Research Papers:
A novel messenger RNA signature as a prognostic biomarker for predicting relapse in pancreatic ductal adenocarcinoma
PDF | HTML | Supplementary Files | How to cite
Metrics: PDF 1882 views | HTML 2687 views | ?
Abstract
Guodong Shi1,2,*, Jingjing Zhang1,2,*, Zipeng Lu1,2,*, Dongfang Liu1,2,*, Yang Wu1,2, Pengfei Wu1,2, Jie Yin1,2, Hao Yuan1,2, Qicong Zhu1,2, Lei Chen1,2, Yue Fu1,2, Yunpeng Peng1,2, Yan Wang3, Kuirong Jiang1,2 and Yi Miao1,2
1Pancreas Center, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
2Pancreas Institute of Nanjing Medical University, Nanjing 210029, China
3Endoscopy Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
*These authors contributed equally to this work
Correspondence to:
Kuirong Jiang, email: [email protected]
Yi Miao, email: [email protected]
Keywords: predictive signature; biomarker; bioinformatics; pancreatic ductal adenocarcinoma; relapse-free survival
Received: June 16, 2017 Accepted: November 04, 2017 Published: December 02, 2017
ABSTRACT
Pancreatic ductal adenocarcinoma (PDAC) death rate and recurrence rate have remained obstinately high. Current methods can not satisfy the need of predicting cancer relapse accurately. Utilizing expression profiles of 10 GEO datasets (N = 774), we identified 154 differentially expressed genes (DEGs) between PDAC and normal pancreas tissue or paracancerous tissue. Next we built a 16-mRNA-based signature by means of the LASSO COX regression model. We also validated the prognostic value of the signature. Patients were classified into high-risk and low-risk group according to the signature risk score; 1 year RFS was 45% (95% CI: 31.6%–63.9%) for high-risk group in contrast to 92.5% (95% CI: 86.3%–99.1%) for low-risk group. Moreover, it could predict RFS well in cases with the receipt of different treatment modalities. The 16-mRNA-based signature was an independent and powerful prognostic biomarker for RFS for PDAC patients (HR = 7.74, 95% CI: 3.25–18.45, p < 0.0001).
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 4.0 License.
PII: 22861