Identification of Important Modules and Biomarkers in Breast Cancer Based on WGCNA
Received 16 April 2020
Accepted for publication 17 June 2020
Published 12 July 2020 Volume 2020:13 Pages 6805—6817
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr William Cho
Zelin Tian,1,* Weixiang He,2,* Jianing Tang,1 Xing Liao,1 Qian Yang,1 Yumin Wu,1 Gaosong Wu1
1Department of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan University, Wuhan, People’s Republic of China; 2Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Gaosong Wu
Department of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan University, Wuhan, People’s Republic of China
Tel +86 150988909890
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: breast cancer, WGCNA, GEO, Oncomine, prognosis
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