Journal
BMC CANCER
Volume 10, Issue -, Pages -Publisher
BIOMED CENTRAL LTD
DOI: 10.1186/1471-2407-10-165
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Funding
- NIH [1CA331160]
- NSF-MRI [DBI-0320858]
- Ohio Board of Regents
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Background: The prostate gland represents a multifaceted system in which prostate epithelia and stroma have distinct physiological roles. To understand the interaction between stroma and glandular epithelia, it is essential to delineate the gene expression profiles of these two tissue types in prostate cancer. Most studies have compared tumor and normal samples by performing global expression analysis using a mixture of cell populations. This report presents the first study of prostate tumor tissue that examines patterns of differential expression between specific cell types using laser capture microdissection (LCM). Methods: LCM was used to isolate distinct cell-type populations and identify their gene expression differences using oligonucleotide microarrays. Ten differentially expressed genes were then analyzed in paired tumor and nonneoplastic prostate tissues by quantitative real-time PCR. Expression patterns of the transcription factors, WT1 and EGR1, were further compared in established prostate cell lines. WT1 protein expression was also examined in prostate tissue microarrays using immunohistochemistry. Results: The two-step method of laser capture and microarray analysis identified nearly 500 genes whose expression levels were significantly different in prostate epithelial versus stromal tissues. Several genes expressed in epithelial cells (WT1, GATA2, and FGFR-3) were more highly expressed in neoplastic than in non-neoplastic tissues; conversely several genes expressed in stromal cells (CCL5, CXCL13, IGF-1, FGF-2, and IGFBP3) were more highly expressed in non-neoplastic than in neoplastic tissues. Notably, EGR1 was also differentially expressed between epithelial and stromal tissues. Expression of WT1 and EGR1 in cell lines was consistent with these patterns of differential expression. Importantly, WT1 protein expression was demonstrated in tumor tissues and was absent in normal and benign tissues. Conclusions: The prostate represents a complex mix of cell types and there is a need to analyze distinct cell populations to better understand their potential interactions. In the present study, LCM and microarray analysis were used to identify novel gene expression patterns in prostate cell populations, including identification of WT1 expression in epithelial cells. The relevance of WT1 expression in prostate cancer was confirmed by analysis of tumor tissue and cell lines, suggesting a potential role for WT1 in prostate tumorigenesis.
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