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Microarray profiling in breast cancer patients.

Qian-Y; Shi-X; Castranova-V; Guo-NL
Cancer Drug Discovery and Development: Genomics and Pharmacogenomics in Anticancer Drug Development and Clinical Response. Part II. Innocenti F, ed., Totowa, NJ: Humana Press, 2009 Oct; :287-298
Breast cancer is the most common cancer among women. It arises from a variety of genetic, epigenetic, and chromosomal alterations. The traditional prognostic and predictive factors in breast cancer mainly focus on the clinical-pathological parameters, which are unable to reveal the diverse molecular alterations of breast cancer and are imprecise in predicting breast cancer progression and clinical outcomes. In recent years, the advances in microarray profiling, including both DNA microarrays and tumor tissue microarrays, provide an unprecedented screen technique to systemically study the pathogenesis of breast cancer. In this chapter, we mainly summarize the progress of our group in microarray profiling for breast cancer. In the first project, we present a population-based study to predict recurrence and metastases of breast cancer using the public gene expression profiles and associated clinical data. In the second project, we develop an integrative model for breast cancer survival and treatment response predictions, which is composed of the expression profiles of several major activated protein kinases as well as traditional clinical-pathological parameters. In the third project, we create a predictive model system to explore proteomic contributions to drug sensitivity, including breast cancer drugs, based on the NCI-60 cell line-related databases. Finally, we discuss the new guidelines for reporting tumor biomarkers in cancer prognostic studies. We believe that an integrated approach combining gene expression profiles, protein expression profiles, as well as clinical information will lead to more informed clinical decision making in breast cancer intervention.
Women; Breast-cancer; Cancer; Chromosome-damage; Chromosome-disorders; Genes; Gene-mutation; Models; Author Keywords: Breast cancer prognosis; transcriptional profiling; proteomic profiling; tissue array; chemosensitivity prediction
Yong Qian, The Pathology and Physiology Research Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Morgantown, WV 26505, USA
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Cancer Drug Discovery and Development: Genomics and Pharmacogenomics in Anticancer Drug Development and Clinical Response