ArticleBioscience reports2019
Co-expression of key gene modules and pathways of human breast cancer cell lines.
Article in Bioscience reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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15 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.
- Meta-analysis of integrated ChIP-seq and transcriptome data revealed genomic regions affected by estrogen receptor alpha in breast cancer.BMC medical genomics · 2023Pooled it
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- Systemic lupus erythematosus dysregulates the expression of long noncoding RNAs in placentas.Arthritis research & therapy · 2022Article
- Data mining and mathematical models in cancer prognosis and prediction.Medical review (2021) · 2022Review
- Identifying key genes in milk fat metabolism by weighted gene co-expression network analysis.Scientific reports · 2022Article
- Five crucial prognostic-related autophagy genes stratified female breast cancer patients aged 40-60 years.BMC bioinformatics · 2021Article
- A Streamlined Approach to Pathway Analysis from RNA-Sequencing Data.Methods and protocols · 2021Article
- Lactation Associated Genes Revealed in Holstein Dairy Cows by Weighted Gene Co-Expression Network Analysis (WGCNA).Animals : an open access journal from MDPI · 2021Article
- Luminal A Breast Cancer Co-expression Network: Structural and Functional Alterations.Frontiers in genetics · 2021Article
- Identification of Hub Genes as Biomarkers Correlated with the Proliferation and Prognosis in Lung Cancer: A Weighted Gene Co-Expression Network Analysis.BioMed research international · 2020Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer (BC) is the most common leading cause of cancer-related death in women worldwide. Gene expression profiling analysis for human BCs has been studied previously. However, co-expression analysis for BC cell lines is still devoid to date. The aim of the study was to identify key pathways and hub genes that may serve as a biomarker for BC and uncover potential molecular mechanism using weighted correlation network analysis. We analyzed microarray data of BC cell lines (GSE 48213) listed in the Gene Expression Omnibus database. Gene co-expression networks were used to construct and explore the biological function in hub modules using the weighted correlation network analysis algorithm method. Meanwhile, Gene ontology and KEGG pathway analysis were performed using Cytoscape plug-in ClueGo. The network of the key module was also constructed using Cytoscape. A total of 5000 genes were selected, 28 modules of co-expressed genes were identified from the gene co-expression network, one of which was found to be significantly associated with a subtype of BC lines. Functional enrichment analysis revealed that the brown module was mainly involved in the pathway of the autophagy, spliceosome, and mitophagy, the black module was mainly enriched in the pathway of colorectal cancer and pancreatic cancer, and genes in midnightblue module played critical roles in ribosome and regulation of lipolysis in adipocytes pathway. Three hub genes CBR3, SF3B6, and RHPN1 may play an important role in the development and malignancy of the disease. The findings of the present study could improve our understanding of the molecular pathogenesis of breast cancer.
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