Weighted correlation network analysis of triple-negative breast cancer progression: Identifying specific modules and hub genes based on the GEO and TCGA database.

ABSTRACT: Triple-negative breast cancer (TNBC) represents an aggressive malignancy of frequent high histologic grade with no effective specific targeted therapies. The present study aimed to identify specific modules and hub genes that may influence the progression of TNBC. The key words 'breast cancer' were used to search microarray datasets in the Gene Expression Omnibus and The Cancer Genome Atlas databases that included 5 datasets. A total of 11 co-expression modules were constructed based on the expression levels of 5,782 genes obtained from 456 patients with TNBC using the weighted correlation network analysis (WGCNA). The results demonstrated that the red module was significantly associated with relapse-free survival (RFS) in patients with TNBC [hazard ratio (HR)=0.381, 95% confidence interva

SUBMITTER: Lan L 

PROVIDER: S-EPMC6607224 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature