4.7 Article

Histologic type, organ of origin, and Wnt pathway status: Effect on gene expression in ovarian and uterine carcinomas

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CLINICAL CANCER RESEARCH
卷 11, 期 6, 页码 2123-2131

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AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1078-0432.CCR-04-2061

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  1. NCI NIH HHS [U19 CA 84953, R01 CA 94172, P30 CA 46952] Funding Source: Medline

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Purpose: Ovarian and uterine carcinomas manifest several differentiation patterns resembling those seen in nonneoplastic epithelia of the gynecologic tract. Specific oncogene and tumor suppressor gene defects have been associated with particular differentiation patterns in carcinomas arising in either the uterus or ovary. For instance, ovarian and uterine carcinomas with endometrioid differentiation frequently show beta-catenin mutations. Whereas type of differentiation is considered in the treatment of uterine carcinomas, it does not presently contribute to decisions about treatment of ovarian carcinomas. A widely accepted view is that the accumulation of specific gene defects and gene expression changes underlies phenotypic traits of cancers, including their response to treatment. Experimental Design: Using oligonucleotide microarrays to assess gene expression in 103 primary ovarian and uterine carcinomas, we sought to address whether organ of origin or type of differentiation (histotype; endometrioid versus serous) had a more substantial effect on gene expression patterns. Results: We found that effects on gene expression due to organ of origin and histotype are similar in magnitude and are parallel in that organ effects are similar in the two histotypes and histotype effects are similar in the two organs. In addition, ovarian and uterine endometrioid adenocarcinomas with beta-catenin defects show a common gene expression signature largely distinct from that seen in tumors lacking such defects. Conclusions: Our results illustrate how organ of origin, type of differentiation, and specific molecular defects all contribute to gene expression in the most common types of ovarian and uterine cancers. The findings also imply gene expression data will be of value for stratifying ovarian cancer patients for new treatment approaches.

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