Breast cancer expression profiling

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In recent years, the advances in microarray profiling, including both DNA microarray and tumor tissue microarray, have provided an unprecedented screen technique to systemically study the pathogenesis of breast cancer. These techniques have enabled researchers to simultaneously study the expression patterns of thousands of genes and hundreds of proteins in breast cancer patients. In this chapter, we will mainly discuss recent progress of our group in microarray profiling for breast cancer. There are several... 

Based on transcriptional profiling, Oncotype DX and MammaPrint, which will be described in details later in this section, have been developed and used in clinics. It has been shown that the gene expression-based microarray profiling offers tremendous potential to define subcategories of breast cancer, to predict disease relapse, to predict chemotherapy response, and to predict progression of ductal carcinoma in situ (7). 

Microarray analyses of breast cancer have identified unique gene expression profiles associated with patient survival. Sorlie et al. (23) found the expression profiles to distinguish ER-i- from ER- tumors with distinct outcomes in a cohort with locally advanced breast cancer treated with primary chemotherapy. Van t Veer et al. (18) established a 70-gene signature to predict metastatic potential in an untreated, node-negative cohort. Sotiriou et al. (24) showed the concordance with these previous analyses in node-positive and node-negative patients with the majority receiving adjuvant treatment. 

Through collaboration with Clinomics Biosciences, Inc., we obtained access to their breast cancer patient database containing clinical information and immunohistochem-istry tissue array data. We developed an integrative profile for breast cancer survival and treatment response predictions, which composed the expression profile of several major activated protein kinases as well as several traditional clinical parameters (39). 

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Van t Veer L, Dai H, van de Vijver M et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002 415 530-536. 

Hudelist, G., Pacher-Zavisin, M., Singer, C.F., Holper, T., Kubista, E., Schreiber, M., Manavi, M., Bilban, M., and K. Czerwenka, 2004, Use of high-throughput protein array for profiling of differentially expressed proteins in normal and malignant breast tissue. Breast Cancer Res Treat. 86(3) 281-91. 

Van t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT, Schreiber GJ, Kerkhoven RM, Roberts C, Linsley PS, Bernards R, Friend SH. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002 415 530-536. 

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