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Updated: Aug 13, 2026

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
Profiling genetic variation along the androgen biosynthesis and metabolism pathways implicates several single
Nina Mononen1, Eija H Seppälä, Priya Duggal
1Laboratory of Cancer Genetics, Institute of Medical Technology, University of Tampere and Tampere University Hospital, Tampere FIN-33014, Finland.
Abstract:
Several candidate genes along androgen pathway have been suggested to affect prostate cancer risk but no single gene seems to be overwhelmingly important for a large fraction of the patients. In this study, we first screened for variants in candidate genes and then chose to explore the association between 18 variants and prostate cancer risk by genotyping DNA samples from unselected (n = 847) and familial (n = 121) prostate cancer patients and population controls (n = 923). We identified a novel single nucleotide polymorphism (SNP) in the CYP19A1 gene, T201M, with a mild significant association with prostate cancer [odds ratio (OR), 2.04; 95% confidence interval (95% CI), 1.03-4.03; P = 0.04]. Stratified analysis revealed that this risk was most apparent in patients with organ-confined (T(1)-T(2)) and low-grade (WHO grade 1) tumors (OR, 5.42; 95% CI, 2.33-12.6; P < 0.0001). In contrast, CYP17A1 -34T>C alteration was associated with moderate to poorly differentiated (WHO grade 2-3) organ-confined disease (OR, 1.42; 95% CI, 1.09-1.83; P = 0.007). We also tested a multigenic model of prostate cancer risk by calculating the joint effect of CYP19A1 T201M with five other common SNPs. Individuals carrying both the CYP19A1 and KLK3 -252A>G variant alleles had a significantly increased risk for prostate cancer (OR, 2.87; 95% CI, 1.10-7.49; P = 0.03). In conclusion, our results suggest that several SNPs along the androgen pathway, especially in CYP19A1 and CYP17A1, may influence prostate cancer development and progression. These genes may have different contributions to distinct clinical subsets as well as combinatorial effects in others illustrating that profiling and joint analysis of several genes along each pathway may be needed to understand genetic contributions to prostate cancer etiology.
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