A rare variant, which destroys a FoxA1 site at 8q24, is associated with prostate cancer risk

Gene Association Analysis of Quantitative Trait Based on Functional Linear Regression Model with Local Sparse Estimator

Functional linear regression models have been widely used in the gene association analysis of complex traits. These models retain all the genetic information in the data and take full advantage of spatial information in genetic variation data, which leads to brilliant detection power. However, the significant association signals identified by the high-power methods are not all the real causal SNPs, because it is easy to regard noise information as significant association signals, leading to a false association. In this paper, a method based on the sparse functional data association test (SFDAT) of gene region association analysis is developed based on a functional linear regression model with local sparse estimation. The evaluation indicators CSR and DL are defined to evaluate the feasibility and performance of the proposed method with other indicators. Simulation studies show that: (1) SFDAT performs well under both linkage equilibrium and linkage disequilibrium simulation; (2) SFDAT performs successfully for gene regions (including common variants, low-frequency variants, rare variants and mix variants); (3) With power and type I error rates comparable to OLS and Smooth, SFDAT has a better ability to handle the zero regions. The Oryza sativa data set is analyzed by SFDAT. It is shown that SFDAT can better perform gene association analysis and eliminate the false positive of gene localization. This study showed that SFDAT can lower the interference caused by noise while maintaining high power. SFDAT provides a new method for the association analysis between gene regions and phenotypic quantitative traits.

The Parkinson's disease variant rs356182 regulates neuronal differentiation independently from alpha-synuclein

One of the most significant risk variants for Parkinson's disease (PD), rs356182, is located at the PD-associated locus near the alpha-synuclein (α-syn) encoding gene, SNCA. SNCA-proximal variants, including rs356182, are thought to function in PD risk through enhancers via allele-specific regulatory effects on SNCA expression. However, this interpretation discounts the complex activity of genetic enhancers and possible non-conical functions of α-syn. Here we investigated a novel risk mechanism for rs356182. We use CRISPR-Cas9 in LUHMES cells, a model for dopaminergic midbrain neurons, to generate precise hemizygous lesions at rs356182. The PD-protective (A/-), PD-risk (G/-) and wild-type (A/G) clones were neuronally differentiated and then compared transcriptionally and morphologically. Among the affected genes was SNCA, whose expression was promoted by the PD-protective allele (A) and repressed in its absence. In addition to SNCA, hundreds of genes were differentially expressed and associated with neurogenesis and axonogenesis-an effect not typically ascribed to α-syn. We also found that the transcription factor FOXO3 specifically binds to the rs356182 A-allele in differentiated LUHMES cells. Finally, we compared the results from the rs356182-edited cells to our previously published knockouts of SNCA and found only minimal overlap between the sets of significant differentially expressed genes. Together, the data implicate a risk mechanism for rs356182 in which the risk-allele (G) is associated with abnormal neuron development, independent of SNCA expression. We speculate that these pathological effects manifest as a diminished population of dopaminergic neurons during development leading to the predisposition for PD later in life.

Identification of Germline Genetic Variants that Increase Prostate Cancer Risk and Influence Development of Aggressive Disease

Prostate cancer (PrCa) is a heterogeneous disease, which presents in individual patients across a diverse phenotypic spectrum ranging from indolent to fatal forms. No robust biomarkers are currently available to enable routine screening for PrCa or to distinguish clinically significant forms, therefore late stage identification of advanced disease and overdiagnosis plus overtreatment of insignificant disease both remain areas of concern in healthcare provision. PrCa has a substantial heritable component, and technological advances since the completion of the Human Genome Project have facilitated improved identification of inherited genetic factors influencing susceptibility to development of the disease within families and populations. These genetic markers hold promise to enable improved understanding of the biological mechanisms underpinning PrCa development, facilitate genetically informed PrCa screening programmes and guide appropriate treatment provision. However, insight remains largely lacking regarding many aspects of their manifestation; especially in relation to genes associated with aggressive phenotypes, risk factors in non-European populations and appropriate approaches to enable accurate stratification of higher and lower risk individuals. This review discusses the methodology used in the elucidation of genetic loci, genes and individual causal variants responsible for modulating PrCa susceptibility; the current state of understanding of the allelic spectrum contributing to PrCa risk; and prospective future translational applications of these discoveries in the developing eras of genomics and personalised medicine.

Pioneer of prostate cancer: past, present and the future of FOXA1

Prostate cancer is the most commonly diagnosed non-cutaneous cancers in North American men. While androgen deprivation has remained as the cornerstone of prostate cancer treatment, resistance ensues leading to lethal disease. Forkhead box A1 (FOXA1) encodes a pioneer factor that induces open chromatin conformation to allow the binding of other transcription factors. Through direct interactions with the Androgen Receptor (AR), FOXA1 helps to shape AR signaling that drives the growth and survival of normal prostate and prostate cancer cells. FOXA1 also possesses an AR-independent role of regulating epithelial-to-mesenchymal transition (EMT). In prostate cancer, mutations converge onto the coding sequence and cis-regulatory elements (CREs) of FOXA1, leading to functional alterations. In addition, FOXA1 activity in prostate cancer can be modulated post-translationally through various mechanisms such as LSD1-mediated protein demethylation. In this review, we describe the latest discoveries related to the function and regulation of FOXA1 in prostate cancer, pointing to their relevance to guide future clinical interventions.

Cumulative evidence of relationships between multiple variants in 8q24 region and cancer incidence

Genome-wide association studies (GWAS) have identified multiple independent cancer susceptibility loci at chromosome 8q24. We aimed to evaluate the associations between variants in the 8q24 region and cancer susceptibility. A comprehensive research synopsis and meta-analysis was performed to evaluate associations between 28 variants in 8q24 and risk of 7 cancers using data from 103 eligible articles totaling 146,932 cancer cases and 219,724 controls. Results: 20 variants were significantly associated with risk of prostate cancer, colorectal cancer, thyroid cancer, breast cancer, bladder cancer, stomach cancer, and glioma, including 1 variant associated with prostate cancer, colorectal cancer, and thyroid cancer. Cumulative epidemiological evidence of an association was graded as strong for DG8S737 -8 allele, rs10090154, rs7000448 in prostate cancer, rs10808556 in colorectal cancer, rs55705857 in gliomas, rs9642880 in bladder cancer, moderate for rs16901979, rs1447295, rs6983267, rs7017300, rs7837688, rs1016343, rs620861, rs10086908 associated in prostate cancer, rs10505477, rs6983267 in colorectal cancer, rs6983267 in thyroid cancer, rs13281615 in breast cancer, and rs1447295 in stomach cancer, weak for rs6983561, rs13254738, rs7008482, rs4242384 in prostate cancer. Data from ENCODE suggested that these variants with strong evidence and other correlated variants might fall within putative functional regions. Our study provides summary evidence that common variants in the 8q24 are associated with risk of multiple cancers in this large-scale research synopsis and meta-analysis. Further studies are needed to explore the mechanisms underlying variants in the 8q24 involved in various human cancers.

Post-GWAS in prostate cancer: from genetic association to biological contribution

Genome-wide association studies (GWAS) have been successful in deciphering the genetic component of predisposition to many human complex diseases including prostate cancer. Germline variants identified by GWAS progressively unravelled the substantial knowledge gap concerning prostate cancer heritability. With the beginning of the post-GWAS era, more and more studies reveal that, in addition to their value as risk markers, germline variants can exert active roles in prostate oncogenesis. Consequently, current research efforts focus on exploring the biological mechanisms underlying specific susceptibility loci known as causal variants by applying novel and precise analytical methods to available GWAS data. Results obtained from these post-GWAS analyses have highlighted the potential of exploiting prostate cancer risk-associated germline variants to identify new gene networks and signalling pathways involved in prostate tumorigenesis. In this Review, we describe the molecular basis of several important prostate cancer-causal variants with an emphasis on using post-GWAS analysis to gain insight into cancer aetiology. In addition to discussing the current status of post-GWAS studies, we also summarize the main molecular mechanisms of potential causal variants at prostate cancer risk loci and explore the major challenges in moving from association to functional studies and their implication in clinical translation.

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 × 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.

Genome-wide association of familial prostate cancer cases identifies evidence for a rare segregating haplotype at 8q24.21

Previous genome-wide association studies (GWAS) of prostate cancer risk focused on cases unselected for family history and have reported over 100 significant associations. The International Consortium for Prostate Cancer Genetics (ICPCG) has now performed a GWAS of 2511 (unrelated) familial prostate cancer cases and 1382 unaffected controls from 12 member sites. All samples were genotyped on the Illumina 5M+exome single nucleotide polymorphism (SNP) platform. The GWAS identified a significant evidence for association for SNPs in six regions previously associated with prostate cancer in population-based cohorts, including 3q26.2, 6q25.3, 8q24.21, 10q11.23, 11q13.3, and 17q12. Of note, SNP rs138042437 (p = 1.7e(-8)) at 8q24.21 achieved a large estimated effect size in this cohort (odds ratio = 13.3). 116 previously sampled affected relatives of 62 risk-allele carriers from the GWAS cohort were genotyped for this SNP, identifying 78 additional affected carriers in 62 pedigrees. A test for an excess number of affected carriers among relatives exhibited strong evidence for co-segregation of the variant with disease (p = 8.5e(-11)). The majority (92 %) of risk-allele carriers at rs138042437 had a consistent estimated haplotype spanning approximately 100 kb of 8q24.21 that contained the minor alleles of three rare SNPs (dosage minor allele frequencies <1.7 %), rs183373024 (PRNCR1), previously associated SNP rs188140481, and rs138042437 (CASC19). Strong evidence for co-segregation of a SNP on the haplotype further characterizes the haplotype as a prostate cancer predisposition locus.

Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation

Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.

Gene regulatory mechanisms underpinning prostate cancer susceptibility

Molecular characterization of genome-wide association study (GWAS) loci can uncover key genes and biological mechanisms underpinning complex traits and diseases. Here we present deep, high-throughput characterization of gene regulatory mechanisms underlying prostate cancer risk loci. Our methodology integrates data from 295 prostate cancer chromatin immunoprecipitation and sequencing experiments with genotype and gene expression data from 602 prostate tumor samples. The analysis identifies new gene regulatory mechanisms affected by risk locus SNPs, including widespread disruption of ternary androgen receptor (AR)-FOXA1 and AR-HOXB13 complexes and competitive binding mechanisms. We identify 57 expression quantitative trait loci at 35 risk loci, which we validate through analysis of allele-specific expression. We further validate predicted regulatory SNPs and target genes in prostate cancer cell line models. Finally, our integrated analysis can be accessed through an interactive visualization tool. This analysis elucidates how genome sequence variation affects disease predisposition via gene regulatory mechanisms and identifies relevant genes for downstream biomarker and drug development.

FOXA1 defines cancer cell specificity

A transcription factor functions differentially and/or identically in multiple cell types. However, the mechanism for cell-specific regulation of a transcription factor remains to be elucidated. We address how a single transcription factor, forkhead box protein A1 (FOXA1), forms cell-specific genomic signatures and differentially regulates gene expression in four human cancer cell lines (HepG2, LNCaP, MCF7, and T47D). FOXA1 is a pioneer transcription factor in organogenesis and cancer progression. Genomewide mapping of FOXA1 by chromatin immunoprecipitation sequencing annotates that target genes associated with FOXA1 binding are mostly common to these cancer cells. However, most of the functional FOXA1 target genes are specific to each cancer cell type. Further investigations using CRISPR-Cas9 genome editing technology indicate that cell-specific FOXA1 regulation is attributable to unique FOXA1 binding, genetic variations, and/or potential epigenetic regulation. Thus, FOXA1 controls the specificity of cancer cell types. We raise a "flower-blooming" hypothesis for cell-specific transcriptional regulation based on these observations.

Whole-exome sequencing of over 4100 men of African ancestry and prostate cancer risk

Prostate cancer is the most common non-skin cancer in males, with a ∼1.5-2-fold higher incidence in African American men when compared with whites. Epidemiologic evidence supports a large heritable contribution to prostate cancer, with over 100 susceptibility loci identified to date that can explain ∼33% of the familial risk. To explore the contribution of both rare and common variation in coding regions to prostate cancer risk, we sequenced the exomes of 2165 prostate cancer cases and 2034 controls of African ancestry at a mean coverage of 10.1×. We identified 395 220 coding variants down to 0.05% frequency [57% non-synonymous (NS), 42% synonymous and 1% gain or loss of stop codon or splice site variant] in 16 751 genes with the strongest associations observed in SPARCL1 on 4q22.1 (rs13051, Ala49Asp, OR = 0.78, P = 1.8 × 10(-6)) and PTPRR on 12q15 (rs73341069, Val239Ile, OR = 1.62, P = 2.5 × 10(-5)). In gene-level testing, the two most significant genes were C1orf100 (P = 2.2 × 10(-4)) and GORAB (P = 2.3 × 10(-4)). We did not observe exome-wide significant associations (after correcting for multiple hypothesis testing) in single variant or gene-level testing in the overall case-control or case-case analyses of disease aggressiveness. In this first whole-exome sequencing study of prostate cancer, our findings do not provide strong support for the hypothesis that NS coding variants down to 0.5-1.0% frequency have large effects on prostate cancer risk in men of African ancestry. Higher-coverage sequencing efforts in larger samples will be needed to study rarer variants with smaller effect sizes associated with prostate cancer risk.

The contribution of rare variation to prostate cancer heritability

We report targeted sequencing of 63 known prostate cancer risk regions in a multi-ancestry study of 9,237 men and use the data to explore the contribution of low-frequency variation to disease risk. We show that SNPs with minor allele frequencies (MAFs) of 0.1-1% explain a substantial fraction of prostate cancer risk in men of African ancestry. We estimate that these SNPs account for 0.12 (standard error (s.e.) = 0.05) of variance in risk (∼42% of the variance contributed by SNPs with MAF of 0.1-50%). This contribution is much larger than the fraction of neutral variation due to SNPs in this class, implying that natural selection has driven down the frequency of many prostate cancer risk alleles; we estimate the coupling between selection and allelic effects at 0.48 (95% confidence interval [0.19, 0.78]) under the Eyre-Walker model. Our results indicate that rare variants make a disproportionate contribution to genetic risk for prostate cancer and suggest the possibility that rare variants may also have an outsize effect on other common traits.

Variants on 8q24 and prostate cancer risk in Chinese population: a meta-analysis

Previous studies have identified 8q24 as an important region to prostate cancer (PCa) susceptibility. The aim of this study was to investigate the role of six genetic variants on 8q24 (rs1447295, A; rs6983267, G; rs6983561, C; rs7837688, T; rs10090154, T and rs16901979, A) on PCa risk in Chinese population. Online electronic databases were searched to retrieve related articles concerning the association between 8q24 variants and PCa risk in men of Chinese population published between 2000 and 2014. Odds ratio (ORs) with its 95% correspondence interval (CI) were employed to assess the strength of association. Total eleven case-control studies were screened out, including 2624 PCa patients and 2438 healthy controls. Our results showed that three risk alleles of rs1447295 A (OR=1.35, 95% CI=1.19-1.53, P<0.00001), rs6983561 C (C vs. A: OR=1.41, 95% CI=1.21-1.63, P<0.00001) and rs10090154 T (T vs. C: OR=1.48, 95% CI=1.22-1.80, P<0.00001) on8q24 were significantly associated with PCa risk in Chinese population. Furthermore, genotypes of rs1447295, AA+AC; rs6983561, CC+AC and CC; rs10090154, TT+TC; and rs16901979, AA were associated with PCa as well (P<0.01). No association was found between rs6983267, rs7837688 and PCa risk. In conclusions, variants including rs1447295, rs6983561, rs10090154 and rs16901979 on 8q24 might be associated with PCa risk in Chinese population, indicating these four variations may contribute risk to this disease. This meta-analysis was the first study to assess the role of 8q24 variants on PCa risk in Chinese population.

Current perspectives on FOXA1 regulation of androgen receptor signaling and prostate cancer

FOXA1 (also known as hepatocyte nuclear factor 3α, or HNF-3α) is a protein of the FKHD family transcription factors. FOXA1 has been termed as a pioneer transcription factor due to its unique ability of chromatin remodeling in which the chromatin can be de-compacted to allow genomic access by nuclear hormone receptors, including androgen receptor (AR) and estrogen receptor (ER). In this review, we discuss our current understanding of FOXA1 regulation of prostatic and non-prostatic AR-chromatin targeting. We present an updated model wherein FOXA1:AR equilibrium in the nuclei defines prostatic AR binding profile, which is perturbed in prostate cancer with FOXA1 and/or AR de-regulation. Finally, we discuss recent efforts in exploring new horizons of AR-independent functions of FOXA1 in prostate cancer and interesting directions to pursue in future studies.

Comprehensive functional annotation of 77 prostate cancer risk loci

Genome-wide association studies (GWAS) have revolutionized the field of cancer genetics, but the causal links between increased genetic risk and onset/progression of disease processes remain to be identified. Here we report the first step in such an endeavor for prostate cancer. We provide a comprehensive annotation of the 77 known risk loci, based upon highly correlated variants in biologically relevant chromatin annotations--we identified 727 such potentially functional SNPs. We also provide a detailed account of possible protein disruption, microRNA target sequence disruption and regulatory response element disruption of all correlated SNPs at r(2) ≥ 0.88%. 88% of the 727 SNPs fall within putative enhancers, and many alter critical residues in the response elements of transcription factors known to be involved in prostate biology. We define as risk enhancers those regions with enhancer chromatin biofeatures in prostate-derived cell lines with prostate-cancer correlated SNPs. To aid the identification of these enhancers, we performed genomewide ChIP-seq for H3K27-acetylation, a mark of actively engaged enhancers, as well as the transcription factor TCF7L2. We analyzed in depth three variants in risk enhancers, two of which show significantly altered androgen sensitivity in LNCaP cells. This includes rs4907792, that is in linkage disequilibrium (r(2) = 0.91) with an eQTL for NUDT11 (on the X chromosome) in prostate tissue, and rs10486567, the index SNP in intron 3 of the JAZF1 gene on chromosome 7. Rs4907792 is within a critical residue of a strong consensus androgen response element that is interrupted in the protective allele, resulting in a 56% decrease in its androgen sensitivity, whereas rs10486567 affects both NKX3-1 and FOXA-AR motifs where the risk allele results in a 39% increase in basal activity and a 28% fold-increase in androgen stimulated enhancer activity. Identification of such enhancer variants and their potential target genes represents a preliminary step in connecting risk to disease process.

Candidate gene association studies: a comprehensive guide to useful in silico tools

The candidate gene approach has been a pioneer in the field of genetic epidemiology, identifying risk alleles and their association with clinical traits. With the advent of rapidly changing technology, there has been an explosion of in silico tools available to researchers, giving them fast, efficient resources and reliable strategies important to find casual gene variants for candidate or genome wide association studies (GWAS). In this review, following a description of candidate gene prioritisation, we summarise the approaches to single nucleotide polymorphism (SNP) prioritisation and discuss the tools available to assess functional relevance of the risk variant with consideration to its genomic location. The strategy and the tools discussed are applicable to any study investigating genetic risk factors associated with a particular disease. Some of the tools are also applicable for the functional validation of variants relevant to the era of GWAS and next generation sequencing (NGS).