A seven-gene signature predicts overall survival of patients with colorectal cancer
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Huarong Chen1,*, Xiaoqiang Sun2,*, Weiting Ge1, Yun Qian3, Rui Bai1 and Shu Zheng1
1Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education, Key Laboratory of Molecular Biology in Medical Sciences, Zhejiang Province, China), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, China
2Zhong-shan School of Medicine, Sun Yat-Sen University, Guangzhou, 510089, China
3Department of Gastroenterology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Institute of Gastroenterology, Zhejiang University, Hangzhou, Zhejiang, 310009, China
*These authors contributed equally to this work
Shu Zheng, email: firstname.lastname@example.org
Keywords: colorectal cancer, gene expression microarray, overall survival
Received: May 09, 2016 Accepted: June 30, 2016 Published: August 01, 2016
Colorectal cancer (CRC) is a major cause of global cancer mortality. Gene expression profiles can help predict prognosis of patients with CRC. In most of previous studies, disease recurrence was analyzed as the survival endpoint. Thus we aim to build a robust gene signature for prediction of overall survival (OS) in patients with CRC. Fresh frozen CRC tissues from 64 patients were analyzed using Affymetrix HG-U133plus 2.0 gene arrays. By performing univariate survival analysis, 6487 genes were found to be associated with the OS in our cohort. KEGG analysis revealed that these genes were mainly involved in pathways such as endocytosis, axon guidance, spliceosome, Wnt signalling and ubiquitin mediated proteolysis. A seven-gene signature was further selected by a robust likelihood-based survival modelling approach. The prognostic model of seven-gene signature (NHLRC3, ZDHHC21, PRR14L, CCBL1, PTPRB, PNPO, and PPIP5K2) was constructed and weighted by regression coefficient, which divided patients into high- and low-risk groups. The OS for patients in high-risk group was significantly poorer compared with patients in low-risk group. Moreover, all seven genes were found to be differentially expressed in CRC tissues as compared with adjacent normal tissues, indicating their potential role in CRC initiation and progression. This seven-gene signature was further validated as an independent prognostic marker for OS prediction in patients with CRC in other two independent cohorts. In short, we developed a robust seven-gene signature that can predict the OS for CRC patients, providing new insights into identification of CRC patients with high risk of mortality.
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