A genome-wide association study of prostate cancer in Latinos

Heterogeneous genetic architectures of prostate cancer susceptibility in sub-Saharan Africa

Men of African descent have the highest prostate cancer incidence and mortality rates, yet the genetic basis of prostate cancer in African men has been understudied. We used genomic data from 3,963 cases and 3,509 controls from Ghana, Nigeria, Senegal, South Africa and Uganda to infer ancestry-specific genetic architectures and fine-map disease associations. Fifteen independent associations at 8q24.21, 6q22.1 and 11q13.3 reached genome-wide significance, including four new associations. Intriguingly, multiple lead associations are private alleles, a pattern arising from recent mutations and the out-of-Africa bottleneck. These African-specific alleles contribute to haplotypes with odds ratios above 2.4. We found that the genetic architecture of prostate cancer differs across Africa, with effect size differences contributing more to this heterogeneity than allele frequency differences. Population genetic analyses reveal that African prostate cancer associations are largely governed by neutral evolution. Collectively, our findings emphasize the utility of conducting genetic studies that use diverse populations.

Prevalence of germline variants in Brazilian pancreatic carcinoma patients

We evaluated the prevalence of pathogenic/likely pathogenic germline variants (PGV) in Brazilian pancreatic adenocarcinoma (PC) patients, that represent a multiethnic population, in a cross-sectional study. We included 192 PC patients unselected for family history of cancer. We evaluated a panel of 113 cancer genes, through genomic DNA sequencing and 46 ancestry-informative markers, through multiplex PCR. The median age was 61 years; 63.5% of the patients presented disease clinical stages III or IV; 8.3% reported personal history of cancer; 4.7% and 16.1% reported first-degree relatives with PC or breast and/or prostate cancer, respectively. Although the main ancestry was European, there was considerable genetic composition admixture. Twelve patients (6.25%) were PGV carriers in PC predisposition genes (ATM, BRCA1, BRCA2, CDKN2A, MSH2, PALB2) and another 25 (13.0%) were PGV carriers in genes with a limited association or not previously associated with PC (ACD, BLM, BRIP1, CHEK2, ERCC4, FANCA, FANCE, FANCM, GALNT12, MITF, MRE11, MUTYH, POLE, RAD51B, RAD51C, RECQL4, SDHA, TERF2IP). The most frequently affected genes were CHEK2, ATM and FANC. In tumor samples from PGV carriers in ACD, BRIP1, MRE11, POLE, SDHA, TERF2IP, which were examined through exome sequencing, the main single base substitutions (SBS) mutational signature was SBS1+5+18, probably associated with age, tobacco smoking and reactive oxygen species. SBS3 associated with homologous repair deficiency was also represented, but on a lower scale. There was no difference in the frequency of PGV carriers between: (a) patients with or without first-degree relatives with cancer; and (b) patients with admixed ancestry versus those with predominantly European ancestry. Furthermore, there was no difference in overall survival between PGV carriers and non-carriers. Therefore, genetic testing should be offered to all Brazilian pancreatic cancer patients, regardless of their ancestry. Genes with limited or previously unrecognized associations with pancreatic cancer should be further investigated to clarify their role in cancer risk.

Genomic landscape of early-stage prostate adenocarcinoma in Mexican patients: an exploratory study

BACKGROUND

Health disparities have been highlighted among patient with prostate adenocarcinoma (PRAD) due to ethnicity. Mexican men present a more aggressive disease than other patients resulting in less favorable treatment outcome. We aimed to identify the mutational landscape which could help to reduce the health disparities among minority groups and generate the first genomics exploratory study of PRAD in Mexican patients.

METHODS

Paraffin-embedded formalin-fixed tumoral tissue from 20 Mexican patients with early-stage PRAD treated at The Instituto Nacional de Cancerología, Mexico City from 2017 to 2019 were analyzed. Tumoral DNA was prepared for whole exome sequencing, the resulting files were mapped against h19 using BWA-MEM. Strelka2 and Lancet packages were used to identify single nucleotide variants (SNV) and insertions or deletions. FACETS was used to determine somatic copy number alterations (SCNA). Cancer Genome Interpreter web interface was used to determine the clinical relevance of variants.

RESULTS

Patients were in an early clinical stage and had a mean age of 59.55 years (standard deviation [SD]: 7.1 years) with 90% of them having a Gleason Score of 7. Follow-up time was 48.50 months (SD: 32.77) with recurrences and progression in 30% and 15% of the patients, respectively. NUP98 (20%), CSMD3 (15%) and FAT1 (15%) were the genes most frequently affected by SNV; ARAF (75%) and ZNF419 (70%) were the most frequently affected by losses and gains SNCA's. One quarter of the patients had mutations useful as biomarkers for the use of PARP inhibitors, they comprise mutations in BRCA, RAD54L and ATM. SBS05, DBS03 and ID08 were the most common mutational signatures present in this cohort. No associations with recurrence or progression were identified.

CONCLUSIONS

This pilot study reveals the mutational landscape of early-stage prostate adenocarcinoma in Mexican men, providing a first approach to understand the mutational patterns and actionable mutations in early prostate cancer can inform personalized treatment approaches and reduce the underrepresentation in genomic cancer studies.

Genomic ancestry and cancer among Latin Americans

Latin American populations, characterized by intricate admixture patterns resulting from the intermingling of ancestries from European, Native American (NA) Asian, and African ancestries which result in a vast and complex genetic landscape, harboring unique combinations of novel variants. This genetic diversity not only poses challenges in traditional population genetics methods but also opens avenues for a deeper understanding of its implications in health. In cancer, the interplay between genetic ancestry, lifestyle factors, and healthcare disparities adds a layer of complexity to the varying incidence and mortality rates observed across different Latin American subpopulations. This complex interdependence has been unveiled through numerous studies, whether conducted on Latin American patients residing on the continent or abroad, revealing discernible differences in germline composition that influence divergent disease phenotypes such as higher incidence of Luminal B and Her2 breast tumors, EGFR and KRAS mutated lung adenocarcinomas in addition to an enrichment in BRCA1/2 pathogenic variants and a higher than expected prevalence of variants in colorectal cancer associated genes such as APC and MLH1. In prostate cancer novel risk variants have also been solely identified in Latin American populations. Due to the complexity of genetic divergence, inputs from each individual ancestry seem to carry independent contributions that interplay in the development of these complex disease phenotypes. By understanding these unique population characteristics, genomic ancestries hold a promising avenue for tailoring prognostic assessments and optimizing responses to oncological interventions.

Comparative analysis of genetic risk scores for predicting biochemical recurrence in prostate cancer patients after radical prostatectomy

BACKGROUND

In recent years, Genome-Wide Association Studies (GWAS) has identified risk variants related to complex diseases, but most genetic variants have less impact on phenotypes. To solve the above problems, methods that can use variants with low genetic effects, such as genetic risk score (GRS), have been developed to predict disease risk.

METHODS

As the GRS model with the most incredible prediction power for complex diseases has not been determined, our study used simulation data and prostate cancer data to explore the disease prediction power of three GRS models, including the simple count genetic risk score (SC-GRS), the direct logistic regression genetic risk score (DL-GRS), and the explained variance weighted GRS based on directed logistic regression (EVDL-GRS).

RESULTS AND CONCLUSIONS

We used 26 SNPs to establish GRS models to predict the risk of biochemical recurrence (BCR) after radical prostatectomy. Combining clinical variables such as age at diagnosis, body mass index, prostate-specific antigen, Gleason score, pathologic T stage, and surgical margin and GRS models has better predictive power for BCR. The results of simulation data (statistical power = 0.707) and prostate cancer data (area under curve = 0.8462) show that DL-GRS has the best prediction performance. The rs455192 was the most relevant locus for BCR (p = 2.496 × 10-6) in our study.

Genetic ancestry and radical prostatectomy findings in Hispanic/Latino patients

Background

African ancestry is a known factor associated with the presentation and aggressiveness of prostate cancer (PC). Hispanic/Latino populations exhibit varying degrees of genetic admixture across Latin American countries, leading to diverse levels of African ancestry. However, it remains unclear whether genetic ancestry plays a role in the aggressiveness of PC in Hispanic/Latino patients. We explored the associations between genetic ancestry and the clinicopathological data in Hispanic/Latino PC patients from Colombia.

Patients and methods

We estimated the European, Indigenous and African genetic ancestry, of 230 Colombian patients with localized/regionally advanced PC through a validated panel for genotypification of 106 Ancestry Informative Markers. We examined the associations of the genetic ancestry components with the Gleason Grade Groups (GG) and the clinicopathological characteristics.

Results

No association was observed between the genetic ancestry with the biochemical recurrence or Gleason GG; however, in a two groups comparison, there were statistically significant differences between GG3 and GG4/GG5 for European ancestry, with a higher mean ancestry proportion in GG4/GG5. A lower risk of being diagnosed at an advanced age was observed for patients with high African ancestry than those with low African ancestry patients (OR: 0.96, CI: 0.92-0.99, p=0.03).

Conclusion

Our findings revealed an increased risk of presentation of PC at an earlier age in patients with higher African ancestry compared to patients with lower African ancestry in our Hispanic/Latino patients.

Heterogeneous genetic architectures and evolutionary genomics of prostate cancer in Sub-Saharan Africa

Men of African descent have the highest prostate cancer (CaP) incidence and mortality rates, yet the genetic basis of CaP in African men has been understudied. We used genomic data from 3,963 CaP cases and 3,509 controls recruited in Ghana, Nigeria, Senegal, South Africa, and Uganda, to infer ancestry-specific genetic architectures and fine-mapped disease associations. Fifteen independent associations at 8q24.21, 6q22.1, and 11q13.3 reached genome-wide significance, including four novel associations. Intriguingly, multiple lead SNPs are private alleles, a pattern arising from recent mutations and the out-of-Africa bottleneck. These African-specific alleles contribute to haplotypes with odds ratios above 2.4. We found that the genetic architecture of CaP differs across Africa, with effect size differences contributing more to this heterogeneity than allele frequency differences. Population genetic analyses reveal that African CaP associations are largely governed by neutral evolution. Collectively, our findings emphasize the utility of conducting genetic studies that use diverse populations.

Ancestry: How researchers use it and what they mean by it

Background: Ancestry is often viewed as a more objective and less objectionable population descriptor than race or ethnicity. Perhaps reflecting this, usage of the term "ancestry" is rapidly growing in genetics research, with ancestry groups referenced in many situations. The appropriate usage of population descriptors in genetics research is an ongoing source of debate. Sound normative guidance should rest on an empirical understanding of current usage; in the case of ancestry, questions about how researchers use the concept, and what they mean by it, remain unanswered. Methods: Systematic literature analysis of 205 articles at least tangentially related to human health from diverse disciplines that use the concept of ancestry, and semi-structured interviews with 44 lead authors of some of those articles. Results: Ancestry is relied on to structure research questions and key methodological approaches. Yet researchers struggle to define it, and/or offer diverse definitions. For some ancestry is a genetic concept, but for many-including geneticists-ancestry is only tangentially related to genetics. For some interviewees, ancestry is explicitly equated to ethnicity; for others it is explicitly distanced from it. Ancestry is operationalized using multiple data types (including genetic variation and self-reported identities), though for a large fraction of articles (26%) it is impossible to tell which data types were used. Across the literature and interviews there is no consistent understanding of how ancestry relates to genetic concepts (including genetic ancestry and population structure), nor how these genetic concepts relate to each other. Beyond this conceptual confusion, practices related to summarizing patterns of genetic variation often rest on uninterrogated conventions. Continental labels are by far the most common type of label applied to ancestry groups. We observed many instances of slippage between reference to ancestry groups and racial groups. Conclusion: Ancestry is in practice a highly ambiguous concept, and far from an objective counterpart to race or ethnicity. It is not uniquely a "biological" construct, and it does not represent a "safe haven" for researchers seeking to avoid evoking race or ethnicity in their work. Distinguishing genetic ancestry from ancestry more broadly will be a necessary part of providing conceptual clarity.

Application of European-specific polygenic risk scores for predicting prostate cancer risk in different ancestry populations

BACKGROUND

Polygenic risk score (PRS) has shown promise in predicting prostate cancer (PCa) risk. However, the application of PRS in non-European ancestry was poorly studied.

METHODS

We constructed PRS using 68, 86, or 128 PCa-associated single-nucleotide polymorphisms (SNPs) identified through a large-scale Genome-wide association study (GWAS) in the European ancestry population. A calibration approach was performed to adjust the PRS exact value for each ancestry. The study was conducted in East Asian (ChinaPCa Consortium, n = 2379), European (UK Biobank, n = 209,172), and African American (African Ancestry Prostate Cancer Consortium, n = 6016).

RESULTS

Individuals with the highest PRS (in >97.5th percentile) had over 2.5-fold increased risk of PCa than those with average PRS (in 40th-60th percentile) in both European (odds ratio [OR] = 3.79, 95% confidence interval [CI] = 3.46-4.16, p < 0.001) and Chinese (OR = 2.87, 95% CI = 1.29-6.40, p = 0.010), while slightly lower in African American (OR = 1.77, 95% CI = 1.22-2.58, p = 0.008). Compared with the lowest PRS (in <2.5th percentile), increased PRS was also associated with the earlier onset of PCa (All log-rank p < 0.05). The highest PRS contributed to having about 5- to 12-fold higher lifetime risk and 5-10 years earlier at disease onset than the lowest category across different ancestry populations.

CONCLUSION

We demonstrated that European-GWAS-based PRS could also significantly predict PCa risk in Asian ancestry and African ancestry populations.

PRState: Incorporating genetic ancestry in prostate cancer risk scores for men of African ancestry

BACKGROUND

Prostate cancer (PrCa) is one of the most genetically driven solid cancers with heritability estimates as high as 57%. Men of African ancestry are at an increased risk of PrCa; however, current polygenic risk score (PRS) models are based on European ancestry groups and may not be broadly applicable. The objective of this study was to construct an African ancestry-specific PrCa PRS (PRState) and evaluate its performance.

METHODS

African ancestry group of 4,533 individuals in ELLIPSE consortium was used for discovery of African ancestry-specific PrCa SNPs. PRState was constructed as weighted sum of genotypes and effect sizes from genome-wide association study (GWAS) of PrCa in African ancestry group. Performance was evaluated using ROC-AUC analysis.

RESULTS

We identified African ancestry-specific PrCa risk loci on chromosomes 3, 8, and 11 and constructed a polygenic risk score (PRS) from 10 African ancestry-specific PrCa risk SNPs, achieving an AUC of 0.61 [0.60-0.63] and 0.65 [0.64-0.67], when combined with age and family history. Performance dropped significantly when using ancestry-mismatched PRS models but remained comparable when using trans-ancestry models. Importantly, we validated the PRState score in the Million Veteran Program (MVP), demonstrating improved prediction of PrCa and metastatic PrCa in individuals of African ancestry.

CONCLUSIONS

African ancestry-specific PRState improves PrCa prediction in African ancestry groups in ELLIPSE consortium and MVP. This study underscores the need for inclusion of individuals of African ancestry in gene variant discovery to optimize PRSs and identifies African ancestry-specific variants for use in future studies.

Testing the generalizability of ancestry-specific polygenic risk scores to predict prostate cancer in sub-Saharan Africa

BACKGROUND

Genome-wide association studies do not always replicate well across populations, limiting the generalizability of polygenic risk scores (PRS). Despite higher incidence and mortality rates of prostate cancer in men of African descent, much of what is known about cancer genetics comes from populations of European descent. To understand how well genetic predictions perform in different populations, we evaluated test characteristics of PRS from three previous studies using data from the UK Biobank and a novel dataset of 1298 prostate cancer cases and 1333 controls from Ghana, Nigeria, Senegal, and South Africa.

RESULTS

Allele frequency differences cause predicted risks of prostate cancer to vary across populations. However, natural selection is not the primary driver of these differences. Comparing continental datasets, we find that polygenic predictions of case vs. control status are more effective for European individuals (AUC 0.608-0.707, OR 2.37-5.71) than for African individuals (AUC 0.502-0.585, OR 0.95-2.01). Furthermore, PRS that leverage information from African Americans yield modest AUC and odds ratio improvements for sub-Saharan African individuals. These improvements were larger for West Africans than for South Africans. Finally, we find that existing PRS are largely unable to predict whether African individuals develop aggressive forms of prostate cancer, as specified by higher tumor stages or Gleason scores.

CONCLUSIONS

Genetic predictions of prostate cancer perform poorly if the study sample does not match the ancestry of the original GWAS. PRS built from European GWAS may be inadequate for application in non-European populations and perpetuate existing health disparities.

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.

Race and prostate cancer: genomic landscape

In the past 20 years, new insights into the genomic pathogenesis of prostate cancer have been provided. Large-scale integrative genomics approaches enabled researchers to characterize the genetic and epigenetic landscape of prostate cancer and to define different molecular subclasses based on the combination of genetic alterations, gene expression patterns and methylation profiles. Several molecular drivers of prostate cancer have been identified, some of which are different in men of different races. However, the extent to which genomics can explain racial disparities in prostate cancer outcomes is unclear. Future collaborative genomic studies overcoming the underrepresentation of non-white patients and other minority populations are essential.

Role of Polygenic Risk Score in Cancer Precision Medicine of Non-European Populations: A Systematic Review

The development of new screening methods and diagnostic tests for traits, common diseases, and cancer is linked to the advent of precision genomic medicine, in which health care is individually adjusted based on a person’s lifestyle, environmental influences, and genetic variants. Based on genome-wide association study (GWAS) analysis, rapid and continuing progress in the discovery of relevant single nucleotide polymorphisms (SNPs) for traits or complex diseases has increased interest in the potential application of genetic risk models for routine health practice. The polygenic risk score (PRS) estimates an individual’s genetic risk of a trait or disease, calculated by employing a weighted sum of allele counts combined with non-genetic variables. However, 98.38% of PRS records held in public databases relate to the European population. Therefore, PRSs for multiethnic populations are urgently needed. We performed a systematic review to discuss the role of polygenic risk scores in advancing precision medicine for different cancer types in multiethnic non-European populations.

Association between genetic variations at 8q24 and prostate cancer risk in Mexican Men

BACKGROUND

Variants of 8q24 locus have been associated with prostate cancer (PCa) susceptibility. This study aims to analyze the genetic basis of PCa susceptibility in Mexican men by analyzing SNPs in the 8q24 locus for the first time.

METHODS

A case-control study was performed in 875 men recruited from the Mexican Social Security Institute, 326 patients with PCa, and 549 non-PCa patients (88 with benign prostatic hyperplasia BPH and 461 healthy controls). The 8q24 locus SNPs: rs16901979, rs16983267, rs1447295, and rs7837328 were genotyped by allelic discrimination assays using TaqMan probes. Statistical analysis was performed using Epi Info statistical 7.0 and SNPstats softwares.

RESULTS

All genotype frequencies were in Hardy-Weinberg Equilibrium. No differences were observed in genotype distribution between PCa and non-PCa patients for rs6983267. Under different inheritance models, the rs16901979, rs1447295, and rs7837328 SNPs were associated with PCa (OR = 2.8, 1.8, and 1.72, respectively; Pc < 0.001) when comparing PCa patients against controls. This association remains between PCa and BPH patients under different models (OR = 8.5, 2.2, and 1.9, respectively; Pc < 0.001). There were no significant differences in allele and genotype distribution among BPH patients and controls. The combined effect of the alleles CGAA for the SNPs rs16901979, rs6983267, rs1447295, and rs7837328 showed significant differences between PCa patients and controls (OR = 2.9, 95% CI = 1.48-5.83, Pc = 0.008). Four 8q24 variants were not associated with D'Amico score, age at diagnosis, and bone metastases.

CONCLUSIONS

Our study provides the first confirmation that variants rs16901979, rs1447295, and 7837328 at 8q24 locus are associated with PCa susceptibility in Mexican men.

Participation in genetic research among Latinx populations by Latin America birth-residency concordance: a global study

Latinx populations are underrepresented in DNA-based research, and risk not benefiting from research if underrepresentation continues. Latinx populations are heterogenous; reflect complex social, migration, and colonial histories; and form strong global diasporas. We conducted a global study using a survey tool (Amazon's Mechanical Turk portal) to ascertain willingness to participate in genetic research by Latin America birth-residency concordance. Participants in the global study identified as Latinx (n=250) were classified as the following: (1) born/live outside of Latin America and the Caribbean (LAC), (2) born within/live outside LAC, and (3) born/live within LAC. Latinx were similarly likely to indicated they would participate DNA-based research as their non-Latinx counterparts (52.8% vs. 56.2%, respectively). Latinx born and living in LAC were significantly more willing to participate in DNA-based research than Latinx born and living outside of LAC (OR: 2.5; 95% CI: 1.3, 4.9, p<.01). Latinx indicating they would participate in genetic research were more likely to trust researchers (<.05), believe genetic research could lead to better understanding of disease (<.05), and that genetic research could lead to new treatments (p<.05) when compared with Latinx not interested in participating in genetic research. In summary, significant variation exists in genetic research interest among Latinx based on where they were born and live, suggesting that this context itself independently influences decisions about participation. Cultivating and investing in a research ecosystem that addresses, values, and respects Latinx priorities, circumstances, and researchers would likely increase research participation and, even more importantly, potentially impact the inequitable health disparities disproportionately represented in Latinx communities.

Germline Predisposition to Prostate Cancer in Diverse Populations

There remains a paucity of data related to germline genetic alterations predisposing patients to prostate cancer. Recent data suggest that African American, Hispanic, and Asian and Pacific Islander men exhibit genetic alterations in both highly penetrant germline genes, including BRCA1/2, ATM, and CHEK2, and the mismatch repair genes associated with Lynch syndrome, as well as low-penetrant single-nucleotide polymorphisms. However, cohort sizes remain small in many studies limiting the ability to determine clinical significance, appropriate risk stratification, and treatment implications in these diverse populations.

Polygenic Risk Scores in Prostate Cancer Risk Assessment and Screening

More than 40% of the risk of developing prostate cancer (PCa) is from genetic factors. Genome-wide association studies have led to the discovery of more than 140 variants associated with PCa risk. Polygenic risk scores (PRS) generated using these variants show promise in identifying individuals at much higher (and lower) lifetime risk than the average man. PCa PRS also improve the predictive value of prostate-specific antigen screening, may inform the age for starting PCa screening, and are informative for development of more aggressive tumors. Despite the promise, few clinical trials have evaluated the benefit of PCa PRS for clinical care.

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.

Cancer health disparities in racial/ethnic minorities in the United States

There are well-established disparities in cancer incidence and outcomes by race/ethnicity that result from the interplay between structural, socioeconomic, socio-environmental, behavioural and biological factors. However, large research studies designed to investigate factors contributing to cancer aetiology and progression have mainly focused on populations of European origin. The limitations in clinicopathological and genetic data, as well as the reduced availability of biospecimens from diverse populations, contribute to the knowledge gap and have the potential to widen cancer health disparities. In this review, we summarise reported disparities and associated factors in the United States of America (USA) for the most common cancers (breast, prostate, lung and colon), and for a subset of other cancers that highlight the complexity of disparities (gastric, liver, pancreas and leukaemia). We focus on populations commonly identified and referred to as racial/ethnic minorities in the USA-African Americans/Blacks, American Indians and Alaska Natives, Asians, Native Hawaiians/other Pacific Islanders and Hispanics/Latinos. We conclude that even though substantial progress has been made in understanding the factors underlying cancer health disparities, marked inequities persist. Additional efforts are needed to include participants from diverse populations in the research of cancer aetiology, biology and treatment. Furthermore, to eliminate cancer health disparities, it will be necessary to facilitate access to, and utilisation of, health services to all individuals, and to address structural inequities, including racism, that disproportionally affect racial/ethnic minorities in the USA.

Cancer PRSweb: An Online Repository with Polygenic Risk Scores for Major Cancer Traits and Their Evaluation in Two Independent Biobanks

To facilitate scientific collaboration on polygenic risk scores (PRSs) research, we created an extensive PRS online repository for 35 common cancer traits integrating freely available genome-wide association studies (GWASs) summary statistics from three sources: published GWASs, the NHGRI-EBI GWAS Catalog, and UK Biobank-based GWASs. Our framework condenses these summary statistics into PRSs using various approaches such as linkage disequilibrium pruning/p value thresholding (fixed or data-adaptively optimized thresholds) and penalized, genome-wide effect size weighting. We evaluated the PRSs in two biobanks: the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort at Michigan Medicine, and the population-based UK Biobank (UKB). For each PRS construct, we provide measures on predictive performance and discrimination. Besides PRS evaluation, the Cancer-PRSweb platform features construct downloads and phenome-wide PRS association study results (PRS-PheWAS) for predictive PRSs. We expect this integrated platform to accelerate PRS-related cancer research.

Evaluation of Polygenic Risk Scores for Prediction of Prostate Cancer in Korean Men

Aims

The purpose of this study is to evaluate an aggregate influence of prostate cancer (PCa) susceptibility variants on the development of PCa in Korean men by using the polygenic risk score (PRS) approach.

Methods

An analysis of 1,001 cases of PCa and 2,641 controls was performed to: (i) identify potential PCa-related risk loci in Koreans and (ii) validate the cumulative association between these loci and PCa using the PRS. Subgroup analyses based on risk stratification were conducted to better characterize the potential correlation to key PCa-related clinical outcomes (e.g., Gleason score, prostate-specific antigen levels). The results were replicated using 514 cases of PCa and 548 controls from an independent cohort.

Results

Genome-wide association analysis from our discovery cohort revealed 11 candidate single-nucleotide polymorphisms (SNPs) associated with PCa showing statistical significance of p < 5.0 × 10^–5. Seven variants were located at 8q24.21 (rs1016343, rs16901979, and rs13252298 in PRNCR1; rs4242384, rs7837688, and rs1447295 in CASC8; and rs1512268 in NKX3). Two variants located within HNF1B (rs7501939 and rs4430796) had a significant negative association with PCa risk [odds ratio (OR) = 0.717 and 0.747, p = 6.42 × 10^–7 and 3.67 × 10^–6, respectively]. Of the six independent SNPs that remained after linkage disequilibrium (LD) pruning, the top four SNPs best predicted PCa risk with an area under the receiver operating characteristic curve (AUC) of 0.637 (95% CI: 0.582–0.692). Those with top 25% polygenic risk had a 4.2-fold increased risk of developing PCa compared with those with low risk.

Conclusion

Eleven PCa risk variants in Korean men were identified; PRSs of a subset of these variants could help predict PCa susceptibility.

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.

Hereditary Predisposition to Prostate Cancer: From Genetics to Clinical Implications

Prostate cancer (PrCa) ranks among the top five cancers for both incidence and mortality worldwide. A significant proportion of PrCa susceptibility has been attributed to inherited predisposition, with 10-20% of cases expected to occur in a hereditary/familial context. Advances in DNA sequencing technologies have uncovered several moderate- to high-penetrance PrCa susceptibility genes, most of which have previously been related to known hereditary cancer syndromes, namely the hereditary breast and ovarian cancer (BRCA1, BRCA2, ATM, CHEK2, and PALB2) and Lynch syndrome (MLH1, MSH2, MSH6, and PMS2) genes. Additional candidate genes have also been suggested, but further evidence is needed to include them in routine genetic testing. Recommendations based on clinical features, family history, and ethnicity have been established for more cost-efficient genetic testing of patients and families who may be at an increased risk of developing PrCa. The identification of alterations in PrCa predisposing genes may help to inform screening strategies, as well as treatment options, in the metastatic setting. This review provides an overview of the genetic basis underlying hereditary predisposition to PrCa, the current genetic screening recommendations, and the implications for clinical management of the disease.

The emerging field of polygenic risk scores and perspective for use in clinical care

Genetic testing is used widely for diagnostic, carrier and predictive testing in monogenic diseases. Until recently, there were no genetic testing options available for multifactorial complex diseases like heart disease, diabetes and cancer. Genome-wide association studies (GWAS) have been invaluable in identifying single-nucleotide polymorphisms (SNPs) associated with increased or decreased risk for hundreds of complex disorders. For a given disease, SNPs can be combined to generate a cumulative estimation of risk known as a polygenic risk score (PRS). After years of research, PRSs are increasingly used in clinical settings. In this article, we will review the literature on how both genome-wide and restricted PRSs are developed and the relative merit of each. The validation and evaluation of PRSs will also be discussed, including the recognition that PRS validity is intrinsically linked to the methodological and analytical approach of the foundation GWAS together with the ethnic characteristics of that cohort. Specifically, population differences may affect imputation accuracy, risk magnitude and direction. Even as PRSs are being introduced into clinical practice, there is a push to combine them with clinical and demographic risk factors to develop a holistic disease risk. The existing evidence regarding the clinical utility of PRSs is considered across four different domains: informing population screening programs, guiding therapeutic interventions, refining risk for families at high risk, and facilitating diagnosis and predicting prognostic outcomes. The evidence for clinical utility in relation to five well-studied disorders is summarized. The potential ethical, legal and social implications are also highlighted.