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Transcriptome profiling in clinical breast cancer: From 3D culture models to prognostic signatures
Author(s) -
Fournier Marcia V.,
Martin Katherine J.
Publication year - 2006
Publication title -
journal of cellular physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.529
H-Index - 174
eISSN - 1097-4652
pISSN - 0021-9541
DOI - 10.1002/jcp.20787
Subject(s) - transcriptome , breast cancer , profiling (computer programming) , computational biology , biology , gene expression profiling , oncology , bioinformatics , medicine , cancer , gene , genetics , computer science , gene expression , operating system
Early detection has been one of the most effective strategies to control the growing cancer burden. The power of earlier detection has been demonstrated by the impact of pap‐smear, mammography, and PSA tests on cancer patient treatment and survival. These tests benefit patients independent of their genetic background or race. However, in many cases, we are still losing the battle against cancer because patients that initially presented with low‐grade disease progress rapidly to aggressive forms of the disease. As of yet, we have limited means to predict a particular patient's fate or to specifically treat subtypes of cancer. A combination of earlier detection and targeted therapy, based on information from transcriptome analysis, could be a powerful ally in this battle. The theme of this review article is to briefly summarize innovative strategies using three‐dimensional (3D) cell cultures of human mammary epithelial cells to predict clinical outcome in breast cancer. This strategy has the potential to further enhance our understanding of breast cancer biology and to contribute to the identification of biologically significant bio‐markers that are also useful drug targets. J. Cell. Physiol. 209: 625–630, 2006. © 2006 Wiley‐Liss, Inc.