Associating transcriptional modules with colon cancer survival through weighted gene co-expression network analysis

BMC Genomics

Research Article

Rong Liu¹  Wei Zhang¹  Hong-Hao Zhou¹  Zhao-Qian Liu¹ 

[1] Department of Clinical Pharmacology, Xiangya Hospital, Central South University, 410008, Changsha, People’s Republic of China;Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, 410078, Changsha, People’s Republic of China;

关键词: Colon cancer;    Gene expression profiling;    Systems biology;    WGCNA;    Biomarker;   

DOI  :  10.1186/s12864-017-3761-z

 received in 2016-05-19, accepted in 2017-05-03,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundColon cancer (CC) is a heterogeneous disease influenced by complex gene networks. As such, the relationship between networks and CC should be elucidated to obtain further insights into tumour biology.ResultsWeighted gene co-expression network analysis, a powerful technique used to extract co-expressed gene networks from mRNA expressions, was conducted to identify 11 co-regulated modules in a discovery dataset with 461 patients.A transcriptional module enriched in cell cycle processes was correlated with the recurrence-free survival of the CC patients in the discovery (HR = 0.59; 95% CI = 0.42–0.81) and validation (HR = 0.51; 95% CI = 0.25–1.05) datasets. The prognostic potential of the hub gene Centromere Protein-A (CENPA) was also identified and the upregulation of this gene was associated with good survival. Another cell cycle phase-related gene module was correlated with the survival of the patients with a KRAS mutation CC subtype. The downregulation of several genes, including those found in this co-expression module, such as cyclin-dependent kinase 1 (CDK1), was associated with poor survival.ConclusionNetwork-based approaches may facilitate the discovery of biomarkers for the prognosis of a subset of patients with stage II or III CC, these approaches may also help direct personalised therapies.

【 授权许可】

CC BY   
© The Author(s). 2017