Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction

Identifying proteomic risk factors for overall, aggressive and early onset prostate cancer using Mendelian randomization and tumor spatial transcriptomics

Background

Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention.

Methods

We investigated the association of 2,002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis-pQTL Mendelian randomization (MR) and colocalization. Findings for proteins with support from both MR, after correction for multiple-testing, and colocalization were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate-specific tissue expression were additionally investigated using spatial transcriptomic data in prostate tumor tissue to assess their role in tumor aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets.

Results

We identified 20 proteins genetically linked to prostate cancer risk (14 for overall [8 specific], 7 for aggressive [3 specific], and 8 for early onset disease [2 specific]), of which a majority were novel and replicated. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54-2.93], PYY [OR = 1.87, 95% CI: 1.43-2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73-0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99-4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67-0.86] and TPM3 [OR = 0.47, 95% CI: 0.34-0.64]. We confirm an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80-0.82], and also find an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82-0.86] and early onset disease [OR = 0.71, 95% CI: 0.68-0.74]. Using spatial transcriptomics data, we identified MSMB as the genome-wide top-most predictive gene to distinguish benign regions from high grade cancer regions that had five-fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk mapped to existing therapeutic interventions.

Conclusion

Our findings emphasize the importance of proteomics for improving our understanding of prostate cancer etiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added benefit of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumors. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer.

Polygenic Risk and Chemotherapy-Related Subsequent Malignancies in Childhood Cancer Survivors: A Childhood Cancer Survivor Study and St Jude Lifetime Cohort Study Report

PURPOSE

Chemotherapeutic exposures are associated with subsequent malignant neoplasm (SMN) risk. The role of genetic susceptibility in chemotherapy-related SMNs should be defined as use of radiation therapy (RT) decreases.

PATIENTS AND METHODS

SMNs among long-term childhood cancer survivors of European (EUR; N = 9,895) and African (AFR; N = 718) genetic ancestry from the Childhood Cancer Survivor Study and St Jude Lifetime Cohort Study were evaluated. An externally validated 179-variant polygenic risk score (PRS) associated with pleiotropic adult cancer risk from the UK Biobank Study (N > 400,000) was computed for each survivor. SMN cumulative incidence comparing top and bottom PRS quintiles was estimated, along with hazard ratios (HRs) from proportional hazards models.

RESULTS

A total of 1,594 survivors developed SMNs, with basal cell carcinomas (n = 822), breast cancers (n = 235), and thyroid cancers (n = 221) being the most frequent. Although SMN risk associations with the PRS were extremely modest in RT-exposed EUR survivors (HR, 1.22; P = .048; n = 4,630), the increase in 30-year SMN cumulative incidence and HRs comparing top and bottom PRS quintiles was statistically significant among nonirradiated EUR survivors (n = 4,322) treated with alkylating agents (17% v 6%; HR, 2.46; P < .01), anthracyclines (20% v 8%; HR, 2.86; P < .001), epipodophyllotoxins (23% v 1%; HR, 12.20; P < .001), or platinums (46% v 7%; HR, 8.58; P < .01). This PRS also significantly modified epipodophyllotoxin-related SMN risk among nonirradiated AFR survivors (n = 414; P < .01). Improvements in prediction attributable to the PRS were greatest for epipodophyllotoxin-exposed (AUC, 0.71 v 0.63) and platinum-exposed (AUC,0.68 v 0.58) survivors.

CONCLUSION

A pleiotropic cancer PRS has strong potential for improving SMN clinical risk stratification among nonirradiated survivors treated with specific chemotherapies. A polygenic risk screening approach may be a valuable complement to an early screening strategy on the basis of treatments and rare cancer-susceptibility mutations.

Polygenic scores in cancer

Since the publication of the first genome-wide association study for cancer in 2007, thousands of common alleles that are associated with the risk of cancer have been identified. The relative risk associated with individual variants is small and of limited clinical significance. However, the combined effect of multiple risk variants as captured by polygenic scores (PGSs) may be much greater and therefore provide risk discrimination that is clinically useful. We review the considerable research efforts over the past 15 years for developing statistical methods for PGSs and their application in large-scale genome-wide association studies to develop PGSs for various cancers. We review the predictive performance of these PGSs and the multiple challenges currently limiting the clinical application of PGSs. Despite this, PGSs are beginning to be incorporated into clinical multifactorial risk prediction models to stratify risk in both clinical trials and clinical implementation studies.

Investigating the tissue specificity and prognostic impact of cis-regulatory cancer risk variants

The tissue-specific incidence of cancers and their genetic basis are poorly understood. Although prior studies have shown global correlation across tissues for cancer risk single-nucleotide polymorphisms (SNPs) identified through genome-wide association studies (GWAS), any shared functional regulation of gene expression on a per SNP basis has not been well characterized. We set to quantify cis-mediated gene regulation and tissue sharing for SNPs associated with eight common cancers. We identify significant tissue sharing for individual SNPs and global enrichment for breast, colorectal, and Hodgkin lymphoma cancer risk SNPs in multiple tissues. In addition, we observe increasing tissue sharing for cancer risk SNPs overlapping with super-enhancers for breast cancer and Hodgkin lymphoma providing further evidence of tissue specificity. Finally, for genes under cis-regulation by breast cancer SNPs, we identify a phenotype characterized by low expression of tumor suppressors and negative regulators of the WNT pathway associated with worse freedom from progression and overall survival in patients who eventually develop breast cancer. Our results introduce a paradigm for functionally annotating individual cancer risk SNPs and will inform the design of future translational studies aimed to personalize assessment of inherited cancer risk across tissues.

Predicted Proteome Association Studies of Breast, Prostate, Ovarian, and Endometrial Cancers Implicate Plasma Protein Regulation in Cancer Susceptibility

BACKGROUND

Predicting protein levels from genotypes for proteome-wide association studies (PWAS) may provide insight into the mechanisms underlying cancer susceptibility.

METHODS

We performed PWAS of breast, endometrial, ovarian, and prostate cancers and their subtypes in several large European-ancestry discovery consortia (effective sample size: 237,483 cases/317,006 controls) and tested the results for replication in an independent European-ancestry GWAS (31,969 cases/410,350 controls). We performed PWAS using the cancer GWAS summary statistics and two sets of plasma protein prediction models, followed by colocalization analysis.

RESULTS

Using Atherosclerosis Risk in Communities (ARIC) models, we identified 93 protein-cancer associations [false discovery rate (FDR) < 0.05]. We then performed a meta-analysis of the discovery and replication PWAS, resulting in 61 significant protein-cancer associations (FDR < 0.05). Ten of 15 protein-cancer pairs that could be tested using Trans-Omics for Precision Medicine (TOPMed) protein prediction models replicated with the same directions of effect in both cancer GWAS (P < 0.05). To further support our results, we applied Bayesian colocalization analysis and found colocalized SNPs for SERPINA3 protein levels and prostate cancer (posterior probability, PP = 0.65) and SNUPN protein levels and breast cancer (PP = 0.62).

CONCLUSIONS

We used PWAS to identify potential biomarkers of hormone-related cancer risk. SNPs in SERPINA3 and SNUPN did not reach genome-wide significance for cancer in the original GWAS, highlighting the power of PWAS for novel locus discovery, with the added advantage of providing directions of protein effect.

IMPACT

PWAS and colocalization are promising methods to identify potential molecular mechanisms underlying complex traits.

Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects

Prostate cancer (PrCa) is the second most common cancer worldwide in males. While strongly warranted, the prediction of mortality risk due to PrCa, especially before its development, is challenging. Here, we address this issue by maximizing the statistical power of genetic data with multi-ancestry meta-analysis and focusing on binding sites of the androgen receptor (AR), which has a critical role in PrCa. Taking advantage of large Japanese samples ever, a multi-ancestry meta-analysis comprising more than 300,000 subjects in total identifies 9 unreported loci including ZFHX3, a tumor suppressor gene, and successfully narrows down the statistically finemapped variants compared to European-only studies, and these variants strongly enrich in AR binding sites. A polygenic risk scores (PRS) analysis restricting to statistically finemapped variants in AR binding sites shows among cancer-free subjects, individuals with a PRS in the top 10% have a strongly higher risk of the future death of PrCa (HR: 5.57, P = 4.2 × 10-10). Our findings demonstrate the potential utility of leveraging large-scale genetic data and advanced analytical methods in predicting the mortality of PrCa.

Prostate Cancer: Genetics, Epigenetics and the Need for Immunological Biomarkers

Epidemiological data highlight prostate cancer as a significant global health issue, with high incidence and substantial impact on patients' quality of life. The prevalence of this disease is associated with various factors, including age, heredity, and race. Recent research in prostate cancer genetics has identified several genetic variants that may be associated with an increased risk of developing the disease. However, despite the significance of these findings, genetic markers for prostate cancer are not currently utilized in clinical practice as reliable indicators of the disease. In addition to genetics, epigenetic alterations also play a crucial role in prostate cancer development. Aberrant DNA methylation, changes in chromatin structure, and microRNA (miRNA) expression are major epigenetic events that influence oncogenesis. Existing markers for prostate cancer, such as prostate-specific antigen (PSA), have limitations in terms of sensitivity and specificity. The cost of testing, follow-up procedures, and treatment for false-positive results and overdiagnosis contributes to the overall healthcare expenditure. Improving the effectiveness of prostate cancer diagnosis and prognosis requires either narrowing the risk group by identifying new genetic factors or enhancing the sensitivity and specificity of existing markers. Immunological biomarkers (both circulating and intra-tumoral), including markers of immune response and immune dysfunction, represent a potentially useful area of research for enhancing the diagnosis and prognosis of prostate cancer. Our review emphasizes the need for developing novel immunological biomarkers to improve the diagnosis, prognosis, and management of prostate cancer. We highlight the most recent achievements in the identification of biomarkers provided by circulating monocytes and tumor-associated macrophages (TAMs). We highlight that monocyte-derived and TAM-derived biomarkers can enable to establish the missing links between genetic predisposition, hormonal metabolism and immune responses in prostate cancer.

Addressing the Challenge of Biomedical Data Inequality: An Artificial Intelligence Perspective

Artificial intelligence (AI) and other data-driven technologies hold great promise to transform healthcare and confer the predictive power essential to precision medicine. However, the existing biomedical data, which are a vital resource and foundation for developing medical AI models, do not reflect the diversity of the human population. The low representation in biomedical data has become a significant health risk for non-European populations, and the growing application of AI opens a new pathway for this health risk to manifest and amplify. Here we review the current status of biomedical data inequality and present a conceptual framework for understanding its impacts on machine learning. We also discuss the recent advances in algorithmic interventions for mitigating health disparities arising from biomedical data inequality. Finally, we briefly discuss the newly identified disparity in data quality among ethnic groups and its potential impacts on machine learning.

Importance of Diversity in Precision Medicine: Generalizability of Genetic Associations Across Ancestry Groups Toward Better Identification of Disease Susceptibility Variants

Genome-wide association studies (GWAS) revolutionized our understanding of common genetic variation and its impact on common human disease and traits. Developed and adopted in the mid-2000s, GWAS led to searchable genotype-phenotype catalogs and genome-wide datasets available for further data mining and analysis for the eventual development of translational applications. The GWAS revolution was swift and specific, including almost exclusively populations of European descent, to the neglect of the majority of the world's genetic diversity. In this narrative review, we recount the GWAS landscape of the early years that established a genotype-phenotype catalog that is now universally understood to be inadequate for a complete understanding of complex human genetics. We then describe approaches taken to augment the genotype-phenotype catalog, including the study populations, collaborative consortia, and study design approaches aimed to generalize and then ultimately discover genome-wide associations in non-European descent populations. The collaborations and data resources established in the efforts to diversify genomic findings undoubtedly provide the foundations of the next chapters of genetic association studies with the advent of budget-friendly whole-genome sequencing.

GATA2 co-opts TGFβ1/SMAD4 oncogenic signaling and inherited variants at 6q22 to modulate prostate cancer progression

BACKGROUND

Aberrant somatic genomic alteration including copy number amplification is a hallmark of cancer genomes. We previously profiled genomic landscapes of prostate cancer (PCa), yet the underlying causal genes with prognostic potential has not been defined. It remains unclear how a somatic genomic event cooperates with inherited germline variants contribute to cancer predisposition and progression.

METHODS

We applied integrated genomic and clinical data, experimental models and bioinformatic analysis to identify GATA2 as a highly prevalent metastasis-associated genomic amplification in PCa. Biological roles of GATA2 in PCa metastasis was determined in vitro and in vivo. Global chromatin co-occupancy and co-regulation of GATA2 and SMAD4 was investigated by coimmunoprecipitation, ChIP-seq and RNA-seq assays. Tumor cellular assays, qRT-PCR, western blot, ChIP, luciferase assays and CRISPR-Cas9 editing methods were performed to mechanistically understand the cooperation of GATA2 with SMAD4 in promoting TGFβ1 and AR signaling and mediating inherited PCa risk and progression.

RESULTS

In this study, by integrated genomics and experimental analysis, we identified GATA2 as a prevalent metastasis-associated genomic amplification to transcriptionally augment its own expression in PCa. Functional experiments demonstrated that GATA2 physically interacted and cooperated with SMAD4 for genome-wide chromatin co-occupancy and co-regulation of PCa genes and metastasis pathways like TGFβ signaling. Mechanistically, GATA2 was cooperative with SMAD4 to enhance TGFβ and AR signaling pathways, and activated the expression of TGFβ1 via directly binding to a distal enhancer of TGFβ1. Strinkingly, GATA2 and SMAD4 globally mediated inherited PCa risk and formed a transcriptional complex with HOXB13 at the PCa risk-associated rs339331/6q22 enhancer, leading to increased expression of the PCa susceptibility gene RFX6.

CONCLUSIONS

Our study prioritizes causal genomic amplification genes with prognostic values in PCa and reveals the pivotal roles of GATA2 in transcriptionally activating the expression of its own and TGFβ1, thereby co-opting to TGFβ1/SMAD4 signaling and RFX6 at 6q22 to modulate PCa predisposition and progression.

Neighbourhood social deprivation and risk of prostate cancer

BACKGROUND

Striking geographic variations in prostate cancer incidence suggest an aetiological role for spatially-distributed factors. We assessed whether neighbourhood social deprivation, which can reflect limited social contacts, unfavourable lifestyle and environmental exposures, is associated with prostate cancer risk.

METHODS

In 2005-2012, we recruited 1931 incident prostate cancer cases and 1994 controls in a case-control study in Montreal, Canada. Lifetime residential addresses were linked to an area-based social deprivation index around recruitment (2006) and about 10 years earlier (1996). Logistic regression estimated adjusted odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

Men residing in areas characterised by greater social deprivation had elevated prostate cancer risks (ORs of 1.54 and 1.60 for recent and past exposures, respectively; highest vs lowest quintiles), independently from area- and individual-level confounders and screening patterns. The increase in risk with recent high social deprivation was particularly elevated for high-grade prostate cancer at diagnosis (OR 1.87, 95% CI 1.32-2.64). Associations were more pronounced for neighbourhoods with higher proportions of separated/divorced or widowed individuals in the past, and with higher percentages of residents living alone recently.

CONCLUSIONS

These novel findings, suggesting that neighbourhood-level social deprivation increases the risk of prostate cancer, point out to potential targeted public health interventions.

ELAC2 is a functional prostate cancer risk allele

Stentenbach and colleagues have unveiled a functional role of a human germline mutation found in the ribonuclease (RNase) Z enzyme, ELAC2, in prostate cancer. Here, we discuss the importance of these findings in enhancing our understanding of how risk variants enable prostate cancer progression and the post-transcriptional mechanisms underlying oncogenesis.

A Systematic Review of Patient Race, Ethnicity, Socioeconomic Status, and Educational Attainment in Prostate Cancer Treatment Randomised Trials-Is the Evidence Base Applicable to the General Patient Population?

Context

Prostate cancer (PC) disproportionately affects men of Black race, and lower educational and socioeconomic status. Guidelines are based on randomised controlled trials (RCTs); however, the representation of different races, educations, and socioeconomic backgrounds in these trials is unclear.

Objective

To assess reporting of equality, diversity, and inclusion characteristics (Equality, Diversity and Inclusion [EDI]) and differences in treatment effects between different races, and educational or socioeconomic status.

Evidence acquisition

We conducted a systematic review of CENTRAL, MEDLINE, and Embase in April 2020 examining RCTs investigating treatments for PC. Outcomes collected were race/ethnicity, educational attainment, and socioeconomic status. RCTs investigating PC treatment in any population or setting were included. Data extraction of characteristics was performed independently by pairs of reviewers and checked by a senior author. The Cochrane risk of bias tool assessed the quality of included papers.

Evidence synthesis

A total of 265 trials were included, and 138 of these were available as full-text articles. Fifty-four trials including 19 039 participants reported any EDI data. All 54 trials reported race, 11 reported ethnicity, three reported educational attainment, and one reported socioeconomic status. Patients of White race were the majority of the recruited population (82.6%), while the minority prevalence was as follows: Black 9.8% and Asian 5.7%. Three studies reported mortality outcomes depending on the participant's race. All three studies investigated different treatments, so a meta-analysis was not performed. No studies reported outcomes stratified by the educational or socioeconomic status of participants.

Conclusions

There is poor reporting of patient race, ethnicity, socioeconomic background, and educational attainment in RCTs for PC treatments between 2010 and 2020. Addressing this for future studies will help explain differences in the incidence of and mortality from PC and improve the generalisability of results.

Patient summary

In this study, we reviewed prostate cancer treatment trials to see whether these reported race, education, and socioeconomic backgrounds of their patient populations. We conclude that reporting of these characteristics is poor. This needs to be improved in future to improve outcomes for patients with prostate cancer of all ethnical, racial, and socioeconomic groups.

Genetic predisposition to metabolically unfavourable adiposity and prostate cancer risk: A Mendelian randomization analysis

BACKGROUND

The associations of adiposity with aggressive prostate cancer risk are unclear. Using two-sample Mendelian randomization, we assessed the association of metabolically unfavourable adiposity (UFA), favourable adiposity (FA) and for comparison body mass index (BMI), with prostate cancer, including aggressive prostate cancer.

METHODS

We examined the association of these genetically predicted adiposity-related traits with risk of prostate cancer overall, aggressive and early onset disease using outcome summary statistics from the PRACTICAL consortium (including 15,167 aggressive cases).

RESULTS

In inverse-variance weighted models, there was little evidence that genetically predicted one standard deviation higher UFA, FA and BMI were associated with aggressive prostate cancer [OR: 0.85 (95% CI:0.61-1.19), 0.80 (0.53-1.23) and 0.97 (0.88-1.08), respectively]; these associations were largely consistent in sensitivity analyses accounting for horizontal pleiotropy. There was no strong evidence that genetically determined UFA, FA or BMI were associated with overall prostate cancer or early age of onset prostate cancer.

CONCLUSIONS

We did not find differences in the associations of UFA and FA with prostate cancer risk, which suggest that adiposity is unlikely to influence prostate cancer via the metabolic factors assessed; however, these did not cover some aspects related to metabolic health that may link obesity with aggressive prostate cancer, which should be explored in future studies.

Equitable machine learning counteracts ancestral bias in precision medicine, improving outcomes for all

Gold standard genomic datasets severely under-represent non-European populations, leading to inequities and a limited understanding of human disease [1-8]. Therapeutics and outcomes remain hidden because we lack insights that we could gain from analyzing ancestry-unbiased genomic data. To address this significant gap, we present PhyloFrame, the first-ever machine learning method for equitable genomic precision medicine. PhyloFrame corrects for ancestral bias by integrating big data tissue-specific functional interaction networks, global population variation data, and disease-relevant transcriptomic data. Application of PhyloFrame to breast, thyroid, and uterine cancers shows marked improvements in predictive power across all ancestries, less model overfitting, and a higher likelihood of identifying known cancer-related genes. The ability to provide accurate predictions for underrepresented groups, in particular, is substantially increased. These results demonstrate how AI can mitigate ancestral bias in training data and contribute to equitable representation in medical research.

Evaluating approaches for constructing polygenic risk scores for prostate cancer in men of African and European ancestry

Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635-0.677) in African and 0.844 (95% CI = 0.840-0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67-2.00) and 2.19 (95% CI = 2.14-2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659-0.700 and AUC = 0.845, 95% CI = 0.841-0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87-2.26 and OR = 2.21, 95% CI = 2.16-2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.

Multi-ancestry meta-analysis and fine-mapping in Alzheimer's disease

Genome-wide association studies (GWAS) of Alzheimer's disease are predominantly carried out in European ancestry individuals despite the known variation in genetic architecture and disease prevalence across global populations. We leveraged published GWAS summary statistics from European, East Asian, and African American populations, and an additional GWAS from a Caribbean Hispanic population using previously reported genotype data to perform the largest multi-ancestry GWAS meta-analysis of Alzheimer's disease and related dementias to date. This method allowed us to identify two independent novel disease-associated loci on chromosome 3. We also leveraged diverse haplotype structures to fine-map nine loci with a posterior probability >0.8 and globally assessed the heterogeneity of known risk factors across populations. Additionally, we compared the generalizability of multi-ancestry- and single-ancestry-derived polygenic risk scores in a three-way admixed Colombian population. Our findings highlight the importance of multi-ancestry representation in uncovering and understanding putative factors that contribute to risk of Alzheimer's disease and related dementias.

Disparities and Trends in Genitourinary Cancer Incidence and Mortality in the USA

BACKGROUND

Previous studies have reported on incidence and mortality patterns for individual genitourinary cancers in the USA. However, these studies addressed individual cancer types rather than genitourinary cancers overall.

OBJECTIVE

To comprehensively examine disparities and trends in the incidence and mortality for the four major genitourinary cancers (bladder, kidney, prostate, and testis) in the USA.

DESIGN, SETTING, AND PARTICIPANTS

We obtained incidence data from the National Cancer Institute 22-registry Surveillance, Epidemiology and End Results (SEER) database and the US Cancer Statistics database (Centers for Disease Control and Prevention) and mortality data from the National Center for Health Statistics to examine cross-sectional and temporal trends in incidence and death rates stratified by sex, race/ethnicity, and county.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Age-adjusted incidence and death rates were calculated using SEER*Stat software. Temporal trends were analyzed using Joinpoint regression for a two-sided significance level of p < 0.05.

RESULTS AND LIMITATIONS

Incidence and mortality rates for bladder and kidney cancers were two to four times higher for men than for women. Among non-Hispanic White individuals, the highest incidence rates were found in the Northeast for bladder cancer and in Appalachia for kidney cancer, whereas the highest death rates for prostate cancer were found in the West. Incidence rates increased for cancers of the kidney and testis and for advanced-stage prostate cancer in almost all racial/ethnic populations and for bladder cancer in the American Indian/Alaska Native population. Death rates increased for testicular cancer in the Hispanic population and stabilized for prostate cancer among White and Asian American/Pacific Islander men after a steady decline since the early 1990s. Study limitations include misclassification of race/ethnicity on medical records and death certificates.

CONCLUSIONS

We found persistent sociodemographic disparities and unfavorable trends in incidence or mortality for all four major genitourinary cancers. Future studies should elucidate the reasons for these patterns.

PATIENT SUMMARY

In the USA, rates of cancer cases are increasing for kidney, testis, and advanced-stage prostate cancers in the overall population, and for bladder cancer in the American Indian/Alaska Native population. Differences in the rates by sex and race/ethnicity remain.

Alterations in the Epigenetic Machinery Associated with Prostate Cancer Health Disparities

Prostate cancer is driven by acquired genetic alterations, including those impacting the epigenetic machinery. With African ancestry as a significant risk factor for aggressive disease, we hypothesize that dysregulation among the roughly 656 epigenetic genes may contribute to prostate cancer health disparities. Investigating prostate tumor genomic data from 109 men of southern African and 56 men of European Australian ancestry, we found that African-derived tumors present with a longer tail of epigenetic driver gene candidates (72 versus 10). Biased towards African-specific drivers (63 versus 9 shared), many are novel to prostate cancer (18/63), including several putative therapeutic targets (CHD7, DPF3, POLR1B, SETD1B, UBTF, and VPS72). Through clustering of all variant types and copy number alterations, we describe two epigenetic PCa taxonomies capable of differentiating patients by ancestry and predicted clinical outcomes. We identified the top genes in African- and European-derived tumors representing a multifunctional "generic machinery", the alteration of which may be instrumental in epigenetic dysregulation and prostate tumorigenesis. In conclusion, numerous somatic alterations in the epigenetic machinery drive prostate carcinogenesis, but African-derived tumors appear to achieve this state with greater diversity among such alterations. The greater novelty observed in African-derived tumors illustrates the significant clinical benefit to be derived from a much needed African-tailored approach to prostate cancer healthcare aimed at reducing prostate cancer health disparities.

A prospective nested case-control study of serum concentrations of per- and polyfluoroalkyl substances and aggressive prostate cancer risk

Per- and polyfluoroalkyl substances (PFAS) are environmentally persistent organic pollutants detectable in the serum of most U.S. adults. Some studies of highly-exposed individuals have suggested an association between PFAS and prostate cancer, but evidence from population-based studies is limited. We investigated the association between pre-diagnostic serum PFAS concentrations and aggressive prostate cancer risk in a large prospective study. We measured pre-diagnostic serum concentrations of eight PFAS, including perfluorooctanoate (PFOA), for 750 aggressive prostate cancer cases and 750 individually matched controls within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. We assessed the reproducibility of PFAS concentrations in serial samples collected up to six years apart among 60 controls using intraclass correlation coefficients (ICCs). Conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association with prostate cancer, adjusting for other PFAS and potential confounders. Concentrations of most PFAS were consistent (ICC>0.7) across the serial samples over time. We observed an inverse association between PFOA and aggressive prostate cancer (ORcontinuous = 0.79, 95% CI = 0.63, 0.99), but the association was limited to cases diagnosed ≤3 years after blood collection and became statistically non-significant for cases diagnosed with later follow-up (>3 years, ORcontinuous = 0.90, 95% CI = 0.79, 1.03). Other PFAS were not associated with aggressive prostate cancer risk. Although we cannot rule out an increased risk at higher levels, our findings from a population with PFAS serum concentrations comparable to the general population do not support an association with increased risk of aggressive prostate cancer.

Evidence of Novel Susceptibility Variants for Prostate Cancer and a Multiancestry Polygenic Risk Score Associated with Aggressive Disease in Men of African Ancestry

BACKGROUND

Genetic factors play an important role in prostate cancer (PCa) susceptibility.

OBJECTIVE

To discover common genetic variants contributing to the risk of PCa in men of African ancestry.

DESIGN, SETTING, AND PARTICIPANTS

We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Common genotyped and imputed variants were tested for their association with PCa risk. Novel susceptibility loci were identified and incorporated into a multiancestry polygenic risk score (PRS). The PRS was evaluated for associations with PCa risk and disease aggressiveness.

RESULTS AND LIMITATIONS

Nine novel susceptibility loci for PCa were identified, of which seven were only found or substantially more common in men of African ancestry, including an African-specific stop-gain variant in the prostate-specific gene anoctamin 7 (ANO7). A multiancestry PRS of 278 risk variants conferred strong associations with PCa risk in African ancestry studies (odds ratios [ORs] >3 and >5 for men in the top PRS decile and percentile, respectively). More importantly, compared with men in the 40-60% PRS category, men in the top PRS decile had a significantly higher risk of aggressive PCa (OR = 1.23, 95% confidence interval = 1.10-1.38, p = 4.4 × 10-4).

CONCLUSIONS

This study demonstrates the importance of large-scale genetic studies in men of African ancestry for a better understanding of PCa susceptibility in this high-risk population and suggests a potential clinical utility of PRS in differentiating between the risks of developing aggressive and nonaggressive disease in men of African ancestry.

PATIENT SUMMARY

In this large genetic study in men of African ancestry, we discovered nine novel prostate cancer (PCa) risk variants. We also showed that a multiancestry polygenic risk score was effective in stratifying PCa risk, and was able to differentiate risk of aggressive and nonaggressive disease.

Agent Orange exposure and prostate cancer risk in the Million Veteran Program

Purpose

Exposure to Agent Orange, a known carcinogen, might increase risk of prostate cancer (PCa). We sought to investigate the association of Agent Orange exposure and PCa risk when accounting for race/ethnicity, family history, and genetic risk in a diverse population of US Vietnam War veterans.

Methods & Materials

This study utilized the Million Veteran Program (MVP), a national, population-based cohort study of United States military veterans conducted 2011-2021 with 590,750 male participants available for analysis. Agent Orange exposure was obtained using records from the Department of Veterans Affairs (VA) using the US government definition of Agent Orange exposure: active service in Vietnam while Agent Orange was in use. Only veterans who were on active duty (anywhere in the world) during the Vietnam War were included in this analysis (211,180 participants). Genetic risk was assessed via a previously validated polygenic hazard score calculated from genotype data. Age at diagnosis of any PCa, diagnosis of metastatic PCa, and death from PCa were assessed via Cox proportional hazards models.

Results

Exposure to Agent Orange was associated with increased PCa diagnosis (HR 1.04, 95% CI 1.01-1.06, p=0.003), primarily among Non-Hispanic White men (HR 1.09, 95% CI 1.06- 1.12, p<0.001). When accounting for race/ethnicity and family history, Agent Orange exposure remained an independent risk factor for PCa diagnosis (HR 1.06, 95% CI 1.04-1.09, p<0.05). Univariable associations of Agent Orange exposure with PCa metastasis (HR 1.08, 95% CI 0.99-1.17) and PCa death (HR 1.02, 95% CI 0.84-1.22) did not reach significance on multivariable analysis. Similar results were found when accounting for polygenic hazard score.

Conclusions

Among US Vietnam War veterans, Agent Orange exposure is an independent risk factor for PCa diagnosis, though associations with PCa metastasis or death are unclear when accounting for race/ethnicity, family history, and/or polygenic risk.

Evaluating significance of European-associated index SNPs in the East Asian population for 31 complex phenotypes

BACKGROUND

Genome-wide association studies (GWASs) have identified many single-nucleotide polymorphisms (SNPs) associated with complex phenotypes in the European (EUR) population; however, the extent to which EUR-associated SNPs can be generalized to other populations such as East Asian (EAS) is not clear.

RESULTS

By leveraging summary statistics of 31 phenotypes in the EUR and EAS populations, we first evaluated the difference in heritability between the two populations and calculated the trans-ethnic genetic correlation. We observed the heritability estimates of some phenotypes varied substantially across populations and 53.3% of trans-ethnic genetic correlations were significantly smaller than one. Next, we examined whether EUR-associated SNPs of these phenotypes could be identified in EAS using the trans-ethnic false discovery rate method while accounting for winner's curse for SNP effect in EUR and difference of sample sizes in EAS. We found on average 54.5% of EUR-associated SNPs were also significant in EAS. Furthermore, we discovered non-significant SNPs had higher effect heterogeneity, and significant SNPs showed more consistent linkage disequilibrium and allele frequency patterns between the two populations. We also demonstrated non-significant SNPs were more likely to undergo natural selection.

CONCLUSIONS

Our study revealed the extent to which EUR-associated SNPs could be significant in the EAS population and offered deep insights into the similarity and diversity of genetic architectures underlying phenotypes in distinct ancestral groups.

Deregulated microRNAs Involved in Prostate Cancer Aggressiveness and Treatment Resistance Mechanisms

Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer deaths among American men. Complex genetic and epigenetic mechanisms are involved in the development and progression of PCa. MicroRNAs (miRNAs) are short noncoding RNAs that regulate protein expression at the post-transcriptional level by targeting mRNAs for degradation or inhibiting protein translation. In the past two decades, the field of miRNA research has rapidly expanded, and emerging evidence has revealed miRNA dysfunction to be an important epigenetic mechanism underlying a wide range of diseases, including cancers. This review article focuses on understanding the functional roles and molecular mechanisms of deregulated miRNAs in PCa aggressiveness and drug resistance based on the existing literature. Specifically, the miRNAs differentially expressed (upregulated or downregulated) in PCa vs. normal tissues, advanced vs. low-grade PCa, and treatment-responsive vs. non-responsive PCa are discussed. In particular, the oncogenic and tumor-suppressive miRNAs involved in the regulation of (1) the synthesis of the androgen receptor (AR) and its AR-V7 splice variant, (2) PTEN expression and PTEN-mediated signaling, (3) RNA splicing mechanisms, (4) chemo- and hormone-therapy resistance, and (5) racial disparities in PCa are discussed and summarized. We further provide an overview of the current advances and challenges of miRNA-based biomarkers and therapeutics in clinical practice for PCa diagnosis/prognosis and treatment.

Genetically adjusted PSA levels for prostate cancer screening

Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. Accounting for genetic determinants of constitutive, non-cancer-related PSA variation has potential to improve screening utility. In this study, we discovered 128 genome-wide significant associations (P < 5 × 10-8) in a multi-ancestry meta-analysis of 95,768 men and developed a PSA polygenic score (PGSPSA) that explains 9.61% of constitutive PSA variation. We found that, in men of European ancestry, using PGS-adjusted PSA would avoid up to 31% of negative prostate biopsies but also result in 12% fewer biopsies in patients with prostate cancer, mostly with Gleason score <7 tumors. Genetically adjusted PSA was more predictive of aggressive prostate cancer (odds ratio (OR) = 3.44, P = 6.2 × 10-14, area under the curve (AUC) = 0.755) than unadjusted PSA (OR = 3.31, P = 1.1 × 10-12, AUC = 0.738) in 106 cases and 23,667 controls. Compared to a prostate cancer PGS alone (AUC = 0.712), including genetically adjusted PSA improved detection of aggressive disease (AUC = 0.786, P = 7.2 × 10-4). Our findings highlight the potential utility of incorporating PGS for personalized biomarkers in prostate cancer screening.

The PANcreatic Disease ReseArch (PANDoRA) consortium: Ten years' experience of association studies to understand the genetic architecture of pancreatic cancer

Pancreatic cancer has an incidence that almost matches its mortality. Only a small number of risk factors and 33 susceptibility loci have been identified. so Moreover, the relative rarity of pancreatic cancer poses significant hurdles for research aimed at increasing our knowledge of the genetic mechanisms contributing to the disease. Additionally, the inability to adequately power research questions prevents small monocentric studies from being successful. Several consortia have been established to pursue a better understanding of the genetic architecture of pancreatic cancers. The Pancreatic disease research (PANDoRA) consortium is the largest in Europe. PANDoRA is spread across 12 European countries, Brazil and Japan, bringing together 29 basic and clinical research groups. In the last ten years, PANDoRA has contributed to the discovery of 25 susceptibility loci, a feat that will be instrumental in stratifying the population by risk and optimizing preventive strategies.

Genetics of skeletal proportions in two different populations

Human height can be divided into sitting height and leg length, reflecting growth of different parts of the skeleton whose relative proportions are captured by the ratio of sitting to total height (as sitting height ratio, SHR). Height is a highly heritable trait, and its genetic basis has been well-studied. However, the genetic determinants of skeletal proportion are much less well-characterized. Expanding substantially on past work, we performed a genome-wide association study (GWAS) of SHR in ∼450,000 individuals with European ancestry and ∼100,000 individuals with East Asian ancestry from the UK and China Kadoorie Biobanks. We identified 565 loci independently associated with SHR, including all genomic regions implicated in prior GWAS in these ancestries. While SHR loci largely overlap height-associated loci (P < 0.001), the fine-mapped SHR signals were often distinct from height. We additionally used fine-mapped signals to identify 36 credible sets with heterogeneous effects across ancestries. Lastly, we used SHR, sitting height, and leg length to identify genetic variation acting on specific body regions rather than on overall human height.

Evaluating Approaches for Constructing Polygenic Risk Scores for Prostate Cancer in Men of African and European Ancestry

Genome-wide polygenic risk scores (GW-PRS) have been reported to have better predictive ability than PRS based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer risk variants from multi-ancestry GWAS and fine-mapping studies (PRS 269 ). GW-PRS models were trained using a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls used to develop the multi-ancestry PRS 269 . Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California/Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI=0.635-0.677) in African and 0.844 (95% CI=0.840-0.848) in European ancestry men and corresponding prostate cancer OR of 1.83 (95% CI=1.67-2.00) and 2.19 (95% CI=2.14-2.25), respectively, for each SD unit increase in the GW-PRS. However, compared to the GW-PRS, in African and European ancestry men, the PRS 269 had larger or similar AUCs (AUC=0.679, 95% CI=0.659-0.700 and AUC=0.845, 95% CI=0.841-0.849, respectively) and comparable prostate cancer OR (OR=2.05, 95% CI=1.87-2.26 and OR=2.21, 95% CI=2.16-2.26, respectively). Findings were similar in the validation data. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the multi-ancestry PRS 269 constructed with fine-mapping.

Germline modifiers of the tumor immune microenvironment implicate drivers of cancer risk and immunotherapy response

With the continued promise of immunotherapy for treating cancer, understanding how host genetics contributes to the tumor immune microenvironment (TIME) is essential to tailoring cancer screening and treatment strategies. Here, we study 1084 eQTLs affecting the TIME found through analysis of The Cancer Genome Atlas and literature curation. These TIME eQTLs are enriched in areas of active transcription, and associate with gene expression in specific immune cell subsets, such as macrophages and dendritic cells. Polygenic score models built with TIME eQTLs reproducibly stratify cancer risk, survival and immune checkpoint blockade (ICB) response across independent cohorts. To assess whether an eQTL-informed approach could reveal potential cancer immunotherapy targets, we inhibit CTSS, a gene implicated by cancer risk and ICB response-associated polygenic models; CTSS inhibition results in slowed tumor growth and extended survival in vivo. These results validate the potential of integrating germline variation and TIME characteristics for uncovering potential targets for immunotherapy.

Association of TP53 Single Nucleotide Polymorphisms with Prostate Cancer in a Racially Diverse Cohort of Men

Growing evidence indicates the involvement of a genetic component in prostate cancer (CaP) susceptibility and clinical severity. Studies have reported the role of germline mutations and single nucleotide polymorphisms (SNPs) of TP53 as possible risk factors for cancer development. In this single institutional retrospective study, we identified common SNPs in the TP53 gene in AA and CA men and performed association analyses for functional TP53 SNPs with the clinico-pathological features of CaP. The SNP genotyping analysis of the final cohort of 308 men (212 AA; 95 CA) identified 74 SNPs in the TP53 region, with a minor allele frequency (MAF) of at least 1%. Two SNPs were non-synonymous in the exonic region of TP53: rs1800371 (Pro47Ser) and rs1042522 (Arg72Pro). The Pro47Ser variant had an MAF of 0.01 in AA but was not detected in CA. Arg72Pro was the most common SNP, with an MAF of 0.50 (0.41 in AA; 0.68 in CA). Arg72Pro was associated with a shorter time to biochemical recurrence (BCR) (p = 0.046; HR = 1.52). The study demonstrated ancestral differences in the allele frequencies of the TP53 Arg72Pro and Pro47Ser SNPs, providing a valuable framework for evaluating CaP disparities among AA and CA men.

Genetic Polymorphisms of the Telomerase Reverse Transcriptase Gene in Relation to Prostate Tumorigenesis, Aggressiveness and Mortality: A Cross-Ancestry Analysis

BACKGROUND

Telomerase reverse transcriptase (TERT) has been consistently associated with prostate cancer (PCa) risk. However, few studies have explored the association between TERT variants and PCa aggressiveness.

METHODS

Individual and genetic data were obtained from UK Biobank and a Chinese PCa cohort (Chinese Consortium for Prostate Cancer Genetics).

RESULTS

A total of 209,694 Europeans (14,550 PCa cases/195,144 controls) and 8873 Chinese (4438 cases/4435 controls) were involved. Nineteen susceptibility loci with five novel ones (rs144704378, rs35311994, rs34194491, rs144020096, and rs7710703) were detected in Europeans, whereas seven loci with two novel ones (rs7710703 and rs11291391) were discovered in the Chinese cohort. The index SNP for the two ancestries was rs2242652 (odds ratio [OR] = 1.16, 95% confidence interval [CI]:1.12-1.20, p = 4.12 × 10^-16) and rs11291391 (OR = 1.73, 95%CI:1.34-2.25, p = 3.04 × 10^-5), respectively. SNPs rs2736100 (OR = 1.49, 95%CI:1.31-1.71, p = 2.91 × 10^-9) and rs2853677 (OR = 1.74, 95%CI:1.52-1.98, p = 3.52 × 10^-16) were found significantly associated with aggressive PCa, while rs35812074 was marginally related to PCa death (hazard ratio [HR] = 1.61, 95%CI:1.04-2.49, p = 0.034). Gene-based analysis showed a significant association of TERT with PCa (European: p = 3.66 × 10^-15, Chinese: p = 0.043) and PCa severity (p = 0.006) but not with PCa death (p = 0.171).

CONCLUSION

TERT polymorphisms were associated with prostate tumorigenesis and severity, and the genetic architectures of PCa susceptibility loci were heterogeneous among distinct ancestries.

Genetic and Genomic Testing for Prostate Cancer: Beyond DNA Repair

Significant progress has been made in genetic and genomic testing for prostate cancer across the disease spectrum. Molecular profiling is increasingly relevant for routine clinical management, fueled in part by advancements in testing technology and integration of biomarkers into clinical trials. In metastatic prostate cancer, defects in DNA damage response genes are now established predictors of benefit to US Food and Drug Administration-approved poly (ADP-ribose) polymerase inhibitors and immune checkpoint inhibitors, and trials are actively investigating these and other targeted treatment strategies in earlier disease states. Excitingly, opportunities for molecularly informed management beyond DNA damage response genes are also maturing. Germline genetic variants (eg, BRCA2 or MSH2/6) and polygenic germline risk scores are being investigated to inform cancer screening and active surveillance in at-risk carriers. RNA expression tests have recently gained traction in localized prostate cancer, enabling patient risk stratification and tailored treatment intensification via radiotherapy and/or androgen deprivation therapy for localized or salvage treatment. Finally, emerging minimally invasive circulating tumor DNA technology promises to enhance biomarker testing in advanced disease pending additional methodological and clinical validation. Collectively, genetic and genomic tests are rapidly becoming indispensable tools for informing the optimal clinical management of prostate cancer.

A polygenic two-hit hypothesis for prostate cancer

Prostate cancer is one of the most heritable cancers. Hundreds of germline polymorphisms have been linked to prostate cancer diagnosis and prognosis. Polygenic risk scores can predict genetic risk of a prostate cancer diagnosis. Although these scores inform the probability of developing a tumor, it remains unknown how germline risk influences the tumor molecular evolution. We cultivated a cohort of 1250 localized European-descent patients with germline and somatic DNA profiling. Men of European descent with higher genetic risk were diagnosed earlier and had less genomic instability and fewer driver genes mutated. Higher genetic risk was associated with better outcome. These data imply a polygenic "two-hit" model where germline risk reduces the number of somatic alterations required for tumorigenesis. These findings support further clinical studies of polygenic risk scores as inexpensive and minimally invasive adjuncts to standard risk stratification. Further studies are required to interrogate generalizability to more ancestrally and clinically diverse populations.

Research Silos in Cancer Disparities: Obstacles to Improving Clinical Outcomes for Underserved Patient Populations

Despite much vaunted progress in cancer therapeutics and diagnostics, outcomes for many groups of non-White patients with cancer remain worse than those for their White compatriots. One reason for this is the lack of inclusion and representation of non-White patients in clinical trials, preclinical datasets, and among researchers, a shortfall that is gaining wide recognition within the cancer research community and the lay public. Several reviews and editorials have commented on the negative impacts of the status quo on progress in cancer research toward medical breakthroughs that help all communities and not just White patients with cancer. In this perspective, we describe the existence of research silos focused either on the impact of socioeconomic factors proceeding from systemic racism on cancer outcomes, or on genetic ancestry as it affects the molecular biology of cancer developing in specific patient populations. While both these research areas are critical for progress toward precision medicine equity, breaking down these silos will help us gain an integrated understanding of how race and racism impact cancer development, progression, and patient outcomes. Bringing this comprehensive approach to cancer disparities research will undoubtedly improve our overall understanding of how stress and environmental factors affect the molecular biology of cancer, which will lead to the development of new diagnostics and therapeutics that are applicable across cancer patient demographics.

Association of rare, recurrent nonsynonymous variants in the germline of prostate cancer patients of African ancestry

BACKGROUND

Although men of African ancestry (AA) have the highest mortality rate from prostate cancer (PCa), relatively little is known about the germline variants that are associated with PCa risk in AA men. The goal of this study is to systematically evaluate rare, recurrent nonsynonymous variants across the exome for their association with PCa in AA men.

METHODS

Whole exome sequencing (WES) of germline DNA in two AA PCa patient cohorts of Johns Hopkins Hospital (N = 960) and Wayne State University (N = 747) was performed. All nonsynonymous variants present in both case cohorts, with a carrier rate between 0.5% and 1%, were identified. Their carrier rates were compared with rates from 8128 African/African American (AFR) control subjects from The Genome Aggregation Database (gnomAD) using Fisher's exact test. Significant variants, defined as false discovery rate (FDR) adjusted p-value ≤ 0.05, were further evaluated in AA PCa cases (N = 132) and controls (N = 1184) from the UK Biobank (UKB).

RESULTS

Two variants reached a pre-specified statistical significance level. The first was p.R14Q in GPRC5C (found in 0.47% of PCa cases and 0.01% of population controls); odds ratio (OR) for PCa was 37.46 (95% confidence interval CI 4.68-299.72), p_exact  = 7.01E-06, FDR-adjusted p-value = 0.05. The second was p.R511Q in IGF1R (found in 0.53% of PCa cases and 0.01% of population controls); OR for PCa was 21.54 (95%CI 4.65-99.76), p_exact  = 5.51E-06, FDR-adjusted p-value = 0.05. The mean percentage of African ancestry was similar between variant carriers and noncarriers of each variant, p > 0.05. In the UKB AA men, GPRC5C R14Q was 0.76% and 0.08% in cases and controls, respectively, OR for PCa was 9.00 (95%CI 0.56-145.23), p_exact  = 0.19. However, IGF1R R511Q was not found in cases or controls.

CONCLUSIONS

This WES study identified two rare, recurrent nonsynonymous PCa risk-associated variants in AA. Confirmation in additional large populations of AA PCa cases and controls is required.

A Healthy Lifestyle in Men at Increased Genetic Risk for Prostate Cancer

BACKGROUND

Prostate cancer is the most heritable cancer. There is a need to identify possible modifiable factors for men at an increased risk of prostate cancer due to genetic factors.

OBJECTIVE

To examine whether men at an increased genetic risk of prostate cancer can offset their risk of disease or disease progression by adhering to a healthy lifestyle.

DESIGN, SETTING, AND PARTICIPANTS

We prospectively followed 12 411 genotyped men in the Health Professionals Follow-up Study (1993-2019) and the Physicians' Health Study (1983-2010). Genetic risk of prostate cancer was quantified using a polygenic risk score (PRS). A healthy lifestyle was defined by healthy weight, vigorous physical activity, not smoking, and a healthy diet.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Overall and lethal prostate cancer events (metastatic disease/prostate cancer-specific death) were analyzed using time-to-event analyses estimating hazard ratios (HRs) and lifetime risks.

RESULTS AND LIMITATIONS

During 27 yr of follow-up, 3005 overall prostate cancer and 435 lethal prostate cancer events were observed. The PRS enabled risk stratification not only for overall prostate cancer, but also for lethal disease with a four-fold difference between men in the highest and lowest quartiles (HR, 4.32; 95% confidence interval [CI], 3.16-5.89). Among men in the highest PRS quartile, adhering to a healthy lifestyle was associated with a decreased rate of lethal prostate cancer (HR, 0.55; 95% CI, 0.36-0.86) compared with having an unhealthy lifestyle, translating to a lifetime risk of 1.6% (95% CI, 0.8-3.1%) among the healthy and 5.3% (95% CI, 3.6-7.8%) among the unhealthy. Adhering to a healthy lifestyle was not associated with a decreased risk of overall prostate cancer.

CONCLUSIONS

Our findings suggest that a genetic predisposition for prostate cancer is not deterministic for a poor cancer outcome. Maintaining a healthy lifestyle may provide a way to offset the genetic risk of lethal prostate cancer.

PATIENT SUMMARY

This study examined whether the genetic risk of prostate cancer can be attenuated by a healthy lifestyle including a healthy weight, regular exercise, not smoking, and a healthy diet. We observed that adherence to a healthy lifestyle reduced the risk of metastatic disease and prostate cancer death among men at the highest genetic risk. We conclude that men at a high genetic risk of prostate cancer may benefit from adhering to a healthy lifestyle.

Primary care physician use of patient race and polygenic risk scores in medical decision-making

PURPOSE

The use of patient race in medicine is controversial for its potential either to exacerbate or address health disparities. Polygenic risk scores (PRSs) have emerged as a tool for risk stratification models used in preventive medicine. We examined whether PRS results affect primary care physician (PCP) medical decision-making and whether that effect varies by patient race.

METHODS

Using an online survey with a randomized experimental design among PCPs in a national database, we ascertained decision-making around atherosclerotic cardiovascular disease prevention and prostate cancer screening for case scenario patients who were clinically identical except for randomized reported race.

RESULTS

Across 369 PCPs (email open rate = 10.8%, partial completion rate = 93.7%), recommendations varied with PRS results in expected directions (low-risk results, no available PRS results, and high-risk results). Still, physicians randomized to scenarios with Black patients were more likely to recommend statin therapy than those randomized to scenarios with White patients (odds ratio = 1.74, 95% CI = 1.16-2.59, P = .007) despite otherwise identical clinical profiles and independent of PRS results. Similarly, physicians were more likely to recommend prostate cancer screening for Black patients than for White patients (odds ratio = 1.58, 95% CI = 1.06-2.35, P = .025) despite otherwise identical clinical and genetic profiles.

CONCLUSION

Despite advances in precision risk stratification, physicians will likely continue to use patient race implicitly or explicitly in medical decision-making.

A Polygenic Risk Score for Prostate Cancer Risk Prediction

This retrospective cohort study compares 2 risk calculator systems that compute the probabilities of finding high-grade or any cancer on biopsy results in men undergoing a first prostate biopsy.

Association between serum uric acid and prostate cancer risk in East Asian populations: a Mendelian randomization study

PURPOSE

Previous observational studies showed that serum uric acid (SUA) was associated with prostate cancer, but the causal relationship is unclear. This study aimed to explore the potential causal association between SUA and prostate cancer risk using Mendelian randomization (MR) analyses in the East Asian populations.

METHODS

Publicly available summary-level genome-wide association studies (GWAS) data on SUA were obtained from a genome-wide meta-analysis of three Japanese cohorts (121,745 subjects). The GWAS data on prostate cancer were derived from Biobank Japan (109,347 subjects with 5,408 cases and 103,939 controls). A total of 34 SUA-related single-nucleotide polymorphisms (SNPs) (P value < 5 × 10^-8) were identified as instrumental variables. The inverse variance weighted method was used as the primary method to compute the odds ratios (ORs) and 95% confidence intervals (95% CIs) for per standard deviation increase in SUA. MR Egger, weighted median, and weighted mode were also applied to test the robustness of the results.

RESULTS

Genetically predicted SUA was positively associated with prostate cancer risk using inverse variance weighted (OR = 1.12; 95% CI 1.00-1.26; P = 0.043). The positive association was robust when MR Egger (OR = 1.16; 95% CI 1.01-1.34; P = 0.048), weighted median (OR = 1.18; 95% CI 1.03-1.36; P = 0.018), and weighted mode (OR = 1.14; 95% CI 1.01-1.29; P = 0.041) were used.

CONCLUSION

There were potential causal associations between higher genetically predicted SUA levels and increased prostate cancer risk. Further, MR studies with more valid SNPs and more cancer cases are needed. Validation of the findings is also recommended.

An approach to genetic testing in patients with metastatic castration-resistant prostate cancer in Singapore

Introduction

There has been a rapid evolution in the treatment strategies for metastatic castration-resistant prostate cancer (mCRPC) following the identification of targetable mutations, making genetic testing essential for patient selection. Although several international guidelines recommend genetic testing for patients with mCRPC, there is a lack of locally endorsed clinical practice guidelines in Singapore.

Method

A multidisciplinary specialist panel with representation from medical and radiation oncology, urology, pathology, interventional radiology, and medical genetics discussed the challenges associated with patient selection, genetic counselling and sample processing in mCRPC.

Results

A clinical model for incorporating genetic testing into routine clinical practice in Singapore was formulated. Tumour testing with an assay that is able to detect both somatic and germline mutations should be utilised. The panel also recommended the "mainstreaming" approach for genetic counselling in which pre-test counselling is conducted by the managing clinician and post-test discussion with a genetic counsellor, to alleviate the bottlenecks at genetic counselling stage in Singapore. The need for training of clinicians to provide pre-test genetic counselling and educating the laboratory personnel for appropriate sample processing that facilitates downstream genetic testing was recognised. Molecular tumour boards and multidisciplinary discussions are recommended to guide therapeutic decisions in mCRPC. The panel also highlighted the issue of reimbursement for genetic testing to reduce patient-borne costs and increase the reach of genetic testing among this patient population.

Conclusion

This article aims to provide strategic and implementable recommendations to overcome the challenges in genetic testing for patients with mCRPC in Singapore.

Biochemical activity induced by a germline variation in KLK3 (PSA) associates with cellular function and clinical outcome in prostate cancer

Genetic variation at the 19q13.3 KLK locus is linked with prostate cancer susceptibility. The non-synonymous KLK3 SNP, rs17632542 (c.536T>C; Ile163Thr-substitution in PSA) is associated with reduced prostate cancer risk, however, the functional relevance is unknown. Here, we identify that the SNP variant-induced change in PSA biochemical activity as a previously undescribed function mediating prostate cancer pathogenesis. The 'Thr' PSA variant led to small subcutaneous tumours, supporting reduced prostate cancer risk. However, 'Thr' PSA also displayed higher metastatic potential with pronounced osteolytic activity in an experimental metastasis in-vivo model. Biochemical characterization of this PSA variant demonstrated markedly reduced proteolytic activity that correlated with differences in in-vivo tumour burden. The SNP is associated with increased risk for aggressive disease and prostate cancer-specific mortality in three independent cohorts, highlighting its critical function in mediating metastasis. Carriers of this SNP allele had reduced serum total PSA and a higher free/total PSA ratio that could contribute to late biopsy decisions and delay in diagnosis. Our results provide a molecular explanation for the prominent 19q13.3 KLK locus, rs17632542 SNP, association with a spectrum of prostate cancer clinical outcomes.

Genetic Risk Prediction for Prostate Cancer: Implications for Early Detection and Prevention

CONTEXT

Prostate cancer (PCa) is a leading cause of death and partially heritable. Genetic risk prediction might be useful for strategies to reduce PCa mortality through early detection and prevention.

OBJECTIVE

To review evidence for genetic risk prediction for PCa.

EVIDENCE ACQUISITION

A collaborative literature review was conducted using PubMed and Google Scholar. Search terms included genetic, risk, prediction, and "prostate cancer". Articles addressing screening, early detection, or prevention were prioritized, as were studies involving diverse populations.

EVIDENCE SYNTHESIS

Rare pathogenic mutations (RPMs), especially in DNA damage repair genes, increase PCa risk. RPMs in BRCA2 are most clearly deleterious, conferring 2-8.6 times higher risk of PCa and a higher risk of aggressive disease. Common genetic variants can be combined into genetic risk scores (GRSs). A high GRS (top 20-25% of the population) confers two to three times higher risk of PCa than average; a very high GRS (top 1-5%) confers six to eight times higher risk. GRSs are not specific for aggressive PCa, possibly due to methodological limitations and/or a field effect of an elevated risk for both low- and high-grade PCa. It is challenging to disentangle genetics from structural racism and social determinants of health to understand PCa racial disparities. GRSs are independently associated with a lethal PCa risk after accounting for family history and race/ancestry. Healthy lifestyle might partially mitigate the risk of lethal PCa.

CONCLUSIONS

Genetic risk assessment is becoming more common; implementation studies are needed to understand the implications and to avoid exacerbating healthcare disparities. Men with a high genetic risk of PCa can reasonably be encouraged to adhere to a healthy lifestyle.

PATIENT SUMMARY

Prostate cancer risk is inherited through rare mutations and through the combination of hundreds of common genetic markers. Some men with a high genetic risk (especially BRCA2 mutations) likely benefit from early screening for prostate cancer. The risk of lethal prostate cancer can be reduced through a healthy lifestyle.

Family History of Prostate Cancer and Survival Outcomes in the UK Genetic Prostate Cancer Study

BACKGROUND

A family history (FH) of prostate cancer (PrCa) is associated with an increased likelihood of PrCa diagnosis. Conflicting evidence exists regarding familial PrCa and clinical outcomes among PrCa patients, including all-cause mortality/overall survival (OS), PrCa-specific survival (PCSS), aggressive histology, and stage at diagnosis.

OBJECTIVE

To determine how the number, degree, and age of a PrCa patient's affected relatives are associated with OS and PCSS of those already diagnosed with PrCa.

DESIGN, SETTING, AND PARTICIPANTS

The UK Genetic Prostate Cancer Study is a longitudinal, multi-institutional, observational study collecting baseline and follow-up clinical data since 1992. We examined OS and PCSS in 16340 men by degree and number of relatives with prostate and genetically related cancers (breast, ovarian, and colorectal).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary outcome was all-cause mortality among PrCa patients. The risk of death with respect to FH was assessed by calculating hazard ratios from Cox proportional hazard regression models, adjusting for relevant factors.

RESULTS AND LIMITATIONS

A stronger FH was inversely associated with the risk of all-cause and PrCa-specific mortality. This association was greater in those with an increasing number (p-trend < 0.001) and increasing closeness (p-trend < 0.001) of the diagnosed relatives. Patients with at least one first-degree relative were at a lower risk of all-cause mortality than those with no FH (hazard ratio = 0.82 [95% confidence interval 0.75-0.89]). The population is largely of European ancestry, and this may cause an issue with representation and generalisation. Data are missing on epidemiological risk factors for death such as smoking and on comorbidities. Recall of family members' diagnoses may affect the classification of FH in unconfirmed cases.

CONCLUSIONS

Based on the investigation of the type and timing of relatives' cancers, it is likely that reductions in mortality are due almost completely to a greater awareness of the disease. This study provides information for clinicians guiding patients and their relatives based on their familial risk. It shows the importance of screening and awareness programmes, which are likely to improve survival among men with an FH.

PATIENT SUMMARY

We were interested in how a family history of prostate cancer affects survival in prostate cancer patients. We studied 16340 patients, categorised them according to the strength of their family history, and found that the stronger their family history, the better they did in terms of overall survival. We looked at the type and timing of patients' diagnoses compared with those of their relatives and found that this effect is likely to be explained by awareness, which indicates the importance of screening and awareness programmes.

AIMedGraph: a comprehensive multi-relational knowledge graph for precision medicine

The development of high-throughput molecular testing techniques has enabled the large-scale exploration of the underlying molecular causes of diseases and the development of targeted treatment for specific genetic alterations. However, knowledge to interpret the impact of genetic variants on disease or treatment is distributed in different databases, scientific literature studies and clinical guidelines. AIMedGraph was designed to comprehensively collect and interrogate standardized information about genes, genetic alterations and their therapeutic and diagnostic relevance and build a multi-relational, evidence-based knowledge graph. Graph database Neo4j was used to represent precision medicine knowledge as nodes and edges in AIMedGraph. Entities in the current release include 30 340 diseases/phenotypes, 26 140 genes, 187 541 genetic variants, 2821 drugs, 15 125 clinical trials and 797 911 supporting literature studies. Edges in this release cover 621 731 drug interactions, 9279 drug susceptibility impacts, 6330 pharmacogenomics effects, 30 339 variant pathogenicity and 1485 drug adverse reactions. The knowledge graph technique enables hidden knowledge inference and provides insight into potential disease or drug molecular mechanisms. Database URL: http://aimedgraph.tongshugene.net:8201.

Addition of a Genetic Risk Score for Identification of Men with a Low Prostate-specific Antigen Level in Midlife at Risk of Developing Lethal Prostate Cancer

Men with a low prostate-specific antigen (PSA) level (<1 ng/ml) in midlife may extend the rescreening interval (if aged 40-59 yr) or forgo future PSA screening (if aged >60 yr) owing to their low risk of aggressive prostate cancer (PCa). However, there is a subset of men who develop lethal PCa despite low baseline PSA. We investigated how a PCa polygenic risk score (PRS) in addition to baseline PSA impacts the prediction of lethal PCa among 483 men aged 40-70 yr from the Physicians' Health Study followed over a median of 33 yr. We examined the association of the PRS with the risk of lethal PCa (lethal cases vs controls) using logistic regression adjusted for baseline PSA. The PCa PRS was associated with risk of lethal PCa (odds ratio per 1 standard deviation in PRS [OR] 1.79, 95% confidence interval [CI] 1.28-2.49). The association between the PRS and lethal PCa was stronger for those with PSA <1 ng/ml (OR 2.23, 95% CI 1.19-4.21) than for men with PSA ≥1 ng/ml (OR 1.61, 95% CI 1.07-2.42). Our PCa PRS improved the identification of men with PSA <1 ng/ml at greater risk of future lethal PCa who should consider ongoing PSA testing.

Patient summary

A subset of men develop fatal prostate cancer despite having low prostate-specific antigen (PSA) levels in middle age. A risk score based on multiple genes can help in predicting men who may be at risk of developing lethal prostate cancer and who should be advised to have regular PSA measurements.

Genome-wide polygenic risk score for major osteoporotic fractures in postmenopausal women using associated single nucleotide polymorphisms

BACKGROUND

Osteoporosis is highly polygenic and heritable, with heritability ranging from 50 to 80%; most inherited susceptibility is associated with the cumulative effect of many common genetic variants. However, existing genetic risk scores (GRS) only provide a few percent predictive power for osteoporotic fracture.

METHODS

We derived and validated a novel genome-wide polygenic score (GPS) comprised of 103,155 common genetic variants to quantify this susceptibility and tested this GPS prediction ability in an independent dataset (n = 15,776).

RESULTS

Among postmenopausal women, we found a fivefold gradient in the risk of major osteoporotic fracture (MOF) (p < 0.001) and a 15.25-fold increased risk of severe osteoporosis (p < 0.001) across the GPS deciles. Compared with the remainder of the GPS distribution, the top GPS decile was associated with a 3.59-, 2.48-, 1.92-, and 1.58-fold increased risk of any fracture, MOF, hip fracture, and spine fracture, respectively. The top GPS decile also identified nearly twofold more high-risk osteoporotic patients than the top decile of conventional GRS based on 1103 conditionally independent genome-wide significant SNPs. Although the relative risk of severe osteoporosis for postmenopausal women at around 50 is relatively similar, the cumulative incident at 20-year follow-up is significantly different between the top GPS decile (13.7%) and the bottom decile (< 1%). In the subgroup analysis, the GPS transferability in non-Hispanic White is better than in other racial/ethnic groups.

CONCLUSIONS

This new method to quantify inherited susceptibility to osteoporosis and osteoporotic fracture affords new opportunities for clinical prevention and risk assessment.

Quantifying portable genetic effects and improving cross-ancestry genetic prediction with GWAS summary statistics

Polygenic risk scores (PRS) calculated from genome-wide association studies (GWAS) of Europeans are known to have substantially reduced predictive accuracy in non-European populations, limiting their clinical utility and raising concerns about health disparities across ancestral populations. Here, we introduce a statistical framework named X-Wing to improve predictive performance in ancestrally diverse populations. X-Wing quantifies local genetic correlations for complex traits between populations, employs an annotation-dependent estimation procedure to amplify correlated genetic effects between populations, and combines multiple population-specific PRS into a unified score with GWAS summary statistics alone as input. Through extensive benchmarking, we demonstrate that X-Wing pinpoints portable genetic effects and substantially improves PRS performance in non-European populations, showing 14.1%-119.1% relative gain in predictive R2 compared to state-of-the-art methods based on GWAS summary statistics. Overall, X-Wing addresses critical limitations in existing approaches and may have broad applications in cross-population polygenic risk prediction.