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

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32764968", "kind": "science-record", "revision": 7, "content_hash": "sha256:86b8e183f3f17fbc909ce03837dbf9ba968a63884072c77a7a663568375fcd33", "created_at": "2026-11-01T15:41:07Z", "updated_at": "2026-11-01T21:23:35Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Important Modules and Biomarkers in Breast Cancer Based on WGCNA.", "doi": "10.2147/OTT.S258439", "pmid": "32764968", "authors": ["Zelin Tian", "Weixiang He", "Jianing Tang", "Xing Liao", "Qian Yang", "Yumin Wu", "Gaosong Wu"], "journal": "OncoTargets and therapy", "year": 2020, "abstract": "INTRODUCTION: Breast cancer (BRCA) has the highest incidence among female malignancies, and the prognosis for these patients remains poor.\nMATERIALS 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).\nRESULTS: 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.\nCONCLUSION: We identified four hub genes as candidate biomarkers for BRCA. These hub genes may provide a theoretical basis for targeted therapy against BRCA.", "claims": [{"id": "claim-method", "statement": "In this study, core modules and central genes related to BRCA were identified through a weighted gene co-expression network analysis (WGCNA). 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