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Updated: May 6, 2026

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
The RTK/ERK pathway is associated with prostate cancer risk on the SNP level: a pooled analysis of 41 sets of data
Yang Chen1, Tianyu Li1, Xiaoqiang Yu2
1Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China; Department of Urology and Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Abstract:
Prostate cancer (PCa) is a malignant disease influencing numerous men worldwide every year. However, the exact pathogenesis and the genes, environment, and other factors involved have not been explained clearly. Some studies have proposed that cell signaling pathways might play a key role in the development and progression of PCa. According to our previous study, the RTK/ERK pathway containing nearly 40 genes was associated with PCa risk. On the basis of these genes, we conducted a meta-analysis with our own Chinese Consortium for Prostate Cancer Genetics (ChinaPCa) study and available studies in the databases to describe the association between the pathway and PCa on the SNP level. The results suggested that rs4764695/IGF1 (recessive model: pooled OR=0.92, 95%CI=0.852-0.994, P=0.034; I(2)=0%, P=0.042; allele analysis: pooled OR=0.915, 95%CI=0.874-0.958, P=0; I(2)=0%, P=0.424; codominant model: OR=0.835, 95%CI=0.762-0.916, P=0; I(2)=0%, P=0.684) and rs1570360/VEGF (recessive model: OR=0.596, 95%CI=0.421-0.843, P=0.003; I(2)=23.9%, P=0.269; codominant model: OR=0.576, 95%CI=0.404-0.820, P=0.002; I(2)=49.1%, P=0.140) were significantly associated with PCa. In subgroup analysis, the relationship was also found in Caucasians for IGF1 (dominant model: OR=0.834, 95%CI=0.769-0.904, P=0; allele analysis: OR=0.908, 95%CI=0.863-0.955, P=0; AA vs CC: OR=0.829, 95%CI=0.750-0.916, P=0; AC vs CC: OR=0.837, 95%CI=0.768-0.912, P=0). In addition, in Asians (allele analysis: OR=0.21, 95%CI=0.168-0.262, P=0) and Caucasians (recessive model: OR=0.453, 95%CI: 0.240-0.855, P=0.015; codominant model: OR=0.464, 95%CI=0.240-0.898, P=0.023) for VEGF, the association was significant. The results indicated that rs4764695/IGF1 and rs1570360/VEGF might play a key role in the development and progression of PCa. On the SNP level, we suggest that the study gives us a new view of gene-pathway analysis and targeted therapy for PCa.
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