Literature DB >> 32764968

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

Zelin Tian1, Weixiang He2, Jianing Tang1, Xing Liao1, Qian Yang1, Yumin Wu1, Gaosong Wu1.   

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.
© 2020 Tian et al.

Entities:  

Keywords:  GEO; Oncomine; WGCNA; breast cancer; prognosis

Year:  2020        PMID: 32764968      PMCID: PMC7367932          DOI: 10.2147/OTT.S258439

Source DB:  PubMed          Journal:  Onco Targets Ther        ISSN: 1178-6930            Impact factor:   4.147


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