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Published in: Journal of Ovarian Research 1/2011

Open Access 01-12-2011 | Research

Differential hRad17 expression by histologic subtype of ovarian cancer

Authors: Jennifer L Young, E Colin Koon, Joseph Kwong, William R Welch, Michael G Muto, Ross S Berkowitz, Samuel C Mok

Published in: Journal of Ovarian Research | Issue 1/2011

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Abstract

Background

In the search for unique ovarian cancer biomarkers, ovarian specific cDNA microarray analysis identified hRad17, a cell cycle checkpoint protein, as over-expressed in ovarian cancer. The aim of this study was to validate this expression.

Methods

Immunohistochemistry was performed on 72 serous, 19 endometrioid, 10 clear cell, and 6 mucinous ovarian cancers, 9 benign ovarian tumors, and 6 normal ovarian tissue sections using an anti-hRad17 antibody. Western blot analysis and quantitative PCR were performed using cell lysates and total RNA prepared from 17 ovarian cancer cell lines and 6 normal ovarian epithelial cell cultures (HOSE).

Results

Antibody staining confirmed upregulation of hRad17 in 49.5% of ovarian cancer cases. Immunohistochemistry demonstrated that only 42% of serous and 47% of endometrioid subtypes showed overexpression compared to 80% of clear cell and 100% of mucinous cancers. Western blot confirmed overexpression of hRad17 in cancer cell lines compared to HOSE. Quantitative PCR demonstrated an upregulation of hRad17 RNA by 1.5-7 fold. hRad17 RNA expression differed by subtype.

Conclusions

hRad17 is over-expressed in ovarian cancer. This over-expression varies by subtype suggesting a role in the pathogenesis of these types. Functional studies are needed to determine the potential role of this protein in ovarian cancer.
Appendix
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Metadata
Title
Differential hRad17 expression by histologic subtype of ovarian cancer
Authors
Jennifer L Young
E Colin Koon
Joseph Kwong
William R Welch
Michael G Muto
Ross S Berkowitz
Samuel C Mok
Publication date
01-12-2011
Publisher
BioMed Central
Published in
Journal of Ovarian Research / Issue 1/2011
Electronic ISSN: 1757-2215
DOI
https://doi.org/10.1186/1757-2215-4-6

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