Summary
October 2006, Vol. 7, No. 15, Pages 2069-2078 , DOI 10.1517/14656566.7.15.2069

Breast cancer expression profiling: the impact of microarray testing on clinical decision making

Olga Modlich1, Hans-Bernd Prisack2 & Hans Bojar3
1Research Scientist, Institut für Onkologische Chemie, University of Düsseldorf, Universitätsstrasse 1, D-40225, Düsseldorf, Germany.
2Research Scientist, Institut für Onkologische Chemie, University of Düsseldorf, Universitätsstrasse 1, D-40225, Düsseldorf, Germany.
3Head of Department, Institut für Onkologische Chemie, University of Düsseldorf, Universitätsstrasse 1, D-40225, Düsseldorf, Germany.
Author for correspondence



The available clinical prognostic tools show an obvious limitation in predicting the outcome of breast cancer patients, and pathological features cannot classify tumours accurately. Microarray-based molecular classification of breast tumours or selection of gene expression panels to improve risk prediction or treatment outcomes are thought to be theoretically superior to established clinical and pathological criteria, based on guidelines such as the St Gallen and National Institute of Health consensus, or which use specific prognostic tools, such as the Nottingham Prognostic Index or Adjuvant-Online algorithm. Although two diagnostic tests based on gene expression profiling of breast cancer are commercially available, a new molecular classification and molecular forecasting of breast cancer based on expression profiling cannot outperform the standard tumour diagnostic at present. This review focuses on some important problems in the practical application of molecular profiling of breast cancer for clinical purposes.

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Forward Links to Citing Articles

Eun-Young Oh, Patricia A. Wood, Xiaoming Yang, William J. M. Hrushesky. (2009) Discovery of candidate genes and pathways that may help explain fertility cycle stage dependent post-resection breast cancer outcome. Breast Cancer Research and Treatment
Online publication date: 3-Jan-2009.
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N. P. S. Crawford, J. Alsarraj, L. Lukes, R. C. Walker, J. S. Officewala, H. H. Yang, M. P. Lee, K. Ozato, K. W. Hunter. (2008) Bromodomain 4 activation predicts breast cancer survival. Proceedings of the National Academy of Sciences 105:17, 6380-6385
Online publication date: 29-May-2008.
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Authors:
Olga Modlich
Hans-Bernd Prisack
Hans Bojar
Keywords:
breast cancer
clinical diagnostic
expression profiling
microarray