2013, Volume 6, Issue 1, pp 14 – 17

Classification of breast carcinomas according to gene expression profiles

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Authors and Affiliations

Correspondence to:: Ligia Moldovan MD, PhD Clinical Studies Department, Panduri Hospital of Bucharest 20 Panduri Road, District 5, Bucharest, Romania Phone: 021 410.69.10, 021 410.08.22, Mobile: 0722794778, E-mail: geamai_ayfer@yahoo.com

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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About this article

PMC ID: 3624639
PubMed ID: 23599813
DOI: 

Article Publishing Date (print): 15-03-2013
Available Online: 25-03-2013

Journal information

ISSN Printing: 1844-122X
ISSN Online: 1844-3117
Journal Title: Journal of Medicine and Life

Copyright License: Open Access

This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited.


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