Identification of Novel Susceptibility Loci and Genes for Prostate Cancer Risk: A Transcriptome-Wide Association Study in over 140,000 European Descendants

Genome-wide association study–identified prostate cancer risk variants explain only a relatively small fraction of its familial relative risk, and the genes responsible for many of these identified associations remain unknown. To discover novel prostate cancer genetic loci and possible causal genes at previously identified risk loci, we performed a transcriptome-wide association study in 79,194 cases and 61,112 controls of European ancestry. Using data from the Genotype-Tissue Expression Project, we established genetic models to predict gene expression across the transcriptome for both prostate models and cross-tissue models and evaluated model performance using two independent datasets. We identified significant associations for 137 genes at P < 2.61 × 10−6, a Bonferroni-corrected threshold, including nine genes that remained significant at P < 2.61 × 10−6 after adjusting for all known prostate cancer risk variants in nearby regions. Of the 128 remaining associated genes, 94 have not yet been reported as potential target genes at known loci. We silenced 14 genes and many showed a consistent effect on viability and colony-forming efficiency in three cell lines. Our study provides substantial new information to advance our understanding of prostate cancer genetics and biology. SIGNIFICANCE: This study identifies novel prostate cancer genetic loci and possible causal genes, advancing our understanding of the molecular mechanisms that drive prostate cancer

Genome-wide association study identifies susceptibility loci for B-cell childhood acute lymphoblastic leukemia.

Genome-wide association studies (GWAS) have advanced our understanding of susceptibility to B-cell precursor acute lymphoblastic leukemia (BCP-ALL); however, much of the heritable risk remains unidentified. Here, we perform a GWAS and conduct a meta-analysis with two existing GWAS, totaling 2442 cases and 14,609 controls. We identify risk loci for BCP-ALL at 8q24.21 (rs28665337, P = 3.86 × 10-9, odds ratio (OR) = 1.34) and for ETV6-RUNX1 fusion-positive BCP-ALL at 2q22.3 (rs17481869, P = 3.20 × 10-8, OR = 2.14). Our findings provide further insights into genetic susceptibility to ALL and its biology

Germline variation at 8q24 and prostate cancer risk in men of European ancestry

An Author Correction to this article was published on 17 January 2019.Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10 −15 ), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification. © 2018, The Author(s).Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10 −15 ), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification. © 2018, The Author(s).Peer reviewe

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk

BACKGROUND: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). RESULTS: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization

Runs of homozygosity and testicular cancer risk

Background: Testicular germ cell tumour (TGCT) is highly heritable but > 50% of the genetic risk remains unexplained. Epidemiological observation of greater relative risk to brothers of men with TGCT compared to sons has long alluded to recessively acting TGCT genetic susceptibility factors, but to date none have been reported. Runs of homozygosity (RoH) are a signature indicating underlying recessively acting alleles and have been associated with increased risk of other cancer types. / Objective: To examine whether RoH are associated with TGCT risk. / Methods: We performed a genome‐wide RoH analysis using GWAS data from 3206 TGCT cases and 7422 controls uniformly genotyped using the OncoArray platform. / Results: Global measures of homozygosity were not significantly different between cases and controls, and the frequency of individual consensus RoH was not significantly different between cases and controls, after correction for multiple testing. RoH at three regions, 11p13‐11p14.3, 5q14.1‐5q22.3 and 13q14.11‐13q.14.13, were, however, nominally statistically significant at p < 0.01. Intriguingly, RoH200 at 11p13‐11p14.3 encompasses Wilms tumour 1 (WT1), a recognized cancer susceptibility gene with roles in sex determination and developmental transcriptional regulation, processes repeatedly implicated in TGCT aetiology. / Discussion and conclusion: Overall, our data do not support a major role in the risk of TGCT for recessively acting alleles acting through homozygosity, as measured by RoH in outbred populations of cases and controls

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer

BACKGROUND: Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer. METHODS: In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients. RESULTS: The most significant global associations for all genes in the pathway were seen in endometrioid (p = 0.082) and clear cell (p = 0.083), with the most significant gene level association seen with TGFBR2 (p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 (p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA (p = 0.035, endometrioid and mucinous), LGALS1 (p = 0.03, mucinous), STAT5B (p = 0.022, clear cell), TGFBR1 (p = 0.021 endometrioid) and TGFBR2 (p = 0.017 and p = 0.025, endometrioid and mucinous, respectively). CONCLUSIONS: Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients

Variants in genes encoding small GTPases and association with epithelial ovarian cancer susceptibility

Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality in American women. Normal ovarian physiology is intricately connected to small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran) which govern processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. We hypothesized that common germline variation in genes encoding small GTPases is associated with EOC risk. We investigated 322 variants in 88 small GTPase genes in germline DNA of 18,736 EOC patients and 26,138 controls of European ancestry using a custom genotype array and logistic regression fitting log-additive models. Functional annotation was used to identify biofeatures and expression quantitative trait loci that intersect with risk variants. One variant, ARHGEF10L (Rho guanine nucleotide exchange factor 10 like) rs2256787, was associated with increased endometrioid EOC risk (OR=1.33, p=4.46 x 10-6). Other variants of interest included another in ARHGEF10L, rs10788679, which was associated with invasive serous EOC risk (OR=1.07, p=0.00026) and two variants in AKAP6 (A-kinase anchoring protein 6) which were associated with risk of invasive EOC (rs1955513, OR=0.90, p=0.00033; rs927062, OR =0.94, p=0.00059). Functional annotation revealed that the two ARHGEF10L variants were located in super-enhancer regions and that AKAP6 rs927062 was associated with expression of GTPase gene ARHGAP5 (Rho GTPase activating protein 5). Inherited variants in ARHGEF10L and AKAP6, with potential transcriptional regulatory function and association with EOC risk, warrant investigation in independent EOC study populations

Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 x 10(-15)), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95% CI = 3.62-4.40) greater risk compared to the population average. These 12 variants account for similar to 25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification

Author Correction: Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Correction to: Nature Communications; https://doi.org/10.1038/s41467-018-06863-1, published online 5 November 2018

Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study.

Background Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer-metabolite associations using two-sample Mendelian randomization (MR).Methods The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.Results Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.Conclusions We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.Impact The metabolome provides a promising set of biomarkers that may aid prostate cancer classification