ArticleOncotarget2017
A pathways-based prediction model for classifying breast cancer subtypes.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 28 citations in OpenAlex.
- Identification of metabolism-associated molecular classification for effect and prognosis in lung adenocarcinoma based on multidatabases including the cancer genome atlas and gene expression omnibus.SAGE open medicine · 2025Article
- Employing Raman Spectroscopy and Machine Learning for the Identification of Breast Cancer.Biological procedures online · 2024Article
- Molecular Subtyping of Cancer Based on Robust Graph Neural Network and Multi-Omics Data Integration.Frontiers in genetics · 2022Article
- MONTI: A Multi-Omics Non-negative Tensor Decomposition Framework for Gene-Level Integrative Analysis.Frontiers in genetics · 2021Article
- Triple negative endometrial cancer: Incidence and prognosis in a monoinstitutional series of 220 patients.Oncology letters · 2020Article
- Identification of 5-Gene Signature Improves Lung Adenocarcinoma Prognostic Stratification Based on Differential Expression Invasion Genes of Molecular Subtypes.BioMed research international · 2020Article
- Article
- Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.Cancer genomics & proteomicsReview
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer is highly heterogeneous and is classified into four subtypes characterized by specific biological traits, treatment responses, and clinical prognoses. We performed a systemic analysis of 698 breast cancer patient samples from The Cancer Genome Atlas project database. We identified 136 breast cancer genes differentially expressed among the four subtypes. Based on unsupervised clustering analysis, these 136 core genes efficiently categorized breast cancer patients into the appropriate subtypes. Functional enrichment based on Kyoto Encyclopedia of Genes and Genomes analysis identified six functional pathways regulated by these genes: JAK-STAT signaling, basal cell carcinoma, inflammatory mediator regulation of TRP channels, non-small cell lung cancer, glutamatergic synapse, and amyotrophic lateral sclerosis. Three support vector machine (SVM) classification models based on the identified pathways effectively classified different breast cancer subtypes, suggesting that breast cancer subtype-specific risk assessment based on disease pathways could be a potentially valuable approach. Our analysis not only provides insight into breast cancer subtype-specific mechanisms, but also may improve the accuracy of SVM classification models.
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