Literature DB >> 16030107

Comparative gene expression analysis of ovarian carcinoma and normal ovarian epithelium by serial analysis of gene expression.

David G Peters1, Donna M Kudla, Julie A Deloia, Tian Jiao Chu, Liane Fairfull, Robert P Edwards, Robert E Ferrell.   

Abstract

Despite the poor prognosis of ovarian cancer and the importance of early diagnosis, there are no reliable noninvasive biomarkers for detection in the early stages of disease. Therefore, to identify novel ovarian cancer markers with potential utility in early-stage screening protocols, we have undertaken an unbiased and comprehensive analysis of gene expression in primary ovarian tumors and normal human ovarian surface epithelium (HOSE) using Serial Analysis of Gene Expression (SAGE). Specifically, we have generated SAGE libraries from three serous adenocarcinomas of the ovary and, using novel statistical tools, have compared these to SAGE data derived from two pools of normal HOSE. Significantly, in contrast to previous SAGE-based studies, our normal SAGE libraries are not derived from cultured cell lines. We have also compared our data with publicly available SAGE data obtained from primary tumors and "normal" HOSE-derived cell lines. We have thus identified several known and novel genes whose expressions are elevated in ovarian cancer. These include but are not limited to CLDN3, WFDC2, FOLR1, COL18A1, CCND1, and FLJ12988. Furthermore, we found marked differences in gene expression patterns in primary HOSE tissue compared with cultured HOSE. The use of HOSE tissue as a control for these experiments, along with hierarchical clustering analysis, identified several potentially novel biomarkers of ovarian cancer, including TACC3, CD9, GNAI2, AHCY, CCT3, and HMGA1. In summary, these data identify several genes whose elevated expressions have not been observed previously in ovarian cancer, confirm the validity of several existing markers, and provide a foundation for future studies in the understanding and management of this disease.

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Year:  2005        PMID: 16030107     DOI: 10.1158/1055-9965.EPI-04-0704

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  20 in total

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