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Saunders EJ, Kote-Jarai Z, Eeles RA. Identification of Germline Genetic Variants that Increase Prostate Cancer Risk and Influence Development of Aggressive Disease. Cancers (Basel) 2021; 13:760. [PMID: 33673083 PMCID: PMC7917798 DOI: 10.3390/cancers13040760] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 02/08/2021] [Accepted: 02/09/2021] [Indexed: 12/15/2022] Open
Abstract
Prostate cancer (PrCa) is a heterogeneous disease, which presents in individual patients across a diverse phenotypic spectrum ranging from indolent to fatal forms. No robust biomarkers are currently available to enable routine screening for PrCa or to distinguish clinically significant forms, therefore late stage identification of advanced disease and overdiagnosis plus overtreatment of insignificant disease both remain areas of concern in healthcare provision. PrCa has a substantial heritable component, and technological advances since the completion of the Human Genome Project have facilitated improved identification of inherited genetic factors influencing susceptibility to development of the disease within families and populations. These genetic markers hold promise to enable improved understanding of the biological mechanisms underpinning PrCa development, facilitate genetically informed PrCa screening programmes and guide appropriate treatment provision. However, insight remains largely lacking regarding many aspects of their manifestation; especially in relation to genes associated with aggressive phenotypes, risk factors in non-European populations and appropriate approaches to enable accurate stratification of higher and lower risk individuals. This review discusses the methodology used in the elucidation of genetic loci, genes and individual causal variants responsible for modulating PrCa susceptibility; the current state of understanding of the allelic spectrum contributing to PrCa risk; and prospective future translational applications of these discoveries in the developing eras of genomics and personalised medicine.
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Affiliation(s)
- Edward J. Saunders
- The Institute of Cancer Research, London SM2 5NG, UK; (Z.K.-J.); (R.A.E.)
| | - Zsofia Kote-Jarai
- The Institute of Cancer Research, London SM2 5NG, UK; (Z.K.-J.); (R.A.E.)
| | - Rosalind A. Eeles
- The Institute of Cancer Research, London SM2 5NG, UK; (Z.K.-J.); (R.A.E.)
- Royal Marsden NHS Foundation Trust, London SW3 6JJ, UK
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Association of germline genetic variants with TMPRSS2-ERG fusion status in prostate cancer. Oncotarget 2020; 11:1321-1333. [PMID: 32341752 PMCID: PMC7170497 DOI: 10.18632/oncotarget.27534] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 03/03/2020] [Indexed: 12/24/2022] Open
Abstract
Introduction: Oncogenic activation of ERG resulting from TMPRSS2-ERG gene fusion is a key molecular genetic alteration in prostate cancer (CaP). The frequency of ERG fusion is variable by race; however, there are limited data available on germline polymorphisms associating with ERG fusion status. The goal of this study is to identify the inherited risk variants associating with ERG status of CaP. Materials and Methods: SNP genotyping was performed on the Illumina platform using Infinium Oncoarray SNP chip on blood derived genomic DNA samples from 400 patients treated by radical prostatectomy at a single military institution. ERG status was determined in whole mounted prostate specimens by immuno-histochemistry (IHC) for ERG protein expression. Data analysis approaches included association analyses based on EMMAX and imputation by IMPUTE2. Imputed SNPs were validated by ddPCR. Results: SNP genotyping analysis using imputation identified rs34349373 (p 4.68 × 10-8) and rs2055272 (p 5.62 × 10-8) in TBC1D22B to be significantly associated with ERG fusion status in index tumor and non-index tumor foci. Imputed SNP rs2055272 was further experimentally validated by ddPCR with 98.04% (100/102) concordance. Initial discovery analysis based on SNPs on Oncoarray SNP chip, showed significant (p 10-5) association for SNPs (rs6698333, rs1889877, rs3798999, rs10215144, rs3818136, rs9380660 and rs1792695) with ERG fusion status. The study also replicated two previously known ERG fusion associated SNPs (rs11704416 in chromsome 22; rs16901979 in chromosome 8). Conclusions: This study identified SNPs associated with ERG status of CaP. Impact: The findings may contribute towards defining the underlying genetics of ERG positive and ERG negative CaP patients.
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Nyberg T, Govindasami K, Leslie G, Dadaev T, Bancroft E, Ni Raghallaigh H, Brook MN, Hussain N, Keating D, Lee A, McMahon R, Morgan A, Mullen A, Osborne A, Rageevakumar R, Kote-Jarai Z, Eeles R, Antoniou AC. Homeobox B13 G84E Mutation and Prostate Cancer Risk. Eur Urol 2019; 75:834-845. [PMID: 30527799 PMCID: PMC6470122 DOI: 10.1016/j.eururo.2018.11.015] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Accepted: 11/08/2018] [Indexed: 12/14/2022]
Abstract
BACKGROUND The homeobox B13 (HOXB13) G84E mutation has been recommended for use in genetic counselling for prostate cancer (PCa), but the magnitude of PCa risk conferred by this mutation is uncertain. OBJECTIVE To obtain precise risk estimates for mutation carriers and information on how these vary by family history and other factors. DESIGN, SETTING, AND PARTICIPANTS Two-fold: a systematic review and meta-analysis of published risk estimates, and a kin-cohort study comprising pedigree data on 11983 PCa patients enrolled during 1993-2014 from 189 UK hospitals and who had been genotyped for HOXB13 G84E. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Relative and absolute PCa risks. Complex segregation analysis with ascertainment adjustment to derive age-specific risks applicable to the population, and to investigate how these vary by family history and birth cohort. RESULTS AND LIMITATIONS A meta-analysis of case-control studies revealed significant heterogeneity between reported relative risks (RRs; range: 0.95-33.0, p<0.001) and differences by case selection (p=0.007). Based on case-control studies unselected for PCa family history, the pooled RR estimate was 3.43 (95% confidence interval [CI] 2.78-4.23). In the kin-cohort study, PCa risk for mutation carriers varied by family history (p<0.001). There was a suggestion that RRs decrease with age, but this was not significant (p=0.068). We found higher RR estimates for men from more recent birth cohorts (p=0.004): 3.09 (95% CI 2.03-4.71) for men born in 1929 or earlier and 5.96 (95% CI 4.01-8.88) for men born in 1930 or later. The absolute PCa risk by age 85 for a male HOXB13 G84E carrier varied from 60% for those with no PCa family history to 98% for those with two relatives diagnosed at young ages, compared with an average risk of 15% for noncarriers. Limitations include the reliance on self-reported cancer family history. CONCLUSIONS PCa risks for HOXB13 G84E mutation carriers are heterogeneous. Counselling should not be based on average risk estimates but on age-specific absolute risk estimates tailored to individual mutation carriers' family history and birth cohort. PATIENT SUMMARY Men who carry a hereditary mutation in the homeobox B13 (HOXB13) gene have a higher than average risk for developing prostate cancer. In our study, we examined a large number of families of men with prostate cancer recruited across UK hospitals, to assess what other factors may contribute to this risk and to assess whether we could create a precise model to help in predicting a man's prostate cancer risk. We found that the risk of developing prostate cancer in men who carry this genetic mutation is also affected by a family history of prostate cancer and their year of birth. This information can be used to assess more personalised prostate cancer risks to men who carry HOXB13 mutations and hence better counsel them on more personalised risk management options, such as tailoring prostate cancer screening frequency.
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Affiliation(s)
- Tommy Nyberg
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Koveela Govindasami
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Goska Leslie
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Tokhir Dadaev
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Elizabeth Bancroft
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK; Royal Marsden NHS Foundation Trust, London, UK
| | - Holly Ni Raghallaigh
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Mark N Brook
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Nafisa Hussain
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Diana Keating
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Andrew Lee
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Romayne McMahon
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Angela Morgan
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK; Royal Marsden NHS Foundation Trust, London, UK
| | - Andrea Mullen
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Andrea Osborne
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Reshma Rageevakumar
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Zsofia Kote-Jarai
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Rosalind Eeles
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, London, UK; Royal Marsden NHS Foundation Trust, London, UK
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
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Prostate Cancer Genomics: Recent Advances and the Prevailing Underrepresentation from Racial and Ethnic Minorities. Int J Mol Sci 2018; 19:ijms19041255. [PMID: 29690565 PMCID: PMC5979433 DOI: 10.3390/ijms19041255] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Revised: 04/15/2018] [Accepted: 04/15/2018] [Indexed: 02/07/2023] Open
Abstract
Prostate cancer (CaP) is the most commonly diagnosed non-cutaneous cancer and the second leading cause of male cancer deaths in the United States. Among African American (AA) men, CaP is the most prevalent malignancy, with disproportionately higher incidence and mortality rates. Even after discounting the influence of socioeconomic factors, the effect of molecular and genetic factors on racial disparity of CaP is evident. Earlier studies on the molecular basis for CaP disparity have focused on the influence of heritable mutations and single-nucleotide polymorphisms (SNPs). Most CaP susceptibility alleles identified based on genome-wide association studies (GWAS) were common, low-penetrance variants. Germline CaP-associated mutations that are highly penetrant, such as those found in HOXB13 and BRCA2, are usually rare. More recently, genomic studies enabled by Next-Gen Sequencing (NGS) technologies have focused on the identification of somatic mutations that contribute to CaP tumorigenesis. These studies confirmed the high prevalence of ERG gene fusions and PTEN deletions among Caucasian Americans and identified novel somatic alterations in SPOP and FOXA1 genes in early stages of CaP. Individuals with African ancestry and other minorities are often underrepresented in these large-scale genomic studies, which are performed primarily using tumors from men of European ancestry. The insufficient number of specimens from AA men and other minority populations, together with the heterogeneity in the molecular etiology of CaP across populations, challenge the generalizability of findings from these projects. Efforts to close this gap by sequencing larger numbers of tumor specimens from more diverse populations, although still at an early stage, have discovered distinct genomic alterations. These research findings can have a direct impact on the diagnosis of CaP, the stratification of patients for treatment, and can help to address the disparity in incidence and mortality of CaP. This review examines the progress of understanding in CaP genetics and genomics and highlight the need to increase the representation from minority populations.
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Ahmed M, Eeles R. Germline genetic profiling in prostate cancer: latest developments and potential clinical applications. Future Sci OA 2016; 2:FSO87. [PMID: 28031937 PMCID: PMC5137984 DOI: 10.4155/fso.15.87] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2015] [Accepted: 11/10/2015] [Indexed: 12/16/2022] Open
Abstract
Familial and twin studies have demonstrated a significant inherited component to prostate cancer predisposition. Genome wide association studies have shown that there are 100 single nucleotide polymorphisms which have been associated with the development of prostate cancer. This review aims to discuss the scientific methods used to identify these susceptibility loci. It will also examine the current clinical utility of these loci, which include the development of risk models as well as predicting treatment efficacy and toxicity. In order to refine the clinical utility of the susceptibility loci, international consortia have been developed to combine statistical power as well as skills and knowledge to further develop models that could be used to predict risk and treatment outcomes.
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Affiliation(s)
- Mahbubl Ahmed
- The Institute of Cancer Research, London SM2 5NG, UK
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6
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Pashayan N, Duffy SW, Neal DE, Hamdy FC, Donovan JL, Martin RM, Harrington P, Benlloch S, Amin Al Olama A, Shah M, Kote-Jarai Z, Easton DF, Eeles R, Pharoah PD. Implications of polygenic risk-stratified screening for prostate cancer on overdiagnosis. Genet Med 2015; 17:789-95. [PMID: 25569441 PMCID: PMC4430305 DOI: 10.1038/gim.2014.192] [Citation(s) in RCA: 72] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2014] [Accepted: 11/20/2014] [Indexed: 01/19/2023] Open
Abstract
PURPOSE This study aimed to quantify the probability of overdiagnosis of prostate cancer by polygenic risk. METHODS We calculated the polygenic risk score based on 66 known prostate cancer susceptibility variants for 17,012 men aged 50-69 years (9,404 men identified with prostate cancer and 7,608 with no cancer) derived from three UK-based ongoing studies. We derived the probabilities of overdiagnosis by quartiles of polygenic risk considering that the observed prevalence of screen-detected prostate cancer is a combination of underlying incidence, mean sojourn time (MST), test sensitivity, and overdiagnosis. RESULTS Polygenic risk quartiles 1 to 4 comprised 9, 18, 25, and 48% of the cases, respectively. For a prostate-specific antigen test sensitivity of 80% and MST of 9 years, 43, 30, 25, and 19% of the prevalent screen-detected cancers in quartiles 1 to 4, respectively, were likely to be overdiagnosed cancers. Overdiagnosis decreased with increasing polygenic risk, with 56% decrease between the lowest and the highest polygenic risk quartiles. CONCLUSION Targeting screening to men at higher polygenic risk could reduce the problem of overdiagnosis and lead to a better benefit-to-harm balance in screening for prostate cancer.
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Affiliation(s)
- Nora Pashayan
- Department of Applied Health Research, University College London, London, UK
| | - Stephen W. Duffy
- Centre for Cancer Prevention, Mathematics and Statistics, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK
| | - David E. Neal
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Freddie C. Hamdy
- Nuffield Department of Surgery, Oxford John Radcliffe Hospital, University of Oxford, Headington, Oxford, UK
| | - Jenny L. Donovan
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Richard M. Martin
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Patricia Harrington
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge, UK
| | - Sara Benlloch
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge, UK
| | - Ali Amin Al Olama
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge, UK
| | - Mitul Shah
- Department of Oncology, Strangeways Research Laboratory, University of Cambridge, Cambridge, UK
| | - Zsofia Kote-Jarai
- Division of Genetics and Epidemiology, Institute of Cancer Research & Royal Marsden NHS Foundation Trust, London, UK
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge, UK
| | - Rosalind Eeles
- Division of Genetics and Epidemiology, Institute of Cancer Research & Royal Marsden NHS Foundation Trust, London, UK
| | - Paul D. Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge, UK
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7
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Amin Al Olama A, Dadaev T, Hazelett DJ, Li Q, Leongamornlert D, Saunders EJ, Stephens S, Cieza-Borrella C, Whitmore I, Benlloch Garcia S, Giles GG, Southey MC, Fitzgerald L, Gronberg H, Wiklund F, Aly M, Henderson BE, Schumacher F, Haiman CA, Schleutker J, Wahlfors T, Tammela TL, Nordestgaard BG, Key TJ, Travis RC, Neal DE, Donovan JL, Hamdy FC, Pharoah P, Pashayan N, Khaw KT, Stanford JL, Thibodeau SN, Mcdonnell SK, Schaid DJ, Maier C, Vogel W, Luedeke M, Herkommer K, Kibel AS, Cybulski C, Wokołorczyk D, Kluzniak W, Cannon-Albright L, Brenner H, Butterbach K, Arndt V, Park JY, Sellers T, Lin HY, Slavov C, Kaneva R, Mitev V, Batra J, Clements JA, Spurdle A, Teixeira MR, Paulo P, Maia S, Pandha H, Michael A, Kierzek A, Govindasami K, Guy M, Lophatonanon A, Muir K, Viñuela A, Brown AA, Freedman M, Conti DV, Easton D, Coetzee GA, Eeles RA, Kote-Jarai Z. Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans. Hum Mol Genet 2015; 24:5589-602. [PMID: 26025378 PMCID: PMC4572072 DOI: 10.1093/hmg/ddv203] [Citation(s) in RCA: 59] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2015] [Revised: 05/26/2015] [Accepted: 05/27/2015] [Indexed: 02/02/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.
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Affiliation(s)
- Ali Amin Al Olama
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory
| | - Tokhir Dadaev
- Division of Genetics and Epidemiology, The Institute of Cancer Research & Royal Marsden NHS Foundation Trust, London, UK
| | - Dennis J Hazelett
- Department of Urology, Norris Comprehensive Cancer Center, Keck School of Medicine, USC, Los Angeles, CA, USA, Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, USC, Los Angeles, CA, USA
| | - Qiuyan Li
- Medical College, Xiamen University, Xiamen, China
| | - Daniel Leongamornlert
- Division of Genetics and Epidemiology, The Institute of Cancer Research & Royal Marsden NHS Foundation Trust, London, UK
| | - Edward J Saunders
- Division of Genetics and Epidemiology, The Institute of Cancer Research & Royal Marsden NHS Foundation Trust, London, UK
| | - Sarah Stephens
- Division of Genetics and Epidemiology, The Institute of Cancer Research & Royal Marsden NHS Foundation Trust, London, UK
| | - Clara Cieza-Borrella
- Division of Genetics and Epidemiology, The Institute of Cancer Research & Royal Marsden NHS Foundation Trust, London, UK
| | - Ian Whitmore
- Division of Genetics and Epidemiology, The Institute of Cancer Research & Royal Marsden NHS Foundation Trust, London, UK
| | - Sara Benlloch Garcia
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory
| | - Graham G Giles
- Cancer Epidemiology Centre, The Cancer Council Victoria, Melbourne, VIC, Australia, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health
| | - Melissa C Southey
- Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, VIC, Australia
| | | | - Henrik Gronberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Fredrik Wiklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Markus Aly
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden, Department of Clinical Sciences, Danderyds Hospital, Stockholm, Sweden
| | - Brian E Henderson
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, USC, Los Angeles, CA, USA
| | - Fredrick Schumacher
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, USC, Los Angeles, CA, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, USC, Los Angeles, CA, USA
| | - Johanna Schleutker
- Department of Medical Biochemistry and Genetics Institute of Biomedicine, University of Turku, Turku, Finland, BioMediTech, University of Tampere and FimLab Laboratories, Tampere, Finland
| | - Tiina Wahlfors
- BioMediTech, University of Tampere and FimLab Laboratories, Tampere, Finland
| | - Teuvo L Tammela
- Department of Urology, Tampere University Hospital and Medical School, University of Tampere, Tampere, Finland
| | - Børge G Nordestgaard
- Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Herlev, Denmark, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tim J Key
- Cancer Epidemiology, Nuffield Department of Population Health
| | - Ruth C Travis
- Cancer Epidemiology, Nuffield Department of Population Health
| | - David E Neal
- Department of Oncology, Addenbrooke's Hospital, Cancer Research UK Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK
| | - Jenny L Donovan
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Freddie C Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK, Faculty of Medical Science, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Paul Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, Strangeways Laboratory
| | - Nora Pashayan
- Centre for Cancer Genetic Epidemiology, Department of Oncology, Strangeways Laboratory, Department of Applied Health Research, University College London, London, UK
| | - Kay-Tee Khaw
- Clinical Gerontology Unit, University of Cambridge, Cambridge, UK
| | - Janet L Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA, Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | | | | | | | | | - Walther Vogel
- Institute of Human Genetics, University of Ulm, Ulm, Germany
| | - Manuel Luedeke
- Department of Urology, University Hospital Ulm, Ulm, Germany
| | - Kathleen Herkommer
- Department of Urology, Klinikum rechts der Isar der Technischen Universitaet Muenchen, Munich, Germany
| | - Adam S Kibel
- Division of Urologic Surgery, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Boston, USA
| | - Cezary Cybulski
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Dominika Wokołorczyk
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Wojciech Kluzniak
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Lisa Cannon-Albright
- Division of Genetic Epidemiology, Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA, George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, USA
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany, German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Katja Butterbach
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany, German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jong Y Park
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Thomas Sellers
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Hui-Yi Lin
- Biostatistics Program, Moffitt Cancer Center, Tampa, FL, USA
| | - Chavdar Slavov
- Department of Urology and Alexandrovska University Hospital, Medical University, Sofia, Bulgaria
| | - Radka Kaneva
- Department of Medical Chemistry and Biochemistry, Molecular Medicine Center, Medical University, Sofia, Bulgaria
| | - Vanio Mitev
- Department of Medical Chemistry and Biochemistry, Molecular Medicine Center, Medical University, Sofia, Bulgaria
| | - Jyotsna Batra
- Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Science, Queensland University of Technology, Brisbane, Australia
| | - Judith A Clements
- Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Science, Queensland University of Technology, Brisbane, Australia
| | - Amanda Spurdle
- Molecular Cancer Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Australia
| | - Manuel R Teixeira
- Department of Genetics, Portuguese Oncology Institute, Porto, Portugal, Biomedical Sciences Institute (ICBAS), University of Porto, Porto, Portugal
| | - Paula Paulo
- Department of Genetics, Portuguese Oncology Institute, Porto, Portugal
| | - Sofia Maia
- Department of Genetics, Portuguese Oncology Institute, Porto, Portugal
| | | | | | | | - Koveela Govindasami
- Division of Genetics and Epidemiology, The Institute of Cancer Research & Royal Marsden NHS Foundation Trust, London, UK
| | - Michelle Guy
- Division of Genetics and Epidemiology, The Institute of Cancer Research & Royal Marsden NHS Foundation Trust, London, UK
| | - Artitaya Lophatonanon
- Institute of Population Health, University of Manchester, Manchester, UK, Warwick Medical School, University of Warwick, Coventry, UK
| | - Kenneth Muir
- Institute of Population Health, University of Manchester, Manchester, UK, Warwick Medical School, University of Warwick, Coventry, UK
| | - Ana Viñuela
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Andrew A Brown
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway, Department of Genetic Medicine and Development, University of Geneva, Switzerland and
| | | | - David V Conti
- Department of Urology, Norris Comprehensive Cancer Center, Keck School of Medicine, USC, Los Angeles, CA, USA, Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, USC, Los Angeles, CA, USA
| | - Douglas Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory
| | - Gerhard A Coetzee
- Department of Urology, Norris Comprehensive Cancer Center, Keck School of Medicine, USC, Los Angeles, CA, USA, Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, USC, Los Angeles, CA, USA
| | - Rosalind A Eeles
- Division of Genetics and Epidemiology, The Institute of Cancer Research & Royal Marsden NHS Foundation Trust, London, UK
| | - Zsofia Kote-Jarai
- Division of Genetics and Epidemiology, The Institute of Cancer Research & Royal Marsden NHS Foundation Trust, London, UK,
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Amin Al Olama A, Benlloch S, Antoniou AC, Giles GG, Severi G, Neal DE, Hamdy FC, Donovan JL, Muir K, Schleutker J, Henderson BE, Haiman CA, Schumacher FR, Pashayan N, Pharoah PDP, Ostrander EA, Stanford JL, Batra J, Clements JA, Chambers SK, Weischer M, Nordestgaard BG, Ingles SA, Sorensen KD, Orntoft TF, Park JY, Cybulski C, Maier C, Doerk T, Dickinson JL, Cannon-Albright L, Brenner H, Rebbeck TR, Zeigler-Johnson C, Habuchi T, Thibodeau SN, Cooney KA, Chappuis PO, Hutter P, Kaneva RP, Foulkes WD, Zeegers MP, Lu YJ, Zhang HW, Stephenson R, Cox A, Southey MC, Spurdle AB, FitzGerald L, Leongamornlert D, Saunders E, Tymrakiewicz M, Guy M, Dadaev T, Little SJ, Govindasami K, Sawyer E, Wilkinson R, Herkommer K, Hopper JL, Lophatonanon A, Rinckleb AE, Kote-Jarai Z, Eeles RA, Easton DF. Risk Analysis of Prostate Cancer in PRACTICAL, a Multinational Consortium, Using 25 Known Prostate Cancer Susceptibility Loci. Cancer Epidemiol Biomarkers Prev 2015; 24:1121-9. [PMID: 25837820 PMCID: PMC4491026 DOI: 10.1158/1055-9965.epi-14-0317] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2014] [Accepted: 03/09/2015] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of prostate cancer. METHODS We genotyped 25 prostate cancer susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS). We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived age-specific absolute risks of developing prostate cancer by PRS stratum and family history. RESULTS The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4-57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2-5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). CONCLUSIONS Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. IMPACT We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs.
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Affiliation(s)
- Ali Amin Al Olama
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, United Kingdom.
| | - Sara Benlloch
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, United Kingdom
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, United Kingdom
| | - Graham G Giles
- Cancer Epidemiology Centre, the Cancer Council Victoria, Carlton, Victoria, Australia. Centre for Molecular, Environmental, Genetic, and Analytic Epidemiology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Gianluca Severi
- Cancer Epidemiology Centre, the Cancer Council Victoria, Carlton, Victoria, Australia
| | - David E Neal
- University of Cambridge, Department of Oncology, Addenbrooke's Hospital, Cambridge, United Kingdom. Cancer Research UK Cambridge Research Institute, Li Ka Shing Centre, Cambridge, United Kingdom
| | - Freddie C Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom. Faculty of Medical Science, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Jenny L Donovan
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Kenneth Muir
- The University of Manchester, Centre for Epidemiology, Institute of Population Health, Manchester, United Kingdom. University of Warwick, University House, Coventry, United Kingdom
| | - Johanna Schleutker
- Institute of Biomedical Technology/BioMediTech, University of Tampere and FimLab Laboratories, Tampere, Finland. Department of Medical Biochemistry and Genetics, University of Turku, Turku, Finland
| | - Brian E Henderson
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Centre, Los Angeles, California
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Centre, Los Angeles, California
| | - Fredrick R Schumacher
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Centre, Los Angeles, California
| | - Nora Pashayan
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, United Kingdom. University College London, Department of Applied Health Research, London, United Kingdom
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, United Kingdom
| | | | - Janet L Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Centre, Seattle, Washington. Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington
| | - Jyotsna Batra
- Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Science, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Judith A Clements
- Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Science, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Suzanne K Chambers
- Griffith Health Institute, Griffith University, Gold Coast, Queensland, Australia. Cancer Council Queensland, Brisbane, Queensland, Australia. Prostate Cancer Foundation of Australia, Sydney, Australia
| | - Maren Weischer
- Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Børge G Nordestgaard
- Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Sue A Ingles
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Centre, Los Angeles, California
| | - Karina D Sorensen
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus N, Denmark
| | - Torben F Orntoft
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus N, Denmark
| | - Jong Y Park
- Division of Cancer Prevention and Control, H. Lee Moffitt Cancer Centre, Tampa, Florida
| | - Cezary Cybulski
- International Hereditary Cancer Centre, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | | | - Thilo Doerk
- Hannover Biomedical Research School, Hannover, Germany
| | - Joanne L Dickinson
- University of Tasmania, Menzies Research Institute Tasmania, Hobart, Tasmania, Australia
| | - Lisa Cannon-Albright
- Division of Genetic Epidemiology, Department of Medicine, University of Utah School of Medicine, Salt Lake City, Utah. George E. Wahlen Department of Veterans Affairs Medical Centre, Salt Lake City, Utah
| | - Hermann Brenner
- Division of Clinical Epidemiology and Ageing Research, German Cancer Research Centre (DKFZ), Heidelberg, Germany. German Cancer Consortium (DKTK), Heidelberg, Germany
| | | | - Charnita Zeigler-Johnson
- Division of Population Sciences, Department of Medical Oncology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Tomonori Habuchi
- Department of Urology, Akita University School of Medicine, Akita, Japan
| | | | - Kathleen A Cooney
- Division of Hematology/Oncology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Pierre O Chappuis
- Divisions of Oncology and Genetic Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Pierre Hutter
- Hopital Cantonal Universitaire de Geneve, Geneva, Switzerland
| | - Radka P Kaneva
- Department of Medical Chemistry and Biochemistry, Molecular Medicine Centre, Medical University-Sofia, Sofia, Bulgaria
| | | | - Maurice P Zeegers
- Department of Complex Genetics, Cluster of Genetics and Cell Biology, NUTRIM School for Nutrition, Toxicology, and Metabolism, Maastricht University Medical Centre+, Maastricht, the Netherlands
| | - Yong-Jie Lu
- Barts Cancer Institute, Queen Mary University of London, John Vane Science Centre, London, United Kingdom
| | - Hong-Wei Zhang
- Second Military Medical University, Shanghai, P.R. China
| | - Robert Stephenson
- Division of Urology, Department of Surgery, University of Utah School of Medicine, Salt Lake City, Utah
| | - Angela Cox
- CR-UK/YCR Sheffield Cancer Research Centre, University of Sheffield, Sheffield, United Kingdom
| | - Melissa C Southey
- Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, Victoria, Australia
| | - Amanda B Spurdle
- Molecular Cancer Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - Liesel FitzGerald
- Cancer Council Victoria, Cancer Epidemiology Centre, Melbourne, Victoria, Australia
| | | | | | | | - Michelle Guy
- The Institute of Cancer Research, London, United Kingdom
| | - Tokhir Dadaev
- The Institute of Cancer Research, London, United Kingdom
| | - Sarah J Little
- The Institute of Cancer Research, London, United Kingdom
| | | | - Emma Sawyer
- The Institute of Cancer Research, London, United Kingdom
| | | | | | - John L Hopper
- Centre for Molecular, Environmental, Genetic, and Analytic Epidemiology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Aritaya Lophatonanon
- University of Warwick, University House, Coventry, United Kingdom. Institute of Biomedical Technology/BioMediTech, University of Tampere and FimLab Laboratories, Tampere, Finland
| | | | | | | | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, United Kingdom.
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Decker B, Ostrander EA. Dysregulation of the homeobox transcription factor gene HOXB13: role in prostate cancer. PHARMACOGENOMICS & PERSONALIZED MEDICINE 2014; 7:193-201. [PMID: 25206306 PMCID: PMC4157396 DOI: 10.2147/pgpm.s38117] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Prostate cancer (PC) is the most common noncutaneous cancer in men, and epidemiological studies suggest that about 40% of PC risk is heritable. Linkage analyses in hereditary PC families have identified multiple putative loci. However, until recently, identification of specific risk alleles has proven elusive. Cooney et al used linkage mapping and segregation analysis to identify a putative risk locus on chromosome 17q21-22. In search of causative variant(s) in genes from the candidate region, a novel, potentially deleterious G84E substitution in homeobox transcription factor gene HOXB13 was observed in multiple hereditary PC families. In follow-up testing, the G84E allele was enriched in cases, especially those with an early diagnosis or positive family history of disease. This finding was replicated by others, confirming HOXB13 as a PC risk gene. The HOXB13 protein plays diverse biological roles in embryonic development and terminally differentiated tissue. In tumor cell lines, HOXB13 participates in a number of biological functions, including coactivation and localization of the androgen receptor and FOXA1. However, no consensus role has emerged and many questions remain. All HOXB13 variants with a proposed role in PC risk are predicted to damage the protein and lie in domains that are highly conserved across species. The G84E variant has the strongest epidemiological support and lies in a highly conserved MEIS protein-binding domain, which binds cofactors required for activation. On the basis of epidemiological and biological data, the G84E variant likely modulates the interaction between the HOXB13 protein and the androgen receptor, as well as affecting FOXA1-mediated transcriptional programming. However, further studies of the mutated protein are required to clarify the mechanisms by which this translates into PC risk.
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Affiliation(s)
- Brennan Decker
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA ; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Elaine A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
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The genomic landscape of prostate cancer. Int J Mol Sci 2013; 14:10822-51. [PMID: 23708091 PMCID: PMC3709705 DOI: 10.3390/ijms140610822] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2013] [Revised: 05/06/2013] [Accepted: 05/09/2013] [Indexed: 12/12/2022] Open
Abstract
By the age of 80, approximately 80% of men will manifest some cancerous cells within their prostate, indicating that prostate cancer constitutes a major health burden. While this disease is clinically insignificant in most men, it can become lethal in others. The most challenging task for clinicians is developing a patient-tailored treatment in the knowledge that this disease is highly heterogeneous and that relatively little adequate prognostic tools are available to distinguish aggressive from indolent disease. Next-generation sequencing allows a description of the cancer at an unprecedented level of detail and at different levels, going from whole genome or exome sequencing to transcriptome analysis and methylation-specific immunoprecipitation, followed by sequencing. Integration of all these data is leading to a better understanding of the initiation, progression and metastatic processes of prostate cancer. Ultimately, these insights will result in a better and more personalized treatment of patients suffering from prostate cancer. The present review summarizes current knowledge on copy number changes, gene fusions, single nucleotide mutations and polymorphisms, methylation, microRNAs and long non-coding RNAs obtained from high-throughput studies.
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11
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Xu J, Sun J, Zheng SL. Prostate cancer risk-associated genetic markers and their potential clinical utility. Asian J Androl 2013; 15:314-22. [PMID: 23564047 PMCID: PMC3739659 DOI: 10.1038/aja.2013.42] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2013] [Revised: 03/16/2013] [Accepted: 03/18/2013] [Indexed: 02/02/2023] Open
Abstract
Prostate cancer (PCa) is one of the most common cancers among men in Western developed countries and its incidence has increased considerably in many other parts of the world, including China. The etiology of PCa is largely unknown but is thought to be multifactorial, where inherited genetics plays an important role. In this article, we first briefly review results from studies of familial aggregation and genetic susceptibility to PCa. We then recap key findings of rare and high-penetrance PCa susceptibility genes from linkage studies in PCa families. We devote a significant portion of this article to summarizing discoveries of common and low-penetrance PCa risk-associated single-nucleotide polymorphisms (SNPs) from genetic association studies in PCa cases and controls, especially those from genome-wide association studies (GWASs). A strong focus of this article is to review the literature on the potential clinical utility of these implicated genetic markers. Most of these published studies described PCa risk estimation using a genetic score derived from multiple risk-associated SNPs and its utility in determining the need for prostate biopsy. Finally, we comment on the newly proposed concept of genetic score; the notion is to treat it as a marker for genetic predisposition, similar to family history, rather than a diagnostic marker to discriminate PCa patients from non-cancer patients. Available evidence to date suggests that genetic score is an objective and better measurement of inherited risk of PCa than family history. Another unique feature of this article is the inclusion of genetic association studies of PCa in Chinese and Japanese populations.
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Affiliation(s)
- Jianfeng Xu
- Fudan Institute of Urology, Huashan Hospital, Fudan UniversityFudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai 200040, China.
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12
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Population-based estimate of prostate cancer risk for carriers of the HOXB13 missense mutation G84E. PLoS One 2013; 8:e54727. [PMID: 23457453 PMCID: PMC3574137 DOI: 10.1371/journal.pone.0054727] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2012] [Accepted: 12/14/2012] [Indexed: 02/07/2023] Open
Abstract
The HOXB13 missense mutation G84E (rs138213197) is associated with increased risk of prostate cancer, but the current estimate of increased risk has a wide confidence interval (width of 95% confidence interval (CI) >200-fold) so the point estimate of 20-fold increased risk could be misleading. Population-based family studies can be more informative for estimating risks for rare variants, therefore, we screened for mutations in an Australian population-based series of early-onset prostate cancer cases (probands). We found that 19 of 1,384 (1.4%) probands carried the missense mutation, and of these, six (32%) had a family history of prostate cancer. We tested the 22 relatives of carriers diagnosed from 1998 to 2008 for whom we had a DNA sample, and found seven more carriers and one obligate carrier. The age-specific incidence for carriers was estimated to be, on average, 16.4 (95% CI 2.5-107.2) times that for the population over the time frame when the relatives were at risk prior to baseline. We then estimated the age and birth year- specific cumulative risk of prostate cancer (penetrance) for carriers. For example, the penetrance for an unaffected male carrier born in 1950 was 19% (95% CI 5-46%) at age 60 years, 44% (95% CI 18-74%) at age 70 years and 60% (95% CI 30-85%) at age 80 years. Our study has provided a population-based estimate of the average risk of prostate cancer for HOXB13 missense mutation G84E carriers that can be used to guide clinical practice and research. This study has also shown that the majority of hereditary prostate cancers due to the HOXB13 missense mutation are 'sporadic' in the sense that unselected cases with the missense mutation do not typically report having a family history of prostate cancer.
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13
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[Ten years national research project "familial prostate cancer": problems in identifying risk families]. Urologe A 2011; 50:813-20. [PMID: 21461841 DOI: 10.1007/s00120-011-2552-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND The German national research project"familial prostate cancer" has been recruiting prostate cancer patients nationwide since 1999. In 2009, a comprehensive data analysis of the 25,065 families recruited was performed. Of these, 77.4% were identified as sporadic, 20.0% as familial and 2.6% as hereditary cases of prostate cancer. However, obtaining comprehensive, validated information about all relatives often fails. RESULTS The high average age of the patients, the lower life expectancy in further generations and the low number of first-degree male relatives hampers the classification of sporadic, familial and hereditary cases. Consequently we describe here that in our database the identification of 100 hereditary cases requires a recruitment of more than 5,000 patients with their families. For 100 sporadic patients with 2 first-degree male relatives without a case history 1,250 patients are needed.
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Macinnis RJ, Antoniou AC, Eeles RA, Severi G, Al Olama AA, McGuffog L, Kote-Jarai Z, Guy M, O'Brien LT, Hall AL, Wilkinson RA, Sawyer E, Ardern-Jones AT, Dearnaley DP, Horwich A, Khoo VS, Parker CC, Huddart RA, Van As N, McCredie MR, English DR, Giles GG, Hopper JL, Easton DF. A risk prediction algorithm based on family history and common genetic variants: application to prostate cancer with potential clinical impact. Genet Epidemiol 2011; 35:549-56. [PMID: 21769933 DOI: 10.1002/gepi.20605] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2011] [Revised: 05/03/2011] [Accepted: 05/31/2011] [Indexed: 01/07/2023]
Abstract
Genome wide association studies have identified several single nucleotide polymorphisms (SNPs) that are independently associated with small increments in risk of prostate cancer, opening up the possibility for using such variants in risk prediction. Using segregation analysis of population-based samples of 4,390 families of prostate cancer patients from the UK and Australia, and assuming all familial aggregation has genetic causes, we previously found that the best model for the genetic susceptibility to prostate cancer was a mixed model of inheritance that included both a recessive major gene component and a polygenic component (P) that represents the effect of a large number of genetic variants each of small effect, where . Based on published studies of 26 SNPs that are currently known to be associated with prostate cancer, we have extended our model to incorporate these SNPs by decomposing the polygenic component into two parts: a polygenic component due to the known susceptibility SNPs, , and the residual polygenic component due to the postulated but as yet unknown genetic variants, . The resulting algorithm can be used for predicting the probability of developing prostate cancer in the future based on both SNP profiles and explicit family history information. This approach can be applied to other diseases for which population-based family data and established risk variants exist.
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Affiliation(s)
- Robert J Macinnis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
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