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Genome-scale analysis to identify prognostic markers in patients with early-stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy

Authors Liao X, Huang K, Huang R, Liu X, Han C, Yu L, Yu T, Yang C, Wang X, Peng T

Received 25 May 2017

Accepted for publication 12 August 2017

Published 12 September 2017 Volume 2017:10 Pages 4493—4506


Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Akshita Wason

Peer reviewer comments 3

Editor who approved publication: Dr Yao Dai

Xiwen Liao,1,* Ketuan Huang,1,* Rui Huang,2 Xiaoguang Liu,1,3 Chuangye Han,1 Long Yu,1,4 Tingdong Yu,1 Chengkun Yang,1 Xiangkun Wang,1 Tao Peng1

1Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, 2Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 3Department of Hepatobiliary Surgery, Affiliated Hospital of Guangdong Medical University, Zhanjiang, 4Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China

*These authors contributed equally to this work

Background: Molecular analysis is a promising source of clinically useful prognostic biomarkers. The aim of this investigation was to identify prognostic biomarkers for patients with early-stage pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy.
Methods: An RNA sequencing dataset of PDAC was obtained from The Cancer Genome Atlas. Survival analysis and weighted gene co-expression network analysis were used to investigate the prognostic markers of early-stage PDAC after pancreaticoduodenectomy.
Results: Using whole genome expression level screening, we identified 1,238 markers that were related to the prognosis of PDAC after pancreaticoduodenectomy, and identified 9 hub genes (ARHGAP30, HCLS1, CD96, FAM78A, ARHGAP15, SLA2, CD247, GVINP1, and IL16) using the weighted gene co-expression network analysis approach. We also constructed a signature comprising the 9 hub genes and weighted by the regression coefficient derived from a multivariate Cox proportional hazards regression model to divide patients into a high-risk group, with increased risk of death, and a low-risk group, with significantly improved overall survival (adjusted P=0.026, adjusted HR =0.513, 95% CI =0.285–0.924). The prognostic signature of the 9 genes demonstrated good performance for predicting 1-year overall survival (area under the respective receiver operating characteristic curves =0.641).
Conclusion: Our results have provided a new prospect for prognostic biomarkers of PDAC after pancreaticoduodenectomy, and may have a value in clinical application.

Keywords: prognostic, pancreatic ductal adenocarcinoma, TCGA, WGCNA, pancreati­coduodenectomy

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