ArticleJournal of clinical medicine2019
Identification of Prognostic Candidate Genes in Breast Cancer by Integrated Bioinformatic Analysis.
Article in Journal of clinical medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.
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Who cites it
54 citing papers in PubMed.
- PIMO: pathway-based interpretable multiomics interactions for multiomics integration.Bioinformatics (Oxford, England) · 2026Article
- Integrated multi-omics analysis and functional validation reveal the role of TRIM2 as a potential novel biomarker in breast cancer.Breast cancer research : BCR · 2026Article
- Characterizing the salivary RNA landscape to identify potential diagnostic, prognostic, and follow-up biomarkers for breast cancer.Molecular oncology · 2026Article
- Assessment of chemical risk factor for breast cancer based on gene expression profiles.Scientific reports · 2025Article
- ADCY4 inhibits cAMP-induced growth of breast cancer by inactivating FAK/AKT and ERK signaling but is frequently silenced by DNA methylation.Scientific reports · 2025Article
- Downregulation of CMIP contributes to preeclampsia development by impairing trophoblast function via the PDE7B-cAMP pathway.Cellular and molecular life sciences : CMLS · 2025Article
- Plasma-Derived Exosomal i-tRF-LeuCAA as Biomarker for Glioma Diagnosis and Promoter of Epithelial-Mesenchymal Transition via TPM4 Regulation.CNS neuroscience & therapeutics · 2025Article
- The Role of the Fox Gene in Breast Cancer Progression.International journal of molecular sciences · 2025Review
- Interpretable machine learning-driven biomarker identification and validation for Alzheimer's disease.Scientific reports · 2024Article
- Whole-genome resequencing reveals new mutations in candidate genes for Beichuan-white goat prolificacya.Animal biotechnology · 2024Article
- Biochemical pharmacology of adenylyl cyclases in cancer.Biochemical pharmacology · 2024Review
- Identification ofTranslational cancer research · 2024Article
- Article
- Identification of driving genes of familial adenomatous polyposis by differential gene expression analysis and weighted gene co-expression network analysis.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024Article
- ADCY6 is a potential prognostic biomarker and suppresses OTSCC progression via Hippo signaling pathway.The Kaohsiung journal of medical sciences · 2023Article
- Understanding Breast Cancer Aggressiveness and Its Implications in Diagnosis and Treatment.Journal of clinical medicine · 2023Article
- Data mining combines bioinformatics discover immunoinfiltration-related gene SERPINE1 as a biomarker for diagnosis and prognosis of stomach adenocarcinoma.Scientific reports · 2023Article
- Overexpression of TPM4 is associated with worse prognosis and immune infiltration in patients with glioma.BMC neurology · 2023Article
- A novel immune-related gene signature correlated with serum IL33 expression in acute myeloid leukemia prognosis.American journal of translational research · 2023Article
- Article
Corrections and comments
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8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer is one of the most common malignancies. However, the molecular mechanisms underlying its pathogenesis remain to be elucidated. The present study aimed to identify the potential prognostic marker genes associated with the progression of breast cancer. Weighted gene coexpression network analysis was used to construct free-scale gene coexpression networks, evaluate the associations between the gene sets and clinical features, and identify candidate biomarkers. The gene expression profiles of GSE48213 were selected from the Gene Expression Omnibus database. RNA-seq data and clinical information on breast cancer from The Cancer Genome Atlas were used for validation. Four modules were identified from the gene coexpression network, one of which was found to be significantly associated with patient survival time. The expression status of 28 genes formed the black module (basal); 18 genes, dark red module (claudin-low); nine genes, brown module (luminal), and seven genes, midnight blue module (nonmalignant). These modules were clustered into two groups according to significant difference in survival time between the groups. Therefore, based on betweenness centrality, we identified
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.