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Assessing the contribution of rare protein-coding germline variants to prostate cancer risk and severity in 37,184 cases

Mitchell, Jonathan, Camacho, Niedzica, Shea, Patrick, Stopsack, Konrad H., Joseph, Vijai, Burren, Oliver S., Dhindsa, Ryan S., Nag, Abhishek +26 more·2025·Nature Communications
DOI 10.1038/s41467-025-56944-1PMC PMC11839991
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Abstract

To assess the contribution of rare coding germline genetic variants to prostate cancer risk and severity, we perform here a meta-analysis of 37,184 prostate cancer cases and 331,329 male controls from five cohorts with germline whole exome or genome sequencing data, and one cohort with imputed array data. At the gene level, our case-control collapsing analysis confirms associations between rare damaging variants in four genes and increased prostate cancer risk: SAMHD1, BRCA2 and ATM at the study-wide significance level (P < 1×10−8), and CHEK2 at the suggestive threshold (P < 2.6×10−6). Our case-only analysis, reveals that rare damaging variants in AOX1 are associated with more aggressive disease (OR = 2.60 [1.75–3.83], P = 1.35×10−6), as well as confirming the role of BRCA2 in determining disease severity. At the single-variant level, our study reveals that a rare missense variant in TERT is associated with substantially reduced prostate cancer risk (OR = 0.13 [0.07–0.25], P = 4.67×10−10), and confirms rare non-synonymous variants in a further three genes associated with reduced risk (ANO7, SPDL1, AR) and in three with increased risk (HOXB13, CHEK2, BIK). Altogether, this work provides deeper insights into the genetic architecture and biological basis of prostate cancer risk and severity, with potential implications for clinical risk prediction and therapeutic strategies.

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  • Clinical implementation programs have identified actionable germline variants even among men without a strong personal or family cancer history.

    “while clinical implementation programs have identified actionable germline variants even among men without a strong personal or family cancer history [17].”

    From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [17]

    The Discussion (page unavailable) describes potential clinical uses of rare germline variants but says these require further study. The Results report genetic associations, not findings from a clinical implementation program. Searches for actionable variants and personal or family cancer history found no passage establishing that such a program identified variants in men without a strong history. (LLM, conf=0.72)

    Experimental — accuracy not yet measured

  • A multicenter analysis of 37,184 cases confirmed associations between rare damaging variants in genes such as BRCA2, ATM, and CHEK2 with prostate cancer risk and severity.

    “A multicenter analysis of 37,184 cases confirmed associations between rare damaging variants in genes such as BRCA2, ATM, and CHEK2 with prostate cancer risk and severity”

    From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [17]

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  1. [2]Sung, H. et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 71, 209–249 (2021). 33538338 · DOI · Paper page
  2. [3]Rebello, R. J. et al. Prostate cancer. Nat. Rev. Dis. Primer 7, 9 (2021). 33542230 · DOI
  3. [4]Siegel, R. L., Miller, K. D. & Jemal, A. Cancer statistics, 2018. Ca. Cancer J. Clin. 68, 7–30 (2018). 29313949 · DOI
  4. [5]Mucci, L. A. et al. Familial risk and heritability of cancer among twins in Nordic countries. JAMA 315, 68–76 (2016). 26746459 PMC5498110 · DOI
  5. [6]Conti, D. V. et al. Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction. Nat. Genet. 53, 65–75 (2021). 33398198 PMC8148035 · DOI
  6. [8]Wang, A. et al. Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants. Nat. Genet. 55, 2065–2074 (2023). 37945903 PMC10841479 · DOI
  7. [9]Claussnitzer, M. et al. A brief history of human disease genetics. Nature 577, 179–189 (2020). 31915397 PMC7405896 · DOI · Paper page
  8. [10]de Bono, J. et al. Olaparib for metastatic castration-resistant prostate cancer. N. Engl. J. Med. 382, 2091–2102 (2020). 32343890 · DOI · Paper page
  9. [11]Cohen, J. C., Boerwinkle, E., Mosley, T. H. & Hobbs, H. H. Sequence variations in PCSK9, low LDL, and protection against coronary heart disease. N. Engl. J. Med. 354, 1264–1272 (2006). 16554528 · DOI · Paper page
  10. [12]Ewing, C. M. et al. Germline mutations in HOXB13 and prostate-cancer risk. N. Engl. J. Med. 366, 141–149 (2012). 22236224 PMC3779870 · DOI
  11. [13]Pritchard, C. C. et al. Inherited DNA-repair gene mutations in men with metastatic prostate cancer. N. Engl. J. Med. 375, 443–453 (2016). 27433846 PMC4986616 · DOI · Paper page
  12. [14]Yang, Z. et al. Limited overlap between genetic effects on disease susceptibility and disease survival. medRxiv 2023.10.10.23296544 10.1101/2023.10.10.23296544 (2023). PMC12513829 41028524 · DOI
  13. [15]Kurki, M. I. et al. FinnGen provides genetic insights from a well-phenotyped isolated population. Nature 613, 508–518 (2023). 36653562 PMC9849126 · DOI · Paper page
  14. [16]Bycroft, C. et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 562, 203–209 (2018). 30305743 PMC6786975 · DOI · Paper page
  15. [17]Van Hout, C. V. et al. Exome sequencing and characterization of 49,960 individuals in the UK Biobank. Nature 586, 749–756 (2020). 33087929 PMC7759458 · DOI · Paper page
  16. [18]Ziyatdinov, A. et al. Genotyping, sequencing and analysis of 140,000 adults from Mexico City. Nature 622, 784–793 (2023). 37821707 PMC10600010 · DOI
  17. [19]Tapia-Conyer, R. et al. Cohort profile: the Mexico City Prospective Study. Int. J. Epidemiol. 35, 243–249 (2006). 16556648 · DOI
  18. [20]100,000 Genomes Project Pilot Investigators. et al. 100,000 genomes pilot on rare-disease diagnosis in health care—preliminary report. N. Engl. J. Med. 385, 1868–1880 (2021). 34758253 PMC7613219 · DOI · Paper page
  19. [21]Sosinsky, A. et al. Insights for precision oncology from the integration of genomic and clinical data of 13,880 tumors from the 100,000 Genomes Cancer Programme. Nat. Med. 30, 279–289 (2024). 38200255 PMC10803271 · DOI
  20. [22]Petrovski, S. et al. An exome sequencing study to assess the role of rare genetic variation in pulmonary fibrosis. Am. J. Respir. Crit. Care Med. 196, 82–93 (2017). 28099038 PMC5519963 · DOI
  21. [23]Wang, Q. et al. Rare variant contribution to human disease in 281,104 UK Biobank exomes. Nature 597, 527–532 (2021). 34375979 PMC8458098 · DOI · Paper page
  22. [24]Kar, S. P. et al. Genome-wide analyses of 200,453 individuals yield new insights into the causes and consequences of clonal hematopoiesis. Nat. Genet. 54, 1155–1166 (2022). 35835912 PMC9355874 · DOI · Paper page
  23. [25]Wang, G., Sarkar, A., Carbonetto, P. & Stephens, M. A simple new approach to variable selection in regression, with application to genetic fine mapping. J. R. Stat. Soc. Ser. B Stat. Methodol. 82, 1273–1300 (2020). PMC10201948 37220626 · DOI · Paper page
  24. [26]Berchuck, J. E. et al. Addition of germline testing to tumor-only sequencing improves detection of pathogenic germline variants in men with advanced prostate cancer. JCO Precis. Oncol. 6, e2200329 (2022). 36103646 PMC9489164 · DOI
  25. [27]Stankovic, S. et al. Genetic links between ovarian ageing, cancer risk and de novo mutation rates. Nature. 10.1038/s41586-024-07931-x (2024). PMC11410666 39261734 · DOI
  26. [28]Burren, O. S. et al. Genetic architecture of telomere length in 462,666 UK Biobank whole-genome sequences. Nat. Genet. 10.1038/s41588-024-01884-7 (2024). 39192095 PMC11387196 · DOI
  27. [29]Codd, V. et al. Polygenic basis and biomedical consequences of telomere length variation. Nat. Genet. 53, 1425–1433 (2021). 34611362 PMC8492471 · DOI
  28. [30]Rode, L., Nordestgaard, B. G. & Bojesen, S. E. Long telomeres and cancer risk among 95 568 individuals from the general population. Int. J. Epidemiol. 45, 1634–1643 (2016). 27498151 · DOI
  29. [31]DeBoy, E. A. et al. Familial clonal hematopoiesis in a long telomere syndrome. N. Engl. J. Med. 388, 2422–2433 (2023). 37140166 PMC10501156 · DOI
  30. [32]Jones, L., Naidoo, M., Machado, L. R. & Anthony, K. The Duchenne muscular dystrophy gene and cancer. Cell. Oncol. Dordr. 44, 19–32 (2021). 33188621 PMC7906933 · DOI
  31. [33]Kaikkonen, E. et al. ANO7 is associated with aggressive prostate cancer. Int. J. Cancer 143, 2479–2487 (2018). 30157291 PMC6589920 · DOI
  32. [34]Barisic, M. et al. Spindly/CCDC99 is required for efficient chromosome congression and mitotic checkpoint regulation. Mol. Biol. Cell 21, 1968–1981 (2010). 20427577 PMC2883941 · DOI
  33. [35]Dhindsa, R. S. et al. Identification of a missense variant in SPDL1 associated with idiopathic pulmonary fibrosis. Commun. Biol. 4, 392 (2021). 33758299 PMC7988141 · DOI
  34. [36]Vancheri, C. Common pathways in idiopathic pulmonary fibrosis and cancer. Eur. Respir. Rev. J. Eur. Respir. Soc. 22, 265–272 (2013). PMC9487347 23997054 · DOI
  35. [37]Chen, Y., Clegg, N. J. & Scher, H. I. Anti-androgens and androgen-depleting therapies in prostate cancer: new agents for an established target. Lancet Oncol. 10, 981–991 (2009). 19796750 PMC2935850 · DOI
  36. [38]Darst, B. F. et al. Germline sequencing analysis to inform clinical gene panel testing for aggressive prostate cancer. JAMA Oncol. 9, 1514–1524 (2023). 37733366 PMC10881219 · DOI
  37. [39]Kote-Jarai, Z. et al. Prevalence of the HOXB13 G84E germline mutation in British men and correlation with prostate cancer risk, tumour characteristics and clinical outcomes. Ann. Oncol. J. Eur. Soc. Med. Oncol. 26, 756–761 (2015). 25595936 · DOI
  38. [40]Li, W. et al. Genome-wide scan identifies role for AOX1 in prostate cancer survival. Eur. Urol. 74, 710–719 (2018). 30289108 PMC6287611 · DOI
  39. [41]Wojcik, G. L. et al. Opportunities and challenges for the use of common controls in sequencing studies. Nat. Rev. Genet. 23, 665–679 (2022). 35581355 PMC9765323 · DOI
  40. [42]Povysil, G. et al. Assessing the role of rare genetic variation in patients with heart failure. JAMA Cardiol. 6, 379–386 (2021). 33326012 PMC7745141 · DOI
  41. [43]Stopsack, K. H. et al. Germline DNA damage repair variants and prognosis of patients with high-risk or metastatic prostate cancer. Clin. Cancer Res. J. Am. Assoc. Cancer Res. 31, 122–129 (2025). PMC12407385 39450704 · DOI
  42. [44]Giovannucci, E., Liu, Y., Platz, E. A., Stampfer, M. J. & Willett, W. C. Risk factors for prostate cancer incidence and progression in the health professionals follow-up study. Int. J. Cancer 121, 1571–1578 (2007). 17450530 PMC2430098 · DOI
  43. [45]Oh, W. K. et al. Development of an integrated prostate cancer research information system. Clin. Genitourin Cancer 5, 61–66 (2006). 16859581 · DOI
  44. [46]Backman, J. D. et al. Exome sequencing and analysis of 454,787 UK Biobank participants. Nature 599, 628–634 (2021). 34662886 PMC8596853 · DOI
  45. [47]Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 6, 80–92 (2012). 22728672 PMC3679285 · DOI · Paper page
  46. [48]Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020). 32461654 PMC7334197 · DOI · Paper page
  47. [49]Rimmer, A. et al. Integrating mapping-, assembly- and haplotype-based approaches for calling variants in clinical sequencing applications. Nat. Genet. 46, 912–918 (2014). 25017105 PMC4753679 · DOI
  48. [50]McLaren, W. et al. The ensembl variant effect predictor. Genome Biol. 17, 122 (2016). 27268795 PMC4893825 · DOI · Paper page
  49. [51]Nag, A. et al. Human genetics uncovers MAP3K15 as an obesity-independent therapeutic target for diabetes. Sci. Adv. 8, eadd5430 (2022). 36383675 PMC9668288 · DOI · Paper page
  50. [52]Manichaikul, A. et al. Robust relationship inference in genome-wide association studies. Bioinformatics 26, 2867–2873 (2010). 20926424 PMC3025716 · DOI · Paper page
  51. [53]Pedersen, B. S. & Quinlan, A. R. Who’s who? Detecting and resolving sample anomalies in human DNA sequencing studies with peddy. Am. J. Hum. Genet. 100, 406–413 (2017). 28190455 PMC5339084 · DOI · Paper page
  52. [55]Willer, C. J., Li, Y. & Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010). 20616382 PMC2922887 · DOI · Paper page

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Authors
Mitchell, J., Camacho, N., Shea, P., Stopsack, K. H., Joseph, V., Burren, O. S., Dhindsa, R. S., Nag, A., Berchuck, J. E., O’Neill, A., Abbasi, A., Zoghbi, A. W., Alegre-Díaz, J., Kuri-Morales, P., Berumen, J., Tapia-Conyer, R., Emberson, J., Torres, J. M., Collins, R., Wang, Q., Goldstein, D., Matakidou, A., Haefliger, C., Anderson-Dring, L., March, R., Jobanputra, V., Dougherty, B., Carss, K., Petrovski, S., Kantoff, P. W., Offit, K., Mucci, L. A., Pomerantz, M., & Fabre, M. A.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2025-02-19
Volume
16
Issue
1
ISSN
2041-1723
DOI
10.1038/s41467-025-56944-1
PMC
PMC11839991
Cited by
16
References
2
Language
en
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