Displaying all 15 publications

Abstract:
Sort:
  1. Salmon C, Song L, Muir K, UKGPCS Collaborators, Pashayan N, Dunning AM, et al.
    Eur J Epidemiol, 2021 Sep;36(9):913-925.
    PMID: 34275018 DOI: 10.1007/s10654-021-00781-1
    While being in a committed relationship is associated with a better prostate cancer prognosis, little is known about how marital status relates to its incidence. Social support provided by marriage/relationship could promote a healthy lifestyle and an increased healthcare seeking behavior. We investigated the association between marital status and prostate cancer risk using data from the PRACTICAL Consortium. Pooled analyses were conducted combining 12 case-control studies based on histologically-confirmed incident prostate cancers and controls with information on marital status prior to diagnosis/interview. Marital status was categorized as married/partner, separated/divorced, single, or widowed. Tumours with Gleason scores ≥ 8 defined high-grade cancers, and low-grade otherwise. NCI-SEER's summary stages (local, regional, distant) indicated the extent of the cancer. Logistic regression was used to derive odds ratios (ORs) and 95% confidence intervals (CI) for the association between marital status and prostate cancer risk, adjusting for potential confounders. Overall, 14,760 cases and 12,019 controls contributed to analyses. Compared to men who were married/with a partner, widowed men had an OR of 1.19 (95% CI 1.03-1.35) of prostate cancer, with little difference between low- and high-grade tumours. Risk estimates among widowers were 1.14 (95% CI 0.97-1.34) for local, 1.53 (95% CI 1.22-1.92) for regional, and 1.56 (95% CI 1.05-2.32) for distant stage tumours. Single men had elevated risks of high-grade cancers. Our findings highlight elevated risks of incident prostate cancer among widowers, more often characterized by tumours that had spread beyond the prostate at the time of diagnosis. Social support interventions and closer medical follow-up in this sub-population are warranted.
  2. Brandão A, Paulo P, Maia S, Pinheiro M, Peixoto A, Cardoso M, et al.
    Cancers (Basel), 2020 Nov 04;12(11).
    PMID: 33158149 DOI: 10.3390/cancers12113254
    The identification of recurrent founder variants in cancer predisposing genes may have important implications for implementing cost-effective targeted genetic screening strategies. In this study, we evaluated the prevalence and relative risk of the CHEK2 recurrent variant c.349A>G in a series of 462 Portuguese patients with early-onset and/or familial/hereditary prostate cancer (PrCa), as well as in the large multicentre PRACTICAL case-control study comprising 55,162 prostate cancer cases and 36,147 controls. Additionally, we investigated the potential shared ancestry of the carriers by performing identity-by-descent, haplotype and age estimation analyses using high-density SNP data from 70 variant carriers belonging to 11 different populations included in the PRACTICAL consortium. The CHEK2 missense variant c.349A>G was found significantly associated with an increased risk for PrCa (OR 1.9; 95% CI: 1.1-3.2). A shared haplotype flanking the variant in all carriers was identified, strongly suggesting a common founder of European origin. Additionally, using two independent statistical algorithms, implemented by DMLE+2.3 and ESTIAGE, we were able to estimate the age of the variant between 2300 and 3125 years. By extending the haplotype analysis to 14 additional carrier families, a shared core haplotype was revealed among all carriers matching the conserved region previously identified in the high-density SNP analysis. These findings are consistent with CHEK2 c.349A>G being a founder variant associated with increased PrCa risk, suggesting its potential usefulness for cost-effective targeted genetic screening in PrCa families.
  3. Huynh-Le MP, Karunamuni R, Fan CC, Asona L, Thompson WK, Martinez ME, et al.
    Prostate Cancer Prostatic Dis, 2022 Apr;25(4):755-761.
    PMID: 35152271 DOI: 10.1038/s41391-022-00497-7
    BACKGROUND: Prostate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets.

    METHODS: In total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry-the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured.

    RESULTS: The final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43-15.16] in ProtecT, 7.07 [6.58-7.60] in African ancestry, 10.31 [9.58-11.11] in Asian ancestry, and 11.18 [10.34-12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11-0.14). For the top 20% and top 5% of PHS290, the PPV of PSA testing was 0.19 (0.15-0.22) and 0.26 (0.19-0.33), respectively.

    CONCLUSIONS: We demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in diverse populations.

  4. Karunamuni RA, Huynh-Le MP, Fan CC, Thompson W, Eeles RA, Kote-Jarai Z, et al.
    Prostate Cancer Prostatic Dis, 2021 Jun;24(2):532-541.
    PMID: 33420416 DOI: 10.1038/s41391-020-00311-2
    BACKGROUND: Polygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46).

    MATERIALS AND METHOD: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.

    RESULTS: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.

    CONCLUSIONS: Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.

  5. Huynh-Le MP, Fan CC, Karunamuni R, Thompson WK, Martinez ME, Eeles RA, et al.
    Nat Commun, 2021 02 23;12(1):1236.
    PMID: 33623038 DOI: 10.1038/s41467-021-21287-0
    Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS1) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS2 (PHS1, adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS2 is associated with age at diagnosis of any and aggressive (Gleason score ≥ 7, stage T3-T4, PSA ≥ 10 ng/mL, or nodal/distant metastasis) cancer and prostate-cancer-specific death. Associations with cancer are significant within European (n = 71,856), Asian (n = 2,382), and African (n = 6,253) genetic ancestries (p 
  6. Machiela MJ, Hofmann JN, Carreras-Torres R, Brown KM, Johansson M, Wang Z, et al.
    Eur Urol, 2017 Nov;72(5):747-754.
    PMID: 28797570 DOI: 10.1016/j.eururo.2017.07.015
    BACKGROUND: Relative telomere length in peripheral blood leukocytes has been evaluated as a potential biomarker for renal cell carcinoma (RCC) risk in several studies, with conflicting findings.

    OBJECTIVE: We performed an analysis of genetic variants associated with leukocyte telomere length to assess the relationship between telomere length and RCC risk using Mendelian randomization, an approach unaffected by biases from temporal variability and reverse causation that might have affected earlier investigations.

    DESIGN, SETTING, AND PARTICIPANTS: Genotypes from nine telomere length-associated variants for 10 784 cases and 20 406 cancer-free controls from six genome-wide association studies (GWAS) of RCC were aggregated into a weighted genetic risk score (GRS) predictive of leukocyte telomere length.

    OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) relating the GRS and RCC risk were computed in individual GWAS datasets and combined by meta-analysis.

    RESULTS AND LIMITATIONS: Longer genetically inferred telomere length was associated with an increased risk of RCC (OR=2.07 per predicted kilobase increase, 95% confidence interval [CI]:=1.70-2.53, p<0.0001). As a sensitivity analysis, we excluded two telomere length variants in linkage disequilibrium (R2>0.5) with GWAS-identified RCC risk variants (rs10936599 and rs9420907) from the telomere length GRS; despite this exclusion, a statistically significant association between the GRS and RCC risk persisted (OR=1.73, 95% CI=1.36-2.21, p<0.0001). Exploratory analyses for individual histologic subtypes suggested comparable associations with the telomere length GRS for clear cell (N=5573, OR=1.93, 95% CI=1.50-2.49, p<0.0001), papillary (N=573, OR=1.96, 95% CI=1.01-3.81, p=0.046), and chromophobe RCC (N=203, OR=2.37, 95% CI=0.78-7.17, p=0.13).

    CONCLUSIONS: Our investigation adds to the growing body of evidence indicating some aspect of longer telomere length is important for RCC risk.

    PATIENT SUMMARY: Telomeres are segments of DNA at chromosome ends that maintain chromosomal stability. Our study investigated the relationship between genetic variants associated with telomere length and renal cell carcinoma risk. We found evidence suggesting individuals with inherited predisposition to longer telomere length are at increased risk of developing renal cell carcinoma.

  7. Fu YP, Kohaar I, Moore LE, Lenz P, Figueroa JD, Tang W, et al.
    Cancer Res, 2014 Oct 15;74(20):5808-18.
    PMID: 25320178 DOI: 10.1158/0008-5472.CAN-14-1531
    A genome-wide association study (GWAS) of bladder cancer identified a genetic marker rs8102137 within the 19q12 region as a novel susceptibility variant. This marker is located upstream of the CCNE1 gene, which encodes cyclin E, a cell-cycle protein. We performed genetic fine-mapping analysis of the CCNE1 region using data from two bladder cancer GWAS (5,942 cases and 10,857 controls). We found that the original GWAS marker rs8102137 represents a group of 47 linked SNPs (with r(2) ≥ 0.7) associated with increased bladder cancer risk. From this group, we selected a functional promoter variant rs7257330, which showed strong allele-specific binding of nuclear proteins in several cell lines. In both GWASs, rs7257330 was associated only with aggressive bladder cancer, with a combined per-allele OR = 1.18 [95% confidence interval (CI), 1.09-1.27, P = 4.67 × 10(-5)] versus OR = 1.01 (95% CI, 0.93-1.10, P = 0.79) for nonaggressive disease, with P = 0.0015 for case-only analysis. Cyclin E protein expression analyzed in 265 bladder tumors was increased in aggressive tumors (P = 0.013) and, independently, with each rs7257330-A risk allele (P(trend) = 0.024). Overexpression of recombinant cyclin E in cell lines caused significant acceleration of cell cycle. In conclusion, we defined the 19q12 signal as the first GWAS signal specific for aggressive bladder cancer. Molecular mechanisms of this genetic association may be related to cyclin E overexpression and alteration of cell cycle in carriers of CCNE1 risk variants. In combination with established bladder cancer risk factors and other somatic and germline genetic markers, the CCNE1 variants could be useful for inclusion into bladder cancer risk prediction models.
  8. Figueroa JD, Middlebrooks CD, Banday AR, Ye Y, Garcia-Closas M, Chatterjee N, et al.
    Hum Mol Genet, 2016 Mar 15;25(6):1203-14.
    PMID: 26732427 DOI: 10.1093/hmg/ddv492
    Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P < 1 × 10(-6)), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.2 (P = 2.19 × 10(-11)) and rs4907479 within the MCF2L gene at 13q34 (P = 3.3 × 10(-10)). Imputation and fine-mapping analyses were performed in these two regions for a subset of 5551 bladder cancer cases and 10 242 controls. Analyses at the 13q34 region suggest a single signal marked by rs4907479. In contrast, we detected two signals in the 20p12.2 region-the first signal is marked by rs6104690, and the second signal is marked by two moderately correlated SNPs (r(2) = 0.53), rs6108803 and the previously reported rs62185668. The second 20p12.2 signal is more strongly associated with the risk of muscle-invasive (T2-T4 stage) compared with non-muscle-invasive (Ta, T1 stage) bladder cancer (case-case P ≤ 0.02 for both rs62185668 and rs6108803). Functional analyses are needed to explore the biological mechanisms underlying these novel genetic associations with risk for bladder cancer.
  9. Dadaev T, Saunders EJ, Newcombe PJ, Anokian E, Leongamornlert DA, Brook MN, et al.
    Nat Commun, 2018 06 11;9(1):2256.
    PMID: 29892050 DOI: 10.1038/s41467-018-04109-8
    Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
  10. Schumacher FR, Al Olama AA, Berndt SI, Benlloch S, Ahmed M, Saunders EJ, et al.
    Nat Genet, 2018 07;50(7):928-936.
    PMID: 29892016 DOI: 10.1038/s41588-018-0142-8
    Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.
  11. Schumacher FR, Olama AAA, Berndt SI, Benlloch S, Ahmed M, Saunders EJ, et al.
    Nat Genet, 2019 02;51(2):363.
    PMID: 30622367 DOI: 10.1038/s41588-018-0330-6
    In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.
  12. Conti DV, Darst BF, Moss LC, Saunders EJ, Sheng X, Chou A, et al.
    Nat Genet, 2021 Jan;53(1):65-75.
    PMID: 33398198 DOI: 10.1038/s41588-020-00748-0
    Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.
  13. Wang A, Shen J, Rodriguez AA, Saunders EJ, Chen F, Janivara R, et al.
    Nat Genet, 2023 Dec;55(12):2065-2074.
    PMID: 37945903 DOI: 10.1038/s41588-023-01534-4
    The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links