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Identification of Important Modules and Biomarkers in Breast Cancer Based on WGCNA.


ABSTRACT: Introduction:Breast cancer (BRCA) has the highest incidence among female malignancies, and the prognosis for these patients remains poor. Materials and Methods:In this study, core modules and central genes related to BRCA were identified through a weighted gene co-expression network analysis (WGCNA). Gene expression profiles and clinical data of GSE25066 were obtained from the Gene Expression Omnibus (GEO) database. The result was validated with RNA-seq data from The Cancer Genome Atlas (TCGA) and Oncomine database. The top 30 key module genes with the highest intramodule connectivity were selected as the core genes (R2 = 0.40). Results:According to TCGA and Oncomine datasets, seven genes were selected as candidate hub genes. Following further experimental verification, four hub genes (FAM171A1, NDFIP1, SKP1, and REEP5) were retained. Conclusion:We identified four hub genes as candidate biomarkers for BRCA. These hub genes may provide a theoretical basis for targeted therapy against BRCA.

SUBMITTER: Tian Z 

PROVIDER: S-EPMC7367932 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification of Important Modules and Biomarkers in Breast Cancer Based on WGCNA.

Tian Zelin Z   He Weixiang W   Tang Jianing J   Liao Xing X   Yang Qian Q   Wu Yumin Y   Wu Gaosong G  

OncoTargets and therapy 20200712


<h4>Introduction</h4>Breast cancer (BRCA) has the highest incidence among female malignancies, and the prognosis for these patients remains poor.<h4>Materials and methods</h4>In this study, core modules and central genes related to BRCA were identified through a weighted gene co-expression network analysis (WGCNA). Gene expression profiles and clinical data of GSE25066 were obtained from the Gene Expression Omnibus (GEO) database. The result was validated with RNA-seq data from The Cancer Genome  ...[more]

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