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Cioffi A, De Cobelli O, Veronesi P, La Vecchia C, Maisonneuve P, Corso G. Prevalence of Germline BRCA1/2 Variants in Ashkenazi and Non-Ashkenazi Prostate Cancer Populations: A Systematic Review and Meta-Analysis. Cancers (Basel) 2023; 15:cancers15010306. [PMID: 36612302 PMCID: PMC9818251 DOI: 10.3390/cancers15010306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 12/27/2022] [Accepted: 12/29/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND AND AIMS International guidelines recommend testing BRCA2 in men with prostate cancer, due to the presence of a strong association with this gene. Some ethnicities present disparities in genetic distribution for the relation with specific founder variants. Ashkenazi Jewish people are, importantly, at high risk of breast cancer for their inherited cluster with germline BRCA1/2 variants. However, in Ashkenazi men with prostate cancer, the prevalence of BRCA1 and/or BRCA2 is not well defined. We assessed the frequency of these variants in Ashkenazi vs. non-Ashkenazi men with prostate cancer. Materials and Methods: In accord with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, we revised all germline BRCA variants reported in MEDLINE from 1996 to 2021 in Ashkenazi and non-Ashkenazi men with prostate cancer. Results: Thirty-five original studies were selected for the analysis. Among populations from Israel and North America, Ashkenazi Jewish men presented higher prevalence of BRCA1 variants [0.9% (0.4-1.5) vs. 0.5% (0.2-1.1), p = 0.09] and a lower prevalence of BRCA2 variants [1.5% (1.1-2.0) vs. 3.5% (1.7-5.9), p = 0.08] in comparison to the non-Ashkenazi population. Conclusions: Since germline BRCA1 variants are more prevalent and BRCA2 variants are less prevalent in PCa patients of Ashkenazi Jewish ethnicity in comparison to non-Ashkenazi patients, prostate cancer genetic screening in Ashkenazi men should not be restricted to the BRCA2 gene.
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Affiliation(s)
- Antonio Cioffi
- Division of Urology, European Institute of Oncology (IEO), IRCCS, 20141 Milan, Italy
| | - Ottavio De Cobelli
- Division of Urology, European Institute of Oncology (IEO), IRCCS, 20141 Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy
| | - Paolo Veronesi
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy
- Division of Breast Surgery, European Institute of Oncology (IEO), IRCCS, 20141 Milan, Italy
| | - Carlo La Vecchia
- Department of Clinical Sciences and Community Health, University of Milan, 20122 Milan, Italy
| | - Patrick Maisonneuve
- Division of Epidemiology and Biostatistics, European Institute of Oncology (IEO), IRCCS, 20141 Milan, Italy
| | - Giovanni Corso
- Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy
- Division of Breast Surgery, European Institute of Oncology (IEO), IRCCS, 20141 Milan, Italy
- European Cancer Prevention Organization (ECP), 20122 Milan, Italy
- Correspondence: ; Tel.: +39-02-9437-5161
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El Hadi C, Ayoub G, Bachir Y, Haykal M, Jalkh N, Kourie HR. Polygenic and Network-Based Studies in Risk Identification and Demystification of cancer. Expert Rev Mol Diagn 2022; 22:427-438. [PMID: 35400274 DOI: 10.1080/14737159.2022.2065195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Diseases were initially thought to be the consequence of a single gene mutation. Advances in DNA sequencing tools and our understanding of gene behavior have revealed that complex diseases, such as cancer, are the product of genes cooperating with each other and with their environment in orchestrated communication networks. Seeing that the function of individual genes is still used to analyze cancer, the shift to using functionally interacting groups of genes as a new unit of study holds promise for demystifying cancer. AREAS COVERED The literature search focused on three types of cancer, namely breast, lung, and prostate, but arguments from other cancers were also included. The aim was to prove that multigene analyses can accurately predict and prognosticate cancer risk, subtype cancer for more personalized and effective treatments, and discover anti-cancer therapies. Computational intelligence is being harnessed to analyze this type of data and is proving indispensable to scientific progress. EXPERT OPINION In the future, comprehensive profiling of all kinds of patient data (e.g., serum molecules, environmental exposures) can be used to build universal networks that should help us elucidate the molecular mechanisms underlying diseases and provide appropriate preventive measures, ensuring lifelong health and longevity.
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Affiliation(s)
| | - George Ayoub
- Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
| | - Yara Bachir
- Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
| | - Michèle Haykal
- Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
| | - Nadine Jalkh
- Medical Genetics Unit, Technology and Health division, Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
| | - Hampig Raphael Kourie
- Department of Hematology-Oncology, Hotel Dieu de France University Hospital, Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
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3
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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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4
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Zhen JT, Syed J, Nguyen KA, Leapman MS, Agarwal N, Brierley K, Llor X, Hofstatter E, Shuch B. Genetic testing for hereditary prostate cancer: Current status and limitations. Cancer 2018; 124:3105-3117. [PMID: 29669169 DOI: 10.1002/cncr.31316] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Accepted: 12/06/2017] [Indexed: 12/22/2022]
Abstract
A significant proportion of prostate cancer diagnoses may be associated with a strong hereditary component. Men who have multiple single-gene polymorphisms and a family history of prostate cancer have a significantly greater risk of developing prostate cancer. Numerous single-gene alterations have been confirmed to increase the risk of prostate cancer. These include breast cancer genes 1 and 2 (BRCA1 and BRCA2, respectively), mutL homolog 1 (MLH1), mutS homologs 2 and 6 (MSH2 and MSH6, respectively), postmeiotic segregation increased 2 (PMS2), homeobox B13 (HOXB13), checkpoint kinase 2 (CHEK2), nibrin (NBN), BRCA1-interacting protein C-terminal helicase 1 (BRIP1), and ataxia telangiectasia mutated (ATM). Currently, there are no uniform guidelines on the definition of hereditary prostate cancer and genetic testing. With the advent of next-generation sequencing, which is capable of testing multiple genes simultaneously, and the approval of olaparib for BRCA1/BRCA2 or ATM-mutated, metastatic, castrate-resistant prostate cancer, it is being recognized that the results of genetic testing have an impact on therapeutic strategies. In this review, the authors examine the role of genetic counseling and testing, the challenges of insurance coverage for testing, the available germline and somatic testing panels, and the complexity of each testing method and its implications. Cancer 2018. © 2018 American Cancer Society.
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Affiliation(s)
- Jun Tu Zhen
- Frank H. Netter School of Medicine at Quinnipiac University, North Haven, Connecticut.,Department of Urology, Yale School of Medicine, New Haven, Connecticut
| | - Jamil Syed
- Department of Urology, Yale School of Medicine, New Haven, Connecticut
| | - Kevin Anh Nguyen
- Department of Urology, Yale School of Medicine, New Haven, Connecticut
| | - Michael S Leapman
- Department of Urology, Yale School of Medicine, New Haven, Connecticut
| | - Neeraj Agarwal
- Huntsman Cancer Center, University of Utah School of Medicine, Salt Lake City, Utah
| | - Karina Brierley
- Cancer Genetics and Prevention Program, Smilow Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Xavier Llor
- Cancer Genetics and Prevention Program, Smilow Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Erin Hofstatter
- Cancer Genetics and Prevention Program, Smilow Cancer Center, Yale School of Medicine, New Haven, Connecticut
| | - Brian Shuch
- Department of Urology, Yale School of Medicine, New Haven, Connecticut.,Cancer Genetics and Prevention Program, Smilow Cancer Center, Yale School of Medicine, New Haven, Connecticut
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5
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Hao Q, Wei D, Zhang Y, Chen X, Yang F, Yang Z, Zhu X, Wang J. Systematic meta-analyses of gene-specific genetic association studies in prostate cancer. Oncotarget 2017; 7:22271-84. [PMID: 26967244 PMCID: PMC5008361 DOI: 10.18632/oncotarget.7926] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2015] [Accepted: 02/23/2016] [Indexed: 12/19/2022] Open
Abstract
In the past twenty-five years, over 700 case-control association studies on the risk of prostate cancer have been published worldwide, but their results were largely inconsistent. To facilitate following and explaining these findings, we performed a systematic meta-analysis using allelic contrasts for gene-specific SNVs from at least three independent population-based case-control studies, which were published in the field of prostate cancer between August 1, 1990 and August 1, 2015. Across 66 meta-analyses, a total of 20 genetic variants involving 584,100 subjects in 19 different genes (KLK3, IGFBP3, ESR1, SOD2, CAT, CYP1B1, VDR, RFX6, HNF1B, SRD5A2, FGFR4, LEP, HOXB13, FAS, FOXP4, SLC22A3, LMTK2, EHBP1 and MSMB) exhibited significant association with prostate cancer. The average summary OR was 1.33 (ranging from: 1.016–3.788) for risk alleles and 0.838 (ranging from: 0.757–0.896) for protective alleles. Of these positive variants, FOXP4 rs1983891, LMTK2 rs6465657 and RFX6 rs339331 had not been previously meta-analyzed. Further analyses with sufficient power design and investigations of the potential biological roles of these genetic variants in prostate cancer should be conducted.
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Affiliation(s)
- Qiang Hao
- Graduate School of Peking Union Medical College, Beijing, 100730, China.,Department of Urology, Beijing Hospital, Beijing, 100730, China.,Key Laboratory of Geriatrics, Beijing Hospital and Beijing Institute of Geriatrics, Ministry of Health, Beijing, 100730, China
| | - Dong Wei
- Department of Urology, Beijing Hospital, Beijing, 100730, China
| | - Yaoguang Zhang
- Department of Urology, Beijing Hospital, Beijing, 100730, China
| | - Xin Chen
- Department of Urology, Beijing Hospital, Beijing, 100730, China
| | - Fan Yang
- Key Laboratory of Geriatrics, Beijing Hospital and Beijing Institute of Geriatrics, Ministry of Health, Beijing, 100730, China
| | - Ze Yang
- Key Laboratory of Geriatrics, Beijing Hospital and Beijing Institute of Geriatrics, Ministry of Health, Beijing, 100730, China
| | - Xiaoquan Zhu
- Key Laboratory of Geriatrics, Beijing Hospital and Beijing Institute of Geriatrics, Ministry of Health, Beijing, 100730, China
| | - Jianye Wang
- Graduate School of Peking Union Medical College, Beijing, 100730, China.,Department of Urology, Beijing Hospital, Beijing, 100730, China.,Key Laboratory of Geriatrics, Beijing Hospital and Beijing Institute of Geriatrics, Ministry of Health, Beijing, 100730, China
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6
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Abstract
Although prostate cancer is the most common malignancy to affect men in the Western world, the molecular mechanisms underlying its development and progression remain poorly understood. Like all cancers, prostate cancer is a genetic disease that is characterized by multiple genomic alterations, including point mutations, microsatellite variations, and chromosomal alterations such as translocations, insertions, duplications, and deletions. In prostate cancer, but not other carcinomas, these chromosome alterations result in a high frequency of gene fusion events. The development and application of novel high-resolution technologies has significantly accelerated the detection of genomic alterations, revealing the complex nature and heterogeneity of the disease. The clinical heterogeneity of prostate cancer can be partly explained by this underlying genetic heterogeneity, which has been observed between patients from different geographical and ethnic populations, different individuals within these populations, different tumour foci within the same patient, and different cells within the same tumour focus. The highly heterogeneous nature of prostate cancer provides a real challenge for clinical disease management and a detailed understanding of the genetic alterations in all cells, including small subpopulations, would be highly advantageous.
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7
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Eeles R, Goh C, Castro E, Bancroft E, Guy M, Al Olama AA, Easton D, Kote-Jarai Z. The genetic epidemiology of prostate cancer and its clinical implications. Nat Rev Urol 2014; 11:18-31. [PMID: 24296704 DOI: 10.1038/nrurol.2013.266] [Citation(s) in RCA: 178] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Worldwide, familial and epidemiological studies have generated considerable evidence of an inherited component to prostate cancer. Indeed, rare highly penetrant genetic mutations have been implicated. Genome-wide association studies (GWAS) have also identified 76 susceptibility loci associated with prostate cancer risk, which occur commonly but are of low penetrance. However, these mutations interact multiplicatively, which can result in substantially increased risk. Currently, approximately 30% of the familial risk is due to such variants. Evaluating the functional aspects of these variants would contribute to our understanding of prostate cancer aetiology and would enable population risk stratification for screening. Furthermore, understanding the genetic risks of prostate cancer might inform predictions of treatment responses and toxicities, with the goal of personalized therapy. However, risk modelling and clinical translational research are needed before we can translate risk profiles generated from these variants into use in the clinical setting for targeted screening and treatment.
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Affiliation(s)
- Rosalind Eeles
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
| | - Chee Goh
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
| | - Elena Castro
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
| | - Elizabeth Bancroft
- Clinical Academic Cancer Genetics Unit, The Royal Marsden NHS Foundation Trust, Sutton, Surrey SM2 5PT, UK
| | - Michelle Guy
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
| | - Ali Amin Al Olama
- Cancer Research UK Centre for Cancer Genetic Epidemiology, Strangeways Laboratory, University of Cambridge, Cambridge CB1 8RN, UK
| | - Douglas Easton
- Departments of Public Health & Primary Care and Oncology, Strangeways Laboratory, University of Cambridge, Cambridge CB1 8RN, UK
| | - Zsofia Kote-Jarai
- Oncogenetics Team, Division of Cancer Genetics and Epidemiology, The Institute of Cancer Research, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
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8
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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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9
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Bailey-Wilson JE, Childs EJ, Cropp CD, Schaid DJ, Xu J, Camp NJ, Cannon-Albright LA, Farnham JM, George A, Powell I, Carpten JD, Giles GG, Hopper JL, Severi G, English DR, Foulkes WD, Mæhle L, Møller P, Eeles R, Easton D, Guy M, Edwards S, Badzioch MD, Whittemore AS, Oakley-Girvan I, Hsieh CL, Dimitrov L, Stanford JL, Karyadi DM, Deutsch K, McIntosh L, Ostrander EA, Wiley KE, Isaacs SD, Walsh PC, Thibodeau SN, McDonnell SK, Hebbring S, Lange EM, Cooney KA, Tammela TLJ, Schleutker J, Maier C, Bochum S, Hoegel J, Grönberg H, Wiklund F, Emanuelsson M, Cancel-Tassin G, Valeri A, Cussenot O, Isaacs WB. Analysis of Xq27-28 linkage in the international consortium for prostate cancer genetics (ICPCG) families. BMC MEDICAL GENETICS 2012; 13:46. [PMID: 22712434 PMCID: PMC3495053 DOI: 10.1186/1471-2350-13-46] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2011] [Accepted: 04/30/2012] [Indexed: 11/20/2022]
Abstract
BACKGROUND Genetic variants are likely to contribute to a portion of prostate cancer risk. Full elucidation of the genetic etiology of prostate cancer is difficult because of incomplete penetrance and genetic and phenotypic heterogeneity. Current evidence suggests that genetic linkage to prostate cancer has been found on several chromosomes including the X; however, identification of causative genes has been elusive. METHODS Parametric and non-parametric linkage analyses were performed using 26 microsatellite markers in each of 11 groups of multiple-case prostate cancer families from the International Consortium for Prostate Cancer Genetics (ICPCG). Meta-analyses of the resultant family-specific linkage statistics across the entire 1,323 families and in several predefined subsets were then performed. RESULTS Meta-analyses of linkage statistics resulted in a maximum parametric heterogeneity lod score (HLOD) of 1.28, and an allele-sharing lod score (LOD) of 2.0 in favor of linkage to Xq27-q28 at 138 cM. In subset analyses, families with average age at onset less than 65 years exhibited a maximum HLOD of 1.8 (at 138 cM) versus a maximum regional HLOD of only 0.32 in families with average age at onset of 65 years or older. Surprisingly, the subset of families with only 2-3 affected men and some evidence of male-to-male transmission of prostate cancer gave the strongest evidence of linkage to the region (HLOD = 3.24, 134 cM). For this subset, the HLOD was slightly increased (HLOD = 3.47 at 134 cM) when families used in the original published report of linkage to Xq27-28 were excluded. CONCLUSIONS Although there was not strong support for linkage to the Xq27-28 region in the complete set of families, the subset of families with earlier age at onset exhibited more evidence of linkage than families with later onset of disease. A subset of families with 2-3 affected individuals and with some evidence of male to male disease transmission showed stronger linkage signals. Our results suggest that the genetic basis for prostate cancer in our families is much more complex than a single susceptibility locus on the X chromosome, and that future explorations of the Xq27-28 region should focus on the subset of families identified here with the strongest evidence of linkage to this region.
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Affiliation(s)
- Joan E Bailey-Wilson
- Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, 21224, USA
- African American Hereditary Prostate Cancer ICPCG Group, Phoenix, AZ, USA
- University of Tampere ICPCG Group, Tampere, Finland
| | - Erica J Childs
- Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, 21224, USA
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Cheryl D Cropp
- Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, 21224, USA
| | - Daniel J Schaid
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA
| | - Jianfeng Xu
- Data Coordinating Center for the ICPCG and Center for Human Genomics, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Nicola J Camp
- University of Utah ICPCG Group and Division of Genetic Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Lisa A Cannon-Albright
- University of Utah ICPCG Group and Division of Genetic Epidemiology, 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
| | - James M Farnham
- University of Utah ICPCG Group and Division of Genetic Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Asha George
- Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, 21224, USA
- African American Hereditary Prostate Cancer ICPCG Group, Phoenix, AZ, USA
- Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Isaac Powell
- African American Hereditary Prostate Cancer ICPCG Group, Phoenix, AZ, USA
- Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA
| | - John D Carpten
- African American Hereditary Prostate Cancer ICPCG Group, Phoenix, AZ, USA
- Translational Genomics Research Institute, Genetic Basis of Human Disease Research Division, Phoenix, AZ, USA
| | - Graham G Giles
- ACTANE consortium
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Australia
| | - John L Hopper
- ACTANE consortium
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Australia
| | - Gianluca Severi
- ACTANE consortium
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Australia
| | - Dallas R English
- ACTANE consortium
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Australia
| | - William D Foulkes
- ACTANE consortium
- Program in Cancer Genetics, McGill University, Montreal, QC, Canada
| | - Lovise Mæhle
- ACTANE consortium
- Department of Medical Genetics, Oslo University Hospital, The Norwegian Radium Hospital, Oslo,Norway
| | - Pål Møller
- ACTANE consortium
- Department of Medical Genetics, Oslo University Hospital, The Norwegian Radium Hospital, Oslo,Norway
| | - Rosalind Eeles
- ACTANE consortium
- Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Surrey, UK
| | - Douglas Easton
- ACTANE consortium
- Cancer Research UK Genetic Epidemiology Unit, Cambridge, UK
| | - Michelle Guy
- ACTANE consortium
- Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Surrey, UK
| | - Steve Edwards
- ACTANE consortium
- Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Surrey, UK
| | - Michael D Badzioch
- ACTANE consortium
- Division of Medical Genetics, University of Washington Medical Center, Seattle, WA, USA
| | - Alice S Whittemore
- BC/CA/HI ICPCG Group, Stanford, CA, USA
- Department of Health Research and Policy, Stanford School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford School of Medicine, Stanford, CA, USA
| | - Ingrid Oakley-Girvan
- BC/CA/HI ICPCG Group, Stanford, CA, USA
- Department of Health Research and Policy, Stanford School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford School of Medicine, Stanford, CA, USA
- Cancer Prevention Institute of California
| | - Chih-Lin Hsieh
- BC/CA/HI ICPCG Group, Stanford, CA, USA
- Department of Urology and Department of Biochemistry and Molecular Biology, University of Southern California, Los Ageles, CA, USA
| | - Latchezar Dimitrov
- Data Coordinating Center for the ICPCG and Center for Human Genomics, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Janet L Stanford
- FHCRC ICPCG Group, Seattle, WA, USA
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA, USA
| | - Danielle M Karyadi
- FHCRC ICPCG Group, Seattle, WA, USA
- Cancer Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kerry Deutsch
- FHCRC ICPCG Group, Seattle, WA, USA
- Institute for Systems Biology, Seattle, WA, USA
| | - Laura McIntosh
- FHCRC ICPCG Group, Seattle, WA, USA
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA, USA
| | - Elaine A Ostrander
- FHCRC ICPCG Group, Seattle, WA, USA
- Cancer Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kathleen E Wiley
- Johns Hopkins University ICPCG Group and Department of Urology, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | - Sarah D Isaacs
- Johns Hopkins University ICPCG Group and Department of Urology, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | - Patrick C Walsh
- Johns Hopkins University ICPCG Group and Department of Urology, Johns Hopkins Medical Institutions, Baltimore, MD, USA
| | | | | | | | - Ethan M Lange
- University of Michigan ICPCG Group, Ann Arbor, MI, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Kathleen A Cooney
- University of Michigan ICPCG Group, Ann Arbor, MI, USA
- University of Michigan, Ann Arbor, MI, USA
| | - Teuvo LJ Tammela
- University of Tampere ICPCG Group, Tampere, Finland
- Institute of Biomedical Technology, University of Tampere, Tampere, Finland
- Centre for Laboratory Medicine and Department of Urology, Tampere University Hospital, Tampere, Finland
| | - Johanna Schleutker
- University of Tampere ICPCG Group, Tampere, Finland
- Institute of Biomedical Technology, University of Tampere, Tampere, Finland
- Centre for Laboratory Medicine and Department of Urology, Tampere University Hospital, Tampere, Finland
| | - Christiane Maier
- University of Ulm ICPCG Group, Ulm, Germany
- Dept of Urology, University of Ulm, Ulm, Germany
- Institute of Human Genetics, University of Ulm, Ulm, Germany
| | - Sylvia Bochum
- University of Ulm ICPCG Group, Ulm, Germany
- Institute of Human Genetics, University of Ulm, Ulm, Germany
| | - Josef Hoegel
- University of Ulm ICPCG Group, Ulm, Germany
- Institute of Human Genetics, University of Ulm, Ulm, Germany
| | - Henrik Grönberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Fredrik Wiklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | | | | | - Olivier Cussenot
- CeRePP ICPCG Group, 75020, Paris, France
- Hopital Tenon, Assistance Publique-Hopitaux de Paris, 75020, Paris, France
| | - William B Isaacs
- Johns Hopkins University ICPCG Group and Department of Urology, Johns Hopkins Medical Institutions, Baltimore, MD, USA
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10
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A meta-analysis of the NAT1 and NAT2 polymorphisms and prostate cancer: a huge review. Med Oncol 2010; 28:365-76. [PMID: 20099048 DOI: 10.1007/s12032-010-9423-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2009] [Accepted: 01/07/2010] [Indexed: 10/19/2022]
Abstract
Studies revealing conflicting results on the role of NAT1 or NAT2 phenotypes on prostate cancer risk led us to perform a meta-analysis to investigate the association of these polymorphisms and prostate cancer risk. The meta-analysis included six studies with NAT1 genotyping (610 prostate cancer cases and 713 controls), and 10 studies with NAT2 genotyping (1,253 cases and 1,722 controls). The fixed effects odds ratio was 0.96 [95% confidence interval (95% CI): 0.75, 1.21; I(2) = 32.9%, P for heterogeneity = 0.189] for the NAT1 genotype, and the random effects odds ratio was 1.10 (95% CI: 0.87, 1.39; I(2) = 49.1%, P for heterogeneity = 0.039) for the NAT2 genotype. For NAT2 polymorphism, a statistically significant association between NAT2 polymorphism and prostate cancer appeared in Asians, but not in Caucasians. In conclusion, the NAT1 or NAT2 phenotypes detoxify carcinogens and their reactive intermediates are unlikely to be the cause of PCa development.
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11
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Hofer MD, Kuefer R, Maier C, Herkommer K, Perner S, Demichelis F, Paiss T, Vogel W, Rubin MA, Hoegel J. Genome-wide linkage analysis of TMPRSS2-ERG fusion in familial prostate cancer. Cancer Res 2009; 69:640-6. [PMID: 19147579 DOI: 10.1158/0008-5472.can-08-2008] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Fusion of the 5'-untranslated region of androgen-regulated TMPRSS2 promoter with ETS transcription factor family members is found frequently in prostate cancers, and recent work suggests that the most common TMPRSS2-ERG fusion is associated with an aggressive clinical phenotype compared with fusion-negative prostate cancer. Thus far, analysis of the fusion has been limited to sporadic cases of prostate cancer. In the current study, we explore for an enrichment of TMPRSS2-ERG fusion in familial prostate cancer. TMPRSS2-ERG fusion was identified using a break-apart fluorescence in situ hybridization assay on tissue microarrays. Presence of TMPRSS2-ERG fusion was associated with higher Gleason scores (P = 0.027). Of 75 patients with established history of prostate cancer, we detected the TMPRSS2-ERG fusion in 44 (59%) patients. Almost three quarters (73%) of fusion-positive patients accumulated within 16 specific families whereas only 27% were single fusion-positive cases within one family. Based on reported prevalence rates, we calculated a sibling recurrence risk ratio of up to 18.9. A subset (63%) of families with uniformly TMPRSS2-ERG-positive prostate cancer underwent a genome-wide linkage scan at 500 markers. This revealed several loci located on chromosomes #9, #18, and X that were suggestive of linkage to the TMPRSS2-ERG fusion-positive prostate cancer phenotype with linkage-of-disease scores up to 2.16 and nonparametric linkage scores up to 2.77. This suggests the presence of an inherited susceptibility to developing the TMPRSS2-ERG fusion. Given the association of TMPRSS2-ERG fusion and aggressive prostate cancer, close surveillance of relatives of patients with established fusion-positive prostate cancer or a family history of prostate cancer in general would be warranted.
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Affiliation(s)
- Matthias D Hofer
- Department of Pathology, Brigham and Women's Hospital, 2Harvard Medical School, Boston, Massachusetts, USA
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12
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Wallace C, Clayton DG. Appropriate Use of Information on Family History of Disease in Recruitment for Linkage Analysis Studies. Ann Hum Genet 2008; 70:360-71. [PMID: 16674558 DOI: 10.1111/j.1529-8817.2005.00233.x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
When conducting genetic studies for complex traits, large samples are commonly required to detect any of the number of genes with relatively low effect thought to underly such traits. This is because, in contrast to monogenic diseases, complex traits typically result from a number of different genetic pathways (genetic heterogeneity) and any sample is likely to contain a considerable fraction of sporadic cases (phenocopies). Such samples are time-consuming and costly to recruit and analyse. Methods which might be used to decrease sample size include attempting to select families, with the aim of reducing genetic heterogeneity or phenocopy rate within the sample. Selecting cases with positive family history of disease should reduce the phenocopy rate, and this strategy has been employed in linkage studies of complex disease, although evaluations of such a strategy have been equivocal. This paper shows how identity by descent (IBD) distributions may be calculated for affected relative pairs recruited conditional on the affection status of a third relative. These distributions are then used to calculate expected power in affected sib and half-sib linkage studies when recruitment is conditional on family history of disease. We consider the proxy conditions of recruitment conditional on disease in an affected parent or third sibling with single-locus and additive multilocus genetic models. We show that while such selection strategies can reduce power if disease risk alleles are common and environmental heterogeneity low, under models more likely to underly common complex diseases power will generally be increased, and that this effect is greater as more loci are involved. Though the proxy cases studied are more extreme than a general strategy of asking potential recruits whether they have any family history of disease, these results suggest that conditional recruitment is more generally useful than previous studies have suggested.
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Affiliation(s)
- C Wallace
- Department of Clinical Pharmacology, Barts and the London, Queen Mary University of London, London, United Kingdom.
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13
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Ostrander EA, Johannesson B. Prostate cancer susceptibility loci: finding the genes. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2008; 617:179-90. [PMID: 18497042 DOI: 10.1007/978-0-387-69080-3_17] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
Abstract
Studies to date suggest that PC is a genetically very heterogeneous disease. High-risk families, in which multiple men are affected likely, reflect the contributions of a number of genes, some that are rare and highly penetrant, while others are more common and weakly penetrant. In this review, we have discussed only the first type of loci, and found that the identification of such genomic regions is a formidable problem. Replication between seemingly similar data sets is weak, likely reflecting the older age of onset associated with the disease, the inability to collect affected individuals from more than two generations in a family, and the variation seen in disease presentation, in addition to the underlying locus heterogeneity. Indeed, the definition of PC is ever changing, as diagnostic criteria and tools for pinpointing early lesions improve. Are we making progress? Clearly the answer is yes. The ability to divide large data sets into homogenous subset of families likely to share common genetic under-pinnings has improved power to identify loci and reproducibility between loci is now more common. Indeed, several groups report linkage to loci on chromosomes 1, 17, 19, and 22. Key to our continued success is our ever increasing ability to understand the disease. Identifying the subset of men who are likely to get clinically significant disease is the goal of genetic studies like these, and identifying the underlying loci is the key for developing diagnostics. The willingness of the community to work together has been an important factor in the successes the community has enjoyed to date, and will likely be as important as we move forward to untangle the genetics of this complex and common disorder.
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Affiliation(s)
- Elanie A Ostrander
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
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14
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Ostrander EA, Kwon EM, Stanford JL. Genetic susceptibility to aggressive prostate cancer. Cancer Epidemiol Biomarkers Prev 2007; 15:1761-4. [PMID: 17035380 DOI: 10.1158/1055-9965.epi-06-0730] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Elaine A Ostrander
- Cancer Genetics Branch, National Human Genome Research Institute, NIH, 50 South Drive, Bethesda, MD 20892, USA.
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15
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Camp NJ, Cannon-Albright LA, Farnham JM, Baffoe-Bonnie AB, George A, Powell I, Bailey-Wilson JE, Carpten JD, Giles GG, Hopper JL, Severi G, English DR, Foulkes WD, Maehle L, Moller P, Eeles R, Easton D, Badzioch MD, Whittemore AS, Oakley-Girvan I, Hsieh CL, Dimitrov L, Xu J, Stanford JL, Johanneson B, Deutsch K, McIntosh L, Ostrander EA, Wiley KE, Isaacs SD, Walsh PC, Thibodeau SN, McDonnell SK, Hebbring S, Schaid DJ, Lange EM, Cooney KA, Tammela TLJ, Schleutker J, Paiss T, Maier C, Grönberg H, Wiklund F, Emanuelsson M, Isaacs WB. Compelling evidence for a prostate cancer gene at 22q12.3 by the International Consortium for Prostate Cancer Genetics. Hum Mol Genet 2007; 16:1271-8. [PMID: 17478474 PMCID: PMC2653215 DOI: 10.1093/hmg/ddm075] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Previously, an analysis of 14 extended, high-risk Utah pedigrees localized in the chromosome 22q linkage region to 3.2 Mb at 22q12.3-13.1 (flanked on each side by three recombinants) contained 31 annotated genes. In this large, multi-centered, collaborative study, we performed statistical recombinant mapping in 54 pedigrees selected to be informative for recombinant mapping from nine member groups of the International Consortium for Prostate Cancer Genetics (ICPCG). These 54 pedigrees included the 14 extended pedigrees from Utah and 40 pedigrees from eight other ICPCG member groups. The additional 40 pedigrees were selected from a total pool of 1213 such that each pedigree was required to contain both at least four prostate cancer (PRCA) cases and exhibit evidence for linkage to the chromosome 22q region. The recombinant events in these 40 independent pedigrees confirmed the previously proposed region. Further, when all 54 pedigrees were considered, the three-recombinant consensus region was narrowed down by more than a megabase to 2.2 Mb at chromosome 22q12.3 flanked by D22S281 and D22S683. This narrower region eliminated 20 annotated genes from that previously proposed, leaving only 11 genes. This region at 22q12.3 is the most consistently identified and smallest linkage region for PRCA. This collaborative study by the ICPCG illustrates the value of consortium efforts and the continued utility of linkage analysis using informative pedigrees to localize genes for complex diseases.
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Affiliation(s)
- Nicola J Camp
- University of Utah ICPCG Group and Division of Genetic Epidemiology, University of Utah School of Medicine, 391 Chipeta Way, Suite D, Salt Lake City, UT 84108, USA.
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16
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Johanneson B, Deutsch K, McIntosh L, Friedrichsen-Karyadi DM, Janer M, Kwon EM, Iwasaki L, Hood L, Ostrander EA, Stanford JL. Suggestive genetic linkage to chromosome 11p11.2-q12.2 in hereditary prostate cancer families with primary kidney cancer. Prostate 2007; 67:732-42. [PMID: 17372923 DOI: 10.1002/pros.20528] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
BACKGROUND The Seattle-based PROGRESS study was started in 1995 to ascertain hereditary prostate cancer (HPC) families for studies of genetic susceptibility. Subsequent studies by several research groups, including our own, suggest that HPC is a genetically heterogeneous disease. To be successful in mapping loci for such a complex disease, one must consider ways of grouping families into subsets that likely share the same genetic origin. Towards that end, we analyzed a genome-wide scan of HPC families with primary kidney cancer. METHODS An 8.1 cM genome-wide scan including 441 microsatellite markers was analyzed by both parametric and non-parametric linkage approaches in fifteen HPC families with the co-occurrence of kidney cancer. RESULTS There was no evidence for significant linkage in the initial findings. However, two regions of suggestive linkage were observed at 11q12 and 4q21, with HLOD scores of 2.59 and 2.10, respectively. The primary result on chromosome 11 was strengthened after excluding two families with members who had rare transitional cell carcinoma (TCC). Specifically, we observed a non-parametric Kong and Cox P-value of 0.004 for marker D11S1290 at 11p11.2. The 8 cM region between 11p11.2 and 11q12.2 was refined by the addition of 16 new markers. The subset of HPC families with a median age of diagnosis >65 years demonstrated the strongest evidence for linkage, with an HLOD = 2.50. The P-values associated with non-parametric analysis ranged from 0.004 to 0.05 across five contiguous markers. CONCLUSIONS Analysis of HPC families with members diagnosed with primary renal cell carcinoma demonstrates suggestive linkage to chromosome 11p11.2-q12.2.
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Affiliation(s)
- Bo Johanneson
- Cancer Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, USA
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17
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Christensen GB, Camp NJ, Farnham JM, Cannon-Albright LA. Genome-wide linkage analysis for aggressive prostate cancer in Utah high-risk pedigrees. Prostate 2007; 67:605-13. [PMID: 17299800 DOI: 10.1002/pros.20554] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND It has been proposed that studying alternative phenotypes, such as tumor aggressiveness, may be a solution for overcoming the apparent heterogeneity that has hindered the identification of prostate cancer (PC) genes. We present the results of a genome-scan for predisposition to aggressive PC using the Utah high-risk pedigree resource. METHODS We identified 259 subjects with aggressive PC in 57 extended and nuclear families. Parametric and non-parametric multipoint linkage statistics were calculated for a genome-wide set of 401 microsatellite markers using the MCLINK software package. Stratification analyses by the number of affected subjects per pedigree (<5, >or=5) and the average age at diagnosis of affected subjects (<70 years, >or=70 years) were also performed. RESULTS No significant results were observed at the genome-wide level, but suggestive evidence for linkage was observed on chromosomes 9q (HLOD = 2.04) and 14q (HLOD = 2.08); several pedigrees showed individual evidence for linkage at each locus (LOD > 0.58). The subset of pedigrees with earlier age at onset demonstrated nominal linkage evidence on chromosomes 3q (HLOD = 1.79), 8q (HLOD = 1.67), and 20q (HLOD=1.82). The late-onset subset showed suggestive linkage on chromosome 6p (HLOD = 2.37) and the subset of pedigrees with fewer than five affected subjects showed suggestive linkage on chromosome 10p (HLOD = 1.99). CONCLUSIONS Linkage evidence observed on chromosomes 6p, 8q, and 20q support previously reported PC aggressiveness loci. While these results are encouraging, further research is necessary to identify the gene or genes responsible for PC aggressiveness and surmount the overarching problem of PC heterogeneity.
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Affiliation(s)
- G B Christensen
- Department of Biomedical Informatics, University of Utah School of Medicine, Utah, USA.
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18
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Pierce BL, Friedrichsen-Karyadi DM, McIntosh L, Deutsch K, Hood L, Ostrander EA, Austin MA, Stanford JL. Genomic scan of 12 hereditary prostate cancer families having an occurrence of pancreas cancer. Prostate 2007; 67:410-5. [PMID: 17192958 DOI: 10.1002/pros.20527] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Prostate cancer is a genetically heterogeneous disease. Using the occurrence of other cancers in hereditary prostate cancer (HPC) families is a promising strategy for developing genetically homogeneous data sets that can enhance the ability to identify susceptibility loci using linkage analysis. METHODS Twelve HPC families with the co-occurrence of adenocarcinoma of the pancreas were selected from the Prostate Cancer Genetic Research Study (PROGRESS). Non-parametric linkage analysis for a prostate/pancreas cancer susceptibility phenotype was performed using 441 genome-wide microsatellite markers. RESULTS No statistically significant linkage signal was detected in this analysis. The strongest linkage signals, as measured by Kong and Cox LOD score (KC LOD), were observed on chromosomes 2q37.2-q37.3 (KC LOD = 1.01; P = 0.02) and 16q23.2 (KC LOC = 1.05; P = 0.01). CONCLUSIONS Despite the lack of statistically significant findings, four chromosomal regions, three of which (2q, 16q, 17q) were previously noted as harboring potential susceptibility loci, showed suggestive linkage results in this scan.
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Affiliation(s)
- Brandon L Pierce
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109-1024, USA
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19
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Schaid DJ, McDonnell SK, Zarfas KE, Cunningham JM, Hebbring S, Thibodeau SN, Eeles RA, Easton DF, Foulkes WD, Simard J, Giles GG, Hopper JL, Mahle L, Moller P, Badzioch M, Bishop DT, Evans C, Edwards S, Meitz J, Bullock S, Hope Q, Guy M, Hsieh CL, Halpern J, Balise RR, Oakley-Girvan I, Whittemore AS, Xu J, Dimitrov L, Chang BL, Adams TS, Turner AR, Meyers DA, Friedrichsen DM, Deutsch K, Kolb S, Janer M, Hood L, Ostrander EA, Stanford JL, Ewing CM, Gielzak M, Isaacs SD, Walsh PC, Wiley KE, Isaacs WB, Lange EM, Ho LA, Beebe-Dimmer JL, Wood DP, Cooney KA, Seminara D, Ikonen T, Baffoe-Bonnie A, Fredriksson H, Matikainen MP, Tammela TLJ, Bailey-Wilson J, Schleutker J, Maier C, Herkommer K, Hoegel JJ, Vogel W, Paiss T, Wiklund F, Emanuelsson M, Stenman E, Jonsson BA, Grönberg H, Camp NJ, Farnham J, Cannon-Albright LA, Catalona WJ, Suarez BK, Roehl KA. Pooled genome linkage scan of aggressive prostate cancer: results from the International Consortium for Prostate Cancer Genetics. Hum Genet 2006; 120:471-85. [PMID: 16932970 DOI: 10.1007/s00439-006-0219-9] [Citation(s) in RCA: 49] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2006] [Accepted: 06/05/2006] [Indexed: 10/24/2022]
Abstract
While it is widely appreciated that prostate cancers vary substantially in their propensity to progress to a life-threatening stage, the molecular events responsible for this progression have not been identified. Understanding these molecular mechanisms could provide important prognostic information relevant to more effective clinical management of this heterogeneous cancer. Hence, through genetic linkage analyses, we examined the hypothesis that the tendency to develop aggressive prostate cancer may have an important genetic component. Starting with 1,233 familial prostate cancer families with genome scan data available from the International Consortium for Prostate Cancer Genetics, we selected those that had at least three members with the phenotype of clinically aggressive prostate cancer, as defined by either high tumor grade and/or stage, resulting in 166 pedigrees (13%). Genome-wide linkage data were then pooled to perform a combined linkage analysis for these families. Linkage signals reaching a suggestive level of significance were found on chromosomes 6p22.3 (LOD = 3.0), 11q14.1-14.3 (LOD = 2.4), and 20p11.21-q11.21 (LOD = 2.5). For chromosome 11, stronger evidence of linkage (LOD = 3.3) was observed among pedigrees with an average at diagnosis of 65 years or younger. Other chromosomes that showed evidence for heterogeneity in linkage across strata were chromosome 7, with the strongest linkage signal among pedigrees without male-to-male disease transmission (7q21.11, LOD = 4.1), and chromosome 21, with the strongest linkage signal among pedigrees that had African American ancestry (21q22.13-22.3; LOD = 3.2). Our findings suggest several regions that may contain genes which, when mutated, predispose men to develop a more aggressive prostate cancer phenotype. This provides a basis for attempts to identify these genes, with potential clinical utility for men with aggressive prostate cancer and their relatives.
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Affiliation(s)
- Daniel J Schaid
- Harwick 7, Mayo Clinic College of Medicine, Rochester, MN 55905, USA.
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20
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Stanford JL, McDonnell SK, Friedrichsen DM, Carlson EE, Kolb S, Deutsch K, Janer M, Hood L, Ostrander EA, Schaid DJ. Prostate cancer and genetic susceptibility: a genome scan incorporating disease aggressiveness. Prostate 2006; 66:317-25. [PMID: 16245279 DOI: 10.1002/pros.20349] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Prostate cancer is a heterogeneous disease, both genetically and phenotypically. Linkage studies attempting to map genes for hereditary prostate cancer (HPC) have proved challenging, and one potential problem contributing to this challenge is the variability in disease phenotypes. METHODS We collected clinical data on 784 affected men with prostate cancer from 248 HPC families for whom a genomic screen was performed. Disease characteristics (i.e., Gleason score, stage, prostate-specific antigen (PSA)) were used to classify affected men into categories of clinically insignificant, moderate, or aggressive prostate cancer. To potentially enrich for a genetic etiology, we restricted linkage analyses to only men with aggressive disease, although we used genotype information from all family members; linkage analyses used both dominant and recessive models. In addition, subset analyses considered age at diagnosis, number of affected men per family and other stratifications to try to increase genetic homogeneity. RESULTS Several regions of interest (heterogeneity LOD score, HLOD>1.0) were identified in families (n=123) with >or=2 affecteds with aggressive prostate cancer. "Suggestive" linkage was observed at chromosome 22q11.1 (Dominant model HLOD=2.18) and the result was stronger (Dominant HLOD=2.75) in families with evidence of male-to-male transmission. A second region at 22q12.3-q13.1 was also highlighted (Recessive model HLOD=1.90) among men with aggressive disease, as was a region on chromosome 18. CONCLUSIONS These analyses suggest that using clinically defined phenotypes may be a useful approach for simplifying the locus heterogeneity problems that confound the search for prostate cancer susceptibility genes.
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Affiliation(s)
- Janet L Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, and Department of Epidemiology, School of Public Health and Community Medicine, University of Washington, Seattle, Washington 98109-1024, USA.
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21
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Camp NJ, Farnham JM, Cannon Albright LA. Genomic search for prostate cancer predisposition loci in Utah pedigrees. Prostate 2005; 65:365-74. [PMID: 16037989 DOI: 10.1002/pros.20287] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
BACKGROUND We report a genome linkage scan in extended Utah pedigrees, utilizing a pedigree-splitting approach to reduce intra-familial heterogeneity. METHODS Fifty-nine pedigrees with at least four Prostate cancer (PrCa) cases and no more than two meioses separating PrCa cases were analyzed using the CIDR genomic search STRP marker set. Parametric linkage analyses using dominant and recessive models were performed on four datasets resulting from a pedigree splitting algorithm. In addition, age at diagnosis subset analyses were performed. RESULTS Four regions of interest (LODs>1.9) were identified on chromosomes 1p, 3q, 5q, and 22q. The linkage peaks on 1p, 3q, and 22q have been previously implicated for PrCa, though not significantly. The 1p region was supported by a single large Utah pedigree with a multipoint LOD score of 3.1. An additional 10 regions gave LOD scores>1.22 (nominal linkage evidence), including moderate evidence supporting the HPC20 region with a recessive model. CONCLUSIONS Our genome-wide search in the informative, extended Utah pedigrees continues to illustrate an ability to identify and replicate linkage peaks, and supports four regions of interest for PrCa predisposition genes.
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Affiliation(s)
- Nicola J Camp
- Genetic Epidemiology, Department of Medical Informatics, University of Utah, Salt Lake City, Utah 84108, USA
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22
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Chang BL, Lange EM, Dimitrov L, Valis CJ, Gillanders EM, Lange LA, Wiley KE, Isaacs SD, Wiklund F, Baffoe-Bonnie A, Langefeld CD, Zheng SL, Matikainen MP, Ikonen T, Fredriksson H, Tammela T, Walsh PC, Bailey-Wilson JE, Schleutker J, Gronberg H, Cooney KA, Isaacs WB, Suh E, Trent JM, Xu J. Two-locus genome-wide linkage scan for prostate cancer susceptibility genes with an interaction effect. Hum Genet 2005; 118:716-24. [PMID: 16328469 DOI: 10.1007/s00439-005-0099-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2005] [Accepted: 09/26/2005] [Indexed: 10/25/2022]
Abstract
Prostate cancer represents a significant worldwide public health burden. Epidemiological and genetic epidemiological studies have consistently provided data supporting the existence of inherited prostate cancer susceptibility genes. Segregation analyses of prostate cancer suggest that a multigene model may best explain familial clustering of this disease. Therefore, modeling gene-gene interactions in linkage analysis may improve the power to detect chromosomal regions harboring these disease susceptibility genes. In this study, we systematically screened for prostate cancer linkage by modeling two-locus gene-gene interactions for all possible pairs of loci across the genome in 426 prostate cancer families from Johns Hopkins Hospital, University of Michigan, University of Umeå, and University of Tampere. We found suggestive evidence for an epistatic interaction for six sets of loci (target chromosome-wide/reference marker-specific P< or =0.0001). Evidence for these interactions was found in two independent subsets from within the 426 families. While the validity of these results requires confirmation from independent studies and the identification of the specific genes underlying this linkage evidence, our approach of systematically assessing gene-gene interactions across the entire genome represents a promising alternative approach for gene identification for prostate cancer.
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Affiliation(s)
- Bao-Li Chang
- Center for Human Genomics, Wake Forest University School of Medicine, Winston-Salem, NC, USA
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23
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Xu J, Dimitrov L, Chang BL, Adams TS, Turner AR, Meyers DA, Eeles RA, Easton DF, Foulkes WD, Simard J, Giles GG, Hopper JL, Mahle L, Moller P, Bishop T, Evans C, Edwards S, Meitz J, Bullock S, Hope Q, Hsieh CL, Halpern J, Balise RN, Oakley-Girvan I, Whittemore AS, Ewing CM, Gielzak M, Isaacs SD, Walsh PC, Wiley KE, Isaacs WB, Thibodeau SN, McDonnell SK, Cunningham JM, Zarfas KE, Hebbring S, Schaid DJ, Friedrichsen DM, Deutsch K, Kolb S, Badzioch M, Jarvik GP, Janer M, Hood L, Ostrander EA, Stanford JL, Lange EM, Beebe-Dimmer JL, Mohai CE, Cooney KA, Ikonen T, Baffoe-Bonnie A, Fredriksson H, Matikainen MP, Tammela TLJ, Bailey-Wilson J, Schleutker J, Maier C, Herkommer K, Hoegel JJ, Vogel W, Paiss T, Wiklund F, Emanuelsson M, Stenman E, Jonsson BA, Grönberg H, Camp NJ, Farnham J, Cannon-Albright LA, Seminara D. A combined genomewide linkage scan of 1,233 families for prostate cancer-susceptibility genes conducted by the international consortium for prostate cancer genetics. Am J Hum Genet 2005; 77:219-29. [PMID: 15988677 PMCID: PMC1224525 DOI: 10.1086/432377] [Citation(s) in RCA: 113] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2005] [Accepted: 05/27/2005] [Indexed: 11/03/2022] Open
Abstract
Evidence of the existence of major prostate cancer (PC)-susceptibility genes has been provided by multiple segregation analyses. Although genomewide screens have been performed in over a dozen independent studies, few chromosomal regions have been consistently identified as regions of interest. One of the major difficulties is genetic heterogeneity, possibly due to multiple, incompletely penetrant PC-susceptibility genes. In this study, we explored two approaches to overcome this difficulty, in an analysis of a large number of families with PC in the International Consortium for Prostate Cancer Genetics (ICPCG). One approach was to combine linkage data from a total of 1,233 families to increase the statistical power for detecting linkage. Using parametric (dominant and recessive) and nonparametric analyses, we identified five regions with "suggestive" linkage (LOD score >1.86): 5q12, 8p21, 15q11, 17q21, and 22q12. The second approach was to focus on subsets of families that are more likely to segregate highly penetrant mutations, including families with large numbers of affected individuals or early age at diagnosis. Stronger evidence of linkage in several regions was identified, including a "significant" linkage at 22q12, with a LOD score of 3.57, and five suggestive linkages (1q25, 8q13, 13q14, 16p13, and 17q21) in 269 families with at least five affected members. In addition, four additional suggestive linkages (3p24, 5q35, 11q22, and Xq12) were found in 606 families with mean age at diagnosis of < or = 65 years. Although it is difficult to determine the true statistical significance of these findings, a conservative interpretation of these results would be that if major PC-susceptibility genes do exist, they are most likely located in the regions generating suggestive or significant linkage signals in this large study.
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Affiliation(s)
- Jianfeng Xu
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Latchezar Dimitrov
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Bao-Li Chang
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Tamara S. Adams
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Aubrey R. Turner
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Deborah A. Meyers
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Rosalind A. Eeles
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Douglas F. Easton
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - William D. Foulkes
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Jacques Simard
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Graham G. Giles
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - John L. Hopper
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Lovise Mahle
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Pal Moller
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Tim Bishop
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Chris Evans
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Steve Edwards
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Julia Meitz
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Sarah Bullock
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Questa Hope
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - ACTANE Consortium
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Chih-lin Hsieh
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Jerry Halpern
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Raymond N. Balise
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Ingrid Oakley-Girvan
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Alice S. Whittemore
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Charles M. Ewing
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Marta Gielzak
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Sarah D. Isaacs
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Patrick C. Walsh
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Kathleen E. Wiley
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - William B. Isaacs
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Stephen N. Thibodeau
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Shannon K. McDonnell
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Julie M. Cunningham
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Katherine E. Zarfas
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Scott Hebbring
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Daniel J. Schaid
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Danielle M. Friedrichsen
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Kerry Deutsch
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Suzanne Kolb
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Michael Badzioch
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Gail P. Jarvik
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Marta Janer
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Leroy Hood
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Elaine A. Ostrander
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Janet L. Stanford
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Ethan M. Lange
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Jennifer L. Beebe-Dimmer
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Caroline E. Mohai
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Kathleen A. Cooney
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Tarja Ikonen
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Agnes Baffoe-Bonnie
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Henna Fredriksson
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Mika P. Matikainen
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Teuvo LJ Tammela
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Joan Bailey-Wilson
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Johanna Schleutker
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Christiane Maier
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Kathleen Herkommer
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Josef J. Hoegel
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Walther Vogel
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Thomas Paiss
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Fredrik Wiklund
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Monica Emanuelsson
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Elisabeth Stenman
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Björn-Anders Jonsson
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Henrik Grönberg
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Nicola J. Camp
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - James Farnham
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Lisa A. Cannon-Albright
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
| | - Daniela Seminara
- Data Coordinating Center, ACTANE, BC/CA/HI, Johns Hopkins University, Mayo Clinic, PROGRESS, University of Michigan, University of Tampere and Tampere University Hospital, University of Ulm, University of Umeå, University of Utah, and National Cancer Institute
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24
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Hope Q, Bullock S, Evans C, Meitz J, Hamel N, Edwards SM, Severi G, Dearnaley D, Jhavar S, Southgate C, Falconer A, Dowe A, Muir K, Houlston RS, Engert JC, Roquis D, Sinnett D, Simard J, Heimdal K, Møller P, Maehle L, Badzioch M, Eeles RA, Easton DF, English DR, Southey MC, Hopper JL, Foulkes WD, Giles GG. Macrophage scavenger receptor 1 999C>T (R293X) mutation and risk of prostate cancer. Cancer Epidemiol Biomarkers Prev 2005; 14:397-402. [PMID: 15734964 DOI: 10.1158/1055-9965.epi-04-0202] [Citation(s) in RCA: 17] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Variants in the gene encoding the macrophage scavenger receptor 1 (MSR1(4)) protein have been identified in men with prostate cancer, and several small studies have suggested that the 999C>T (R293X) protein-truncating mutation may be associated with an increased risk for this disease. METHODS Using large case-control, cohort, and prostate cancer family studies conducted in several Western countries, we tested for the 999C>T mutation in 2,943 men with invasive prostate carcinoma, including 401 males from multiple-case families, 1,982 cases unselected for age, and 575 men diagnosed before the age of 56 years, and in 2,870 male controls. Risk ratios were estimated by unconditional logistic regression adjusting for country and by a modified segregation analysis. A meta-analysis was conducted pooling our data with published data. RESULTS The prevalence of MSR1*999C>T mutation carriers was 0.027 (SE, 0.003) in cases and 0.022 (SE, 0.002) in controls, and did not differ by country, ethnicity, or source. The adjusted risk ratio for prostate cancer associated with being a 999C>T carrier was 1.31 [95% confidence interval (CI), 0.93-1.84; P = 0.16]. The modified segregation analysis estimated the risk ratio to be 1.20 (95% CI, 0.87-1.66; P = 0.16). The risk ratio estimated from the meta-analysis was 1.34 (95% CI, 0.94-1.89; P = 0.10). CONCLUSION Our large-scale analysis of case and controls from several countries found no evidence that the 999C>T mutation is associated with increased risk of prostate cancer. The meta-analysis suggests it is unlikely that this mutation confers more than a 2-fold increased risk.
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Affiliation(s)
- Questa Hope
- Translational Cancer Genetics Team, Section of Cancer Genetics and Urology Unit, Male Urological Centre and Institute of Cancer Research and Royal Marsden NHS Trust, Surrey, United Kingdom
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25
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Schaid DJ, Chang BL. Description of the International Consortium For Prostate Cancer Genetics, and failure to replicate linkage of hereditary prostate cancer to 20q13. Prostate 2005; 63:276-90. [PMID: 15599943 DOI: 10.1002/pros.20198] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The International Consortium for Prostate Cancer Genetics (ICPCG) is an international collaborative effort to pool pedigrees with hereditary prostate cancer (PC) in order to replicate linkage findings for PC. A strength of the ICPCG is the large number of well-characterized pedigrees, allowing linkage analyses within large subsets. Given the heterogeneity and complexity of PC, the historical difficulties of synthesizing different studies reporting positive and negative linkage replication, and the use of different statistical analysis methods and different stratification criteria, the ICPCG provides a valuable resource to evaluate linkage for hereditary PC. To date, linkage of chromosome 20 (HPC20) to hereditary PC has been one of the strongest linkage signals, yet the efforts to replicate this linkage have been limited. This paper reports a linkage analysis of chromosome 20 markers for 1,234 pedigrees with multiple cases of PC ascertained through the ICPCG, and represents the most thorough attempt to confirm or refute linkage to chromosome 20. From the original 158 Mayo pedigrees in which linkage was detected, the maximum heterogeneity LOD (HLOD) score, under a recessive model, was 2.78. In contrast, for the 1,076 pedigrees not included in the original study, the maximum HLOD score (recessive model) was 0.06. Although, a few small linkage signals for chromosome 20 were found in various strata of this pooled analysis, this large study failed to replicate linkage to HPC20. This study illustrates the value of the ICPCG family collection to evaluate reported linkage signals and suggests that the HPC20 region does not make a major contribution to PC susceptibility.
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Affiliation(s)
- Daniel J Schaid
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
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26
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Schaid DJ, Guenther JC, Christensen GB, Hebbring S, Rosenow C, Hilker CA, McDonnell SK, Cunningham JM, Slager SL, Blute ML, Thibodeau SN. Comparison of microsatellites versus single-nucleotide polymorphisms in a genome linkage screen for prostate cancer-susceptibility Loci. Am J Hum Genet 2004; 75:948-65. [PMID: 15514889 PMCID: PMC1182157 DOI: 10.1086/425870] [Citation(s) in RCA: 117] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2004] [Accepted: 09/08/2004] [Indexed: 12/19/2022] Open
Abstract
Prostate cancer is one of the most common cancers among men and has long been recognized to occur in familial clusters. Brothers and sons of affected men have a 2-3-fold increased risk of developing prostate cancer. However, identification of genetic susceptibility loci for prostate cancer has been extremely difficult. Although the suggestion of linkage has been reported for many chromosomes, the most promising regions have been difficult to replicate. In this study, we compare genome linkage scans using microsatellites with those using single-nucleotide polymorphisms (SNPs), performed in 467 men with prostate cancer from 167 families. For the microsatellites, the ABI Prism Linkage Mapping Set version 2, with 402 microsatellite markers, was used, and, for the SNPs, the Early Access Affymetrix Mapping 10K array was used. Our results show that the presence of linkage disequilibrium (LD) among SNPs can lead to inflated LOD scores, and this seems to be an artifact due to the assumption of linkage equilibrium that is required by the current genetic-linkage software. After excluding SNPs with high LD, we found a number of new LOD-score peaks with values of at least 2.0 that were not found by the microsatellite markers: chromosome 8, with a maximum model-free LOD score of 2.2; chromosome 2, with a LOD score of 2.1; chromosome 6, with a LOD score of 4.2; and chromosome 12, with a LOD score of 3.9. The LOD scores for chromosomes 6 and 12 are difficult to interpret, because they occurred only at the extreme ends of the chromosomes. The greatest gain provided by the SNP markers was a large increase in the linkage information content, with an average information content of 61% for the SNPs, versus an average of 41% for the microsatellite markers. The strengths and weaknesses of microsatellite versus SNP markers are illustrated by the results of our genome linkage scans.
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Affiliation(s)
- Daniel J Schaid
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN 55905, USA.
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27
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Kommu S. Suppressor screening - a potential new model for understanding the genetic components of urological malignancies. BJU Int 2004; 94:759-60. [PMID: 15476503 DOI: 10.1111/j.1464-410x.2004.05027.x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Edwards SM, Eeles RA. Unravelling the genetics of prostate cancer. AMERICAN JOURNAL OF MEDICAL GENETICS PART C-SEMINARS IN MEDICAL GENETICS 2004; 129C:65-73. [PMID: 15264274 DOI: 10.1002/ajmg.c.30027] [Citation(s) in RCA: 52] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
This review describes what is currently known about the genetics of prostate cancer. Traditionally, the genetics of a suspected inherited cancer predisposition have generally been thought of in terms of a single, high-risk gene with a dominant mode of inheritance. Such a gene might be observed in families, as has been documented in familial breast cancer (BRCA1/2), familial colorectal cancer (HNPCC), retinoblastoma (RB1), and Wilms tumor (WT1). This review investigates the evidence for the existence, first of familial prostate cancer, and second, for the presence of such a high-risk gene in those families by epidemiological and experimental approaches. Another current area of interest in prostate cancer is the investigation of the contribution of common lower penetrance genes to the disease. This alternative approach has become popular, as it raises the issue of frequently seen genetic variations such as single nucleotide polymorphisms (SNPs) having relevance to the risk of developing the disease. Finally, this article will explore the way forward, with emphasis on worldwide collaboration from teams attempting to find the genes responsible for the disease and investment in new technologies that will aid in their discovery.
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Affiliation(s)
- Stephen M Edwards
- Translational Cancer Genetics Team, Institute of Cancer Research, Sutton, Surrey SM2 5NG, UK
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Angèle S, Falconer A, Edwards SM, Dörk T, Bremer M, Moullan N, Chapot B, Muir K, Houlston R, Norman AR, Bullock S, Hope Q, Meitz J, Dearnaley D, Dowe A, Southgate C, Ardern-Jones A, Easton DF, Eeles RA, Hall J. ATM polymorphisms as risk factors for prostate cancer development. Br J Cancer 2004; 91:783-7. [PMID: 15280931 PMCID: PMC2364767 DOI: 10.1038/sj.bjc.6602007] [Citation(s) in RCA: 71] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
The risk of prostate cancer is known to be elevated in carriers of germline mutations in BRCA2, and possibly also in carriers of BRCA1 and CHEK2 mutations. These genes are components of the ATM-dependent DNA damage signalling pathways. To evaluate the hypothesis that variants in ATM itself might be associated with prostate cancer risk, we genotyped five ATM variants in DNA from 637 prostate cancer patients and 445 controls with no family history of cancer. No significant differences in the frequency of the variant alleles at 5557G>A (D1853N), 5558A>T (D1853V), ivs38-8t>c and ivs38-15g>c were found between the cases and controls. The 3161G (P1054R) variant allele was, however, significantly associated with an increased risk of developing prostate cancer (any G vs CC OR 2.13, 95% CI 1.17–3.87, P=0.016). A lymphoblastoid cell line carrying both the 3161G and the 2572C (858L) variant in the homozygote state shows a cell cycle progression profile after exposure to ionising radiation that is significantly different to that seen in cell lines carrying a wild-type ATM gene. These results provide evidence that the presence of common variants in the ATM gene, may confer an altered cellular phenotype, and that the ATM 3161C>G variant might be associated with prostate cancer risk.
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Affiliation(s)
- S Angèle
- DNA Repair Group, International Agency for Research on Cancer, 150 cours Albert Thomas, 69373 Lyon, France
| | - A Falconer
- The Institute of Cancer Research, Sutton, Surrey, UK
| | - S M Edwards
- The Institute of Cancer Research, Sutton, Surrey, UK
| | - T Dörk
- Clinics of Obstetrics and Gynaecology, Medical School Hannover, Podbielskistr. 380, D-30659 Hannover, Germany
| | - M Bremer
- Department of Radiation Oncology, Medical School Hannover, Carl-Neuberg-Str. 1, D-30625 Hannover, Germany
| | - N Moullan
- DNA Repair Group, International Agency for Research on Cancer, 150 cours Albert Thomas, 69373 Lyon, France
| | - B Chapot
- DNA Repair Group, International Agency for Research on Cancer, 150 cours Albert Thomas, 69373 Lyon, France
| | - K Muir
- Department of Epidemiology, University of Nottingham, UK
| | - R Houlston
- The Institute of Cancer Research, Sutton, Surrey, UK
| | - A R Norman
- Royal Marsden NHS Trust, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
| | - S Bullock
- The Institute of Cancer Research, Sutton, Surrey, UK
| | - Q Hope
- The Institute of Cancer Research, Sutton, Surrey, UK
| | - J Meitz
- The Institute of Cancer Research, Sutton, Surrey, UK
| | - D Dearnaley
- The Institute of Cancer Research, Sutton, Surrey, UK
- Royal Marsden NHS Trust, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
| | - A Dowe
- Royal Marsden NHS Trust, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
| | - C Southgate
- The Institute of Cancer Research, Sutton, Surrey, UK
| | - A Ardern-Jones
- Royal Marsden NHS Trust, 15 Cotswold Road, Sutton, Surrey SM2 5NG, UK
| | | | - D F Easton
- Cancer Research UK, Genetic Epidemiology Unit, Strangeways Research Laboratory, Worts Causeway, Cambridge CB1 8RN, UK
| | - R A Eeles
- The Institute of Cancer Research, Sutton, Surrey, UK
| | - J Hall
- DNA Repair Group, International Agency for Research on Cancer, 150 cours Albert Thomas, 69373 Lyon, France
- DNA Repair Group, International Agency for Research on Cancer, 150 cours Albert Thomas, 69373 Lyon, France. E-mail:
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Kommu S, Edwards S, Eeles R. The clinical genetics of prostate cancer. Hered Cancer Clin Pract 2004; 2:111-21. [PMID: 20233465 PMCID: PMC4392519 DOI: 10.1186/1897-4287-2-3-111] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2004] [Accepted: 07/27/2004] [Indexed: 12/24/2022] Open
Abstract
Prostate cancer is the most common cancer in men and the second highest cause of cancer-related mortality in the U.K. A genetic component in predisposition to prostate cancer has been recognized for decades. One of the strongest epidemiological risk factors for prostate cancer is a positive family history. The hunt for the genes that predispose to prostate cancer in families has been the focus of many research groups worldwide for the past 10 years. Both epidemiological and twin studies support a role for genetic predisposition to prostate cancer. Familial cancer loci have been found, but the genes that cause familial prostate cancer remain largely elusive. Unravelling the genetics of prostate cancer is challenging and is likely to involve the analysis of numerous predisposition genes. Current evidence supports the hypothesis that excess familial risk of prostate cancer could be due to the inheritance of multiple moderate-risk genetic variants. Although research on hereditary prostate cancer has improved our knowledge of the genetic aetiology of the disease, a lot of questions still remain unanswered. This article explores the current evidence that there is a genetic component to the aetiology of prostate cancer and attempts to put into context the diverse findings that have been shown to be possibly associated with the development of hereditary prostate cancer. Linkage searches over the last decade are summarised. It explores issues as to why understanding the genetics of prostate cancer has been so difficult and why despite this, it is still a major focus of research. Finally, current and future management strategies of men with Hereditary Prostate Cancer (HPC) are discussed.
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Affiliation(s)
- Sashi Kommu
- Reader in Clinical Cancer Genetics, Translational Cancer Genetics Team, Institute of Cancer Research, Sutton, UK.
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Easton DF, Schaid DJ, Whittemore AS, Isaacs WJ. Where are the prostate cancer genes?--A summary of eight genome wide searches. Prostate 2003; 57:261-9. [PMID: 14601022 DOI: 10.1002/pros.10300] [Citation(s) in RCA: 93] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND There is strong evidence for genetic susceptibility to prostate cancer, but most of the genes underlying this susceptibility remain to be identified. METHODS We reviewed the results of eight genome-wide linkage searches based on 1,293 families with multiple cases of prostate cancer. RESULTS Across these studies, 11 linkage peaks with LOD scores in excess of 2 were identified. However, no chromosomal region was reported as significant at this level by more than one study and only one corresponded to a peak previously suggested by another group. CONCLUSIONS These results indicate that prostate cancer is genetically complex, and that combined analyses of large family sets will be required to evaluate reliably the linkage evidence.
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Affiliation(s)
- Douglas F Easton
- Cancer Research U.K. Genetic Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, United Kingdom.
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