Upstream regulators among genes neighboring SNPs in high LD with prostate cancer risk alleles.

<p>The IPA Upstream Regulator tool was used to identify potential upstream regulators based on the statistical significance of genes in the gene list that function downstream of this regulator. The top 5 upstream regulators identified were flufenamic acid, androgen receptor (AR), cadmium chloride, prostate transmembrane protein, androgen induced 1 (PMEPA1), and prefoldin-like chaperone (URI1). Upstream regulators (red); upstream regulator and on the gene list (purple shading); genes from the gene list (blue).</p

Gene-gene interactions among genes neighboring SNPs in high LD with prostate cancer risk alleles.

<p>A total of 78 unique genes contained or were located within 100 Kb of SNPs in high LD (r²>0.80). Gene-gene interactions were identified using the Ingenuity Pathway Analysis software. The most significant functional network demonstrating connectivity between genes was identified as having a potential function in <i>Cancer</i>, <i>Cellular Growth and Proliferation</i>, <i>and Organismal Injury and Abnormalities</i>. Gene products shaded in gray represent genes originating from the gene list.</p

Upstream regulators among genes flanking prostate cancer risk alleles.

<p>The IPA Upstream Regulator tool was used to identify potential upstream regulators based on the statistical significance of genes in the gene list that function downstream of this regulator. The top 5 upstream regulators identified were androgen, androgen receptor (AR), lymphoid enhancer-binding factor 1 (LEF1), hedgehog (HH), and cadmium chloride. Upstream regulators (red); AR was both and upstream regulator and on the gene list (purple shading); genes from the gene list (blue).</p

Gene-gene interaction networks and associated diseases and biological functions among genes neighboring SNPs in high LD with prostate cancer risk variants.

<p>* Genes indicated in bold are on the genes neighboring SNPs in high LD (r²>0.80) prostate cancer risk variants.</p><p>Gene-gene interaction networks and associated diseases and biological functions among genes neighboring SNPs in high LD with prostate cancer risk variants.</p

<i>In Silico</i> Functional Pathway Annotation of 86 Established Prostate Cancer Risk Variants

<div><p>Heritability is one of the strongest risk factors of prostate cancer, emphasizing the importance of the genetic contribution towards prostate cancer risk. To date, 86 established prostate cancer risk variants have been identified by genome-wide association studies (GWAS). To determine if these risk variants are located near genes that interact together in biological networks or pathways contributing to prostate cancer initiation or progression, we generated gene sets based on proximity to the 86 prostate cancer risk variants. We took two approaches to generate gene lists. The first strategy included all immediate flanking genes, up- and downstream of the risk variant, regardless of distance from the index variant, and the second strategy included genes closest to the index GWAS marker and to variants in high LD (r² ≥0.8 in Europeans) with the index variant, within a 100 kb window up- and downstream. Pathway mapping of the two gene sets supported the importance of the androgen receptor-mediated signaling in prostate cancer biology. In addition, the hedgehog and Wnt/β-catenin signaling pathways were identified in pathway mapping for the flanking gene set. We also used the HaploReg resource to examine the 86 risk loci and variants high LD (r² ≥0.8) for functional elements. We found that there was a 12.8 fold (p = 2.9 x 10^-4) enrichment for enhancer motifs in a stem cell line and a 4.4 fold (p = 1.1 x 10^-3) enrichment of DNase hypersensitivity in a prostate adenocarcinoma cell line, indicating that the risk and correlated variants are enriched for transcriptional regulatory motifs. Our pathway-based functional annotation of the prostate cancer risk variants highlights the potential regulatory function that GWAS risk markers, and their highly correlated variants, exert on genes. Our study also shows that these genes may function cooperatively in key signaling pathways in prostate cancer biology.</p></div

Gene-gene interactions among genes flanking prostate cancer risk alleles.

<p>A total of 97 unique genes contained or flanking the 86 prostate cancer risk loci. Gene-gene interactions were identified using the Ingenuity Pathway Analysis software. The most significant functional network demonstrating connectivity between genes was identified as having a potential function in <i>Organismal Development</i>, <i>Embryonic Development</i>, <i>and Organ Development</i>. The representative gene products are listed and putative functions listed in the legend. Gene products shaded in gray represent genes originating from the gene list.</p

Gene-gene interaction networks and associated diseases and biological functions among genes flanking prostate cancer risk variants.

<p>* Genes indicated in bold are on the genes flanking prostate cancer risk variants.</p><p>Gene-gene interaction networks and associated diseases and biological functions among genes flanking prostate cancer risk variants.</p

Study characteristics of the advanced prostate cancer cases and controls.

a<p>P-values obtained using either a Student t-test (quantitative coding) or a Chi-square test (qualitative coding).</p>b<p>The sum of all categories does not add to the total due to missing data.</p

Multivariate relative risks and 95% CIs of prostate cancer associated with prostatitis and STD history by number of PSA tests during follow-up, California Men's Health Study, 2002–2006^*.

*<p>Adjusted for age, race, family history, BMI, and income.</p>a<p><i>P</i> = 0.018.</p>b<p><i>P</i> = 0.029.</p>c<p><i>P</i> = 0.019.</p>d<p><i>P</i> = 0.010.</p

Association of SNPs with advanced prostate cancer risk (P-value <0.01).

<p>Odds ratios (OR), 95% confidence intervals (95% CI) and P-values obtained using the unconditional multivariate logistic model adjusted on age, institution, and genetic ancestry (first Principal Component) for SNPs that had at least one of the three tests (heterozygous, rare homozygous or trend) with a P-value below 0.01.</p