ArticleFrontiers in genetics2020
Classifying Breast Cancer Molecular Subtypes by Using Deep Clustering Approach.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
- Tumor ecosystem subtyping of breast cancer based on somatic mutations and network propagation reveals distinct prognostic and genomic landscapes.Frontiers in genetics · 2026Article
- Deep Clustering-Based Metabolic Stratification of Non-Small Cell Lung Cancer Patients Through Integration of Somatic Mutation Profile and Network Propagation Algorithm.Interdisciplinary sciences, computational life sciences · 2025Article
- DeepCMS: A Feature Selection-Driven Model for Cancer Molecular Subtyping with a Case Study on Testicular Germ Cell Tumors.Diagnostics (Basel, Switzerland) · 2025Article
- Deep-embedded clustering by relevant scales and genome-wide association study in autism.PloS one · 2025Article
- Review
- Machine learning survival prediction using tumor lipid metabolism genes for osteosarcoma.Scientific reports · 2024Article
- Integrating somatic mutation profiles with structural deep clustering network for metabolic stratification in pancreatic cancer: a comprehensive analysis of prognostic and genomic landscapes.Briefings in bioinformatics · 2023Article
- Review
- Omics-Based Investigations of Breast Cancer.Molecules (Basel, Switzerland) · 2023Review
- Polo-like kinase 1 as a biomarker predicts the prognosis and immunotherapy of breast invasive carcinoma patients.Oncology research · 2023Article
- Developing a label propagation approach for cancer subtype classification problem.Turkish journal of biology = Turk biyoloji dergisi · 2022Article
- Identifying and characterizing high-risk clusters in a heterogeneous ICU population with deep embedded clustering.Scientific reports · 2021Article
- A computational method for drug sensitivity prediction of cancer cell lines based on various molecular information.PloS one · 2021Article
- Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.Frontiers in oncology · 2021Article
- Molecular Subtypes of Oral Squamous Cell Carcinoma Based on Immunosuppression Genes Using a Deep Learning Approach.Frontiers in cell and developmental biology · 2021Article
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2 authors.
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Abstract
Cancer is a complex disease with a high rate of mortality. The characteristics of tumor masses are very heterogeneous; thus, the appropriate classification of tumors is a critical point in the effective treatment. A high level of heterogeneity has also been observed in breast cancer. Therefore, detecting the molecular subtypes of this disease is an essential issue for medicine that could be facilitated using bioinformatics. This study aims to discover the molecular subtypes of breast cancer using somatic mutation profiles of tumors. Nonetheless, the somatic mutation profiles are very sparse. Therefore, a network propagation method is used in the gene interaction network to make the mutation profiles dense. Afterward, the deep embedded clustering (DEC) method is used to classify the breast tumors into four subtypes. In the next step, gene signature of each subtype is obtained using Fisher's exact test. Besides the enrichment of gene signatures in numerous biological databases, clinical and molecular analyses verify that the proposed method using mutation profiles can efficiently detect the molecular subtypes of breast cancer. Finally, a supervised classifier is trained based on the discovered subtypes to predict the molecular subtype of a new patient. The code and material of the method are available at: https://github.com/nrohani/MolecularSubtypes.
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