OncoTargets and Therapy (2020-07-01)

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

  • Tian Z,
  • He W,
  • Tang J,
  • Liao X,
  • Yang Q,
  • Wu Y,
  • Wu G

Journal volume & issue
Vol. Volume 13
pp. 6805 – 6817

Abstract

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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 workCorrespondence: Gaosong WuDepartment of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan University, Wuhan, People’s Republic of ChinaTel +86 150988909890Email [email protected]: 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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