Identification of seven new prostate cancer susceptibility loci through a genome-wide association study

An indel introduced by Neanderthal introgression, rs3835124:ATTTATT > ATT, might contribute to prostate cancer risk by regulating PDK1 expression

INTRODUCTION

Prostate cancer is one of the most common cancer types in males and rs12621278:A > G has been suggested to be associated with this disease by previous genome-wide association studies. One thousand genomes project data analysis indicated that rs12621278:A > G is within two long-core haplotypes. However, the origin, causal variant(s), and molecular function of these haplotypes were remaining unclear.

MATERIALS AND METHODS

Population genetics analysis and functional genomics work was performed for this locus.

RESULTS

Phylogeny analysis verified that the rare haplotype is derived from Neanderthal introgression. Genome annotation suggested that three genetic variants in the core haplotypes, rs116108611:G > A, rs139972066:AAAAAAAA > AAAAAAAAA, and rs3835124:ATTTATT > ATT, are located in functional regions. Luciferase assay indicated that rs139972066:AAAAAAAA > AAAAAAAAA and rs116108611:G > A are not able to alter ITGA6 (integrin alpha 6) and ITGA6 antisense RNA 1 expression, respectively. In contrast, rs3835124:ATTTATT > ATT can significantly influence PDK1 (pyruvate dehydrogenase kinase 1) expression, which was verified by expression quantitative trait locus analysis. This genetic variant can alter transcription factor cut like homeobox 1 interaction efficiency. The introgressed haplotype was observed to be subject to positive selection in East Asian populations. The molecular function of the haplotype suggested that Neanderthal should be with lower PDK1 expression and further different energy homeostasis from modern human.

CONCLUSION

This study provided new insight into the contribution of Neanderthal introgression to human phenotypes.

Identifying Cancer Type-Specific Transcriptional Programs through Network Analysis

Identifying cancer type-specific genes that define cell states is important to develop effective therapies for patients and methods for detection, early diagnosis, and prevention. While molecular mechanisms that drive malignancy have been identified for various cancers, the identification of cell-type defining transcription factors (TFs) that distinguish normal cells from cancer cells has not been fully elucidated. Here, we utilized a network biology framework, which assesses the fidelity of cell fate conversions, to identify cancer type-specific gene regulatory networks (GRN) for 17 types of cancer. Through an integrative analysis of a compendium of expression data, we elucidated core TFs and GRNs for multiple cancer types. Moreover, by comparing normal tissues and cells to cancer type-specific GRNs, we found that the expression of key network-influencing TFs can be utilized as a survival prognostic indicator for a diverse cohort of cancer patients. These findings offer a valuable resource for exploring cancer type-specific networks across a broad range of cancer types.

Extensive germline-somatic interplay contributes to prostate cancer progression through HNF1B co-option of TMPRSS2-ERG

Genome-wide association studies have identified 270 loci conferring risk for prostate cancer (PCa), yet the underlying biology and clinical impact remain to be investigated. Here we observe an enrichment of transcription factor genes including HNF1B within PCa risk-associated regions. While focused on the 17q12/HNF1B locus, we find a strong eQTL for HNF1B and multiple potential causal variants involved in the regulation of HNF1B expression in PCa. An unbiased genome-wide co-expression analysis reveals PCa-specific somatic TMPRSS2-ERG fusion as a transcriptional mediator of this locus and the HNF1B eQTL signal is ERG fusion status dependent. We investigate the role of HNF1B and find its involvement in several pathways related to cell cycle progression and PCa severity. Furthermore, HNF1B interacts with TMPRSS2-ERG to co-occupy large proportion of genomic regions with a remarkable enrichment of additional PCa risk alleles. We finally show that HNF1B co-opts ERG fusion to mediate mechanistic and biological effects of the PCa risk-associated locus 17p13.3/VPS53/FAM57A/GEMIN4. Taken together, we report an extensive germline-somatic interaction between TMPRSS2-ERG fusion and genetic variations underpinning PCa risk association and progression.

Review of prostate cancer genomic studies in Africa

Prostate cancer (PCa) is the second most commonly diagnosed in men worldwide and one of the most frequent cancers in men in Africa. The heterogeneity of this cancer fosters the need to identify potential genetic risk factors/biomarkers. Omics variations may significantly contribute to early diagnosis and personalized treatment. However, there are few genomic studies of this disease in African populations. This review sheds light on the status of genomics research on PCa in Africa and outlines the common variants identified thus far. The allele frequencies of the most significant SNPs in Afro-native, Afro-descendants, and European populations were compared. We advocate how these few but promising data will aid in understanding, better diagnosing, and precisely treating this cancer and the need for further collaborative research on the genomics of PCa in the African continent.

Inherited risk assessment and its clinical utility for predicting prostate cancer from diagnostic prostate biopsies

BACKGROUND

Many studies on prostate cancer (PCa) germline variants have been published in the last 15 years. This review critically assesses their clinical validity and explores their utility in prediction of PCa detection rates from prostate biopsy.

METHODS

An integrative review was performed to (1) critically synthesize findings on PCa germline studies from published papers since 2016, including risk-associated single nucleotide polymorphisms (SNPs), polygenic risk score methods such as genetic risk score (GRS), and rare pathogenic mutations (RPMs); (2) exemplify the findings in a large population-based cohort from the UK Biobank (UKB); (3) identify gaps for implementing inherited risk assessment in clinic based on experience from a healthcare system; (4) evaluate available GRS data on their clinical utility in predicting PCa detection rates from prostate biopsies; and (5) describe a prospective germline-based biopsy trial to address existing gaps.

RESULTS

SNP-based GRS and RPMs in four genes (HOXB13, BRCA2, ATM, and CHEK2) were significantly and consistently associated with PCa risk in large well-designed studies. In the UKB, positive family history, RPMs in the four implicated genes, and a high GRS (>1.5) identified 8.12%, 1.61%, and 17.38% of men to be at elevated PCa risk, respectively, with hazard ratios of 1.84, 2.74, and 2.39, respectively. Additionally, the performance of GRS for predicting PCa detection rate on prostate biopsy was consistently supported in several retrospective analyses of transrectal ultrasound (TRUS)-biopsy cohorts. Prospective studies evaluating the performance of all three inherited measures in predicting PCa detection rate from contemporary multiparametric MRI (mpMRI)-based biopsy are lacking. A multicenter germline-based biopsy trial to address these gaps is warranted.

CONCLUSIONS

The complementary performance of three inherited risk measures in PCa risk stratification is consistently supported. Their clinical utility in predicting PCa detection rate, if confirmed in prospective clinical trials, may improve current decision-making for prostate biopsy.

The human ATP-binding cassette (ABC) transporter superfamily

The ATP-binding cassette (ABC) transporter superfamily comprises membrane proteins that efflux various substrates across extra- and intracellular membranes. Mutations in ABC genes cause 21 human disorders or phenotypes with Mendelian inheritance, including cystic fibrosis, adrenoleukodystrophy, retinal degeneration, cholesterol, and bile transport defects. To provide tools to study the function of human ABC transporters we compiled data from multiple genomics databases. We analyzed ABC gene conservation within human populations and across vertebrates and surveyed phenotypes of ABC gene mutations in mice. Most mouse ABC gene disruption mutations have a phenotype that mimics human disease, indicating they are applicable models. Interestingly, several ABCA family genes, whose human function is unknown, have cholesterol level phenotypes in the mouse. Genome-wide association studies confirm and extend ABC traits and suggest several new functions to investigate. Whole-exome sequencing of tumors from diverse cancer types demonstrates that mutations in ABC genes are not common in cancer, but specific genes are overexpressed in select tumor types. Finally, an analysis of the frequency of loss-of-function mutations demonstrates that many human ABC genes are essential with a low level of variants, while others have a higher level of genetic diversity.

Fibromodulin Gene Variants (FMOD) as Potential Biomarkers for Prostate Cancer and Benign Prostatic Hyperplasia

By the year 2050, the world's elderly population may increase exponentially, raising the rate of disease characteristic of this group, such as prostate cancer (PCa) and benign prostatic hyperplasia (BPH). Prostate disorders have a multifactorial etiology, especially age and genetic factors. Currently, PCa is the second most frequent neoplasm in the male population worldwide. The fibromodulin gene encodes a small leucine-rich proteoglycan (SLRP) which acts in the collagen fibrillogenesis pathway, cell adhesion, and modulation of TGF-β signaling pathways, which has been recently associated with PCa. The present study sequenced the coding region of the FMOD in a sample of 44 PCa, 90 BPH, and 82 controls from a Brazilian population, and the results identified 6 variants: 2 missenses (p.(Tyr42Ser) and p.(Pro24Ala)); 3 synonymous (p.(His253=), p.(Asn353=), and p.(Glu79=)); and 1 intronic (c.980-114A>G). Of these, p.(Tyr42Ser), p.(Pro24Ala), and p.(Asn353=) are rare variants, and p.(Tyr42Ser) was predicted as potential pathogenic by the algorithms used here, in addition to not being observed in controls, suggesting that may be a potential biomarker for development of PCa and BPH. In conclusion, we identified for the first time, in Brazilian individuals with PCa and BPH, a potentially pathogenic variant in the analysis of FMOD gene. Further studies are needed to investigate the deleterious effect of this variant on the structure and/or function of the FMOD protein.

DSCMF: prediction of LncRNA-disease associations based on dual sparse collaborative matrix factorization

BACKGROUND

In the development of science and technology, there are increasing evidences that there are some associations between lncRNAs and human diseases. Therefore, finding these associations between them will have a huge impact on our treatment and prevention of some diseases. However, the process of finding the associations between them is very difficult and requires a lot of time and effort. Therefore, it is particularly important to find some good methods for predicting lncRNA-disease associations (LDAs).

RESULTS

In this paper, we propose a method based on dual sparse collaborative matrix factorization (DSCMF) to predict LDAs. The DSCMF method is improved on the traditional collaborative matrix factorization method. To increase the sparsity, the L2,1-norm is added in our method. At the same time, Gaussian interaction profile kernel is added to our method, which increase the network similarity between lncRNA and disease. Finally, the AUC value obtained by the experiment is used to evaluate the quality of our method, and the AUC value is obtained by the ten-fold cross-validation method.

CONCLUSIONS

The AUC value obtained by the DSCMF method is 0.8523. At the end of the paper, simulation experiment is carried out, and the experimental results of prostate cancer, breast cancer, ovarian cancer and colorectal cancer are analyzed in detail. The DSCMF method is expected to bring some help to lncRNA-disease associations research. The code can access the https://github.com/Ming-0113/DSCMF website.

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.

The Population-Specific Impact of Neandertal Introgression on Human Disease

Since the discovery of admixture between modern humans and Neandertals, multiple studies investigated the effect of Neandertal-derived DNA on human disease and nondisease phenotypes. These studies have linked Neandertal ancestry to skin- and hair-related phenotypes, immunity, neurological, and behavioral traits. However, these inferences have so far been limited to cohorts with participants of European ancestry. Here, I analyze summary statistics from 40 disease GWAS (genome-wide association study) cohorts of ∼212,000 individuals provided by the Biobank Japan Project for phenotypic effects of Neandertal DNA. I show that Neandertal DNA is associated with autoimmune diseases, prostate cancer and type 2 diabetes. Many of these disease associations are linked to population-specific Neandertal DNA, highlighting the importance of studying a wider range of ancestries to characterize the phenotypic legacy of Neandertals in people today.

Novel prostate cancer susceptibility gene SP6 predisposes patients to aggressive disease

Prostate cancer (PrCa) is one of the most common cancers in men, but little is known about factors affecting its clinical outcomes. Genome-wide association studies have identified more than 170 germline susceptibility loci, but most of them are not associated with aggressive disease. We performed a genome-wide analysis of 185,478 SNPs in Finnish samples (2738 cases, 2400 controls) from the international Collaborative Oncological Gene-Environment Study (iCOGS) to find underlying PrCa risk variants. We identified a total of 21 common, low-penetrance susceptibility loci, including 10 novel variants independently associated with PrCa risk. Novel risk loci were located in the 8q24 (CASC8 rs16902147, OR 1.86, p_adj = 3.53 × 10^-8 and rs58809953, OR 1.71, p_adj = 4.00 × 10^-6; intergenic rs79012498, OR 1.81, p_adj = 4.26 × 10^-8), 17q21 (SP6 rs2074187, OR 1.66, p_adj = 3.75 × 10^-5), 11q13 (rs12795301, OR 1.42, p_adj = 2.89 × 10^-5) and 8p21 (rs995432, OR 1.38, p_adj = 3.00 × 10^-11) regions. Here, we describe SP6, a transcription factor gene, as a new, potentially high-risk gene for PrCa. The intronic variant rs2074187 in SP6 was associated not only with overall susceptibility to PrCa (OR 1.66) but also with a higher odds ratio for aggressive PrCa (OR 1.89) and lower odds for non-aggressive PrCa (OR 1.43). Furthermore, the new intergenic variant rs79012498 at 8q24 conferred risk for aggressive PrCa. Our findings highlighted the power of a population-stratified approach to identify novel, clinically actionable germline PrCa risk loci and strongly suggested SP6 as a new PrCa candidate gene that may be involved in the pathogenesis of PrCa.

Global Autozygosity Is Associated with Cancer Risk, Mutational Signature and Prognosis

Simple Summary

Global autozygosity in the form of runs of homozygosity is associated with various diseases. Heterozygosity ratio, an alternative measure of global autozygosity, is used to assess cancer risk in this study. Our analysis shows strong and consistent associations between heterozygosity ratios and various cancer types. Further analysis reveals the heterozygosity ratio’s potential connections to mutational signatures and cancer prognosis.

Abstract

Global autozygosity quantifies the genome-wide levels of homozygous and heterozygous variants. It is the signature of non-random reproduction, though it can also be driven by other factors, and has been used to assess risk in various diseases. However, the association between global autozygosity and cancer risk has not been studied. From 4057 cancer subjects and 1668 healthy controls, we found strong associations between global autozygosity and risk in ten different cancer types. For example, the heterozygosity ratio was found to be significantly associated with breast invasive carcinoma in Blacks and with male skin cutaneous melanoma in Caucasians. We also discovered eleven associations between global autozygosity and mutational signatures which can explain a portion of the etiology. Furthermore, four significant associations for heterozygosity ratio were revealed in disease-specific survival analyses. This study demonstrates that global autozygosity is effective for cancer risk assessment.

The CHEK2 Variant C.349A>G Is Associated with Prostate Cancer Risk and Carriers Share a Common Ancestor

The identification of recurrent founder variants in cancer predisposing genes may have important implications for implementing cost-effective targeted genetic screening strategies. In this study, we evaluated the prevalence and relative risk of the CHEK2 recurrent variant c.349A>G in a series of 462 Portuguese patients with early-onset and/or familial/hereditary prostate cancer (PrCa), as well as in the large multicentre PRACTICAL case-control study comprising 55,162 prostate cancer cases and 36,147 controls. Additionally, we investigated the potential shared ancestry of the carriers by performing identity-by-descent, haplotype and age estimation analyses using high-density SNP data from 70 variant carriers belonging to 11 different populations included in the PRACTICAL consortium. The CHEK2 missense variant c.349A>G was found significantly associated with an increased risk for PrCa (OR 1.9; 95% CI: 1.1-3.2). A shared haplotype flanking the variant in all carriers was identified, strongly suggesting a common founder of European origin. Additionally, using two independent statistical algorithms, implemented by DMLE+2.3 and ESTIAGE, we were able to estimate the age of the variant between 2300 and 3125 years. By extending the haplotype analysis to 14 additional carrier families, a shared core haplotype was revealed among all carriers matching the conserved region previously identified in the high-density SNP analysis. These findings are consistent with CHEK2 c.349A>G being a founder variant associated with increased PrCa risk, suggesting its potential usefulness for cost-effective targeted genetic screening in PrCa families.

Validation of a prostate cancer polygenic risk score

BACKGROUND

Genome-wide association studies have identified over 100 single-nucleotide polymorphisms (SNPs) associated with prostate cancer (PrCa), and polygenic risk scores (PRS) based on their combined genotypes have been developed for risk stratification. We aimed to assess the contribution of PRS to PrCa risk in a large multisite study.

METHODS

The sample included 1972 PrCa cases and 1919 unaffected controls. Next-generation sequencing was used to assess pathogenic variants in 14 PrCa-susceptibility genes and 72 validated PrCa-associated SNPs. We constructed a population-standardized PRS and tested its association with PrCa using logistic regression adjusted for age and family history of PrCa.

RESULTS

The mean age of PrCa cases at diagnosis and age of controls at testing/last clinic visit was 59.5 ± 7.2 and 57.2 ± 13.0 years, respectively. Among 1740 cases with pathology data, 57.4% had Gleason score ≤ 6, while 42.6% had Gleason score ≥ 8. In addition, 39.6% cases and 20.1% controls had a family history of PrCa. The PRS was significantly higher in cases than controls (mean ± SD: 1.42 ± 1.11 vs 1.02 ± 0.76; P < .0001). Compared with men in the 1st quartile of age-adjusted PRS, those in the 2nd, 3rd, and 4th quartile were 1.58 (95% confidence interval [CI]: 1.31-1.90), 2.36 (95% CI: 1.96-2.84), and 3.98 (95% CI: 3.29-4.82) times as likely to have PrCa (all P < .0001). Adjustment for family history yielded similar results. PRS predictive performance was consistent with prior literature (area under the receiver operating curve = 0.64; 95% CI: 0.62-0.66).

CONCLUSIONS

These data suggest that a 72-SNP PRS is predictive of PrCa, supporting its potential use in clinical risk assessment.

Multi-ethnic transcriptome-wide association study of prostate cancer

The genetic risk for prostate cancer has been governed by a few rare variants with high penetrance and over 150 commonly occurring variants with lower impact on risk; however, most of these variants have been identified in studies containing exclusively European individuals. People of non-European ancestries make up less than 15% of prostate cancer GWAS subjects. Across the globe, incidence of prostate cancer varies with population due to environmental and genetic factors. The discrepancy between disease incidence and representation in genetics highlights the need for more studies of the genetic risk for prostate cancer across diverse populations. To better understand the genetic risk for prostate cancer across diverse populations, we performed PrediXcan and GWAS in a case-control study of 4,769 self-identified African American (2,463 cases and 2,306 controls), 2,199 Japanese American (1,106 cases and 1,093 controls), and 2,147 Latin American (1,081 cases and 1,066 controls) individuals from the Multiethnic Genome-wide Scan of Prostate Cancer. We used prediction models from 46 tissues in GTEx version 8 and five models from monocyte transcriptomes in the Multi-Ethnic Study of Atherosclerosis. Across the three populations, we predicted 19 gene-tissue pairs, including five unique genes, to be significantly (lfsr < 0.05) associated with prostate cancer. One of these genes, NKX3-1, replicated in a larger European study. At the SNP level, 110 SNPs met genome-wide significance in the African American study while 123 SNPs met significance in the Japanese American study. Fine mapping revealed three significant independent loci in the African American study and two significant independent loci in the Japanese American study. These identified loci confirm findings from previous GWAS of prostate cancer in diverse populations while PrediXcan-identified genes suggest potential new directions for prostate cancer research in populations across the globe.

An overview of advances in multi-omics analysis in prostate cancer

Prostate cancer (PCa) is a deadly disease for men, and studies of all types of omics data are necessary to promote precision medicine. The maturity of sequencing technology, the improvements of computer processing power, and the progress achieved in omics analysis methods have improved research efficiency and saved research costs. The occurrence and development of PCa is due to multisystem and multilevel pathological changes. Although omics research at a single level is important, this approach often has limitations. In contrast, the combined analysis of multiple types of omics data can better analyze PCa changes as a whole, thus ensuring the validity of research results to the greatest extent. This paper introduces the applications of single omics in PCa and then summarizes research progress in the combined analysis of two or more types of omics data, so as to systematically and comprehensively analyze the necessity of combined analysis of multiple omics data in PCa.

Pan-cancer study detects genetic risk variants and shared genetic basis in two large cohorts

Deciphering the shared genetic basis of distinct cancers has the potential to elucidate carcinogenic mechanisms and inform broadly applicable risk assessment efforts. Here, we undertake genome-wide association studies (GWAS) and comprehensive evaluations of heritability and pleiotropy across 18 cancer types in two large, population-based cohorts: the UK Biobank (408,786 European ancestry individuals; 48,961 cancer cases) and the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging cohorts (66,526 European ancestry individuals; 16,001 cancer cases). The GWAS detect 21 genome-wide significant associations independent of previously reported results. Investigations of pleiotropy identify 12 cancer pairs exhibiting either positive or negative genetic correlations; 25 pleiotropic loci; and 100 independent pleiotropic variants, many of which are regulatory elements and/or influence cross-tissue gene expression. Our findings demonstrate widespread pleiotropy and offer further insight into the complex genetic architecture of cross-cancer susceptibility.

Ethnic variation in prostate cancer detection: a feasibility study for use of the Stockholm3 test in a multiethnic U.S. cohort

BACKGROUND

The Stockholm3 test improves Gleason Grade Group ≥2 (GG ≥ 2) prostate cancer (PC) detection, however it has not been evaluated in an American cohort where clinical practice patterns and ethnicity differ. We aimed to identify subgroups within a Stockholm population with PC risk profiles matching American ethnicity-specific subgroups and compare the detection of PC and describe Stockholm3 performance within these subgroups.

METHODS

All men age 49-70 years presenting for prostate biopsies were evaluated at UIC from 2016 to 2019, as well as men in Stockholm from 2012 to 2014 in the STHLM3 study. Propensity scores (PS) were estimated for each person using logistic regression for age, PSA, prostate volume, family history of PC, 5-alpha reductase inhibitor use, and prior biopsy. 3:1 PS matching was performed for Stockholm to Chicago ethnicity-specific cohorts and odds ratios (OR) were computed to compare detection of GG ≥ 2 PC between groups.

RESULTS

504 Chicago men and 6980 Stockholm men were included. In African American (AA) men, 51% had GG ≥ 2 PC detected, while in risk-matched Stockholm men, 34% had GG ≥ 2 PC detected (OR: 2.1, p < 0.001). There was no statistical difference in GG ≥ 2 PC detected when matching Stockholm men to non-Hispanic Caucasian men (31% vs. 24%, OR: 0.7, p = 0.30) or Hispanic Caucasian men (31% vs. 27%, OR: 1.2, p = 0.42). The AUC for the Stockholm3 test of the matched Stockholm cohorts for AA, non-Hispanic Caucasian, and Hispanic Caucasian men was 0.85, 0.89, and 0.90, respectively.

CONCLUSIONS

Using statistical techniques to simulate a multi-ethnic Chicago cohort within the STHLM3 population, we found an excess risk of GG ≥ 2 PC among AA men. Our hypothesis that the Stockholm3 may have good predictive value in a multiethnic cohort is strengthened, and that recalibration to at least AA men seems likely to be needed to obtain well-calibrated predictions.

SNPs in lncRNA Regions and Breast Cancer Risk

Long non-coding RNAs (lncRNAs) play crucial roles in human physiology, and have been found to be associated with various cancers. Transcribed ultraconserved regions (T-UCRs) are a subgroup of lncRNAs conserved in several species, and are often located in cancer-related regions. Breast cancer is the most common cancer in women worldwide and the leading cause of female cancer deaths. We investigated the association of genetic variants in lncRNA and T-UCR regions with breast cancer risk to uncover candidate loci for further analysis. Our focus was on low-penetrance variants that can be discovered in a large dataset. We selected 565 regions of lncRNAs and T-UCRs that are expressed in breast or breast cancer tissue, or show expression correlation to major breast cancer associated genes. We studied the association of single nucleotide polymorphisms (SNPs) in these regions with breast cancer risk in the 122970 case samples and 105974 controls of the Breast Cancer Association Consortium's genome-wide data, and also by in silico functional analyses using Integrated Expression Quantitative trait and in silico prediction of GWAS targets (INQUISIT) and expression quantitative trait loci (eQTL) analysis. The eQTL analysis was carried out using the METABRIC dataset and analyses from GTEx and ncRNA eQTL databases. We found putative breast cancer risk variants (p < 1 × 10-5) targeting the lncRNA GABPB1-AS1 in INQUISIT and eQTL analysis. In addition, putative breast cancer risk associated SNPs (p < 1 × 10-5) in the region of two T-UCRs, uc.184 and uc.313, located in protein coding genes CPEB4 and TIAL1, respectively, targeted these genes in INQUISIT and in eQTL analysis. Other non-coding regions containing SNPs with the defined p-value and highly significant false discovery rate (FDR) for breast cancer risk association were discovered that may warrant further studies. These results suggest candidate lncRNA loci for further research on breast cancer risk and the molecular mechanisms.

DNA methylation and cis-regulation of gene expression by prostate cancer risk SNPs

Genome-wide association studies have identified more than 100 SNPs that increase the risk of prostate cancer (PrCa). We identify and compare expression quantitative trait loci (eQTLs) and CpG methylation quantitative trait loci (meQTLs) among 147 established PrCa risk SNPs in primary prostate tumors (n = 355 from a Seattle-based study and n = 495 from The Cancer Genome Atlas, TCGA) and tumor-adjacent, histologically benign samples (n = 471 from a Mayo Clinic study). The role of DNA methylation in eQTL regulation of gene expression was investigated by data triangulation using several causal inference approaches, including a proposed adaptation of the Causal Inference Test (CIT) for causal direction. Comparing eQTLs between tumors and benign samples, we show that 98 of the 147 risk SNPs were identified as eQTLs in the tumor-adjacent benign samples, and almost all 34 eQTL identified in tumor sets were also eQTLs in the benign samples. Three lines of results support the causal role of DNA methylation. First, nearly 100 of the 147 risk SNPs were identified as meQTLs in one tumor set, and almost all eQTLs in tumors were meQTLs. Second, the loss of eQTLs in tumors relative to benign samples was associated with altered DNA methylation. Third, among risk SNPs identified as both eQTLs and meQTLs, mediation analyses suggest that over two-thirds have evidence of a causal role for DNA methylation, mostly mediating genetic influence on gene expression. In summary, we provide a comprehensive catalog of eQTLs, meQTLs and putative cancer genes for known PrCa risk SNPs. We observe that a substantial portion of germline eQTL regulatory mechanisms are maintained in the tumor development, despite somatic alterations in tumor genome. Finally, our mediation analyses illuminate the likely intermediary role of CpG methylation in eQTL regulation of gene expression.

Use of empiric methods to inform prostate cancer health disparities: Comparison of neighborhood-wide association study "hits" in black and white men

BACKGROUND

Black men are more likely to die of prostate cancer (PCa) compared with white men. Factors ranging from genetics to neighborhood environment contribute to these disparities. However, unlike genetics, agnostic investigations that identify candidate variables from large-scale data, and that allow for empiric investigations into differential associations between neighborhood and PCa by race/ethnicity, to the authors' knowledge have not been well explored. Thus, herein, the authors built on their previously developed, empiric neighborhood-wide association study (NWAS) in white men and conducted a NWAS in black men to determine whether findings differed by race.

METHODS

Pennsylvania Cancer Registry data were linked to US Census data. For the NWAS in non-Hispanic black men, the authors evaluated the association between 14,663 neighborhood census variables and advanced PCa (11 high-stage and/or high-grade cases and 8632 low-stage and/or low-grade cases), adjusting for age, diagnosis year, spatial correlation, and multiple testing. Odds ratios and 95% credible intervals were reported. Replication of NWAS findings across black and white races was assessed using Bayesian mixed effects models.

RESULTS

Five variables related to housing (3 variables), education (1 variable), and employment and/or transportation (1 variable) were found to be significantly associated with advanced PCa in black men compared with 17 socioeconomic variables (mostly related to poverty and/or income) in white men. The top hit in black men was related to crowding in renter-occupied housing (odds ratio, 1.10; 95% credible interval, 1.001-1.12). Nine of 22 NWAS hits (4 of 5 hits in black men) were replicated across racial/ethnic groups.

CONCLUSIONS

Different neighborhood variables, or "candidates," were identified across race-specific NWASs. These findings and empiric approaches warrant additional study and may inform PCa racial disparities, particularly future gene-environment studies aimed at identifying patients and/or communities at risk of advanced PCa.

Identification of Novel Loci and New Risk Variant in Known Loci for Colorectal Cancer Risk in East Asians

BACKGROUND

Risk variants identified so far for colorectal cancer explain only a small proportion of familial risk of this cancer, particularly in Asians.

METHODS

We performed a genome-wide association study (GWAS) of colorectal cancer in East Asians, including 23,572 colorectal cancer cases and 48,700 controls. To identify novel risk loci, we selected 60 promising risk variants for replication using data from 58,131 colorectal cancer cases and 67,347 controls of European descent. To identify additional risk variants in known colorectal cancer loci, we performed conditional analyses in East Asians.

RESULTS

An indel variant, rs67052019 at 1p13.3, was found to be associated with colorectal cancer risk at P = 3.9 × 10-8 in Asians (OR per allele deletion = 1.13, 95% confidence interval = 1.08-1.18). This association was replicated in European descendants using a variant (rs2938616) in complete linkage disequilibrium with rs67052019 (P = 7.7 × 10-3). Of the remaining 59 variants, 12 showed an association at P < 0.05 in the European-ancestry study, including rs11108175 and rs9634162 at P < 5 × 10-8 and two variants with an association near the genome-wide significance level (rs60911071, P = 5.8 × 10-8; rs62558833, P = 7.5 × 10-8) in the combined analyses of Asian- and European-ancestry data. In addition, using data from East Asians, we identified 13 new risk variants at 11 loci reported from previous GWAS.

CONCLUSIONS

In this large GWAS, we identified three novel risk loci and two highly suggestive loci for colorectal cancer risk and provided evidence for potential roles of multiple genes and pathways in the etiology of colorectal cancer. In addition, we showed that additional risk variants exist in many colorectal cancer risk loci identified previously.

IMPACT

Our study provides novel data to improve the understanding of the genetic basis for colorectal cancer risk.

Genome-wide germline correlates of the epigenetic landscape of prostate cancer

Oncogenesis is driven by germline, environmental and stochastic factors. It is unknown how these interact to produce the molecular phenotypes of tumors. We therefore quantified the influence of germline polymorphisms on the somatic epigenome of 589 localized prostate tumors. Predisposition risk loci influence a tumor's epigenome, uncovering a mechanism for cancer susceptibility. We identified and validated 1,178 loci associated with altered methylation in tumoral but not nonmalignant tissue. These tumor methylation quantitative trait loci influence chromatin structure, as well as RNA and protein abundance. One prominent tumor methylation quantitative trait locus is associated with AKT1 expression and is predictive of relapse after definitive local therapy in both discovery and validation cohorts. These data reveal intricate crosstalk between the germ line and the epigenome of primary tumors, which may help identify germline biomarkers of aggressive disease to aid patient triage and optimize the use of more invasive or expensive diagnostic assays.

First-degree family history of breast cancer is associated with prostate cancer risk: a systematic review and meta-analysis

Background

The relationship between first-degree family history of female breast cancer and prostate cancer risk in the general population remains unclear. We performed a meta-analysis to determine the association between first-degree family history of female breast cancer and prostate cancer risk.

Methods

Databases, including MEDLINE, Embase, and Web of Science, were searched for all associated studies that evaluated associations between first-degree family history of female breast cancer and prostate cancer risk up to December 31, 2018. Information on study characteristics and outcomes were extracted based on the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) statement and Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. The quality of evidence was assessed using the GRADE approach.

Results

Eighteen studies involving 17,004,892 individuals were included in the meta-analysis. Compared with no family history of female breast cancer, history of female breast cancer in first-degree relatives was associated with an increased risk of prostate cancer [relative risk (RR) 1.18, 95% confidence interval (CI) 1.12–1.25] with moderate-quality evidence. A history of breast cancer in mothers only (RR 1.19, 95% CI 1.10–1.28) and sisters only (RR 1.71, 95% CI 1.43–2.04) was associated with increased prostate cancer risk with moderate-quality evidence. However, a family history of breast cancer in daughters only was not associated with prostate cancer incidence (RR 1.74, 95% CI 0.74–4.12) with moderate-quality evidence. A family history of female breast cancer in first-degree relatives was associated with an 18% increased risk of lethal prostate cancer (95% CI 1.04–1.34) with low-quality evidence.

Conclusions

This review demonstrates that men with a family history of female breast cancer in first-degree relatives had an increased risk of prostate cancer, including risk of lethal prostate cancer. These findings may guide screening, earlier detection, and treatment of men with a family history of female breast cancer in first-degree relatives.

DNA damage and hormone-related cancer: a repair pathway view

In this short review, we examine the overlap between genes known to be mutated in the germlines of individuals at risk of breast, ovarian and prostate cancers, and their positions in DNA damage repair pathways. Cancer risk mutations have been consistently reported in certain genes at the top of these pathways, but none have been reported in others. We consider whether some of these gene products are too crucial to life for mutations to be tolerated, whilst others, further down the pathways, are less essential.

The Human TET2 Gene Contains Three Distinct Promoter Regions With Differing Tissue and Developmental Specificities

Tet methylcytosine dioxygenase 2 (TET2) is a tumor suppressor gene that is inactivated in a wide range of hematological cancers. TET2 enzymatic activity converts 5-methylcytosine (5-mC) into 5-hydroxymethylcytosine (5-hmC), an essential step in DNA demethylation. Human TET2 is highly expressed in pluripotent cells and down-regulated in differentiated cells: however, transcriptional regulation of the human TET2 gene has not been investigated in detail. Here we define three promoters within a 2.5 kb region located ∼ 87 kb upstream of the first TET2 coding exon. The three promoters, designated as Pro1, Pro2, and Pro3, generate three alternative first exons, and their presence in TET2 mRNAs varies with cell type and developmental stage. In general, all three TET2 transcripts are more highly expressed in human tissues rich in hematopoietic stem cells, such as spleen and bone marrow, compared to other tissues, such as brain and kidney. Transcripts from Pro2 are expressed by a broad range of tissues and at a significantly higher level than Pro1 or Pro3 transcripts. Pro3 transcripts were highly expressed by embryoid bodies generated from the H9 ES cell line, and the major Pro3 transcript is an alternatively spliced mRNA isoform that produces a truncated TET2 protein lacking the catalytic domain. Our study demonstrates distinct tissue-specific mechanisms of TET2 transcriptional regulation during early pluripotent states and in differentiated cell types.

Glioma risk associated with extent of estimated European genetic ancestry in African Americans and Hispanics

Glioma incidence is highest in non-Hispanic Whites, and to date, glioma genome-wide association studies (GWAS) to date have only included European ancestry (EA) populations. African Americans and Hispanics in the US have varying proportions of EA, African (AA) and Native American ancestries (NAA). It is unknown if identified GWAS loci or increased EA is associated with increased glioma risk. We assessed whether EA was associated with glioma in African Americans and Hispanics. Data were obtained for 832 cases and 675 controls from the Glioma International Case-Control Study and GliomaSE Case-Control Study previously estimated to have <80% EA, or self-identify as non-White. We estimated global and local ancestry using fastStructure and RFMix, respectively, using 1,000 genomes project reference populations. Within groups with ≥40% AA (AFR_≥0.4 ), and ≥15% NAA (AMR_≥0.15 ), genome-wide association between local EA and glioma was evaluated using logistic regression conditioned on global EA for all gliomas. We identified two regions (7q21.11, p = 6.36 × 10^-4 ; 11p11.12, p = 7.0 × 10^-4 ) associated with increased EA, and one associated with decreased EA (20p12.13, p = 0.0026) in AFR_≥0.4 . In addition, we identified a peak at rs1620291 (p = 4.36 × 10^-6 ) in 7q21.3. Among AMR_≥0.15 , we found an association between increased EA in one region (12q24.21, p = 8.38 × 10^-4 ), and decreased EA in two regions (8q24.21, p = 0. 0010; 20q13.33, p = 6.36 × 10^-4 ). No other significant associations were identified. This analysis identified an association between glioma and two regions previously identified in EA populations (8q24.21, 20q13.33) and four novel regions (7q21.11, 11p11.12, 12q24.21 and 20p12.13). The identifications of novel association with EA suggest regions to target for future genetic association studies.

An expanded variant list and assembly annotation identifies multiple novel coding and noncoding genes for prostate cancer risk using a normal prostate tissue eQTL data set

Prostate cancer (PrCa) is highly heritable; 284 variants have been identified to date that are associated with increased prostate cancer risk, yet few genes contributing to its development are known. Expression quantitative trait loci (eQTL) studies link variants with affected genes, helping to determine how these variants might regulate gene expression and may influence prostate cancer risk. In the current study, we performed eQTL analysis on 471 normal prostate epithelium samples and 249 PrCa-risk variants in 196 risk loci, utilizing RNA sequencing transcriptome data based on ENSEMBL gene definition and genome-wide variant data. We identified a total of 213 genes associated with known PrCa-risk variants, including 141 protein-coding genes, 16 lncRNAs, and 56 other non-coding RNA species with differential expression. Compared to our previous analysis, where RefSeq was used for gene annotation, we identified an additional 130 expressed genes associated with known PrCa-risk variants. We detected an eQTL signal for more than half (n = 102, 52%) of the 196 loci tested; 52 (51%) of which were a Group 1 signal, indicating high linkage disequilibrium (LD) between the peak eQTL variant and the PrCa-risk variant (r2>0.5) and may help explain how risk variants influence the development of prostate cancer.

Cross-Cancer Pleiotropic Associations with Lung Cancer Risk in African Americans

BACKGROUND

Identifying genetic variants with pleiotropic associations across multiple cancers can reveal shared biologic pathways. Prior pleiotropic studies have primarily focused on European-descent individuals. Yet population-specific genetic variation can occur, and potential pleiotropic associations among diverse racial/ethnic populations could be missed. We examined cross-cancer pleiotropic associations with lung cancer risk in African Americans.

METHODS

We conducted a pleiotropic analysis among 1,410 African American lung cancer cases and 2,843 controls. We examined 36,958 variants previously associated (or in linkage disequilibrium) with cancer in prior genome-wide association studies. Logistic regression analyses were conducted, adjusting for age, sex, global ancestry, study site, and smoking status.

RESULTS

We identified three novel genomic regions significantly associated (FDR-corrected P <0.10) with lung cancer risk (rs336958 on 5q14.3, rs7186207 on 16q22.2, and rs11658063 on 17q12). On chromosome16q22.2, rs7186207 was significantly associated with reduced risk [OR = 0.43; 95% confidence interval (CI), 0.73-0.89], and functional annotation using GTEx showed rs7186207 modifies DHODH gene expression. The minor allele at rs336958 on 5q14.3 was associated with increased lung cancer risk (OR = 1.47; 95% CI, 1.22-1.78), whereas the minor allele at rs11658063 on 17q12 was associated with reduced risk (OR = 0.80; 95% CI, 0.72-0.90).

CONCLUSIONS

We identified novel associations on chromosomes 5q14.3, 16q22.2, and 17q12, which contain HNF1B, DHODH, and HAPLN1 genes, respectively. SNPs within these regions have been previously associated with multiple cancers. This is the first study to examine cross-cancer pleiotropic associations for lung cancer in African Americans.

IMPACT

Our findings demonstrate novel cross-cancer pleiotropic associations with lung cancer risk in African Americans.

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

BACKGROUND

Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer-metabolite associations using two-sample Mendelian randomization (MR).

METHODS

The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.

RESULTS

Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.

CONCLUSIONS

We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.

IMPACT

The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.

Discovery of common and rare genetic risk variants for colorectal cancer

To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P < 5 × 10-8, bringing the number of known independent signals for CRC to ~100. New signals implicate lower-frequency variants, Krüppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs and somatic drivers, and support a role for immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of biology underlying this risk and influence personalized screening strategies and drug development.

The association between IGF1 Gene 3'-UTR polymorphisms and cancer risk: A Meta-analysis

BACKGROUND AND OBJECTIVE

Insulin-like growth factor 1 (IGF1) gene three prime untranslated region (3'-UTR) polymorphisms have been reported to be associated with cancer risk. However, the conclusions of the relevant studies are not consistent. The present meta-analysis evaluates the relationship between IGF1 gene 3'-UTR polymorphisms (rs5742714, rs6214, and rs6220) and cancer risk.

METHODS

Articles regarding the relationship between IGF1 rs5742714, rs6214, and rs6220 polymorphisms and cancer risk were selected by searching the PubMed, Embase, and Web of Science databases before April 30, 2018. Altogether, we obtained 34 case-controlled studies from 20 articles, including 21,568 cases and 31,199 controls. The strength of associations was quantified using odds ratios (ORs) and the corresponding 95% confidence intervals (CIs).

RESULTS

In the present meta-analysis, no significant associations were detected between rs5742714, rs6214, and rs6220 and overall cancer risk. Thus, in stratified analyses, we found that rs6214 was associated with a significantly reduced risk of breast cancer under the allele, heterozygote, and dominant models (A vs G: OR, 0.94, 95% CI,0.88-1.00, P = .044; GA vs GG: OR, 0.88, 95% CI, 0.80-0.97, P = .012; AA + GA vs GG: OR, 0.89, 95% CI, 0.81-0.97, P = .011), as well as pancreatic cancer under the recessive model (AA vs GA + GG: OR, 0.68, 95% CI,0.53-0.87, P = .003). Also, rs6220 was associated with a significantly increased risk of breast cancer under the homozygote model (GG vs AA: OR, 1.23, 95% CI, 1.02-1.48, P = .031). In addition, rs6220 was found to increase overall cancer risk among Caucasians under the allele model (G vs A: OR, 1.06, 95% CI, 1.00-1.13, P = .043).

CONCLUSIONS

In this meta-analysis, we investigated and reviewed the relationship between IGF1 gene 3'-UTR polymorphisms (rs5742714, rs6214, and rs6220) and cancer risk based on present epidemiological studies. Further studies are needed to draw more precise conclusions in the future.

Transformation-induced stress at telomeres is counteracted through changes in the telomeric proteome including SAMHD1

The authors apply telomeric chromatin analysis to identify factors that accumulate at telomeres during cellular transformation, promoting telomere replication and repair and counteracting oncogene-borne telomere replication stress.

Telomeres play crucial roles during tumorigenesis, inducing cellular senescence upon telomere shortening and extensive chromosome instability during telomere crisis. However, it has not been investigated if and how cellular transformation and oncogenic stress alter telomeric chromatin composition and function. Here, we transform human fibroblasts by consecutive transduction with vectors expressing hTERT, the SV40 early region, and activated H-RasV12. Pairwise comparisons of the telomeric proteome during different stages of transformation reveal up-regulation of proteins involved in chromatin remodeling, DNA repair, and replication at chromosome ends. Depletion of several of these proteins induces telomere fragility, indicating their roles in replication of telomeric DNA. Depletion of SAMHD1, which has reported roles in DNA resection and homology-directed repair, leads to telomere breakage events in cells deprived of the shelterin component TRF1. Thus, our analysis identifies factors, which accumulate at telomeres during cellular transformation to promote telomere replication and repair, resisting oncogene-borne telomere replication stress.

Transcriptional Regulation in Prostate Cancer

Prostate cancer development involves corruption of the normal prostate transcriptional network, following deregulated expression or mutation of key transcription factors. Here, we provide an overview of the transcription factors that are important in normal prostate homeostasis (NKX3-1, p63, androgen receptor [AR]), primary prostate cancer (ETS family members, c-MYC), castration-resistant prostate cancer (AR, FOXA1), and AR-independent castration-resistant neuroendocrine prostate cancer (RB1, p53, N-MYC). We use functional (in vitro and in vivo) as well as clinical data to discuss evidence that unveils their roles in the initiation and progression of prostate cancer, with an emphasis on results of chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq).

Molecular Biomarkers in the Clinical Management of Prostate Cancer

Prostate cancer, one of the most common noncutaneous malignancies in men, is a heterogeneous disease with variable clinical outcome. Although the majority of patients harbor indolent tumors that are essentially cured by local therapy, subsets of patients present with aggressive disease or recur/progress after primary treatment. With this in mind, modern clinical approaches to prostate cancer emphasize the need to reduce overdiagnosis and overtreatment via personalized medicine. Advances in our understanding of prostate cancer pathogenesis, coupled with recent technologic innovations, have facilitated the development and validation of numerous molecular biomarkers, representing a range of macromolecules assayed from a variety of patient sample types, to help guide the clinical management of prostate cancer, including early detection, diagnosis, prognostication, and targeted therapeutic selection. Herein, we review the current state of the art regarding prostate cancer molecular biomarkers, emphasizing those with demonstrated utility in clinical practice.

CRISPR-mediated deletion of prostate cancer risk-associated CTCF loop anchors identifies repressive chromatin loops

BACKGROUND

Recent genome-wide association studies (GWAS) have identified more than 100 loci associated with increased risk of prostate cancer, most of which are in non-coding regions of the genome. Understanding the function of these non-coding risk loci is critical to elucidate the genetic susceptibility to prostate cancer.

RESULTS

We generate genome-wide regulatory element maps and performed genome-wide chromosome confirmation capture assays (in situ Hi-C) in normal and tumorigenic prostate cells. Using this information, we annotate the regulatory potential of 2,181 fine-mapped prostate cancer risk-associated SNPs and predict a set of target genes that are regulated by prostate cancer risk-related H3K27Ac-mediated loops. We next identify prostate cancer risk-associated CTCF sites involved in long-range chromatin loops. We use CRISPR-mediated deletion to remove prostate cancer risk-associated CTCF anchor regions and the CTCF anchor regions looped to the prostate cancer risk-associated CTCF sites, and we observe up to 100-fold increases in expression of genes within the loops when the prostate cancer risk-associated CTCF anchor regions are deleted.

CONCLUSIONS

We identify GWAS risk loci involved in long-range loops that function to repress gene expression within chromatin loops. Our studies provide new insights into the genetic susceptibility to prostate cancer.

Prostate Cancer Germline Variations and Implications for Screening and Treatment

Prostate cancer (PCa) is a highly heritable disease, and rapid evolution of sequencing technologies has enabled marked progression of our understanding of its genetic inheritance. A complex polygenic model that involves common low-penetrance susceptibility alleles causing individually small but cumulatively significant risk and rarer genetic variants causing greater risk represent the current most accepted model. Through genome-wide association studies, more than 100 single-nucleotide polymorphisms (SNPs) associated with PCa risk have been identified. Consistent reports have identified germline mutations in the genes BRCA1, BRCA2, MMR, HOXB13, CHEK2, and NBS1 as conferring moderate risks, with some leading to a more aggressive disease behavior. Considering this knowledge, several research strategies have been developed to determine whether targeted prostate screening using genetic information can overcome the limitations of population-based prostate-specific antigen (PSA) screening. Germline DNA-repair mutations are more frequent in men with metastatic disease than previously thought, and these patients have a more favorable response to therapy with poly(adenosine diphosphate [ADP]-ribose) polymerase (PARP) inhibitors. Genomic information is a practical tool that has the potential to enable the concept of precision medicine to become a reality in all steps of PCa patient care.

Synergistic Interaction of HOXB13 and CIP2A Predisposes to Aggressive Prostate Cancer

PURPOSE

Distinguishing aggressive prostate cancer from indolent disease improves personalized treatment. Although only few genetic variants are known to predispose to aggressive prostate cancer, synergistic interactions of HOXB13 G84E high-risk prostate cancer susceptibility mutation with other genetic loci remain unknown. The purpose of this study was to examine the interplay of HOXB13 rs138213197 (G84E) and CIP2A rs2278911 (R229Q) germline variants on prostate cancer risk.

EXPERIMENTAL DESIGN

Genotyping was done in Finnish discovery cohort (n = 2,738) and validated in Swedish (n = 3,132) and independent Finnish (n = 1,155) prostate cancer cohorts. Expression pattern analysis was followed by functional studies in prostate cancer cell models.

RESULTS

Interplay of HOXB13 (G84E) and CIP2A (R229Q) variants results in highest observed inherited prostate cancer risk (OR, 21.1; P = 0.000024). In addition, this synergism indicates a significant association of HOXB13 T and CIP2A T dual carriers with elevated risk for high Gleason score (OR, 2.3; P = 0.025) and worse prostate cancer-specific life expectancy (HR, 3.9; P = 0.048), and it is linked with high PSA at diagnosis (OR, 3.30; P = 0.028). Furthermore, combined high expression of HOXB13-CIP2A correlates with earlier biochemical recurrence. Finally, functional experiments showed that ectopic expression of variants stimulates prostate cancer cell growth and migration. In addition, we observed strong chromatin binding of HOXB13 at CIP2A locus and revealed that HOXB13 functionally promotes CIP2A transcription. The study is limited to retrospective Nordic cohorts.

CONCLUSIONS

Simultaneous presence of HOXB13 T and CIP2A T alleles confers for high prostate cancer risk and aggressiveness of disease, earlier biochemical relapse, and lower disease-specific life expectancy. HOXB13 protein binds to CIP2A gene and functionally promotes CIP2A transcription.

Genome-Based Classification and Therapy of Prostate Cancer

In the past decade, multi-national and multi-center efforts were launched to sequence prostate cancer genomes, transcriptomes, and epigenomes with the aim of discovering the molecular underpinnings of tumorigenesis, cancer progression, and therapy resistance. Multiple biological markers and pathways have been discovered to be tumor drivers, and a molecular classification of prostate cancer is emerging. Here, we highlight crucial findings of these genome-sequencing projects in localized and advanced disease. We recapitulate the utility and limitations of current clinical practices to diagnosis, prognosis, and therapy, and we provide examples of insights generated by the molecular profiling of tumors. Novel treatment concepts based on these molecular alterations are currently being addressed in clinical trials and will lead to an enhanced implementation of precision medicine strategies.

Genetics and biology of prostate cancer

Despite the high long-term survival in localized prostate cancer, metastatic prostate cancer remains largely incurable even after intensive multimodal therapy. The lethality of advanced disease is driven by the lack of therapeutic regimens capable of generating durable responses in the setting of extreme tumor heterogeneity on the genetic and cell biological levels. Here, we review available prostate cancer model systems, the prostate cancer genome atlas, cellular and functional heterogeneity in the tumor microenvironment, tumor-intrinsic and tumor-extrinsic mechanisms underlying therapeutic resistance, and technological advances focused on disease detection and management. These advances, along with an improved understanding of the adaptive responses to conventional cancer therapies, anti-androgen therapy, and immunotherapy, are catalyzing development of more effective therapeutic strategies for advanced disease. In particular, knowledge of the heterotypic interactions between and coevolution of cancer and host cells in the tumor microenvironment has illuminated novel therapeutic combinations with a strong potential for more durable therapeutic responses and eventual cures for advanced disease. Improved disease management will also benefit from artificial intelligence-based expert decision support systems for proper standard of care, prognostic determinant biomarkers to minimize overtreatment of localized disease, and new standards of care accelerated by next-generation adaptive clinical trials.

Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.

Association Analysis between Body Mass Index and Genomic DNA Methylation across 15 Major Cancer Types

Cancer incidence and mortality increase with increasing body mass index (BMI), but BMI-associated epigenetic alterations in cancer remain elusive. We hypothesized that BMI would be associated with DNA methylation alterations in cancers. To test this hypothesis, here, we estimated the associations between DNA methylation and BMI through two different methods across 15 cancer types, at approximately 485,000 CpG sites and 2415 samples using data from The Cancer Genome Atlas. After comparing the DNA methylation levels in control BMI and high BMI individuals, we found differentially methylated CpG sites (DMSs) in cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), and uterine corpus endometrial carcinoma (UCEC) (False Discovery Rate < 0.05). The DMSs of COAD or UCEC were enriched in several obesity-induced and cancer-related pathways. Next, when BMI was used as a continuous variable, we identified BMI-associated methylated CpG sites (BMS) (P (Bonferroni) < 0.05) in CHOL (BMS = 1), COAD (BMS = 1), and UCEC (BMS = 4) using multivariable linear regression. In UCEC, three of the BMSs can predict the clinical outcomes and survival of patients with the tumors. Overall, we observed associations between DNA methylation and high BMI in CHOL, COAD, and UCEC. Furthermore, three BMI-associated CpGs were identified as potential biomarkers for UCEC prognosis.

Prostate Cancer Genomics: Recent Advances and the Prevailing Underrepresentation from Racial and Ethnic Minorities

Prostate cancer (CaP) is the most commonly diagnosed non-cutaneous cancer and the second leading cause of male cancer deaths in the United States. Among African American (AA) men, CaP is the most prevalent malignancy, with disproportionately higher incidence and mortality rates. Even after discounting the influence of socioeconomic factors, the effect of molecular and genetic factors on racial disparity of CaP is evident. Earlier studies on the molecular basis for CaP disparity have focused on the influence of heritable mutations and single-nucleotide polymorphisms (SNPs). Most CaP susceptibility alleles identified based on genome-wide association studies (GWAS) were common, low-penetrance variants. Germline CaP-associated mutations that are highly penetrant, such as those found in HOXB13 and BRCA2, are usually rare. More recently, genomic studies enabled by Next-Gen Sequencing (NGS) technologies have focused on the identification of somatic mutations that contribute to CaP tumorigenesis. These studies confirmed the high prevalence of ERG gene fusions and PTEN deletions among Caucasian Americans and identified novel somatic alterations in SPOP and FOXA1 genes in early stages of CaP. Individuals with African ancestry and other minorities are often underrepresented in these large-scale genomic studies, which are performed primarily using tumors from men of European ancestry. The insufficient number of specimens from AA men and other minority populations, together with the heterogeneity in the molecular etiology of CaP across populations, challenge the generalizability of findings from these projects. Efforts to close this gap by sequencing larger numbers of tumor specimens from more diverse populations, although still at an early stage, have discovered distinct genomic alterations. These research findings can have a direct impact on the diagnosis of CaP, the stratification of patients for treatment, and can help to address the disparity in incidence and mortality of CaP. This review examines the progress of understanding in CaP genetics and genomics and highlight the need to increase the representation from minority populations.

Obtaining high quality transcriptome data from formalin-fixed, paraffin-embedded diagnostic prostate tumor specimens

Prognostic genomic biomarkers that can be measured at diagnosis to aid choice of treatment options are unavailable for most common cancers. This is due in part to the poor quality and quantity of available diagnostic specimens for discovery research and to limitations in genomic technologies. Recent technical advances now enable high-density molecular analyses using suboptimal biological specimens. Here we describe the optimization of a transcriptome-specific protocol for use with formalin-fixed, paraffin-embedded (FFPE) diagnostic prostate cancer (PrCa) specimens. We applied the Ion AmpliSeq Transcriptome Human Gene Expression Kit (AmpliSeq Kit) to RNA samples extracted from 36 tumor-enriched and 16 adjacent normal tissues (ADJ_NT) from 37 FFPE PrCa specimens over a series of eight pilot studies, incorporating protocol modifications from Pilots 2 to 5. Data quality were measured by (1) the total number of mapped reads; (2) the percentage of reads that mapped to AmpliSeq target regions (OnTarget%); (3) the percentage of genes on the AmpliSeq panel with a read count ≥10 (TargetsDetected%); and (4) comparing the gene read-count distribution of the prostate tissue samples with the median gene read-count distribution of cell line-derived RNA samples. Modifications incorporated into Pilot study 5 provided gene expression data equivalent to cell line-derived RNA samples. These modifications included the use of freshly cut slides for macrodissection; increased tissue section thickness (8 µm); RNA extraction using the RecoverAll Total Nucleic Acid Isolation Kit for FFPE (ThermoFisher); 18 target amplification cycles; and processing six samples per Ion PI chip. This protocol will facilitate the discovery of prognostic biomarkers for cancer by allowing researchers to exploit previously underutilized diagnostic FFPE specimens.

Men with a susceptibility to prostate cancer and the role of genetic based screening

Prostate cancer is the second most common malignancy affecting men worldwide, and the commonest affecting men of African descent. Significant diagnostic and therapeutic advances have been made in the past decade. Improvements in the accuracy of prostate cancer diagnosis include the uptake of multi-parametric MRI and a shift towards targeted biopsy. We also now have more life-prolonging systemic and hormonal therapies for men with advanced disease at our disposal than ever before. However, the development of robust screening tools and targeted screening programs has not followed at the same pace. Evidence to support population-based screening remains unclear, with the use of PSA as a screening test limiting our ability to discriminate between clinically significant and insignificant disease. Prostate cancer has a large heritable component. Given that most men without risk factors have a low lifetime risk of developing lethal prostate cancer, much work is being done to further our knowledge of how we can best screen men in higher risk categories, such as those with a family history (FH) of the disease or those of African ancestry. These men have been reported to carry upwards of a two-fold increased risk of developing the disease at an earlier age, with evidence suggesting poorer survival outcomes. In men with a FH of prostate cancer, this is felt to be due to rare, high-penetrance mutations and the presence of multiple, common low penetrance alleles, with men carrying specific germline mutations in the BRCA and other DNA repair genes at particularly high risk. To date, large scale genome-wide association studies (GWAS) have led to the discovery of approximately 170 single nucleotide polymorphisms (SNPs) associated with prostate cancer risk, allowing over 30% of prostate cancer risk to be explained. Genomic tests, utilising somatic (prostate biopsy) tissue can also predict the risk of unfavourable pathology, biochemical recurrence and the likelihood of metastatic disease using gene expression. Targeted screening studies are currently under way in men with DNA repair mutations, men with a FH and those of Afro-Caribbean ethnicity which will greater inform our understanding of disease incidence and behaviour in these men, treatment outcomes and developing the most appropriate screening regime for such men. Incorporating a patient's genetic mutation status into risk algorithms allows us an opportunity to develop targeted screening programs for men in whom early cancer detection and treatment will positively influence survival, and in the process offer male family members of affected men the chance to be counselled and screened accordingly.

Combined Performance of Screening and Variable Selection Methods in Ultra-High Dimensional Data in Predicting Time-To-Event Outcomes

BACKGROUND

Building prognostic models of clinical outcomes is an increasingly important research task and will remain a vital area in genomic medicine. Prognostic models of clinical outcomes are usually built and validated utilizing variable selection methods and machine learning tools. The challenges, however, in ultra-high dimensional space are not only to reduce the dimensionality of the data, but also to retain the important variables which predict the outcome. Screening approaches, such as the sure independence screening (SIS), iterative SIS (ISIS) and principled SIS (PSIS) have been developed to overcome the challenge of high dimensionality. We are interested in identifying important single-nucleotide polymorphisms (SNPs) and integrating them into a validated prognostic model of overall survival in patients with metastatic prostate cancer. While the abovementioned variable selection approaches have theoretical justification in selecting SNPs, the comparison and the performance of these combined methods in predicting time-to-event outcomes have not been previously studied in ultra-high dimensional space with hundreds of thousands of variables.

METHODS

We conducted a series of simulations to compare the performance of different combinations of variable selection approaches and classification trees, such as the least absolute shrinkage and selection operator (LASSO), adaptive least absolute shrinkage and selection operator (ALASSO) and random survival forest (RSF), in ultra-high dimensional setting data for the purpose of developing prognostic models for a time-to-event outcome that is subject to censoring. The variable selection methods were evaluated for discrimination (Harrell's concordance statistic), calibration and overall performance. In addition, we applied these approaches to 498,081 SNPs from 623 Caucasian patients with prostate cancer.

RESULTS

When n=300, ISIS-LASSO and ISIS-ALASSO chose all the informative variables which resulted in the highest Harrell's c-index (>0.80). On the other hand, with a small sample size (n=150), ALASSO performed better than any other combinations as demonstrated by the highest c-index and/or overall performance, although there was evidence of overfitting. In analyzing the prostate cancer data, ISIS-ALASSO, SIS-LASSO, and SIS-ALASSO combinations achieved the highest discrimination with c-index of 0.67.

CONCLUSIONS

Choosing the appropriate variable selection method for training a model is a critical step in developing a robust prognostic model. Based on the simulation studies, the effective use of ALASSO or a combination of methods, such as ISIS-LASSO and ISIS-ALASSO, allows both for the development of prognostic models with high predictive accuracy and a low risk of overfitting assuming moderate sample sizes.

Nutrient Sensing, Signaling and Ageing: The Role of IGF-1 and mTOR in Ageing and Age-Related Disease

Nutrient signaling through insulin/IGF-1 was the first pathway demonstrated to regulate ageing and age-related disease in model organisms. Pharmacological or dietary interventions targeting nutrient signaling pathways have been shown to robustly attenuate ageing in many organisms. Caloric restriction, the most widely studied longevity promoting intervention, works through multiple nutrient signaling pathways, while inhibition of mTOR through treatment with rapamycin reproducibly delays ageing and disease through specific inhibition of the mTOR complexes. Although the benefits of reduced insulin/IGF-1 in lifespan and health are well documented in model organisms, defining the precise role of the IGF-1 in human ageing and age-related disease has proven more difficult. Association studies provide some insight but also reveal paradoxes. Low serum IGF-1 predicts longevity, but IGF-1 decreases with age and IGF-1 therapy benefits some of age-related pathologies. Circulating IGF-1 has been associated both positively and negatively with risk of age-related diseases in humans, and in some cases both activation and inhibition of IGF-1 signaling have provided benefit in animal models of the same diseases. Interventions designed modulate the nutrient sensing signaling pathways positively or negatively are already available for clinical use, highlighting the need for a clear understanding of the role of nutrient signaling in ageing and age-related disease. This chapter examines data from model organisms and human genetic association studies, with a special emphasis on IGF-1 and mTOR, and discusses potential models for resolving the paradoxes surrounding IGF-1 data.

The molecular biology of prostate cancer: current understanding and clinical implications

BACKGROUND

With continuous progress over the past few decades in understanding diagnosis, treatment, and genetics, much has been learned about the prostate cancer-diagnosed genome.

METHODS

A comprehensive MEDLINE® and Google scholar literature search was conducted using keyword variations relating to the genetics of prostate cancer such as chromosomal alterations, androgen receptor, castration-resistant, inheritance, polymorphisms, oncogenes, metastasis, biomarkers, and immunotherapy.

RESULTS

Traditionally, androgen receptors (AR) have been the focus of research. Recently, identification of recurrent chromosomal alterations that lead to either multiplication of regions (gain-of-function) or deletion of regions (loss-of-function) has opened the door to greater genetic accessibility. These chromosomal aberrations lead to variation in copy number and gene expression. Some of these chromosomal alterations are inherited, while others undergo somatic mutations during disease progression. Inherited gene mutations that make one susceptible to prostate cancer have been identified with familial-linked studies. Somatic genes that progress tumorigenesis have also been identified. Research on the molecular biology of prostate cancer has characterized these genes into tumor suppressor genes or oncogenes. Additionally, genome-wide assay studies have identified many high-risk single-nucleotide polymorphisms recurrent throughout the prostate cancer-diagnosed genome. Castration-resistant prostate cancer is the most aggressive form of prostate cancer, and its research has elucidated many types of mutations associated with AR itself, including enhanced expression and amplification, point mutations, and alternative splicing. Understanding the molecular biology of prostate cancer has permitted more accurate identification using advanced biomarkers and therapy for aggressive forms using immunotherapy.

CONCLUSIONS

An age-related disease, prostate cancer commands profound attention. With increasing life expectancy and the continuous pursuit of it, prostate cancer is a powerful obstacle best defeated using targeted therapies specifically designed for the unique molecular profile of the malignancy.