Skip Navigation LinksHome > May 2010 - Volume 20 - Issue 4 > Kallikrein-Related Peptidase 10 (KLK10) Expression and Singl...
International Journal of Gynecological Cancer:
doi: 10.1111/IGC.0b013e3181d9273e
Ovarian Cancer

Kallikrein-Related Peptidase 10 (KLK10) Expression and Single Nucleotide Polymorphisms in Ovarian Cancer Survival

Batra, Jyotsna PhD*; Tan, Olivia L. PhD*; O'Mara, Tracy BSc (Hons)*†; Zammit, Rebecca BSc (Hons)*; Nagle, Christina M. PhD‡; Clements, Judith A. PhD*; Kedda, Mary-Anne PhD*†; Spurdle, Amanda B. PhD‡

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Abstract

Introduction: Kallikrein-related peptidase 10 (KLK10) overexpression is a predictor of poor disease outcome in women with late-stage ovarian cancer. We aimed to identify whether KLK10 overexpression could be attributed to genetic variants, in particular, in hormone response elements or transcription factor binding sites.

Methods: Cox regression analysis was used to assess the association between 2 tag and 1 exonic KLK10 single nucleotide polymorphisms (SNPs) and the survival of 319 patients with ovarian cancer. Four different ovarian cancer cell lines were investigated for KLK10 expression after hormone stimulation, and sequence variation in the 3.6-Kb upstream of the KLK10 start site. In silico analyses of SNPs in cell lines and from published databases were undertaken to identify further research novel and potentially functional SNPs that are not covered by tag SNPs.

Results: The KLK10 SNPs investigated were not associated with ovarian cancer survival. However, steroid hormone treatment of ovarian cell lines showed KLK10 up-regulation in response to estrogen and estrogen plus progesterone treatments in the aggressive cell line PEO1 and affirmed a role for KLK10 in aggressive ovarian cancer. Potentially functional KLK10 SNPs were identified by cell line sequencing and bioinformatic analysis.

Conclusion: Potentially functional candidate KLK10 SNPs require investigation in future association studies of ovarian cancer risk and survival, including rs3760738 identified in aggressive ovarian cancer cell lines and predicted to affect transcription factor binding sites.

Copyright © 2010 by IGCS and ESGO

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