samples and clinicopathological data corrected with PC were downloaded from The Cancer Genome Atlas (TCGA). Resectable PC patients were randomly divided into a primary set and a validation set. Univariable Cox regression analysis, lasso-penalized Cox regression analysis, and multivariable Cox analysis were implemented to distinguish survival-related genes (SRGs). A risk score based on the SRGs was calculated by univariable Cox regression analysis. A genomic-clinical nomogram was established by integrating the risk score and clinicopathological data to predict overall survival (OS) in resectable PC.ResultsFive survival-related genes (AADAC, DEF8, HIST1H1C, MET, and CHFR) were significantly correlated with OS in resectable PC. The resectable PC patients, based on risk score, were sorted into a high-risk group that showed considerably unfavorable OS (p < 0.001) than the low-risk group, in both the primary set and the validation set. The concordance index (C-index) was calculated to evaluate the predictive performance of the nomogram were respectively in the primary set [0.696 (0.608–0.784)] and the validation set [0.682 (0.606–0.758)]. Additionally, gene set enrichment Analysis discovered several meaningful enriched pathways.ConclusionOur study identified five prognostic gene biomarkers for OS prediction and which facilitate postoperative molecular target therapy for the resectable PC, especially the nomic-clinical nomogram which may be used as an effective model for the postoperative OS evaluation and also an optimal therapeutic tool for the resectable PC.

Highlights

Pancreatic cancer is a malignant neoplasm with a high incidence and mortality worldwide [1, 2]
Building and validation of survival-related gene set One hundred twenty-one patients and 1055 genes were involved in the primary set to build the prognostic model
The risk score was calculated as 0.022 × Expression of Arylacetamide deacetylase gene (AADAC)-0.320 × Expression of DEF8+ 0.007 × Expression of HIST1H1C + 0.041 × Expression of MET-0.989 × Expression of CHFR

Summary

Introduction

Pancreatic cancer is a malignant neoplasm with a high incidence and mortality worldwide [1, 2]. Accumulating studies have indicated that aberrant genes play important roles in the initiation, progression, and prognosis of tumors and have been explored as cancer biomarkers in past decades [7,8,9,10,11,12]. These aberrant gene have been utilized to establish predictive models for PC prognosis prediction, no consensus on their effectiveness has yet been reached. In this study, we aimed to identify significant aberrant genes and clinicopathological data that could be used to establish a genomic-clinical nomogram, which in turn to predict the prognosis of PC and develop an optimal therapeutic schedule for resectable PC patients. Genes have been previously detected in pancreatic cancer (PC), aberrant genes that play roles in resectable pancreatic cancer should be further assessed

Objectives

Methods

Results

Conclusion