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

Zelin Tian; Weixiang He; Jianing Tang; Xing Liao; Qian Yang; Yumin Wu; Gaosong Wu

doi:10.2147/OTT.S258439

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

Onco Targets Ther. 2020 Jul 12:13:6805-6817. doi: 10.2147/OTT.S258439. eCollection 2020.

Authors

Zelin Tian^#¹, Weixiang He^#², Jianing Tang¹, Xing Liao¹, Qian Yang¹, Yumin Wu¹, Gaosong Wu¹

Affiliations

¹ Department of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China.
² Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, People's Republic of China.

^# Contributed equally.

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.

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

Grants and funding

This study did not receive funding support.