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.
- Kallikrein-related peptidase 10
- Ovarian cancer
- Steroid hormone regulation
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Batra and Tan are equal first authors and Kedda and Spurdle are equal last authors.
This work was supported by funding from the National Health and Medical Research Council of Australia (NHMRC) grant 390123. ABS and JC are NHMRC senior and principal research fellows. CN is supported by NHMRC career award. JB and OT are supported by Institute of Health and Biomedical Innovation postdoctoral fellowships. TO is supported by Australian Postgraduate Award, IHBI PhD top-up and Queensland government Smart State PhD top-up award.
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