ArticleJournal of medicine and life2013
Classification of breast carcinomas according to gene expression profiles.
Article in Journal of medicine and life, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Disrupted circadian control promotes oncogenesis in breast cancer.Bioinformation · 2025Article
- Lipid kinases PIP5Ks and PIP4Ks: potential drug targets for breast cancer.Frontiers in oncology · 2023Review
- Screening of core genes and pathways in breast cancer development via comprehensive analysis of multi gene expression datasets.Oncology letters · 2019Article
- Integrated bioinformatics analysis to identify 15 hub genes in breast cancer.Oncology letters · 2019Article
- Article
- The association of the expression of miR-122-5p and its target ADAM10 with human breast cancer.Molecular biology reports · 2015Article
- Clinicopathologic features of triple negative breast cancers: an experience from Pakistan.Diagnostic pathology · 2014Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast carcinomas represent an important health problem. Understanding the development of breast cancer from precursor is critical for clinical treatment and prevention, however little is known about the molecular events involved in the progression to cancer. The advent of gene expression microarray technology provides a new powerful tool to assist in the determination of diagnosis, prognosis and treatment. In this paper, we present the recent DNA microarray studies that describe how gene expression profiling is being used to classify specimens of breast carcinomas based on molecular properties of the tumor and to identify gene expression patterns related to clinical outcome. In present, data are available that show that gene expression profiles can be used to distinguish cell type-specific gene clusters (stromal, epithelial, mesenchymal and proliferation status) and to classify breast tumors as basal-like, luminal-like, ERBB2 overexpressing and normal breast-like. Profiles associated with good prognosis and poor prognosis of young axillary node negative patients have been identified. The microarray technology will become in the near future a molecular complement to histopathology and immnuhistochemistry.
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23599813PMC3624639What OpenQuestion holds
Registered trials
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