ArticleMedicine2020
Identification of candidate biomarkers correlated with the pathogenesis and prognosis of breast cancer via integrated bioinformatics analysis.
Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 26 citations in OpenAlex.
- Integrated Analysis of Bulk and Single-Cell Transcriptomics Identifies Prognostic Biomarkers in Breast Cancer Metastasis.Biochemical genetics · 2026Article
- Identification of candidate biomarkers correlated with the pathogenesis of breast cancer patients.Scientific reports · 2025Article
- Transcriptomic analysis revealed potential regulatory biomarkers and repurposable drugs for breast cancer treatment.Cancer reports (Hoboken, N.J.) · 2024Article
- Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer.Bioinformatics and biology insights · 2024Article
- Particle filter-based parameter estimation algorithm for prognostic risk assessment of progression in non-small cell lung cancer.BMC medical informatics and decision making · 2023Article
- Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer.Medicina (Kaunas, Lithuania) · 2023Article
- Understanding Breast Cancers through Spatial and High-Resolution Visualization Using Imaging Technologies.Cancers · 2022Review
- A genomic and transcriptomic study toward breast cancer.Frontiers in genetics · 2022Article
- Targeting Adenylate Cyclase Family: New Concept of Targeted Cancer Therapy.Frontiers in oncology · 2022Review
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- Identification of candidate biomarkers correlated with poor prognosis of breast cancer based on bioinformatics analysis.Bioengineered · 2021Article
Corrections and comments
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study was carried out to identify potential key genes associated with the pathogenesis and prognosis of breast cancer (BC).
methodsSeven GEO datasets (GSE24124, GSE32641, GSE36295, GSE42568, GSE53752, GSE70947, GSE109169) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between BC and normal breast tissue samples were screened by an integrated analysis of multiple gene expression profile datasets. Hub genes related to the pathogenesis and prognosis of BC were verified by employing protein-protein interaction (PPI) network.
resultsTen hub genes with high degree were identified, including CDK1, CDC20, CCNA2, CCNB1, CCNB2, BUB1, BUB1B, CDCA8, KIF11, and TOP2A. Lastly, the Kaplan-Meier plotter (KM plotter) online database demonstrated that higher expression levels of these genes were related to lower overall survival. Experimental validation showed that all 10 hub genes had the same expression trend as predicted.
conclusionThe findings of this research would provide some directive significance for further investigating the diagnostic and prognostic biomarkers to facilitate the molecular targeting therapy of BC, which could be used as a new biomarker for diagnosis and to guide the combination medicine of BC.
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