A Review of Prostate Cancer Genome-Wide Association Studies (GWAS)

From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine

Prostate cancer is the most common cancer in men worldwide and has a high mortality rate. The complex and heterogeneous development of prostate cancer has become a core obstacle in the treatment of prostate cancer. Simultaneously, the issues of overtreatment in early-stage diagnosis, oligometastasis and dormant tumor recognition, as well as personalized drug utilization, are also specific concerns that require attention in the clinical management of prostate cancer. Some typical genetic mutations have been proved to be associated with prostate cancer's initiation and progression. However, single-omic studies usually are not able to explain the causal relationship between molecular alterations and clinical phenotypes. Exploration from a systems genetics perspective is also lacking in this field, that is, the impact of gene network, the environmental factors, and even lifestyle behaviors on disease progression. At the meantime, current trend emphasizes the utilization of artificial intelligence (AI) and machine learning techniques to process extensive multidimensional data, including multi-omics. These technologies unveil the potential patterns, correlations, and insights related to diseases, thereby aiding the interpretable clinical decision making and applications, namely intelligent medicine. Therefore, there is a pressing need to integrate multidimensional data for identification of molecular subtypes, prediction of cancer progression and aggressiveness, along with perosonalized treatment performing. In this review, we systematically elaborated the landscape from molecular mechanism discovery of prostate cancer to clinical translational applications. We discussed the molecular profiles and clinical manifestations of prostate cancer heterogeneity, the identification of different states of prostate cancer, as well as corresponding precision medicine practices. Taking multi-omics fusion, systems genetics, and intelligence medicine as the main perspectives, the current research results and knowledge-driven research path of prostate cancer were summarized.

Prognostic value of germline mutations in metastatic hormone-sensitive prostate cancer (mHSPC)

BACKGROUND

About 8% to 12% of patients presenting with mHSPC exhibit germline pathogenic variants (PV) in cancer predisposition genes. The aim of this study is to assess the presence of germline PV as a prognostic factor in the setting of mHSPC and to determine whether mutational status can predict rapid progression to castration resistance.

METHODS

Genetic analysis using a multigene next-generation sequencing (NGS) panel was performed on 34 patients diagnosed with mHSPC undergoing treatment. We assessed the prevalence of germline PV and examined differences based on clinical-pathological characteristics, family history (FH), prostate-specific antigen (PSA) response, impact on time to castration-resistant prostate cancer (TTCRPC), and overall survival (OS).

RESULTS

Germline PV were identified in 6 patients (17,6%). When comparing the clinical-pathological characteristics of PV carriers (n = 6) to noncarriers (n = 28), no significant associations were observed except for the presence of FH of hereditary breast and ovarian cancer (HBOC) syndrome and/or Lynch syndrome (P = 0.024). At a median follow-up of 33 months, significant differences in OS were observed based on the presence of PV (26 months in carriers vs. 74 months in noncarriers; P < 0.01). Patients who harbored a BRCA2 mutation (n = 3) showed a worse clinical outcome, presenting a shorter TTCRPC (7 months vs. 23 months; P = 0.005) and lower OS (7 months vs. 74 months; P < 0.001) compared to noncarriers (n = 31).

CONCLUSION

mHSPC germline PV carriers had a worse survival outcome. Furthermore, BRCA2 germline mutation was an independent poor prognostic factor for mHSPC disease, associated with earlier progression to castration-resistant prostate cancer, and shorter OS. These results highlight the importance of evaluating germline mutational status in patients with hormone-sensitive prostate cancer.

Homologous Recombination Repair Testing Patterns and Outcomes in mCRPC by Alteration Status and Race

Background

Alterations in DNA damage repair genes in advanced prostate cancer (PC) may impact responses to therapy and clinical outcomes. This study described homologous recombination repair (HRR) testing patterns and clinical outcomes among patients with metastatic castration-resistant prostate cancer (mCRPC) by HRR alteration status and race in the United States (US).

Methods

Clinical data in the nationwide (US-based) Flatiron Health-Foundation Medicine, Inc. (FMI) Metastatic PC Clinico-Genomic Database were evaluated (01/01/2011-12/31/2022). Patients initiating first-line (1L) mCRPC therapy on or after mCRPC diagnosis were included. Testing patterns, time-to-next treatment, overall survival (OS), and time-to-prostate specific antigen response were described.

Results

Of the 1367 patients with mCRPC and at least one HRR panel test prior to or on the date of 1L mCRPC therapy initiation, 332 (24.3%) were HRR positive (White patients: n = 219 [66.0%]; Black patients: n = 37 [11.1%]) and 1035 (75.7%) were HRR negative (White patients: n = 702 [67.8%]; Black patients: n = 84 [8.1%]). The mean time between first positive test and 1L mCRPC therapy initiation date was 588 days (White patients: 589 days; Black patients: 639 days). Among HRR positive relative to negative patients, trends for faster progression (respective 12-month rate overall: 71.1% and 63.7%; White patients: 72.5% and 64.0%; Black patients: 65.4% and 56.4%), shorter OS (respective 24-month rate overall: 46.8% and 51.9%; White patients: 48.6% and 46.2%; Black patients: 52.8% and 54.1%), and decreased treatment response (respective 12-month rate overall: 24.3% and 37.9%; White patients: 24.5% and 35.2%; Black patients: 17.0% and 43.9%) were observed.

Conclusion

Patients with mCRPC positive for HRR alterations tended to exhibit poorer treatment responses and clinical outcomes than those with a negative status. These findings highlight the importance of timely genetic testing in mCRPC, particularly among Black patients, and the need for improved 1L targeted therapies to address the unmet need in HRR positive mCRPC.

Genetics of prostate cancer: a review of latest evidence

Prostate cancer (PrCa) is a largely heritable and polygenic disease. It is the most common cancer in people with prostates (PwPs) in Europe and the USA, including in PwPs of African descent. In the UK in 2020, 52% of all cancers were diagnosed at stage I or II. The National Health Service (NHS) long-term plan is to increase this to 75% by 2028, to reduce absolute incidence of late-stage disease. In the absence of a UK PrCa screening programme, we should explore how to identify those at increased risk of clinically significant PrCa.Incorporating genomics into the PrCa screening, diagnostic and treatment pathway has huge potential for transforming patient care. Genomics can increase efficiency of PrCa screening by focusing on those with genetic predisposition to cancer-which when combined with risk factors such as age and ethnicity, can be used for risk stratification in risk-based screening (RBS) programmes. The goal of RBS is to facilitate early diagnosis of clinically significant PrCa and reduce overdiagnosis/overtreatment in those unlikely to experience PrCa-related symptoms in their lifetime. Genetic testing can guide PrCa management, by identifying those at risk of lethal PrCa and enabling access to novel targeted therapies.PrCa is curable if diagnosed below stage III when most people do not experience symptoms. RBS using genetic profiling could be key here if we could show better survival outcomes (or reduction in cancer-specific mortality accounting for lead-time bias), in addition to more cost efficiency than age-based screening alone. Furthermore, PrCa outcomes in underserved communities could be optimised if genetic testing was accessible, minimising health disparities.

Preliminary effects of risk-adapted PSA screening for prostate cancer after integrating PRS-specific and age-specific variation

Background

Although the risk of prostate cancer (PCa) varies across different ages and genetic risks, it's unclear about the effects of genetic-specific and age-specific prostate-specific antigen (PSA) screening for PCa.

Methods

Weighed and unweighted polygenic risk scores (PRS) were constructed to classify the participants from the PLCO trial into low- or high-PRS groups. The age-specific and PRS-specific cut-off values of PSA for PCa screening were determined with time-dependent receiver-operating-characteristic curves and area-under-curves (tdAUCs). Improved screening strategies integrating PRS-specific and age-specific cut-off values of PSA were compared to traditional PSA screening on accuracy, detection rates of high-grade PCa (Gleason score ≥7), and false positive rate.

Results

Weighted PRS with 80 SNPs significantly associated with PCa was determined as the optimal PRS, with an AUC of 0.631. After stratifying by PRS, the tdAUCs of PSA with a 10-year risk of PCa were 0.818 and 0.816 for low- and high-PRS groups, whereas the cut-off values were 1.42 and 1.62 ng/mL, respectively. After further stratifying by age, the age-specific cut-off values of PSA were relatively lower for low PRS (1.42, 1.65, 1.60, and 2.24 ng/mL for aged <60, 60-64, 65-69, and ≥70 years) than high PRS (1.48, 1.47, 1.89, and 2.72 ng/mL). Further analyses showed an obvious interaction of positive PSA and high PRS on PCa incidence and mortality. Very small difference in PCa risk were observed among subgroups with PSA (-) across different age and PRS, and PCa incidence and mortality with PSA (+) significantly increased as age and PRS, with highest risk for high-PRS/PSA (+) in participants aged ≥70 years [HRs (95%CI): 16.00 (12.62-20.29) and 19.48 (9.26-40.96)]. The recommended screening strategy reduced 12.8% of missed PCa, ensured high specificity, but not caused excessive false positives than traditional PSA screening.

Conclusion

Risk-adapted screening integrating PRS-specific and age-specific cut-off values of PSA would be more effective than traditional PSA screening.

Impact of Family History and Germline Genetic Risk Single Nucleotide Polymorphisms on Long-Term Outcomes of Favorable-Risk Prostate Cancer

PURPOSE

Family history and germline genetic risk single nucleotide polymorphisms (SNPs) have been separately shown to stratify lifetime risk of prostate cancer. Here, we evaluate the combined prognostic value of family history of prostate and other related cancers and germline risk SNPs among patients with favorable-risk prostate cancer.

MATERIALS AND METHODS

A total of 1367 participants from the prospective Health Professionals Follow-up Study diagnosed with low- or favorable intermediate-risk prostate cancer from 1986 to 2017 underwent genome-wide SNP genotyping. Multivariable Cox regression was used to estimate the association between family history, specific germline risk variants, and a 269 SNP polygenic risk score with prostate cancer‒specific death.

RESULTS

Family history of prostate, breast, and/or pancreatic cancer was observed in 489 (36%) participants. With median follow-up from diagnosis of 14.9 years, participants with favorable-risk prostate cancer with a positive family history had a significantly higher risk of prostate cancer‒specific death (HR 1.95, 95% CI 1.15-3.32, P = .014) compared to those without any family history. The rs2735839 (19q13) risk allele was associated with prostate cancer‒specific death (HR 1.81 per risk allele, 95% CI 1.04-3.17, P = .037), whereas the polygenic risk score was not. Combined family history and rs2735839 risk allele were each associated with an additive risk of prostate cancer‒specific death (HR 1.78 per risk factor, 95% CI 1.25-2.53, P = .001).

CONCLUSIONS

Family history of prostate, breast, or pancreatic cancer and/or a 19q13 germline risk allele are associated with an elevated risk of prostate cancer‒specific death among favorable-risk patients. These findings have implications for how family history and germline genetic risk SNPs should be factored into clinical decision-making around favorable-risk prostate cancer.

Combined SNPs sequencing and allele specific proteomics capture reveal functional causality underpinning the 2p25 prostate cancer susceptibility locus

Genome wide association studies (GWASs) have identified numerous risk loci associated with prostate cancer, yet unraveling their functional significance remains elusive. Leveraging our high-throughput SNPs-seq method, we pinpointed rs4519489 within the multi-ancestry GWAS-discovered 2p25 locus as a potential functional SNP due to its significant allelic differences in protein binding. Here, we conduct a comprehensive analysis of rs4519489 and its associated gene, NOL10, employing diverse cohort data and experimental models. Clinical findings reveal a synergistic effect between rs4519489 genotype and NOL10 expression on prostate cancer prognosis and severity. Through unbiased proteomics screening, we reveal that the risk allele A of rs4519489 exhibits enhanced binding to USF1, a novel oncogenic transcription factor (TF) implicated in prostate cancer progression and prognosis, resulting in elevated NOL10 expression. Furthermore, we elucidate that NOL10 regulates cell cycle pathways, fostering prostate cancer progression. The concurrent expression of NOL10 and USF1 correlates with aggressive prostate cancer characteristics and poorer prognosis. Collectively, our study offers a robust strategy for functional SNP screening and TF identification through high-throughput SNPs-seq and unbiased proteomics, highlighting the rs4519489-USF1-NOL10 regulatory axis as a promising biomarker or therapeutic target for clinical diagnosis and treatment of prostate cancer.

MAOB expression correlates with a favourable prognosis in prostate cancer, and its genetic variants are associated with the metastasis of the disease

Monoamine oxidase B (MAOB), a neurotransmitter-degrading enzyme, was reported to reveal conflicting roles in various cancers. However, the functional role of MAOB and impacts of its genetic variants on prostate cancer (PCa) is unknown. Herein, we genotyped four loci of MAOB single-nucleotide polymorphisms (SNPs), including rs1799836 (A/G), rs3027452 (G/A), rs6651806 (A/C) and rs6324 (G/A) in 702 PCa Taiwanese patients. We discovered that PCa patients carrying the MAOB rs6324 A-allele exhibited an increased risk of having a high initial prostate-specific antigen (iPSA) level (>10 ng/mL). Additionally, patients with the rs3027452 A-allele had a higher risk of developing distal metastasis, particularly in the subpopulation with high iPSA levels. In a subpopulation without postoperative biochemical recurrence, patients carrying the rs1799836 G-allele had a higher risk of developing lymph node metastasis and recurrence compared to those carrying the A-allele. Furthermore, genotype screening in PCa cell lines revealed that cells carrying the rs1799836 G-allele expressed lower MAOB levels than those carrying the A-allele. Functionally, overexpression and knockdown of MAOB in PCa cells respectively suppressed and enhanced cell motility and proliferation. In clinical observations, correlations of lower MAOB expression levels with higher Gleason scores, advanced clinical T stages, tumour metastasis, and poorer prognosis in PCa patients were noted. Our findings suggest that MAOB may act as a suppressor of PCa progression, and the rs3027452 and rs1799836 genetic variants of MAOB are linked to PCa metastasis within the Taiwanese population.

Possible prognostic impact of PKCι genetic variants in prostate cancer

BACKGROUND

Single nucleotide polymorphisms (SNPs) have been linked with prostate cancer (PCa) and have shown potential as prognostic markers for advanced stages. Loss of function mutations in PKCι have been linked with increased risk of malignancy by enhancing tumor cell motility and invasion. We have evaluated the impact of two coding region SNPs on the PKCι gene (PRKCI) and their prognostic potential.

METHODS

Genotypic association of non-synonymous PKCι SNPs rs1197750201 and rs1199520604 with PCa was determined through tetra-ARMS PCR. PKCι was docked with interacting partner Par-6 to determine the effect of these variants on PKCι binding capabilities. Molecular dynamic simulations of PKCι docked with Par-6 were performed to determine variant effects on PKCι protein interactions. The possible impact of changes in PKCι protein interactions on epithelial cell polarity was hypothesized.

RESULTS

PKCι rs1199520604 mutant genotype TT showed association with PCa (p = 0.0055), while rs1197750201 mutant genotype AA also showed significant association with PCa (P = 0.0006). The binding interaction of PKCι with Par-6 was altered for both variants, with changes in Van der Waals energy and electrostatic energy of docked structures.

CONCLUSION

Genotypic analysis of two non-synonymous PKCι variants in association with PCa prognosis was performed. Both variants in the PB1 domain showed potential as a prognostic marker for PCa. In silico analysis of the effect of the variants on PKCι protein interactions indicated they may be involved in PCa progression through aberration of epithelial cell polarity pathways.

Prostate Cancer, Race, and Health Disparity: What We Know

ABSTRACT

Prostate cancer (PCa) in African American men is one of the most common cancers with a great disparity in outcomes. The higher incidence and tendency to present with more advanced disease have prompted investigators to postulate that this is a problem of innate biology. However, unequal access to health care and poorer quality of care raise questions about the relative importance of genetics versus social/health injustice. Although race is inconsistent with global human genetic diversity, we need to understand the sociocultural reality that race and racism impact biology. Genetic studies reveal enrichment of PCa risk alleles in populations of West African descent and population-level differences in tumor immunology. Structural racism may explain some of the differences previously reported in PCa clinical outcomes; fortunately, there is high-level evidence that when care is comparable, outcomes are comparable.

Identification of Candidate Genes for Economically Important Carcass Cutting in Commercial Pigs through GWAS

During the process of pork production, the carcasses of pigs are divided and sold, which provides better economic benefits and market competitiveness for pork production than selling the carcass as a whole. Due to the significant cost of post-slaughter phenotypic measurement, the genetic architecture of tenderloin weight (TLNW) and rib weight (RIBW)-important components of pig carcass economic value-remain unknown. In this study, we conducted genome-wide association studies (GWAS) for TLNW and RIBW traits in a population of 431 Duroc × Landrace × Yorkshire (DLY) pigs. In our study, the most significant single nucleotide polymorphism (SNP) associated with TLNW was identified as ASGA0085853 (3.28 Mb) on Sus scrofa chromosome 12 (SSC12), while for RIBW, it was Affx-1115046258 (172.45 Mb) on SSC13. Through haplotype block analysis, we discovered a novel quantitative trait locus (QTL) associated with TLNW, spanning a 5 kb region on SSC12, and a novel RIBW-associated QTL spanning 1.42 Mb on SSC13. Furthermore, we hypothesized that three candidate genes, TIMP2 and EML1, and SMN1, are associated with TLNW and RIBW, respectively. Our research not only addresses the knowledge gap regarding TLNW, but also serves as a valuable reference for studying RIBW. The identified SNP loci strongly associated with TLNW and RIBW may prove useful for marker-assisted selection in pig breeding programs.

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.

Germline Genetic Variants Associated with Somatic TMPRSS2:ERG Fusion Status in Prostate Cancer: A Genome-Wide Association Study

BACKGROUND

The prostate cancer subtype defined by the presence of TMPRSS2:ERG has been shown to be molecularly and epidemiologically distinct. However, few studies have investigated germline genetic variants associating with TMPRSS2:ERG fusion status.

METHODS

We performed a genome-wide association study with 396 TMPRSS2:ERG(+) cases, 390 TMPRSS2:ERG(-) cases, and 2,386 cancer-free controls from the Physicians' Health Study (PHS), the Health Professionals Follow-up Study (HPFS), and a Seattle-based Fred Hutchinson (FH) Cancer Center Prostate Cancer Study. We applied logistic regression models to test the associations between ∼5 million SNPs with TMPRSS2:ERG fusion status accounting for population stratification.

RESULTS

We did not identify genome-wide significant variants comparing the TMPRSS2:ERG(+) to the TMPRSS2:ERG(-) prostate cancer cases in the meta-analysis. When comparing TMPRSS2:ERG(+) prostate cancer cases with controls without prostate cancer, 10 genome-wide significant SNPs on chromosome 17q24.3 were observed in the meta-analysis. When comparing TMPRSS2:ERG(-) prostate cancer cases with controls without prostate cancer, two SNPs on chromosome 8q24.21 in the meta-analysis reached genome-wide significance.

CONCLUSIONS

We observed SNPs at several known prostate cancer risk loci (17q24.3, 1q32.1, and 8q24.21) that were differentially and exclusively associated with the risk of developing prostate tumors either with or without the gene fusion.

IMPACT

Our findings suggest that tumors with the TMPRSS2:ERG fusion exhibit a different germline genetic etiology compared with fusion negative cases.

Genetic variants of dipeptidyl peptidase IV are linked to the clinicopathologic development of prostate cancer

CD26/dipeptidyl peptidase IV (DPP4) is a multifunctional cell-surface glycoprotein widely found in many cell types, and a soluble form is present in body fluids. There is longstanding evidence indicating a tumour-promoting or -suppressive role of DPP4 in different cancer types. However, studies focusing on the impacts of genetic variants of DPP4 on cancers are very rare. Herein, we conducted a case-control study to evaluate whether single-nucleotide polymorphisms (SNPs) of DPP4 were associated with the risk or clinicopathologic development of prostate cancer (PCa). We genotyped four loci of DPP4 SNPs, including rs7608798 (A/G), rs3788979 (C/T), rs2268889 (T/C) and rs6741949 (G/C), using a TaqMan allelic discrimination assay in 704 PCa patients and 704 healthy controls. Our results showed that PCa patients with the DPP4 rs7608798 AG+GG genotype or rs2268889 TC+CC genotype had a higher risk of developing an advanced clinical primary tumour (cT) stage (adjusted odds ratio (AOR): 1.680, 95% confidence interval (CI): 1.062-2.659, p = 0.025; AOR: 1.693, 95% CI: 1.092-2.624, p = 0.018). Additionally, in The Cancer Genome Atlas (TCGA) database, we observed that lower DPP4 expression levels were correlated with higher Gleason scores, advanced cT and pathological stages, tumour metastasis, and shorter progression-free survival rates in PCa patients. Furthermore, overexpression of DPP4 suppressed migration/invasion of metastatic PC3 PCa cells. Our findings suggest that DPP4 levels may affect the progression of PCa, and the DPP4 rs7608798 and rs2268889 SNPs are associated with the clinicopathologic development of PCa in a Taiwanese population.

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.

Defining aggressive prostate cancer: a geospatial perspective

BACKGROUND

Spatial analysis can identify communities where men are at risk for aggressive prostate cancer (PCan) and need intervention. However, there are several definitions for aggressive PCan. In this study, we evaluate geospatial patterns of 3 different aggressive PCan definitions in relation to PCan-specific mortality and provide methodologic and practical insights into how each definition may affect intervention targets.

METHODS

Using the Pennsylvania State Cancer Registry data (2005-2015), we used 3 definitions to assign "aggressive" status to patients diagnosed with PCan. Definition one (D1, recently recommended as the primary definition, given high correlation with PCan death) was based on staging criteria T4/N1/M1 or Gleason score ≥ 8. Definition two (D2, most frequently-used definition in geospatial studies) included distant SEER summary stage. Definition three (D3) included Gleason score ≥ 7 only. Using Bayesian spatial models, we identified geographic clusters of elevated odds ratios for aggressive PCan (binomial model) for each definition and compared overlap between those clusters to clusters of elevated hazard ratios for PCan-specific mortality (Cox regression).

RESULTS

The number of "aggressive" PCan cases varied by definition, and influenced quantity, location, and extent/size of geographic clusters in binomial models. While spatial patterns overlapped across all three definitions, using D2 in binomial models provided results most akin to PCan-specific mortality clusters as identified through Cox regression. This approach resulted in fewer clusters for targeted intervention and less sensitive to missing data compared to definitions that rely on clinical TNM staging.

CONCLUSIONS

Using D2, based on distant SEER summary stage, in future research may facilitate consistency and allow for standardized comparison across geospatial studies.

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.

Mismatch repair gene germline mutations in patients with prostate cancer

OBJECTIVES

To investigate the prevalence of pathogenic germline mutations of mismatch repair (MMR) genes in prostate cancer patients and its relationship with clinicopathological characteristics.

METHODS

Germline sequencing data of 855 prostate cancer patients admitted in Fudan University Shanghai Cancer Center from 2018 to 2022 were retrospectively analyzed. The pathogenicity of mutations was assessed according to the American College of Medical Genetics and Genomics (ACMG) standard guideline, Clinvar and Intervar databases. The clinicopathological characteristics and responses to castration treatment were compared among patients with MMR gene mutation (MMR+ group), patients with DNA damage repair (DDR) gene germline pathogenic mutation without MMR gene (DDR+MMR－ group) and patients without DDR gene germline pathogenic mutation (DDR－ group).

RESULTS

Thirteen (1.52%) MMR+ patients were identified in 855 prostate cancer patients, including 1 case with MLH1 gene mutation, 6 cases with MSH2 gene mutation, 4 cases with MSH6 gene mutation and 2 cases with PMS2 gene mutation. 105 (11.9%) patients were identified as DDR gene positive (except MMR gene), and 737 (86.2%) patients were DDR gene negative. Compared with DDR－ group, MMR+ group had lower age of onset (P<0.05) and initial prostate-specific antigen (PSA) (P<0.01), while no significant differences were found between the two groups in Gleason score and TMN staging (both P>0.05). The median time to castration resistance was 8 months (95%CI: 6 months-not achieved), 16 months (95%CI: 12-32 months) and 24 months (95%CI: 21-27 months) for MMR+ group, DDR+MMR－ group and DDR－ group, respectively. The time to castration resistance in MMR+ group was significantly shorter than that in DDR+MMR－ group and DDR－ group (both P<0.01), while there was no significant difference between DDR+MMR－ group and DDR－ group (P>0.05).

CONCLUSIONS

MMR gene mutation testing is recommended for prostate cancer patients with early onset, low initial PSA, metastasis or early resistance to castration therapy.

Association between interleuleukin-1β polymorphism (rs16944) and biomarkers levels in Iraqi patients with prostate cancer

OBJECTIVE

Prostate cancer (PCa) is the second-leading cause of mortality in men and the most commonly diagnosed non-cutaneous male malignancy. Host genetic factors, and inflammation-induced cytokines, play a key role in prostate oncogenesis. Single Nucleotide Polymorphisms (SNP) in cytokine genes were suggested to increase the susceptibility for PCa development and progression. This study aimed to investigate the association between the SNP (rs16944) in the interleukin-1 β (IL-1β) gene and the serum levels of Prostate Specific Antigen (PSA) Prolactine (PRL), testosterone, and IL-1β in Iraqi PCa patients versus healthy controls.

METHODS

Taqman Real Time-PCR, was performed to investigate the IL-1β (rs16944) polymorphism in 100 Iraqi PCa patients and 50 age-matched healthy controls in a case-control study. Serum levels of PSA, PRL, and testosterone were determined by ELISA and FIA, and associated with the IL-1β serum level as well as with the SNP (rs 16944). The association between the clinico-pathological parameters and the genotype distribution of PCa patients was also studied.

RESULTS

There level of IL-1β was significant increased in the serum of PCa patients compared to controls (P = 8.19 10^-7). Serum levels for other biomarkers such as PSA, PRL and testosterone were also significantly elevated in patients compared to controls (P < 0.0001). No differences were seen for genotype and allele distribution between PCa patients and controls. Nevertheless, in the group of controls, we found that 36% carried the GG genotype against only 26% in the patients group.This suggests that this could be a protective genotype (OR 0.62, P = 0.254). In addition, we found that the GA genotype is slightly more frequent in patients as compared to controls (OR 1.22, P = 0.605). Interestingly, serum levels of IL-1β, PSA, PRL and testosterone were significantly higher in PCa patients carrying the GA genotype, and the GA and AA genotypes are strongly associated with the aggressive behavior of the disease such as advanced TNM, and high Gleason score.

CONCLUSION

Our data suggest that both serum IL-1β level and IL-1β SNP (rs16944) may be considered as candidate biomarkers for PCa. Moreover, the GA, and AA genotypes carriers along with high sera levels of IL-1β, PSA and PRL, have an increased risk for PCa with aggressive behavior in Iraqi men.

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.

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

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

Germline Variants in DNA Damage Repair Genes and HOXB13 Among Black Patients With Early-Onset Prostate Cancer

PURPOSE

Genetic studies of prostate cancer susceptibility have predominantly focused on non-Hispanic White men, despite the observation that Black men are more likely to develop prostate cancer and die from the disease. Therefore, we sought to identify genetic variants in Black patients diagnosed with early-onset prostate cancer.

METHODS

Whole-exome sequencing of germline DNA from a population-based cohort of Black men diagnosed with prostate cancer at age 62 years or younger was performed. Analysis was focused on a panel of DNA damage repair (DDR) genes and HOXB13. All discovered variants were ranked according to their pathogenic potential based upon REVEL score, evidence from existing literature, and prevalence in the cohort. Logistic regression was used to investigate associations between mutation status and relevant clinical characteristics.

RESULTS

Among 743 Black prostate cancer patients, we identified 26 unique pathogenic (P) or likely pathogenic (LP) variants in 14 genes (including HOXB13, BRCA1/2, BRIP1, ATM, CHEK2, and PALB2) among 30 men, or approximately 4.0% of the patient population. We also identified 33 unique variants of unknown significance in 16 genes among 39 men. Because of the rarity of these variants in the population, most associations between clinical characteristics did not achieve statistical significance. However, our results suggest that carriers for P or LP (P/LP) variants were more likely to have a first-degree relative diagnosed with DDR gene-associated cancer, have a higher prostate-specific antigen at time of diagnosis, and be diagnosed with metastatic disease.

CONCLUSION

Variants in DDR genes and HOXB13 may be important cancer risk factors for Black men diagnosed with early-onset prostate cancer, and are more frequently observed in men with a family history of cancer.

Cumulative Effect Assessment of Common Genetic Variants on Prostate Cancer: Preliminary Studies

Single nucleotide polymorphisms (SNPs) are the most common type of genetic variation among people. Genome Wide Association studies (GWASs) have generated multiple genetic variants associated with prostate cancer (PC) risk. Taking into account previously identified genetic susceptibility variants, the purpose of our study was to determine the cumulative association between four common SNPs and the overall PC risk. A total of 78 specimens from both PC and benign prostate hyperplasia (BPH) patients were included in the study. Genotyping of all selected SNPs was performed using the TaqMan assay. The association between each SNP and the PC risk was assessed individually and collectively. Analysis of the association between individual SNPs and PC risk revealed that only the rs4054823 polymorphism was significantly associated with PC, and not with BPH (p < 0.001). Statistical analysis also showed that the heterozygous genotype of the rs2735839 polymorphism is more common within the BPH group than in the PC group (p = 0.042). The cumulative effect of high-risk alleles on PC was analyzed using a logistic regression model. As a result, the carriers of at least one risk allele copy in each particular region had a cumulative odd ratio (OR) of 1.42 times, compared to subjects who did not have any of these factors. In addition, the combination of these four genetic variants increased the overall risk of PC by 52%. Our study provides further evidence of the cumulative effects of genetic risk factors on overall PC risk. These results should encourage future research to explain the interactions between known susceptibility variants and their contribution to the development and progression of PC disease.

Review of prostate cancer genomic studies in Africa

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

Is early-onset cancer an emerging global epidemic? Current evidence and future implications

Over the past several decades, the incidence of early-onset cancers, often defined as cancers diagnosed in adults <50 years of age, in the breast, colorectum, endometrium, oesophagus, extrahepatic bile duct, gallbladder, head and neck, kidney, liver, bone marrow, pancreas, prostate, stomach and thyroid has increased in multiple countries. Increased use of screening programmes has contributed to this phenomenon to a certain extent, although a genuine increase in the incidence of early-onset forms of several cancer types also seems to have emerged. Evidence suggests an aetiological role of risk factor exposures in early life and young adulthood. Since the mid-20th century, substantial multigenerational changes in the exposome have occurred (including changes in diet, lifestyle, obesity, environment and the microbiome, all of which might interact with genomic and/or genetic susceptibilities). However, the effects of individual exposures remain largely unknown. To study early-life exposures and their implications for multiple cancer types will require prospective cohort studies with dedicated biobanking and data collection technologies. Raising awareness among both the public and health-care professionals will also be critical. In this Review, we describe changes in the incidence of early-onset cancers globally and suggest measures that are likely to reduce the burden of cancers and other chronic non-communicable diseases.

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.

Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 1: Raman spectroscopy fiber-optics system and in situ tissue characterization

SIGNIFICANCE

The diagnosis of prostate cancer (PCa) and focal treatment by brachytherapy are limited by the lack of precise intraoperative information to target tumors during biopsy collection and radiation seed placement. Image-guidance techniques could improve the safety and diagnostic yield of biopsy collection as well as increase the efficacy of radiotherapy.

AIM

To estimate the accuracy of PCa detection using in situ Raman spectroscopy (RS) in a pilot in-human clinical study and assess biochemical differences between in vivo and ex vivo measurements.

APPROACH

A new miniature RS fiber-optics system equipped with an electromagnetic (EM) tracker was guided by trans-rectal ultrasound-guided imaging, fused with preoperative magnetic resonance imaging to acquire 49 spectra in situ (in vivo) from 18 PCa patients. In addition, 179 spectra were acquired ex vivo in fresh prostate samples from 14 patients who underwent radical prostatectomy. Two machine-learning models were trained to discriminate cancer from normal prostate tissue from both in situ and ex vivo datasets.

RESULTS

A support vector machine (SVM) model was trained on the in situ dataset and its performance was evaluated using leave-one-patient-out cross validation from 28 normal prostate measurements and 21 in-tumor measurements. The model performed at 86% sensitivity and 72% specificity. Similarly, an SVM model was trained with the ex vivo dataset from 152 normal prostate measurements and 27 tumor measurements showing reduced cancer detection performance mostly attributable to spatial registration inaccuracies between probe measurements and histology assessment. A qualitative comparison between in situ and ex vivo measurements demonstrated a one-to-one correspondence and similar ratios between the main Raman bands (e.g., amide I-II bands, phenylalanine).

CONCLUSIONS

PCa detection can be achieved using RS and machine learning models for image-guidance applications using in situ measurements during prostate biopsy procedures.

Genome-Wide 3'-UTR Single Nucleotide Polymorphism Association Study Identifies Significant Prostate Cancer Risk-Associated Functional Loci at 8p21.2 in Chinese Population

MicroRNAs (miRNAs) are involved in the regulation of gene expression via incomplete base pairing to sequence motifs at the three prime untranslated regions (3'-UTRs) of mRNAs and play critical roles in the etiology of cancers. Single nucleotide polymorphisms (SNPs) in the 3'-UTR miRNA-binding regions may influence the miRNA affinity. However, this biological mechanism in prostate cancer (PCa) remains unclear. Here, a three-stage genome-wide association study of 3'-UTR SNPs (n=33 117) is performed in 5515 Chinese men. Three genome-wide significant variants are discovered at 8p21.2 (rs1567669, rs4872176, and rs4872177), which are all located in a linkage disequilibrium region of the NKX3-1 gene. Phenome-wide association analysis using the FinnGen data reveals a specific association of rs1567669 with PCa over 2,264 disease endpoints. Expression quantitative trait locus analyses based on both Chinese PCa cohort and the GTEx database show that risk alleles of these SNPs are significantly associated with low expression of NKX3-1. Based on the MirSNP database, dual-luciferase reporter assays show that risk alleles of these SNPs downregulate the expression of NKX3-1 via increased miRNA binding. These results indicate that the SNPs at the 3'-UTR of NKX3-1 significantly downregulate NKX3-1 expression by influencing the affinity of miRNA and increase the PCa risk.

Unravelling genetic variants of a swedish family with high risk of prostate cancer

BACKGROUND

Prostate cancer is the most prevalent cancer in men worldwide. It is a polygenic disease with a substantial proportion of heritability. Identification of novel candidate biomarkers is crucial for clinical cancer prevention and the development of therapeutic strategies. Here, we describe the analysis of rare and common genetic variants that can predispose to the development of prostate cancer.

METHODS

Whole-genome sequencing was performed on germline DNA of five Swedish siblings which were diagnosed with prostate cancer. The high-risk variants were identified setting the minor allele frequency < 0.01, CADD > 10 and if tested in PRACTICAL, OR > 1.5, while the low-risk variants were identified minor allele frequency > 0.01, CADD > 10 and if tested in PRACTICAL, OR > 1.1.

RESULTS

We identified 38 candidate high-risk gene variants and 332 candidate low-risk gene variants, where 2 and 14 variants were in coding regions, respectively, that were shared by the brothers with prostate cancer.

CONCLUSIONS

This study expanded the knowledge of potential risk factor candidates involved in hereditary and familial prostate cancer. Our findings can be beneficial when applying targeted screening in families with a high risk of developing the disease.

Identifying genes targeted by disease-associated non-coding SNPs with a protein knowledge graph

Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) that play important roles in the genetic heritability of traits and diseases. With most of these SNPs located on the non-coding part of the genome, it is currently assumed that these SNPs influence the expression of nearby genes on the genome. However, identifying which genes are targeted by these disease-associated SNPs remains challenging. In the past, protein knowledge graphs have often been used to identify genes that are associated with disease, also referred to as “disease genes”. Here, we explore whether protein knowledge graphs can be used to identify genes that are targeted by disease-associated non-coding SNPs by testing and comparing the performance of six existing methods for a protein knowledge graph, four of which were developed for disease gene identification. We compare our performance against two baselines: (1) an existing state-of-the-art method that is based on guilt-by-association, and (2) the leading assumption that SNPs target the nearest gene on the genome. We test these methods with four reference sets, three of which were obtained by different means. Furthermore, we combine methods to investigate whether their combination improves performance. We find that protein knowledge graphs that include predicate information perform comparable to the current state of the art, achieving an area under the receiver operating characteristic curve (AUC) of 79.6% on average across all four reference sets. Protein knowledge graphs that lack predicate information perform comparable to our other baseline (genetic distance) which achieved an AUC of 75.7% across all four reference sets. Combining multiple methods improved performance to 84.9% AUC. We conclude that methods for a protein knowledge graph can be used to identify which genes are targeted by disease-associated non-coding SNPs.

Considering hormone-sensitive cancers as a single disease in the UK biobank reveals shared aetiology

Hormone-related cancers, including cancers of the breast, prostate, ovaries, uterine, and thyroid, globally contribute to the majority of cancer incidence. We hypothesize that hormone-sensitive cancers share common genetic risk factors that have rarely been investigated by previous genomic studies of site-specific cancers. Here, we show that considering hormone-sensitive cancers as a single disease in the UK Biobank reveals shared genetic aetiology. We observe that a significant proportion of variance in disease liability is explained by the genome-wide single nucleotide polymorphisms (SNPs), i.e., SNP-based heritability on the liability scale is estimated as 10.06% (SE 0.70%). Moreover, we find 55 genome-wide significant SNPs for the disease, using a genome-wide association study. Pair-wise analysis also estimates positive genetic correlations between some pairs of hormone-sensitive cancers although they are not statistically significant. Our finding suggests that heritable genetic factors may be a key driver in the mechanism of carcinogenesis shared by hormone-sensitive cancers.

Polymorphic variants of the CASP3, CASP9, BCL-2 and NKX3-1 genes as candidate markers for prostate cancer susceptibility and poor prognosis

BACKGROUND

There is an ongoing search for molecular markers that are specific, sensitive, and able to predict the stage of prostate cancer (PCa), which is the second most prevalent type of cancer in men worldwide. This study examined whether different single nucleotide polymorphisms (SNPs) were reliable markers of susceptibility to and prognosis of PCa in a sample of Brazilian patients.

METHODS AND RESULTS

DNA samples were extracted from peripheral blood cells of 283 PCa patients and matched with samples from healthy controls. Single nucleotide polymorphisms (SNPs in four genes (BCL-2-rs2279115, CASP3-rs4647603, CASP9-rs1052571, and NKX3-1-rs11781886) were genotyped by real-time PCR using the TaqMan® probe. Odds Ratios with 95% confidence intervals were calculated for allelic and genotypic frequencies. The association between polymorphic variants, risk of developing PCa, and clinicopathological characteristics was analyzed by univariate and multivariate logistic regression analysis. SNPs in CASP3, CASP9, and NKX3-1 genes, either alone or in combination (BCL-2+NKX3-1 and CASP3+NKX3-1) were associated with the risk of developing PCa. Genotypes and tumor histopathological data indicated that the BCL-2, NKX3-1, and CASP3 allelic variants, either alone or combined in pairs, were associated with a poor prognosis of PCa.

CONCLUSIONS

Genetic polymorphisms in CASP3, NKX3-1, and BCL-2 genes were associated with susceptibility to PCa. The SNPs in the three genes alone and the SNP in the BCL-2 gene combined with the other two genes were strongly associated with adverse outcomes in PCa patients and are promising candidates for molecular markers for PCa prognosis.

The promising role of new molecular biomarkers in prostate cancer: from coding and non-coding genes to artificial intelligence approaches

Background

Risk stratification or progression in prostate cancer is performed with the support of clinical-pathological data such as the sum of the Gleason score and serum levels PSA. For several decades, methods aimed at the early detection of prostate cancer have included the determination of PSA serum levels. The aim of this systematic review is to provide an overview about recent advances in the discovery of new molecular biomarkers through transcriptomics, genomics and artificial intelligence that are expected to improve clinical management of the prostate cancer patient.

Methods

An exhaustive search was conducted by Pubmed, Google Scholar and Connected Papers using keywords relating to the genetics, genomics and artificial intelligence in prostate cancer, it includes “biomarkers”, “non-coding RNAs”, “lncRNAs”, “microRNAs”, “repetitive sequence”, “prognosis”, “prediction”, “whole-genome sequencing”, “RNA-Seq”, “transcriptome”, “machine learning”, and “deep learning”.

Results

New advances, including the search for changes in novel biomarkers such as mRNAs, microRNAs, lncRNAs, and repetitive sequences, are expected to contribute to an earlier and accurate diagnosis for each patient in the context of precision medicine, thus improving the prognosis and quality of life of patients. We analyze several aspects that are relevant for prostate cancer including its new molecular markers associated with diagnosis, prognosis, and prediction to therapy and how bioinformatic approaches such as machine learning and deep learning can contribute to clinic. Furthermore, we also include current techniques that will allow an earlier diagnosis, such as Spatial Transcriptomics, Exome Sequencing, and Whole-Genome Sequencing.

Conclusion

Transcriptomic and genomic analysis have contributed to generate knowledge in the field of prostate carcinogenesis, new information about coding and non-coding genes as biomarkers has emerged. Synergies created by the implementation of artificial intelligence to analyze and understand sequencing data have allowed the development of clinical strategies that facilitate decision-making and improve personalized management in prostate cancer.

The BARCODE1 Pilot: a feasibility study of using germline single nucleotide polymorphisms to target prostate cancer screening

OBJECTIVES

To assess the feasibility and uptake of a community-based prostate cancer (PCa) screening programme selecting men according to their genetic risk of PCa. To assess the uptake of PCa screening investigations by men invited for screening. The uptake of the pilot study would guide the opening of the larger BARCODE1 study recruiting 5000 men.

SUBJECTS AND METHODS

Healthy males aged 55-69 years were invited to participate via their general practitioners (GPs). Saliva samples were collected via mailed collection kits. After DNA extraction, genotyping was conducted using a study specific assay. Genetic risk was based on genotyping 130 germline PCa risk single nucleotide polymorphisms (SNPs). A polygenic risk score (PRS) was calculated for each participant using the sum of weighted alleles for 130 SNPs. Study participants with a PRS lying above the 90th centile value were invited for PCa screening by prostate magnetic resonance imaging (MRI) and biopsy.

RESULTS

Invitation letters were sent to 1434 men. The overall study uptake was 26% (375/1436) and 87% of responders were eligible for study entry. DNA genotyping data were available for 297 men and 25 were invited for screening. After exclusions due to medical comorbidity/invitations declined, 18 of 25 men (72%) underwent MRI and biopsy of the prostate. There were seven diagnoses of PCa (38.9%). All cancers were low-risk and were managed with active surveillance.

CONCLUSION

The BARCODE1 Pilot has shown this community study in the UK to be feasible, with an overall uptake of 26%. The main BARCODE1 study is now open and will recruit 5000 men. The results of BARCODE1 will be important in defining the role of genetic profiling in targeted PCa population screening. Patient Summary What is the paper about? Very few prostate cancer screening programmes currently exist anywhere in the world. Our pilot study investigated if men in the UK would find it acceptable to have a genetic test based on a saliva sample to examine their risk of prostate cancer development. This test would guide whether men are offered prostate cancer screening tests. What does it mean for patients? We found that the study design was acceptable: 26% of men invited to take part agreed to have the test. The majority of men who were found to have an increased genetic risk of prostate cancer underwent further tests offered (prostate MRI scan and biopsy). We have now expanded the study to enrol 5000 men. The BARCODE1 study will be important in examining whether this approach could be used for large-scale population prostate cancer screening.

Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure

Background

Numerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly because the majority of single-nucleotide polymorphisms (SNPs) map to the non-coding regions of the human genome. The functional characterization of these non-coding variants and the identification of their target genes remain challenging.

Results

In this communication, we explore the potential functional mechanisms of non-coding SNPs by integrating GWAS with the high-resolution chromosome conformation capture (Hi-C) data for breast and prostate cancers. We show that more genetic variants map to regulatory elements through the 3D genome structure than the 1D linear genome lacking physical chromatin interactions. Importantly, the association of enhancers, transcription factors, and their target genes with breast and prostate cancers tends to be higher when these regulatory elements are mapped to high-risk SNPs through spatial interactions compared to simply using a linear proximity. Finally, we demonstrate that topologically associating domains (TADs) carrying high-risk SNPs also contain gene regulatory elements whose association with cancer is generally higher than those belonging to control TADs containing no high-risk variants.

Conclusions

Our results suggest that many SNPs may contribute to the cancer development by affecting the expression of certain tumor-related genes through long-range chromatin interactions with gene regulatory elements. Integrating large-scale genetic datasets with the 3D genome structure offers an attractive and unique approach to systematically investigate the functional mechanisms of genetic variants in disease risk and progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-01021-x.

Germline variant screening with targeted next generation sequencing in prostate cancer: phenotype-genotype correlation

BACKGROUND

Next generation sequencing provides new information about the molecular pathogenesis of cancer. We used a targeted NGS-based multiple gene panel comprising prostate cancer (PCa) predisposing genes to assess the prevalence of germline mutations in PCa patients.

METHODS

In a cohort of twenty-one PCa patients with a family history of cancer, a targeted multigene panel consisting of 39 genes associated with hereditary cancer was created and analyzed using the next generation sequencing method. The novel and pathogenic mutations detected were confirmed by Sanger sequencing method. Thereafter, the data obtained were evaluated using different genomic variant classifiers and databases.

RESULTS

With an incidence of less than 5% in different populations (MAF<0.05); a total of 81 variants were identified, including 41 missense, 16 synonymous, 3 splice-site, 11 intronic, 5 in-del and 5 novels. According to the ACMG criteria, 5 (6.2%) of these variants are pathogenic/likely pathogenic; 5 (6.2%) of them were classified as novel variants. In addition, variants having very low-frequency and unknown clinical significance (VUS) in the databases were detected.

Clinical Significance of Hepsin and Underlying Signaling Pathways in Prostate Cancer

The hepsin gene encodes a type II transmembrane serine protease. Previous studies have shown the overexpression of hepsin in prostate cancer, and the dysregulation of hepsin promotes cancer cell proliferation, migration, and metastasis in vitro and in vivo. The review incorporated with our work showed that hepsin expression levels were specifically increased in prostate cancer, and higher expression in metastatic tumors than in primary tumors was also observed. Moreover, increased expression was associated with poor outcomes for patients with prostate cancer. Using in silico protein–protein interaction prediction, mechanistic analysis showed that hepsin interacted with eight other oncogenic proteins, whose expression was significantly correlated with hepsin expression in prostate cancer. The oncogenic functions of hepsin are mainly linked to proteolytic activities that disrupt epithelial integrity and regulatorily interact with other genes to influence cell-proliferation, EMT/metastasis, inflammatory, and tyrosine-kinase-signaling pathways. Moreover, genomic amplifications of hepsin, not deletions or other alterations, were significantly associated with prostate cancer metastasis. Targeting hepsin using a specific inhibitor or antibodies significantly attenuates its oncogenic behaviors. Therefore, hepsin could be a novel biomarker and therapeutic target for prostate cancer.

Assessment of factors associated with PSA level in prostate cancer cases and controls from three geographical regions

It is being debated whether prostate-specific antigen (PSA)-based screening effectively reduces prostate cancer mortality. Some of the uncertainty could be related to deficiencies in the age-based PSA cut-off thresholds used in screening. Current study considered 2779 men with prostate cancer and 1606 men without a cancer diagnosis, recruited for various studies in New Zealand, US, and Taiwan. Association of PSA with demographic, lifestyle, clinical characteristics (for cases), and the aldo–keto reductase 1C3 (AKR1C3) rs12529 genetic polymorphisms were analysed using multiple linear regression and univariate modelling. Pooled multivariable analysis of cases showed that PSA was significantly associated with demographic, lifestyle, and clinical data with an interaction between ethnicity and age further modifying the association. Pooled multivariable analysis of controls data also showed that demographic and lifestyle are significantly associated with PSA level. Independent case and control analyses indicated that factors associated with PSA were specific for each cohort. Univariate analyses showed a significant age and PSA correlation among all cases and controls except for the US-European cases while genetic stratification in cases showed variability of correlation. Data suggests that unique PSA cut-off thresholds factorized with demographics, lifestyle and genetics may be more appropriate for prostate cancer screening.

Identifying prognostic signatures in the microenvironment of prostate cancer

Background

An increasing number of studies has indicated that the tumor microenvironment (TME), an important component of tumor tissue, has clinicopathological significance in predicting disease outcome and therapeutic efficacy. However, little evidence in prostate cancer (PCa) is available.

Methods

The cohort of TCGA-PRAD (n=477) was used in this study. Based on the proportion of 22 types of immune cells calculated by CIBERSORT, the TME was classified by K-means clustering and differentially expressed genes (DEGs) were determined. The TMEscore was calculated based on cluster signature genes, which were obtained from DEGs by the random forest method, and the samples were classified into two subtypes. Analyses of somatic mutation and copy number variation (CNVs) were further conducted to identify the genetic characteristics of the two subtypes. Correlation analysis was performed to explore the correlation between TMEscore and the tumor response to immune checkpoint inhibitors (ICIs) as well as the prognosis of PCa.

Results

Based on the distribution of infiltrating immune cells in the TME, we constructed the TMEscore model and classified PCa samples into high and low TMEscore groups. Survival analysis indicated that the high TMEscore group had significantly better survival outcome than the low TMEscore group. Correlation analysis showed a significantly positive correlation between TMEscore and the known prognostic factors of PCa.

Conclusions

Our study indicates that the TMEscore could be a potential prognostic biomarker in PCa. A comprehensive description of the characteristics of TME may help predict the response to therapies and provide new treatment strategies for PCa patients.

A transcriptome-wide association study identifies novel candidate susceptibility genes for prostate cancer risk

A large proportion of heritability for prostate cancer risk remains unknown. Transcriptome-wide association study combined with validation comparing overall levels will help to identify candidate genes potentially playing a role in prostate cancer development. Using data from the Genotype-Tissue Expression Project, we built genetic models to predict normal prostate tissue gene expression using the statistical framework PrediXcan, a modified version of the unified test for molecular signatures and Joint-Tissue Imputation. We applied these prediction models to the genetic data of 79 194 prostate cancer cases and 61 112 controls to investigate the associations of genetically determined gene expression with prostate cancer risk. Focusing on associated genes, we compared their expression in prostate tumor vs normal prostate tissue, compared methylation of CpG sites located at these loci in prostate tumor vs normal tissue, and assessed the correlations between the differentiated genes' expression and the methylation of corresponding CpG sites, by analyzing The Cancer Genome Atlas (TCGA) data. We identified 573 genes showing an association with prostate cancer risk at a false discovery rate (FDR) ≤ 0.05, including 451 novel genes and 122 previously reported genes. Of the 573 genes, 152 showed differential expression in prostate tumor vs normal tissue samples. At loci of 57 genes, 151 CpG sites showed differential methylation in prostate tumor vs normal tissue samples. Of these, 20 CpG sites were correlated with expression of 11 corresponding genes. In this TWAS, we identified novel candidate susceptibility genes for prostate cancer risk, providing new insights into prostate cancer genetics and biology.

Burden of Prostate Cancer in China, 1990-2019: Findings From the 2019 Global Burden of Disease Study

Our study is the first to illustrate the age and geographic distribution differences in the epidemiology of prostate cancer from 1990 to 2019 in China. Prostate cancer (PC) is a malignant tumor derived from prostate epithelial cells and is one of the most commonly diagnosed cancers in men. In recent years, the global incidence and the annual deaths number of PC showed a continuous increase, which has caused a huge disease burden on human health. In terms of the global average, the incidence and mortality of PC in China are relatively low. However, the age-standardized incidence rate of PC was 17.3/100,000 in 2019 in China, with a 95.2% rise compared to 1990, while the global growth rate of incidence rate over the same period is 13.2%. This showed that the development trend of PC in China is not optimistic. There are few precise studies on the epidemiology of PC in China. After the general analysis strategy used in the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) 2019, we elaborated on the incidence, mortality, and disability-adjusted life-years (DALYs) and the corresponding age-standardized rate of the Chinese PC population from 1990 to 2019 according to different ages and provinces. We used joinpoint regression analysis to estimate the incidence and mortality trends. Our analysis shows that elderly people over 80 are still the main focus of incidence and death. The epidemiology and disease burden of PC of different provinces in China show obvious regional differences, and some certain provinces such as HongKong, Macao, and Zhejiang should be paid more attention. More targeted and effective strategies should be developed to reduce the burden of PC in China.

Prostate Cancer Genomics Research Disparities in Africa: Advancing Knowledge in Resource Constrained Settings

Prostate cancer disproportionately affects men of African descent and it is estimated that Africa will bear the highest disease burden in the next decade. Underlying genomic factors may contribute to prostate cancer disparities; however, it is unclear whether Africa has prioritised genomics research toward addressing these disparities. A Pubmed review was performed of publications spanning a 15-year period, with specific focus on prostate cancer genomics research that included samples from Africa and investigators in Africa. Data are presented on research publications from Africa relative to similar publications from different geographical regions, and more specifically, the extent of disparities and the contributions to prostate cancer knowledge as a result of genomics research that included African samples and African institutions. Limited publication output may reflect the infrastructure and funding challenges in Africa. Widespread cooperation should be fostered by sharing capacity and leveraging existing expertise to address the growing cancer burden facing the continent.

H3K27ac HiChIP in prostate cell lines identifies risk genes for prostate cancer susceptibility

Genome-wide association studies (GWASs) have identified more than 200 prostate cancer (PrCa) risk regions, which provide potential insights into causal mechanisms. Multiple lines of evidence show that a significant proportion of PrCa risk can be explained by germline causal variants that dysregulate nearby target genes in prostate-relevant tissues, thus altering disease risk. The traditional approach to explore this hypothesis has been correlating GWAS variants with steady-state transcript levels, referred to as expression quantitative trait loci (eQTLs). In this work, we assess the utility of chromosome conformation capture (3C) coupled with immunoprecipitation (HiChIP) to identify target genes for PrCa GWAS risk loci. We find that interactome data confirm previously reported PrCa target genes identified through GWAS/eQTL overlap (e.g., MLPH). Interestingly, HiChIP identifies links between PrCa GWAS variants and genes well-known to play a role in prostate cancer biology (e.g., AR) that are not detected by eQTL-based methods. HiChIP predicted enhancer elements at the AR and NKX3-1 prostate cancer risk loci, and both were experimentally confirmed to regulate expression of the corresponding genes through CRISPR interference (CRISPRi) perturbation in LNCaP cells. Our results demonstrate that looping data harbor additional information beyond eQTLs and expand the number of PrCa GWAS loci that can be linked to candidate susceptibility genes.

Genetics of prostate cancer and its utility in treatment and screening

Prostate cancer heritability is attributed to a combination of rare, moderate to highly penetrant genetic variants as well as commonly occurring variants conferring modest risks [single nucleotide polymorphisms (SNPs)]. Some of the former type of variants (e.g., BRCA2 mutations) predispose particularly to aggressive prostate cancer and confer poorer prognoses compared to men who do not carry mutations. Molecularly targeted treatments such as PARP inhibitors have improved outcomes in men carrying somatic and/or germline DNA repair gene mutations. Ongoing clinical trials are exploring other molecular targeted approaches based on prostate cancer somatic alterations. Genome wide association studies have identified >250 loci that associate with prostate cancer risk. Multi-ancestry analyses have identified shared as well as population specific risk SNPs. Prostate cancer risk SNPs can be used to estimate a polygenic risk score (PRS) to determine an individual's genetic risk of prostate cancer. The odds ratio of prostate cancer development in men whose PRS lies in the top 1% of the risk profile ranges from 9 to 11. Ongoing studies are investigating the utility of a prostate cancer PRS to target population screening to those at highest risk. With the advent of personalized medicine and development of DNA sequencing technologies, access to clinical genetic testing is increasing, and oncology guidelines from bodies such as NCCN and ESMO have been updated to provide criteria for germline testing of "at risk" healthy men as well as those with prostate cancer. Both germline and somatic prostate cancer research have significantly evolved in the past decade and will lead to further development of precision medicine approaches to prostate cancer treatment as well as potentially developing precision population screening models.

Mechanistic insights into genetic susceptibility to prostate cancer

Prostate cancer (PCa) is the second most common cancer in men and is a highly heritable disease that affects millions of individuals worldwide. Genome-wide association studies have to date discovered nearly 270 genetic loci harboring hundreds of single nucleotide polymorphisms (SNPs) that are associated with PCa susceptibility. In contrast, the functional characterization of the mechanisms underlying PCa risk association is still growing. Given that PCa risk-associated SNPs are highly enriched in noncoding cis-regulatory genomic regions, accumulating evidence suggests a widespread modulation of transcription factor chromatin binding and allelic enhancer activity by these noncoding SNPs, thereby dysregulating gene expression. Emerging studies have shown that a proportion of noncoding variants can modulate the formation of transcription factor complexes at enhancers and CTCF-mediated 3D genome architecture. Interestingly, DNA methylation-regulated CTCF binding could orchestrate a long-range chromatin interaction between PCa risk enhancer and causative genes. Additionally, one-causal-variant-two-risk genes or multiple-risk-variant-multiple-genes are prevalent in some PCa risk-associated loci. In this review, we will discuss the current understanding of the general principles of SNP-mediated gene regulation, experimental advances, and functional evidence supporting the mechanistic roles of several PCa genetic loci with potential clinical impact on disease prevention and treatment.

Long non-coding RNAs and their potential impact on diagnosis, prognosis, and therapy in prostate cancer: racial, ethnic, and geographical considerations

INTRODUCTION

Advances in high-throughput sequencing have greatly advanced our understanding of long non-coding RNAs (lncRNAs) in a relatively short period of time. This has expanded our knowledge of cancer, particularly how lncRNAs drive many important cancer phenotypes via their regulation of gene expression.

AREAS COVERED

Men of African descent are disproportionately affected by PC in terms of incidence, morbidity, and mortality. LncRNAs could serve as biomarkers to differentiate low-risk from high-risk diseases. Additionally, they may represent therapeutic targets for advanced and castrate-resistant cancer. We review current research surrounding lncRNAs and their association with PC. We discuss how lncRNAs can provide new insights and diagnostic biomarkers for African American men. Finally, we review advances in computational approaches that predict the regulatory effects of lncRNAs in cancer.

EXPERT OPINION

PC diagnostic biomarkers that offer high specificity and sensitivity are urgently needed. PC specific lncRNAs are compelling as diagnostic biomarkers owing to their high tissue and tumor specificity and presence in bodily fluids. Recent studies indicate that PCA3 clinical utility might be restricted to men of European descent. Further work is required to develop lncRNA biomarkers tailored for men of African descent.

Association of a common genetic variant (insertion/deletion) in ACE gene with prostate cancer susceptibility in a Tunisian population

Background

Angiotensin‐converting enzyme (ACE) plays a pivotal role in several pathologies including cancers. The association of insertion/deletion (I/D) polymorphism of the ACE gene with prostate cancer (PC) risk remains controversial. We aimed to investigate for the first time, to our Knowledge, in North Africa the potential relationship between ACE I/D polymorphism with PC susceptibility and clinical outcomes of PC patients.

Methods

This case‐control study included 143 healthy individuals and 124 patients diagnosed with PC. Using genomic DNA, the samples were genotyped for ACE I/D polymorphism by polymerase chain reaction (PCR).

Results

We found that The D allele is significantly associated with an increased risk of PC and D/D + D/I genotypes were at 3 times increased risk of PC ([p = 0.005], OR = 2.95, IC 95% = 1.26–7.09) compared with I/I genotype (p = 0.003, OR = 0.3, IC 95% = 0.12–0.74). We observed an association between D/D and D/I genotypes with advanced age (≥70 years) (p = 0.014; r² = 0.22). Furthermore, there is a significant prediction of advanced Gleason score ≥8 based on epidemiological parameters and ACE genotype (p = 0.000; R² = 0.349), although no significant association was observed with stage and metastasis.

Conclusion

The ACE I/D polymorphism is likely to predispose to PC and could play a role in PC progression and aggressiveness.

Genetic Contributions to Prostate Cancer Disparities in Men of West African Descent

Prostate cancer (PCa) is the second most frequently diagnosed malignancy and the second leading cause of death in men worldwide, after adjusting for age. According to the International Agency for Research on Cancer, continents such as North America and Europe report higher incidence of PCa; however, mortality rates are highest among men of African ancestry in the western, southern, and central regions of Africa and the Caribbean. The American Cancer Society reports, African Americans (AAs), in the United States, have a 1.7 increased incidence and 2.4 times higher mortality rate, compared to European American's (EAs). Hence, early population history in west Africa and the subsequent African Diaspora may play an important role in understanding the global disproportionate burden of PCa shared among Africans and other men of African descent. Nonetheless, disparities involved in diagnosis, treatment, and survival of PCa patients has also been correlated to socioeconomic status, education and access to healthcare. Although recent studies suggest equal PCa treatments yield equal outcomes among patients, data illuminates an unsettling reality of disparities in treatment and care in both, developed and developing countries, especially for men of African descent. Yet, even after adjusting for the effects of the aforementioned factors; racial disparities in mortality rates remain significant. This suggests that molecular and genomic factors may account for much of PCa disparities.