A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer

A Prostate Cancer Risk Element Functions as a Repressive Loop that Regulates HOXA13

Prostate cancer (PCa) is the leading cancer among men in the United States, with genetic factors contributing to ∼42% of the susceptibility to PCa. We analyzed a PCa risk region located at 7p15.2 to gain insight into the mechanisms by which this noncoding region may affect gene regulation and contribute to PCa risk. We performed Hi-C analysis and demonstrated that this region has long-range interactions with the HOXA locus, located ∼873 kb away. Using the CRISPR/Cas9 system, we deleted a 4-kb region encompassing several PCa risk-associated SNPs and performed RNA-seq to investigate transcriptomic changes in prostate cells lacking the regulatory element. Our results suggest that the risk element affects the expression of HOXA13 and HOTTIP, but not other genes in the HOXA locus, via a repressive loop. Forced expression of HOXA13 was performed to gain further insight into the mechanisms by which this risk element affects PCa risk.

Genome-wide association studies of cancer: current insights and future perspectives

Genome-wide association studies (GWAS) provide an agnostic approach for investigating the genetic basis of complex diseases. In oncology, GWAS of nearly all common malignancies have been performed, and over 450 genetic variants associated with increased risks have been identified. As well as revealing novel pathways important in carcinogenesis, these studies have shown that common genetic variation contributes substantially to the heritable risk of many common cancers. The clinical application of GWAS is starting to provide opportunities for drug discovery and repositioning as well as for cancer prevention. However, deciphering the functional and biological basis of associations is challenging and is in part a barrier to fully unlocking the potential of GWAS.

Integration of Genome Scale Metabolic Networks and Gene Regulation of Metabolic Enzymes With Physiologically Based Pharmacokinetics

The scope of physiologically based pharmacokinetic (PBPK) modeling can be expanded by assimilation of the mechanistic models of intracellular processes from systems biology field. The genome scale metabolic networks (GSMNs) represent a whole set of metabolic enzymes expressed in human tissues. Dynamic models of the gene regulation of key drug metabolism enzymes are available. Here, we introduce GSMNs and review ongoing work on integration of PBPK, GSMNs, and metabolic gene regulation. We demonstrate example models.

Circulating vitamin D concentration and risk of seven cancers: Mendelian randomisation study

Objective To determine if circulating concentrations of vitamin D are causally associated with risk of cancer.Design Mendelian randomisation study.Setting Large genetic epidemiology networks (the Genetic Associations and Mechanisms in Oncology (GAME-ON), the Genetic and Epidemiology of Colorectal Cancer Consortium (GECCO), and the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortiums, and the MR-Base platform).Participants 70 563 cases of cancer (22 898 prostate cancer, 15 748 breast cancer, 12 537 lung cancer, 11 488 colorectal cancer, 4369 ovarian cancer, 1896 pancreatic cancer, and 1627 neuroblastoma) and 84 418 controls.Exposures Four single nucleotide polymorphisms (rs2282679, rs10741657, rs12785878 and rs6013897) associated with vitamin D were used to define a multi-polymorphism score for circulating 25-hydroxyvitamin D (25(OH)D) concentrations.Main outcomes measures The primary outcomes were the risk of incident colorectal, breast, prostate, ovarian, lung, and pancreatic cancer and neuroblastoma, which was evaluated with an inverse variance weighted average of the associations with specific polymorphisms and a likelihood based approach. Secondary outcomes based on cancer subtypes by sex, anatomic location, stage, and histology were also examined.Results There was little evidence that the multi-polymorphism score of 25(OH)D was associated with risk of any of the seven cancers or their subtypes. Specifically, the odds ratios per 25 nmol/L increase in genetically determined 25(OH)D concentrations were 0.92 (95% confidence interval 0.76 to 1.10) for colorectal cancer, 1.05 (0.89 to 1.24) for breast cancer, 0.89 (0.77 to 1.02) for prostate cancer, and 1.03 (0.87 to 1.23) for lung cancer. The results were consistent with the two different analytical approaches, and the study was powered to detect relative effect sizes of moderate magnitude (for example, 1.20-1.50 per 25 nmol/L decrease in 25(OH)D for most primary cancer outcomes. The Mendelian randomisation assumptions did not seem to be violated.Conclusions There is little evidence for a linear causal association between circulating vitamin D concentration and risk of various types of cancer, though the existence of causal clinically relevant effects of low magnitude cannot be ruled out. These results, in combination with previous literature, provide evidence that population-wide screening for vitamin D deficiency and subsequent widespread vitamin D supplementation should not currently be recommended as a strategy for primary cancer prevention.

Network-directed cis-mediator analysis of normal prostate tissue expression profiles reveals downstream regulatory associations of prostate cancer susceptibility loci

Large-scale genome-wide association studies have identified multiple single-nucleotide polymorphisms associated with risk of prostate cancer. Many of these genetic variants are presumed to be regulatory in nature; however, follow-up expression quantitative trait loci (eQTL) association studies have to-date been restricted largely to cis-acting associations due to study limitations. While trans-eQTL scans suffer from high testing dimensionality, recent evidence indicates most trans-eQTL associations are mediated by cis-regulated genes, such as transcription factors. Leveraging a data-driven gene co-expression network, we conducted a comprehensive cis-mediator analysis using RNA-Seq data from 471 normal prostate tissue samples to identify downstream regulatory associations of previously identified prostate cancer risk variants. We discovered multiple trans-eQTL associations that were significantly mediated by cis-regulated transcripts, four of which involved risk locus 17q12, proximal transcription factor HNF1B, and target trans-genes with known HNF response elements (MIA2, SRC, SEMA6A, KIF12). We additionally identified evidence of cis-acting down-regulation of MSMB via rs10993994 corresponding to reduced co-expression of NDRG1. The majority of these cis-mediator relationships demonstrated trans-eQTL replicability in 87 prostate tissue samples from the Gene-Tissue Expression Project. These findings provide further biological context to known risk loci and outline new hypotheses for investigation into the etiology of prostate cancer.

Deletion of tumor suppressors adenomatous polyposis coli and Smad4 in murine luminal epithelial cells causes invasive prostate cancer and loss of androgen receptor expression

Prostate cancer is the most diagnosed non-skin cancer in the US and kills approximately 27,000 men per year in the US. Additional genetic mouse models are needed that recapitulate the heterogeneous nature of human prostate cancer. The Wnt/beta-catenin signaling pathway is important for human prostate tumorigenesis and metastasis, and also drives tumorigenesis in mouse models. Loss of Smad4 has also been found in human prostate cancer and drives tumorigenesis and metastasis when coupled with other genetic aberrations in mouse models. In this work, we concurrently deleted Smad4 and the tumor suppressor and endogenous Wnt/beta-catenin inhibitor adenomatous polyposis coli (Apc) in luminal prostate cells in mice. This double conditional knockout model produced invasive castration-resistant prostate carcinoma with no evidence of metastasis. We observed mixed differentiation phenotypes, including basaloid and squamous differentiation. Interestingly, tumor cells in this model commonly lose androgen receptor expression. In addition, tumors disappear in these mice during androgen cycling (castration followed by testosterone reintroduction). These mice model non-metastatic castration resistant prostate cancer and should provide novel information for tumors that have genetic aberrations in the Wnt pathway or Smad4.

Next generation mapping reveals novel large genomic rearrangements in prostate cancer

Complex genomic rearrangements are common molecular events driving prostate carcinogenesis. Clinical significance, however, has yet to be fully elucidated. Detecting the full range and subtypes of large structural variants (SVs), greater than one kilobase in length, is challenging using clinically feasible next generation sequencing (NGS) technologies. Next generation mapping (NGM) is a new technology that allows for the interrogation of megabase length DNA molecules outside the detection range of single-base resolution NGS. In this study, we sought to determine the feasibility of using the Irys (Bionano Genomics Inc.) nanochannel NGM technology to generate whole genome maps of a primary prostate tumor and matched blood from a Gleason score 7 (4 + 3), ETS-fusion negative prostate cancer patient. With an effective mapped coverage of 35X and sequence coverage of 60X, and an estimated 43% tumor purity, we identified 85 large somatic structural rearrangements and 6,172 smaller somatic variants, respectively. The vast majority of the large SVs (89%), of which 73% are insertions, were not detectable ab initio using high-coverage short-read NGS. However, guided manual inspection of single NGS reads and de novo assembled scaffolds of NGM-derived candidate regions allowed for confirmation of 94% of these large SVs, with over a third impacting genes with oncogenic potential. From this single-patient study, the first cancer study to integrate NGS and NGM data, we hypothesise that there exists a novel spectrum of large genomic rearrangements in prostate cancer, that these large genomic rearrangements are likely early events in tumorigenesis, and they have potential to enhance taxonomy.

Improvement in prediction of prostate cancer prognosis with somatic mutational signatures

Prostate cancer is a leading male malignancy worldwide, while the prognosis prediction remains quite inaccurate. The study aimed to observe whether there was an association between the prognosis of prostate cancer and genetic mutation profile, and to build an accurate prognostic predictor based on the genetic signatures. The patients diagnosed of prostate cancer from The Cancer Genomic Atlas were used for prognostic stratification, while the somatic gene mutation profiles were compared between different prognostic groups. The genetic features were further used for training machine-learning models to predict prostate cancer prognosis. No significant gene with somatic mutation rate difference was found between prognostic groups of prostate cancer. Total 43 atypical genes were screened for building a support vector machine model to predict prostate cancer prognosis, with an average accuracy of 66% and 64% for 5-fold cross-validation or training-testing evaluation respectively. When combined with the National Institute for Health and Care Excellence (NICE) features, the model could be further improved, with the 5-fold cross-validation accuracy of ~71%, much better than NICE itself (62%). To our knowledge, for the first time, the research studied the relationship of genome-wide somatic mutations with prostate prognosis, and developed an effective prognostic prediction model with the atypical genetic signatures.

The Mediterranean Diet Reduces the Risk and Mortality of the Prostate Cancer: A Narrative Review

Prostate cancer is the second most common cancer in the world among men, and is the fifth most common cause of cancer death among men. The aim of our review was to analyze observational and case–control studies to point out the effects of overweight and diets components on the cancer risk, particularly on risk of prostate cancer, and the effect of the Mediterranean diet (MD) on the reduction of risk and mortality of prostate cancer. It is known that incidence and progression of cancer is multifactorial. Cancer of the large bowel, breast, endometrium, and prostate are due also to a high body mass index and to high consumption of high carcinogenic dietary factors, as red and processed meat or saturated fats rich foods, and to a low consumption of vegetables and fruits. Previous meta-analysis suggested that high adherence to diet model based on the traditional MD pattern gives a significant protection from incidence and mortality of cancer of all types. The main component of the MD is olive oil, consumed in high amount by Mediterranean basin populations. In addition, phenolic compounds exert some strong chemo-preventive effects, which are due to several mechanisms, including both antioxidant effects and actions on cancer cell signaling and cell cycle progression and proliferation. The protective effect of the MD against the prostate cancer is also due to the high consumption of tomato sauce. Lycopene is the most relevant functional component in tomatoes; after activating by the cooking of tomato sauce, it exerts antioxidant properties by acting in the modulation of downregulation mechanisms of the inflammatory response. MD, therefore, represents a healthy dietary pattern in the context of a healthy lifestyle habits. In conclusion, our narrative review allows us to reaffirm how nutritional factors play an important role in cancer initiation and development, and how a healthy dietary pattern represented by MD and its components, especially olive oil, could exert a protective role by the development and progression of prostate cancer.

Height, selected genetic markers and prostate cancer risk: results from the PRACTICAL consortium

BACKGROUND

Evidence on height and prostate cancer risk is mixed, however, recent studies with large data sets support a possible role for its association with the risk of aggressive prostate cancer.

METHODS

We analysed data from the PRACTICAL consortium consisting of 6207 prostate cancer cases and 6016 controls and a subset of high grade cases (2480 cases). We explored height, polymorphisms in genes related to growth processes as main effects and their possible interactions.

RESULTS

The results suggest that height is associated with high-grade prostate cancer risk. Men with height >180 cm are at a 22% increased risk as compared to men with height <173 cm (OR 1.22, 95% CI 1.01-1.48). Genetic variants in the growth pathway gene showed an association with prostate cancer risk. The aggregate scores of the selected variants identified a significantly increased risk of overall prostate cancer and high-grade prostate cancer by 13% and 15%, respectively, in the highest score group as compared to lowest score group.

CONCLUSIONS

There was no evidence of gene-environment interaction between height and the selected candidate SNPs.Our findings suggest a role of height in high-grade prostate cancer. The effect of genetic variants in the genes related to growth is seen in all cases and high-grade prostate cancer. There is no interaction between these two exposures.

African-American Prostate Cancer Disparities

PURPOSE OF REVIEW

The purpose of this review is to examine prostate cancer racial disparities specific to the African-American population.

RECENT FINDINGS

African-American men are more likely to be diagnosed with prostate cancer, present at an earlier age; are more likely to have locally advanced or metastatic disease at diagnosis; and have suboptimal outcomes to standard treatments. Prostate cancer treatment requires a nuanced approach, particularly when applying screening, counseling, and management of African-American men. Oncological as well as functional outcomes may differ and are potentially due to a combination of genetic, molecular, behavioral, and socioeconomic factors.

Two Novel Susceptibility Loci for Prostate Cancer in Men of African Ancestry

Prostate cancer incidence is 1.6-fold higher in African Americans than in other populations. The risk factors that drive this disparity are unknown and potentially consist of social, environmental, and genetic influences. To investigate the genetic basis of prostate cancer in men of African ancestry, we performed a genome-wide association meta-analysis using two-sided statistical tests in 10 202 case subjects and 10 810 control subjects. We identified novel signals on chromosomes 13q34 and 22q12, with the risk-associated alleles found only in men of African ancestry (13q34: rs75823044, risk allele frequency = 2.2%, odds ratio [OR] = 1.55, 95% confidence interval [CI] = 1.37 to 1.76, P = 6.10 × 10-12; 22q12.1: rs78554043, risk allele frequency = 1.5%, OR = 1.62, 95% CI = 1.39 to 1.89, P = 7.50 × 10-10). At 13q34, the signal is located 5' of the gene IRS2 and 3' of a long noncoding RNA, while at 22q12 the candidate functional allele is a missense variant in the CHEK2 gene. These findings provide further support for the role of ancestry-specific germline variation in contributing to population differences in prostate cancer risk.

Reclassification of prostate cancer risk using sequentially identified SNPs: Results from the REDUCE trial

BACKGROUND

Although the clinical validity of risk-associated single nucleotide polymorphisms (SNPs) for assessment of disease susceptibility has been consistently established, risk reclassification from increasing numbers of implicated risk-associated SNPs raises concern that it is premature for clinical use. Our objective is to assess the degree and impact of risk reclassification with the increasing number of SNPs.

METHODS

A total of 3239 patients from the Reduction by Dutasteride of Prostate Cancer Events (REDUCE) trial were included. Four genetic risk scores (GRSs) were calculated based on sets of sequentially discovered prostate cancer (PCa) risk-associated SNPs (17, 34, 51, and 68 SNPs).

RESULTS

Pair-wise correlation coefficients between sets of GRSs increased as more SNPs were included in the GRS: 0.80, 0.86, and 0.95 for 17 versus 34 SNPs, 34 versus 51 SNPs, and 51 versus 68 SNPs, respectively. Using a GRS of 1.5 as a cutoff for higher versus lower risk, reclassification rates of PCa risk decreased: 14.11%, 12.04%, and 8.15% for 17 versus 34 SNPs, 34 versus 51 SNPs, and 51 versus 68 SNPs, respectively. Evolving GRSs, nevertheless, provide a tool for further refining risk assessment. When all four sequential GRSs were considered, the detection rates of PCa for men whose GRSs were consistently <1.5, reclassified, and consistently ≥1.5 were 20.8%, 29.67%, and 39.26%, respectively (Ptrend  = 1.12 × 10-8 ). In comparison, the detection rates of PCa in men with negative or positive family history were 23.75% and 31.78%, respectively.

CONCLUSIONS

Risk assessment using currently available SNPs is justified. Multiple GRS values from evolving sets of SNPs provide a valuable tool for better refining risk.

Prediction of Breast and Prostate Cancer Risks in Male BRCA1 and BRCA2 Mutation Carriers Using Polygenic Risk Scores

Purpose BRCA1/2 mutations increase the risk of breast and prostate cancer in men. Common genetic variants modify cancer risks for female carriers of BRCA1/2 mutations. We investigated-for the first time to our knowledge-associations of common genetic variants with breast and prostate cancer risks for male carriers of BRCA1/ 2 mutations and implications for cancer risk prediction. Materials and Methods We genotyped 1,802 male carriers of BRCA1/2 mutations from the Consortium of Investigators of Modifiers of BRCA1/2 by using the custom Illumina OncoArray. We investigated the combined effects of established breast and prostate cancer susceptibility variants on cancer risks for male carriers of BRCA1/2 mutations by constructing weighted polygenic risk scores (PRSs) using published effect estimates as weights. Results In male carriers of BRCA1/2 mutations, PRS that was based on 88 female breast cancer susceptibility variants was associated with breast cancer risk (odds ratio per standard deviation of PRS, 1.36; 95% CI, 1.19 to 1.56; P = 8.6 × 10-6). Similarly, PRS that was based on 103 prostate cancer susceptibility variants was associated with prostate cancer risk (odds ratio per SD of PRS, 1.56; 95% CI, 1.35 to 1.81; P = 3.2 × 10-9). Large differences in absolute cancer risks were observed at the extremes of the PRS distribution. For example, prostate cancer risk by age 80 years at the 5th and 95th percentiles of the PRS varies from 7% to 26% for carriers of BRCA1 mutations and from 19% to 61% for carriers of BRCA2 mutations, respectively. Conclusion PRSs may provide informative cancer risk stratification for male carriers of BRCA1/2 mutations that might enable these men and their physicians to make informed decisions on the type and timing of breast and prostate cancer risk management.

Exome-based genome-wide association study and risk assessment using genetic risk score to prostate cancer in the Korean population

PURPOSE

To investigate exome-wide genetic variants associated with prostate cancer (PCa) in Koreans and evaluate the discriminative ability by the genetic risk score (GRS).

PATIENTS AND METHODS

We prospectively recruited 1,001 PCa cases from a tertiary hospital and conducted a case-control study including 2,641 healthy men (Stage I). Participants were analyzed using HumanExome BeadChip. For the external validation, additionally enrolled 514 PCa cases and 548 controls (independent cohort) were analyzed for the identified single nucleotide polymorphisms (SNPs) of Stage I (Stage II). The GRS was calculated as a non-weighted sum of the risk allele counts and investigated for accuracy of prediction of PCa.

RESULTS

the mean age was 66.3 years, and the median level of prostate specific antigen (PSA) was 9.19 ng/ml in PCa cases. In Stage I, 4 loci containing 5 variants (rs1512268 on 8p21.2; rs1016343 and rs7837688 on 8q24.21; rs7501939 on 17q12, and rs2735839 on 19q13.33) were confirmed to reach exome-wide significance (p<8.3x10-7). In Stage II, the mean GRS was 4.23 ± 1.44 for the controls and 4.78 ± 1.43 for the cases. As a reference to GRS 4, GRS 6, 7 and 8 showed a statistically significant risk of PCa (OR=1.85, 2.11 and 3.34, respectively).

CONCLUSIONS

The five variants were validated to associate with PCa in firstly performed exome-wide study in Koreans. The addition of individualized calculated GRS effectively enhanced the accuracy of prediction. These results need to be validated in future studies.

Exploration of the molecular mechanism of prostate cancer based on mRNA and miRNA expression profiles

Prostate cancer, the second most common cancer in men, has been rarely explored by integrating mRNA and miRNA expression profiles. In this study, we combined two mRNA expression datasets and six documented miRNAs to uncover the comprehensive molecular mechanism of prostate cancer. Results showed that a total of 30 genes were significantly differentially expressed in 49 tumor samples by comparing with 22 normal samples. Importantly, all samples from the two datasets can be clearly classified into two groups, tumor group and normal group, based on the selected differentially expressed genes (DEGs). The miRNA–mRNA regulation network indicated that 4 out of 30 DEGs can be regulated by three miRNAs. In addition, prognostic performance validation using in silico databases showed that the DEGs can significantly differentiate between low-risk and high-risk prostate cancer. In summary, multiple biological processes are probably involved in the development and progression of prostate cancer. First, dysregulation of SV2 can regulate transporter and transmembrane transporter activity and then provide the necessary nutrients for tumor cell proliferation. Second, HOXD10 can induce cell proliferation via TCF-4. Finally, dysregulation of CACNA1D can further suppress tumor apoptosis in prostate cancer. The identification of critical genes and valuable biological processes can be useful for the understanding of the molecular mechanism of prostate cancer.

Inherited determinants of early recurrent somatic mutations in prostate cancer

Prostate cancer is a highly heritable molecularly and clinically heterogeneous disease. To discover germline events involved in prostate cancer predisposition, we develop a computational approach to nominate heritable facilitators of somatic genomic events in the context of the androgen receptor signaling. Here, we use a ranking score and benign prostate transcriptomes to identify a non-coding polymorphic regulatory element at 7p14.3 that associates with DNA repair and hormone-regulated transcript levels and with an early recurrent prostate cancer-specific somatic mutation in the Speckle-Type POZ protein (SPOP) gene. The locus shows allele-specific activity that is concomitantly modulated by androgen receptor and by CCAAT/enhancer-binding protein (C/EBP) beta (CEBPB). Deletion of this locus via CRISPR-Cas9 leads to deregulation of the genes predicted to interact with the 7p14.3 locus by Hi-C chromosome conformation capture data. This study suggests that a polymorphism at 7p14.3 may predispose to SPOP mutant prostate cancer subclass through a hormone-dependent DNA damage response.

Prostate cancer is a heterogeneous disease, and many cases show somatic mutations of SPOP. Here, the authors show that a non-coding polymorphic regulatory element at 7p14.3 may predispose to SPOP mutant prostate cancer subclass through a hormone dependent DNA damage response.

Genome-Wide Association Studies of Cancer in Diverse Populations

Genome-wide association studies (GWAS) of cancer have identified more than 700 risk loci, of which approximately 80% were first discovered in European ancestry populations, approximately 15% in East Asians, 3% in multiethnic scans, and less than 1% in African and Latin American populations. These percentages closely mirror the distribution of samples included in the discovery phase of cancer GWAS to date (84% European, 11% East Asian, 4% African, and 1% Latin American ancestry). GWAS in non-European ancestry populations have provided insight into ancestry-specific variation in cancer and have pointed to regions of susceptibility that are of particular importance in certain populations. Uncovering and characterizing cancer risk loci in diverse populations is critical for understanding underlying biological mechanisms and developing future genetic risk prediction models in non-European ancestry populations. New GWAS and continued collaborations will be required to eliminate population inequalities in the number of studies, sample sizes, and variant content on GWAS arrays, and to better align genetic research in cancer to the global distribution of race/ethnicity Cancer Epidemiol Biomarkers Prev; 27(4); 405-17. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

[CCAFU french national guidelines 2016-2018 on prostate cancer]

OBJECTIVES

The purpose of the guidelines national committee CCAFU was to propose updated french guidelines for localized and metastatic prostate cancer (PCa).

METHODS

A Medline search was achieved between 2013 and 2016, as regards diagnosis, options of treatment and follow-up of PCa, to evaluate different references with levels of evidence.

RESULTS

Epidemiology, classification, staging systems, diagnostic evaluation are reported. Disease management options are detailed. Recommandations are reported according to the different clinical situations. Active surveillance is a major option in low risk PCa. Radical prostatectomy remains a standard of care of localized PCa. The three-dimensional conformal radiotherapy is the technical standard. A dose of > 74Gy is recommended. Moderate hypofractionation provides short-term biochemical control comparable to conventional fractionation. In case of intermediate risk PCa, radiotherapy can be combined with short-term androgen deprivation therapy (ADT). In case of high risk disease, long-term ADT remains the standard of care. ADT is the backbone therapy of metastatic disease. In men with metastases at first presentation, upfront chemotherapy combined with ADT should be considered as a new standard. In case of metastatic castration-resistant PCa (mCRPC), new hormonal treatments and chemotherapy provide a better control of tumor progression and increase survival.

CONCLUSIONS

These updated french guidelines will contribute to increase the level of urological care for the diagnosis and treatment for prostate cancer. © 2016 Elsevier Masson SAS. All rights reserved.

Estimating Heritability of Prostate Cancer-Specific Survival Using Population-Based Registers

BACKGROUND

There is a strong genetic component in prostate cancer development with an estimated heritability of 58%. In addition, recent epidemiological assessments show a familial component in prostate cancer-specific survival, which could be due to either common genetics or environment. In this study we sought to estimate the heritability of prostate cancer-specific survival by studying brothers and father-son pairs in Sweden.

METHODS

We used linkage records from three Swedish national registers: the Multi-Generation Register, the Cancer Register, and the Cause of Death Register. One thousand seven hundred twenty-eight brother pairs and 6,444 father-son pairs, where both family members were diagnosed with prostate cancer, were followed for prostate cancer mortality. By assuming that (i) brothers on average share 50% of their segregating alleles and 100% environment and (ii) fathers and sons share 50% of their segregating alleles and no environment, we implemented a model including influences of additive genetics (heritability), shared environment and non-shared environment for survival data. A conditional likelihood estimation procedure was developed to fit the model. Data simulation was applied to validate model assumptions.

RESULTS

In a model that adjusted for age at diagnosis and calendar period, the estimated heritability of prostate cancer-specific survival was 0.10 (95% CI = 0.00-0.20) that was borderline significantly different from zero (P = 0.057). The shared environment component was not significantly different from zero with a point estimate of 0.00 (95% CI = 0.00-0.13). Simulation studies and sensitivity analysis revealed that the estimated heritability component was robust, whereas the shared environmental component may be underestimated.

CONCLUSIONS

Heritability of prostate cancer-specific survival is considerably lower than for prostate cancer incidence. This supports a hypothesis that susceptibility of disease and progression of disease are separate mechanisms that involve different genes. Further assessment of the genetic basis of prostate cancer-specific survival is warranted. Prostate 77:900-907, 2017. © 2017 Wiley Periodicals, Inc.

Exome Array Analysis Identifies Variants in SPOCD1 and BTN3A2 That Affect Risk for Gastric Cancer

BACKGROUND & AIMS

Several genetic variants have been associated with gastric cancer risk, although these account for only a fraction of cases of gastric cancer. We aimed to identify low-frequency and other genetic variants that determine gastric cancer susceptibility.

METHODS

We performed exome array analysis of DNA in blood samples from 1113 patients with gastric cancer, collected at hospitals from 2006 to 2010 in China, and 1848 individuals without cancer (controls) undergoing physical examinations. Among 71,290 variants analyzed (including 25,784 common variants), 24 variants were selected and replicated in an analysis of DNA in blood samples from 4687 additional cases of gastric cancer and 5780 controls. We compared expression of candidate genes in tumor vs normal gastric tissues using data from TCGA and performed functional annotation analyses. An immortalized human gastric epithelial cell line (GES1) and 7 human gastric cancer lines were used to express transgenes, knock down gene expression (with small interfering RNAs), disrupt genes (using the CRISPR/Cas9 system), or assess expression of reporter constructs. We measured cell proliferation, colony formation, invasion, and migration, and assessed growth of xenograft tumors in nude mice.

RESULTS

A low-frequency missense variant rs112754928 in the SPOC domain containing 1 gene (SPOCD1; encoding p.Arg71Trp), at 1p35.2, was reproducibly associated with reduced risk of gastric cancer (odds ratio, 0.56; P = 3.48 × 10^-8). SPOCD1 was overexpressed in gastric tumors, and knockout of SPOCD1 reduced gastric cancer cell proliferation, invasive activity, and migration, as well as growth of xenograft tumors in nude mice. We also associated the variant rs1679709 at 6p22.1 with reduced risk for gastric cancer (odds ratio, 0.80; P = 1.17 × 10^-13). The protective allele rs1679709-A correlated with the surrounding haplotype rs2799077-T-rs2799079-C, which reduced the enhancer activity of this site to decrease expression of the butyrophilin subfamily 3 member A2 gene (BTN3A2). BTN3A2 is overexpressed in gastric tumors, and deletion of BTN3A2 inhibited proliferation, migration, and invasion of gastric cancer cells.

CONCLUSIONS

We have associated variants at 1p35.2 and 6p22.1 with gastric cancer risk, indicating a role for SPOCD1 and BTN3A2 in gastric carcinogenesis.

Genetic association study of exfoliation syndrome identifies a protective rare variant at LOXL1 and five new susceptibility loci

Exfoliation syndrome (XFS) is the most common known risk factor for secondary glaucoma and a major cause of blindness worldwide. Variants in two genes, LOXL1 and CACNA1A, have previously been associated with XFS. To further elucidate the genetic basis of XFS, we collected a global sample of XFS cases to refine the association at LOXL1, which previously showed inconsistent results across populations, and to identify new variants associated with XFS. We identified a rare protective allele at LOXL1 (p.Phe407, odds ratio (OR) = 25, P = 2.9 × 10^-14) through deep resequencing of XFS cases and controls from nine countries. A genome-wide association study (GWAS) of XFS cases and controls from 24 countries followed by replication in 18 countries identified seven genome-wide significant loci (P < 5 × 10^-8). We identified association signals at 13q12 (POMP), 11q23.3 (TMEM136), 6p21 (AGPAT1), 3p24 (RBMS3) and 5q23 (near SEMA6A). These findings provide biological insights into the pathology of XFS and highlight a potential role for naturally occurring rare LOXL1 variants in disease biology.

Genetic risk score to predict biochemical recurrence after radical prostatectomy in prostate cancer: prospective cohort study

Purpose

To investigate the genetic risk score (GRS) from a large-scale exome-wide association study as a tool of prediction for biochemical recurrence (BCR) after radical prostatectomy (RP) in prostate cancer (PCa).

Results

The 16 SNPs were selected as significant predictors of BCR. The GRS in men experiencing BCR was -1.21, significantly higher than in non-BCR patients (–2.43) (p < 0.001). The 10-year BCR-free survival rate was 46.3% vs. 81.8% in the high-versus low GRS group, respectively (p < 0.001). The GRS was a significant factor after adjusting for other variables in Cox proportional hazard models (HR:1.630, p < 0.001). The predictive ability of the multivariate model without GRS was 84.4%, increased significantly to 88.0% when GRS was included (p = 0.0026).

Materials and Methods

Total 912 PCa patients were enrolled who had received RP and genotype analysis using Exome chip (HumanExome BeadChip). Genetic results were obtained by the methods of logistic regression analysis which measured the odds ratio (OR) to BCR. The GRS was calculated by the sum of each weighted-risk allele count multiplied by the natural logarithm of the respective ORs. Survival analyses were performed using the GRS. We compared the accuracy of separate multivariate models incorporating clinicopathological factors that either included or excluded the GRS.

Conclusions

GRS had additional predictive gain of BCR after RP in PCa. The addition of personally calculated GRS significantly increased the BCR prediction rate. After validation of these results, GRS of BCR could be potential biomarker to predict clinical outcomes.

Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study

IMPORTANCE

The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation.

OBJECTIVE

To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases.

DATA SOURCES

Genomewide association studies (GWAS) published up to January 15, 2015.

STUDY SELECTION

GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available.

DATA EXTRACTION AND SYNTHESIS

Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population.

MAIN OUTCOMES AND MEASURES

Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation.

RESULTS

Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]).

CONCLUSIONS AND RELEVANCE

It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.

Genetic variants associated with mosaic Y chromosome loss highlight cell cycle genes and overlap with cancer susceptibility

The Y chromosome is frequently lost in hematopoietic cells, which represents the most common somatic alteration in men. However, the mechanisms that regulate mosaic loss of chromosome Y (mLOY), and its clinical relevance, are unknown. We used genotype-array-intensity data and sequence reads from 85,542 men to identify 19 genomic regions (P < 5 × 10-8) that are associated with mLOY. Cumulatively, these loci also predicted X chromosome loss in women (n = 96,123; P = 4 × 10-6). Additional epigenome-wide methylation analyses using whole blood highlighted 36 differentially methylated sites associated with mLOY. The genes identified converge on aspects of cell proliferation and cell cycle regulation, including DNA synthesis (NPAT), DNA damage response (ATM), mitosis (PMF1, CENPN and MAD1L1) and apoptosis (TP53). We highlight the shared genetic architecture between mLOY and cancer susceptibility, in addition to inferring a causal effect of smoking on mLOY. Collectively, our results demonstrate that genotype-array-intensity data enables a measure of cell cycle efficiency at population scale and identifies genes implicated in aneuploidy, genome instability and cancer susceptibility.

Molecular classification of prostate adenocarcinoma by the integrated somatic mutation profiles and molecular network

Prostate cancer is one of the most common cancers in men and a leading cause of cancer death worldwide, displaying a broad range of heterogeneity in terms of clinical and molecular behavior. Increasing evidence suggests that classifying prostate cancers into distinct molecular subtypes is critical to exploring the potential molecular variation underlying this heterogeneity and to better treat this cancer. In this study, the somatic mutation profiles of prostate cancer were downloaded from the TCGA database and used as the source nodes of the random walk with restart algorithm (RWRA) for generating smoothed mutation profiles in the STRING network. The smoothed mutation profiles were selected as the input matrix of the Graph-regularized Nonnegative Matrix Factorization (GNMF) for classifying patients into distinct molecular subtypes. The results were associated with most of the clinical and pathological outcomes. In addition, some bioinformatics analyses were performed for the robust subtyping, and good results were obtained. These results indicated that prostate cancers can be usefully classified according to their mutation profiles, and we hope that these subtypes will help improve the treatment stratification of this cancer in the future.

GeneImp: Fast Imputation to Large Reference Panels Using Genotype Likelihoods from Ultralow Coverage Sequencing

We address the task of genotype imputation to a dense reference panel given genotype likelihoods computed from ultralow coverage sequencing as inputs. In this setting, the data have a high-level of missingness or uncertainty, and are thus more amenable to a probabilistic representation. Most existing imputation algorithms are not well suited for this situation, as they rely on prephasing for computational efficiency, and, without definite genotype calls, the prephasing task becomes computationally expensive. We describe GeneImp, a program for genotype imputation that does not require prephasing and is computationally tractable for whole-genome imputation. GeneImp does not explicitly model recombination, instead it capitalizes on the existence of large reference panels-comprising thousands of reference haplotypes-and assumes that the reference haplotypes can adequately represent the target haplotypes over short regions unaltered. We validate GeneImp based on data from ultralow coverage sequencing (0.5×), and compare its performance to the most recent version of BEAGLE that can perform this task. We show that GeneImp achieves imputation quality very close to that of BEAGLE, using one to two orders of magnitude less time, without an increase in memory complexity. Therefore, GeneImp is the first practical choice for whole-genome imputation to a dense reference panel when prephasing cannot be applied, for instance, in datasets produced via ultralow coverage sequencing. A related future application for GeneImp is whole-genome imputation based on the off-target reads from deep whole-exome sequencing.

Genetic pleiotropy between age-related macular degeneration and 16 complex diseases and traits

BACKGROUND

Age-related macular degeneration (AMD) is a common condition of vision loss with disease development strongly influenced by environmental and genetic factors. Recently, 34 loci were associated with AMD at genome-wide significance. So far, little is known about a genetic overlap between AMD and other complex diseases or disease-relevant traits.

METHODS

For each of 60 complex diseases/traits with publicly available genome-wide significant association data, the lead genetic variant per independent locus was extracted and a genetic score was calculated for each disease/trait as the weighted sum of risk alleles. The association with AMD was estimated based on 16,144 AMD cases and 17,832 controls using logistic regression.

RESULTS

Of the respective disease/trait variance, the 60 genetic scores explained on average 4.8% (0.27-20.69%) and 16 of them were found to be significantly associated with AMD (Q-values < 0.01, p values from < 1.0 × 10^-16 to 1.9 × 10^-3). Notably, an increased risk for AMD was associated with reduced risk for cardiovascular diseases, increased risk for autoimmune diseases, higher HDL and lower LDL levels in serum, lower bone-mineral density as well as an increased risk for skin cancer. By restricting the analysis to 1824 variants initially used to compute the 60 genetic scores, we identified 28 novel AMD risk variants (Q-values < 0.01, p values from 1.1 × 10^-7 to 3.0 × 10^-4), known to be involved in cardiovascular disorders, lipid metabolism, autoimmune diseases, anthropomorphic traits, ocular disorders, and neurological diseases. The latter variants represent 20 novel AMD-associated, pleiotropic loci. Genes in the novel loci reinforce previous findings strongly implicating the complement system in AMD pathogenesis.

CONCLUSIONS

We demonstrate a substantial overlap of the genetics of several complex diseases/traits with AMD and provide statistically significant evidence for an additional 20 loci associated with AMD. This highlights the possibility that so far unrelated pathologies may have disease pathways in common.

SNP interaction pattern identifier (SIPI): an intensive search for SNP-SNP interaction patterns

Motivation

Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped.

Results

We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR , EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP-SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns.

Availability and Implementation

The SIPI software is freely available at http://publichealth.lsuhsc.edu/LinSoftware/ .

Contact

hlin1@lsuhsc.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Interactions Between Genome-Wide Significant Genetic Variants and Circulating Concentrations of 25-Hydroxyvitamin D in Relation to Prostate Cancer Risk in the National Cancer Institute BPC3

Genome-wide association studies (GWAS) have identified over 100 single nucleotide polymorphisms (SNPs) associated with prostate cancer. However, information on the mechanistic basis for some associations is limited. Recent research has been directed towards the potential association of vitamin D concentrations and prostate cancer, but little is known about whether the aforementioned genetic associations are modified by vitamin D. We investigated the associations of 46 GWAS-identified SNPs, circulating concentrations of 25-hydroxyvitamin D (25(OH)D), and prostate cancer (3,811 cases, 511 of whom died from the disease, compared with 2,980 controls-from 5 cohort studies that recruited participants over several periods beginning in the 1980s). We used logistic regression models with data from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) to evaluate interactions on the multiplicative and additive scales. After allowing for multiple testing, none of the SNPs examined was significantly associated with 25(OH)D concentration, and the SNP-prostate cancer associations did not differ by these concentrations. A statistically significant interaction was observed for each of 2 SNPs in the 8q24 region (rs620861 and rs16902094), 25(OH)D concentration, and fatal prostate cancer on both multiplicative and additive scales (P ≤ 0.001). We did not find strong evidence that associations between GWAS-identified SNPs and prostate cancer are modified by circulating concentrations of 25(OH)D. The intriguing interactions between rs620861 and rs16902094, 25(OH)D concentration, and fatal prostate cancer warrant replication.

A comparison of genetic risk score with family history for estimating prostate cancer risk

Prostate cancer (PCa) testing is recommended by most authoritative groups for high-risk men including those with a family history of the disease. However, family history information is often limited by patient knowledge and clinician intake, and thus, many men are incorrectly assigned to different risk groups. Alternate methods to assess PCa risk are required. In this review, we discuss how genetic variants, referred to as PCa-risk single-nucleotide polymorphisms, can be used to calculate a genetic risk score (GRS). GRS assigns a relatively unique value to all men based on the number of PCa-risk SNPs that an individual carries. This GRS value can provide a more precise estimate of a man's PCa risk. This is particularly relevant in situations when an individual is unaware of his family history. In addition, GRS has utility and can provide a more precise estimate of risk even among men with a positive family history. It can even distinguish risk among relatives with the same degree of family relationships. Taken together, this review serves to provide support for the clinical utility of GRS as an independent test to provide supplemental information to family history. As such, GRS can serve as a platform to help guide-shared decision-making processes regarding the timing and frequency of PCa testing and biopsies.

Clinical validity and utility of genetic risk scores in prostate cancer

Current issues related to prostate cancer (PCa) clinical care (e.g., over-screening, over-diagnosis, and over-treatment of nonaggressive PCa) call for risk assessment tools that can be combined with family history (FH) to stratify disease risk among men in the general population. Since 2007, genome-wide association studies (GWASs) have identified more than 100 SNPs associated with PCa susceptibility. In this review, we discuss (1) the validity of these PCa risk-associated SNPs, individually and collectively; (2) the various methods used for measuring the cumulative effect of multiple SNPs, including genetic risk score (GRS); (3) the adequate number of SNPs needed for risk assessment; (4) reclassification of risk based on evolving numbers of SNPs used to calculate genetic risk, (5) risk assessment for men from various racial groups, and (6) the clinical utility of genetic risk assessment. In conclusion, data available to date support the clinical validity of PCa risk-associated SNPs and GRS in risk assessment among men with or without FH. PCa risk-associated SNPs are not intended for diagnostic use; rather, they should be used the same way as FH. Combining GRS and FH can significantly improve the performance of risk assessment. Improved risk assessment may have important clinical utility in targeted PCa testing. However, clinical trials are urgently needed to evaluate this clinical utility as well as the acceptance of GRS by patients and physicians.

Population-standardized genetic risk score: the SNP-based method of choice for inherited risk assessment of prostate cancer

Several different approaches are available to clinicians for determining prostate cancer (PCa) risk. The clinical validity of various PCa risk assessment methods utilizing single nucleotide polymorphisms (SNPs) has been established; however, these SNP-based methods have not been compared. The objective of this study was to compare the three most commonly used SNP-based methods for PCa risk assessment. Participants were men (n = 1654) enrolled in a prospective study of PCa development. Genotypes of 59 PCa risk-associated SNPs were available in this cohort. Three methods of calculating SNP-based genetic risk scores (GRSs) were used for the evaluation of individual disease risk such as risk allele count (GRS-RAC), weighted risk allele count (GRS-wRAC), and population-standardized genetic risk score (GRS-PS). Mean GRSs were calculated, and performances were compared using area under the receiver operating characteristic curve (AUC) and positive predictive value (PPV). All SNP-based methods were found to be independently associated with PCa (all P < 0.05; hence their clinical validity). The mean GRSs in men with or without PCa using GRS-RAC were 55.15 and 53.46, respectively, using GRS-wRAC were 7.42 and 6.97, respectively, and using GRS-PS were 1.12 and 0.84, respectively (all P < 0.05 for differences between patients with or without PCa). All three SNP-based methods performed similarly in discriminating PCa from non-PCa based on AUC and in predicting PCa risk based on PPV (all P > 0.05 for comparisons between the three methods), and all three SNP-based methods had a significantly higher AUC than family history (all P < 0.05). Results from this study suggest that while the three most commonly used SNP-based methods performed similarly in discriminating PCa from non-PCa at the population level, GRS-PS is the method of choice for risk assessment at the individual level because its value (where 1.0 represents average population risk) can be easily interpreted regardless of the number of risk-associated SNPs used in the calculation.

Clinical and histopathological characteristics of patients with prostate cancer in the BioBank Japan project

Background

Prostate cancer is the sixth leading cause of cancer-related deaths in Japan. We aimed to elucidate the clinical and histopathological characteristics of patients with prostate cancer in the BioBank Japan (BBJ) project.

Methods

Four thousand, seven hundred and ninety-three patients diagnosed with prostate cancer in the BBJ project were included. Clinical and histopathological data, including causes of death, were analyzed. Relative survival (RS) rates of prostate cancer were calculated.

Results

Four thousand, one hundred and seventy-one prostate cancer patients with available histological data had adenocarcinoma. The mean age of the patients was 72.5 years. The proportion of patients who were non-smokers, non-drinkers, had a normal body mass index, did not exercise, had a normal prostate-specific antigen level, and had a family history of prostate cancer were 30.7%, 28.0%, 66.6%, 58.1%, 67.6%, and 6.5%, respectively. The proportion of patients with Stage II, III, and IV disease were 24.4%, 7.3%, and 4.4%, respectively. After limiting to patients with a time from the initial diagnosis of prostate cancer to entry into the study cohort of ≤90 days (n = 869), the 5- and 10-year RS rates were 96.3% and 100.5%, respectively, although we were unable to consider management strategies due to a plenty of data missing.

Conclusions

We provide an overview of patients with prostate cancer in the BBJ project. Our findings, coupled with those from various high throughput “omics” technologies, will contribute to the implementation of prevention interventions and medical management of prostate cancer patients.

•

Prostate cancer represents the second leading cause of cancer incidence worldwide.

•

We aimed to provide an overview of patients with prostate cancer.

•

Based on prostate cancer histology, 99.3% had adenocarcinoma.

•

The 5- and 10-year relative survival rates were 96.3% and 100.5%.

•

Future studies will help develop preventive programs for prostate cancer.

Genome-wide two-locus interaction analysis identifies multiple epistatic SNP pairs that confer risk of prostate cancer: A cross-population study

Prostate cancer is one of the most common carcinomas among adult males. Recently, genome-wide association studies (GWAS) have identified several susceptibility genes of prostate cancer. However, these single locus results can only explain a small proportion of the genetic etiology. In order to understand how multiple genetic variants may contribute to the penetrance of prostate cancer, we conducted a genome-wide SNP-SNP interaction study in four populations, involving 5,269 cases and 5,289 controls. We exhaustively evaluated all pairs of SNP-SNP interactions for 661,658 SNPs that were consensus in all four groups, and then performed a meta-analysis to combine the results. We found multiple variants within region 7p21.3 and 18p11.22 significantly interacted with each other and reached genome-wide significance levels. The most significant epistasis was between rs1105255 (intergenic, near RBSG3) and rs651431 (intergenic, near VAPA) (p = 1.4 × 10^-14 ). Notably, VAPA was identified to be the protein-coding transcripts as PTEN competing endogenous RNA in prostate cancer. And PTEN is a critical tumor suppressor gene frequently altered in cancers. In addition, 7p21.3 involves several pseudogenes, whose parental genes are cancer-related. Recently, growing evidence strongly suggests they are of multifaceted involvements in the pathogenesis of cancer. Multiple regulatory elements were found within 7p21.3 and 18p11.22, indicating the variants might regulate the nearby genes and confer risk of disease. Additionally, we also found several other significant epistasis, most of which were near or in cancer-related genes. Drug target enrichment analysis suggested genes in top epistasis significantly overlapped with target genes of FDA-approved drugs for treatment of prostate cancer.

Integration of VDR genome wide binding and GWAS genetic variation data reveals co-occurrence of VDR and NF-κB binding that is linked to immune phenotypes

Background

The nuclear hormone receptor superfamily acts as a genomic sensor of diverse signals. Their actions are often intertwined with other transcription factors. Nuclear hormone receptors are targets for many therapeutic drugs, and include the vitamin D receptor (VDR). VDR signaling is pleotropic, being implicated in calcaemic function, antibacterial actions, growth control, immunomodulation and anti-cancer actions. Specifically, we hypothesized that the biologically significant relationships between the VDR transcriptome and phenotype-associated biology could be discovered by integrating the known VDR transcription factor binding sites and all published trait- and disease-associated SNPs. By integrating VDR genome-wide binding data (ChIP-seq) with the National Human Genome Research Institute (NHGRI) GWAS catalog of SNPs we would see where and which target gene interactions and pathways are impacted by inherited genetic variation in VDR binding sites, indicating which of VDR’s multiple functions are most biologically significant.

Results

To examine how genetic variation impacts VDR function we overlapped 23,409 VDR genomic binding peaks from six VDR ChIP-seq datasets with 191,482 SNPs, derived from GWAS-significant SNPs (Lead SNPs) and their correlated variants (r² > 0.8) from HapMap3 and the 1000 genomes project. In total, 574 SNPs (71 Lead and 503 SNPs in linkage disequilibrium with Lead SNPs) were present at VDR binding loci and associated with 211 phenotypes. For each phenotype a hypergeometric test was used to determine if SNPs were enriched at VDR binding sites. Bonferroni correction for multiple testing across the 211 phenotypes yielded 42 SNPs that were either disease- or phenotype-associated with seven predominately immune related including self-reported allergy; esophageal cancer was the only cancer phenotype. Motif analyses revealed that only two of these 42 SNPs reside within a canonical VDR binding site (DR3 motif), and that 1/3 of the 42 SNPs significantly impacted binding and gene regulation by other transcription factors, including NF-κB. This suggests a plausible link for the potential cross-talk between VDR and NF-κB.

Conclusions

These analyses showed that VDR peaks are enriched for SNPs associated with immune phenotypes suggesting that VDR immunomodulatory functions are amongst its most important actions. The enrichment of genetic variation in non-DR3 motifs suggests a significant role for the VDR to bind in multimeric complexes containing other transcription factors that are the primary DNA binding component. Our work provides a framework for the combination of ChIP-seq and GWAS findings to provide insight into the underlying phenotype-associated biology of a given transcription factor.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3481-4) contains supplementary material, which is available to authorized users.

Is the Genetic Background of Co-Stimulatory CD28/CTLA-4 Pathway the Risk Factor for Prostate Cancer?

The impairment of immunological surveillance caused by aberrant T cell activation can lead to an inadequate anti-tumor response. Therefore, deregulation in co-stimulatory pathway might be associated with cancer susceptibility. Here we undertook a prospective study to investigate whether genetic variations in gene encoding molecule CD28 and CTLA-4 playing pivotal role in regulating adoptive immune response can influence susceptibility to prostate cancer. Single nucleotide polymorphisms (SNPs) in CTLA-4 and CD28 genes were genotyped in 301 prostate cancer (PCa) patients and 301 controls. The distributions of the genotypes and haplotypes in the CTLA-4/CD28 SNPs were similar in both studied groups. However, the overrepresentation of carriers of CTLA-4c.49A>G[A] allele and carriers of CTLA-4g.319C>T[T] allele in PCa as compared to controls was observed (p = 0.082 and p = 0.13, respectively). The risk of disease was higher (OR 1.78) for carriers of both susceptibility alleles as compared to carriers of protective genotypes (p = 0.03). The CTLA-4c.49A>G and CTLA-4g.319C>T SNPs might be considered as low risk susceptibility locus for PCa.

Estimation of heritability for nine common cancers using data from genome-wide association studies in Chinese population

The familial aggregation indicated the inheritance of cancer risk. Recent genome-wide association studies (GWASs) have identified a number of common single-nucleotide polymorphisms (SNPs). Following heritability analyses have shown that SNPs could explain a moderate amount of variance for different cancer phenotypes among Caucasians. However, little information was available in Chinese population. We performed a genome-wide complex trait analysis for common cancers at nine anatomical sites in Chinese population (14,629 cancer cases vs. 17,554 controls) and estimated the heritability of these cancers based on the common SNPs. We found that common SNPs explained certain amount of heritability with significance for all nine cancer sites: gastric cancer (20.26%), esophageal squamous cell carcinoma (19.86%), colorectal cancer (16.30%), lung cancer (LC) (15.17%), and epithelial ovarian cancer (13.31%), and a similar heritability around 10% for hepatitis B virus-related hepatocellular carcinoma, prostate cancer, breast cancer and nasopharyngeal carcinoma. We found that nearly or less than 25% change was shown when removing the regions expanding 250 kb or 500 kb upward and downward of the GWAS-reported SNPs. We also found strong linear correlations between variance partitioned by each chromosome and chromosomal length only for LC (R2  = 0.641, p = 0.001) and esophageal squamous cell cancer (R2  = 0.633, p = 0.002), which implied us the complex heterogeneity of cancers. These results indicate polygenic genetic architecture of the nine common cancers in Chinese population. Further efforts should be made to discover the hidden heritability of different cancer types among Chinese.

New insights into the genetics of primary open-angle glaucoma based on meta-analyses of intraocular pressure and optic disc characteristics

Primary open-angle glaucoma (POAG), the most common optic neuropathy, is a heritable disease. Siblings of POAG cases have a ten-fold increased risk of developing the disease. Intraocular pressure (IOP) and optic nerve head characteristics are used clinically to predict POAG risk. We conducted a genome-wide association meta-analysis of IOP and optic disc parameters and validated our findings in multiple sets of POAG cases and controls. Using imputation to the 1000 genomes (1000G) reference set, we identified 9 new genomic regions associated with vertical cup-disc ratio (VCDR) and 1 new region associated with IOP. Additionally, we found 5 novel loci for optic nerve cup area and 6 for disc area. Previously it was assumed that genetic variation influenced POAG either through IOP or via changes to the optic nerve head; here we present evidence that some genomic regions affect both IOP and the disc parameters. We characterized the effect of the novel loci through pathway analysis and found that pathways involved are not entirely distinct as assumed so far. Further, we identified a novel association between CDKN1A and POAG. Using a zebrafish model we show that six6b (associated with POAG and optic nerve head variation) alters the expression of cdkn1a. In summary, we have identified several novel genes influencing the major clinical risk predictors of POAG and showed that genetic variation in CDKN1A is important in POAG risk.

Identifying aggressive prostate cancer foci using a DNA methylation classifier

BACKGROUND

Slow-growing prostate cancer (PC) can be aggressive in a subset of cases. Therefore, prognostic tools to guide clinical decision-making and avoid overtreatment of indolent PC and undertreatment of aggressive disease are urgently needed. PC has a propensity to be multifocal with several different cancerous foci per gland.

RESULTS

Here, we have taken advantage of the multifocal propensity of PC and categorized aggressiveness of individual PC foci based on DNA methylation patterns in primary PC foci and matched lymph node metastases. In a set of 14 patients, we demonstrate that over half of the cases have multiple epigenetically distinct subclones and determine the primary subclone from which the metastatic lesion(s) originated. Furthermore, we develop an aggressiveness classifier consisting of 25 DNA methylation probes to determine aggressive and non-aggressive subclones. Upon validation of the classifier in an independent cohort, the predicted aggressive tumors are significantly associated with the presence of lymph node metastases and invasive tumor stages.

CONCLUSIONS

Overall, this study provides molecular-based support for determining PC aggressiveness with the potential to impact clinical decision-making, such as targeted biopsy approaches for early diagnosis and active surveillance, in addition to focal therapy.

Whole exome sequencing in 75 high-risk families with validation and replication in independent case-control studies identifies TANGO2, OR5H14, and CHAD as new prostate cancer susceptibility genes

Prostate cancer (PCa) susceptibility is defined by a continuum from rare, high-penetrance to common, low-penetrance alleles. Research to date has concentrated on identification of variants at the ends of that continuum. Taking an alternate approach, we focused on the important but elusive class of low-frequency, moderately penetrant variants by performing disease model-based variant filtering of whole exome sequence data from 75 hereditary PCa families. Analysis of 341 candidate risk variants identified nine variants significantly associated with increased PCa risk in a population-based, case-control study of 2,495 men. In an independent nested case-control study of 7,121 men, there was risk association evidence for TANGO2 p.Ser17Ter and the established HOXB13 p.Gly84Glu variant. Meta-analysis combining the case-control studies identified two additional variants suggestively associated with risk, OR5H14 p.Met59Val and CHAD p.Ala342Asp. The TANGO2 and HOXB13 variants co-occurred in cases more often than expected by chance and never in controls. Finally, TANGO2 p.Ser17Ter was associated with aggressive disease in both case-control studies separately. Our analyses identified three new PCa susceptibility alleles in the TANGO2, OR5H14 and CHAD genes that not only segregate in multiple high-risk families but are also of importance in altering disease risk for men from the general population. This is the first successful study to utilize sequencing in high-risk families for the express purpose of identifying low-frequency, moderately penetrant PCa risk mutations.

The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers

BACKGROUND

Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits.

METHODS

The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background.

RESULTS

The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis.

CONCLUSIONS

Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures.

IMPACT

Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126-35. ©2016 AACR.

Alcohol consumption and prostate cancer incidence and progression: A Mendelian randomisation study

Prostate cancer is the most common cancer in men in developed countries, and is a target for risk reduction strategies. The effects of alcohol consumption on prostate cancer incidence and survival remain unclear, potentially due to methodological limitations of observational studies. In this study, we investigated the associations of genetic variants in alcohol-metabolising genes with prostate cancer incidence and survival. We analysed data from 23,868 men with prostate cancer and 23,051 controls from 25 studies within the international PRACTICAL Consortium. Study-specific associations of 68 single nucleotide polymorphisms (SNPs) in 8 alcohol-metabolising genes (Alcohol Dehydrogenases (ADHs) and Aldehyde Dehydrogenases (ALDHs)) with prostate cancer diagnosis and prostate cancer-specific mortality, by grade, were assessed using logistic and Cox regression models, respectively. The data across the 25 studies were meta-analysed using fixed-effect and random-effects models. We found little evidence that variants in alcohol metabolising genes were associated with prostate cancer diagnosis. Four variants in two genes exceeded the multiple testing threshold for associations with prostate cancer mortality in fixed-effect meta-analyses. SNPs within ALDH1A2 associated with prostate cancer mortality were rs1441817 (fixed effects hazard ratio, HRfixed  = 0.78; 95% confidence interval (95%CI):0.66,0.91; p values = 0.002); rs12910509, HRfixed  = 0.76; 95%CI:0.64,0.91; p values = 0.003); and rs8041922 (HRfixed  = 0.76; 95%CI:0.64,0.91; p values = 0.002). These SNPs were in linkage disequilibrium with each other. In ALDH1B1, rs10973794 (HRfixed  = 1.43; 95%CI:1.14,1.79; p values = 0.002) was associated with prostate cancer mortality in men with low-grade prostate cancer. These results suggest that alcohol consumption is unlikely to affect prostate cancer incidence, but it may influence disease progression.

Winner's Curse Correction and Variable Thresholding Improve Performance of Polygenic Risk Modeling Based on Genome-Wide Association Study Summary-Level Data

Recent heritability analyses have indicated that genome-wide association studies (GWAS) have the potential to improve genetic risk prediction for complex diseases based on polygenic risk score (PRS), a simple modelling technique that can be implemented using summary-level data from the discovery samples. We herein propose modifications to improve the performance of PRS. We introduce threshold-dependent winner's-curse adjustments for marginal association coefficients that are used to weight the single-nucleotide polymorphisms (SNPs) in PRS. Further, as a way to incorporate external functional/annotation knowledge that could identify subsets of SNPs highly enriched for associations, we propose variable thresholds for SNPs selection. We applied our methods to GWAS summary-level data of 14 complex diseases. Across all diseases, a simple winner's curse correction uniformly led to enhancement of performance of the models, whereas incorporation of functional SNPs was beneficial only for selected diseases. Compared to the standard PRS algorithm, the proposed methods in combination led to notable gain in efficiency (25-50% increase in the prediction R2) for 5 of 14 diseases. As an example, for GWAS of type 2 diabetes, winner's curse correction improved prediction R2 from 2.29% based on the standard PRS to 3.10% (P = 0.0017) and incorporating functional annotation data further improved R2 to 3.53% (P = 2×10-5). Our simulation studies illustrate why differential treatment of certain categories of functional SNPs, even when shown to be highly enriched for GWAS-heritability, does not lead to proportionate improvement in genetic risk-prediction because of non-uniform linkage disequilibrium structure.

Common germline variants within the CDKN2A/2B region affect risk of pancreatic neuroendocrine tumors

Pancreatic neuroendocrine tumors (PNETs) are heterogeneous neoplasms which represent only 2% of all pancreatic neoplasms by incidence, but 10% by prevalence. Genetic risk factors could have an important role in the disease aetiology, however only a small number of case control studies have been performed yet. To further our knowledge, we genotyped 13 SNPs belonging to the pleiotropic CDKN2A/B gene region in 320 PNET cases and 4436 controls, the largest study on the disease so far. We observed a statistically significant association between the homozygotes for the minor allele of the rs2518719 SNP and an increased risk of developing PNET (OR_hom = 2.08, 95% CI 1.05-4.11, p = 0.035). This SNP is in linkage disequilibrium with another polymorphic variant associated with increased risk of several cancer types. In silico analysis suggested that the SNP could alter the sequence recognized by the Neuron-Restrictive Silencer Factor (NRSF), whose deregulation has been associated with the development of several tumors. The mechanistic link between the allele and the disease has not been completely clarified yet but the epidemiologic evidences that link the DNA region to increased cancer risk are convincing. In conclusion, our results suggest rs2518719 as a pleiotropic CDKN2A variant associated with the risk of developing PNETs.