Large numbers of individuals are required to classify and define risk for rare variants in known cancer risk genes

Genetics in Medicine

Volumn 16, Issue 7, 2014, Pages 529-534

  Shirts, Brian H ^a   Jacobson, Angela ^a   Jarvik, Gail P ^a,b   Browning, Brian L ^b  

^a UNIVERSITY OF WASHINGTON   (United States)

^b UNIVERSITY OF WASHINGTON SCHOOL OF MEDICINE   (United States)

Author keywords

Cancer risk; Odds ratio; Power; Relative risk; Sample size calculation; Study design; Variant of uncertain significance; VUS

Indexed keywords

ADULT; AGED; ARTICLE; BREAST CANCER; CALCULATION; CANCER RISK; CLINICAL PRACTICE; COLON CANCER; CONTROLLED STUDY; FALSE POSITIVE RESULT; FAMILIAL CANCER; GENE FREQUENCY; GENETIC RISK; GENETIC VARIABILITY; HUMAN; KNOWLEDGE; MAJOR CLINICAL STUDY; PROBABILITY; RISK FACTOR; SAMPLE SIZE; BREAST TUMOR; CLASSIFICATION; COLON TUMOR; FEMALE; GENETIC VARIATION; GENETICS; HUMAN GENOME; RISK ASSESSMENT;

TUMOR MARKER;

BIOMARKERS, TUMOR; BREAST NEOPLASMS; COLONIC NEOPLASMS; FEMALE; GENE FREQUENCY; GENETIC VARIATION; GENOME, HUMAN; HUMANS; RISK ASSESSMENT; SAMPLE SIZE;

EID: 84903753841     PISSN: 10983600     EISSN: 15300366     Source Type: Journal    
DOI: 10.1038/gim.2013.187     Document Type: Article

References (40)

1. Peltomäki P, Vasen H. Mutations associated with HNPCC predisposition - Update of ICG-HNPCC/INSiGHT mutation database. Dis Markers 2004;20:269- 276.
2. Frank TS, Deffenbaugh AM, Reid JE, et al. Clinical characteristics of individuals with germline mutations in BRCA1 and BRCA2: analysis of 10,000 individuals. J Clin Oncol 2002;20:1480-1490.
3. Goldgar DE, Easton DF, Byrnes GB, Spurdle AB, Iversen ES, Greenblatt MS; IARC Unclassified Genetic Variants Working Group. Genetic evidence and integration of various data sources for classifying uncertain variants into a single model. Hum Mutat 2008;29:1265-1272.
4. Tennessen JA, Bigham AW, O'Connor TD, et al.; Broad GO; Seattle GO; NHLBI Exome Sequencing Project. Evolution and functional impact of rare coding variation from deep sequencing of human exomes. Science 2012;337:64-69.
5. Walsh T, Lee MK, Casadei S, et al. Detection of inherited mutations for breast and ovarian cancer using genomic capture and massively parallel sequencing. Proc Natl Acad Sci USA 2010;107:12629-12633.
6. Miller-Samuel S, MacDonald DJ, McDonald DJ, et al. Variants of uncertain significance in breast cancer-related genes: real-world implications for a clinical conundrum. Part one: clinical genetics recommendations. Semin Oncol 2011;38:469-480.
7. O'Neill SC, Rini C, Goldsmith RE, Valdimarsdottir H, Cohen LH, Schwartz MD. Distress among women receiving uninformative BRCA1/2 results: 12-month outcomes. Psychooncology 2009;18:1088-1096.
8. Culver J, Brinkerhoff C, Clague J, et al. Variants of uncertain significance in BRCA testing: evaluation of surgical decisions, risk perception, and cancer distress. Clin Genet 2013;17:12097.
9. Plon SE, Eccles DM, Easton D, et al.; IARC Unclassified Genetic Variants Working Group. Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results. Hum Mutat 2008;29:1282-1291.
10. Rhem HL. Laboratory for Molecular Medicine Variant Classification Rules. Partners Laboratory for Molecular Medicine: Cambridge, MA, 2012. http://pcpgm.partners.org/sites/default/files/LMM/Resources/LMM- VariantClassification-05.26.11.pdf.Accessed17July2013.
11. Bell J, Bodmer D, Sistermans E, Ramsden SC. Practice guidelines for the interpretation and reporting of unclassified variants (UVs) in clinical molecular genetics. UK Clinical Molecular Genetics Society; 11 January 2008: UK Clinical Molecular Genetics Society and Dutch Society of Clinical Genetics Laboratory Specialists. Unclassified variants good practice meeting, Manchester, UK, 2007.
12. Lindor NM, Goldgar DE, Tavtigian SV, Plon SE, Couch FJ. BRCA1/2 sequence variants of uncertain significance: a primer for providers to assist in discussions and in medical management. Oncologist 2013;18:518-524.
13. Dorschner MO, Amendola LM, Turner EH, et al.; National Heart, Lung, and Blood Institute Grand Opportunity Exome Sequencing Project. Actionable, pathogenic incidental findings in 1,000 participants' exomes. Am J Hum Genet 2013;93:631-640.
14. Thompson BA, Goldgar DE, Paterson C, et al.; Colon Cancer Family Registry. A multifactorial likelihood model for MMR gene variant classification incorporating probabilities based on sequence bioinformatics and tumor characteristics: a report from the Colon Cancer Family Registry. Hum Mutat 2013;34:200-209.
15. Bayrak-Toydemir P, McDonald J, Mao R, et al. Likelihood ratios to assess genetic evidence for clinical significance of uncertain variants: hereditary hemorrhagic telangiectasia as a model. Exp Mol Pathol 2008;85:45-49.
16. Spurdle AB. Clinical relevance of rare germline sequence variants in cancer genes: evolution and application of classification models. Curr Opin Genet Dev 2010;20:315-323.
17. Lindor NM, Guidugli L, Wang X, et al. A review of a multifactorial probabilitybased model for classification of BRCA1 and BRCA2 variants of uncertain significance (VUS). Hum Mutat 2012;33:8-21.
18. Zhang B, Beeghly-Fadiel A, Long J, Zheng W. Genetic variants associated with breast-cancer risk: comprehensive research synopsis, meta-analysis, and epidemiological evidence. Lancet Oncol 2011;12:477-488.
19. Vink GR, van Asperen CJ, Devilee P, Breuning MH, Bakker E. Unclassified variants in disease-causing genes: nonuniformity of genetic testing and counselling, a proposal for guidelines. Eur J Hum Genet 2005;13:525-527.
20. Nieuwenhuis MH, Vasen HF. Correlations between mutation site in APC and phenotype of familial adenomatous polyposis (FAP): a review of the literature. Crit Rev Oncol Hematol 2007;61:153-161.
21. Ziegler A, Konig IR. A Statistical Approach to Genetic Epidemiology. Wiley-VCH Verlag & Co: Weinheim, Germany, 2006.
22. Fleiss JL, Levin B, Paik MC. Statistical Methods for Rates and Proportions, 3rd edn. Wiley-Interscience: Hoboken, NJ, 2003.
23. Antoniou A, Pharoah PD, Narod S, et al. Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case Series unselected for family history: a combined analysis of 22 studies. Am J Hum Genet 2003;72:1117-1130.
24. Chen S, Parmigiani G. Meta-analysis of BRCA1 and BRCA2 penetrance. J Clin Oncol 2007;25:1329-1333.
25. Quehenberger F, Vasen HF, van Houwelingen HC. Risk of colorectal and endometrial cancer for carriers of mutations of the hMLH1 and hMSH2 gene: correction for ascertainment. J Med Genet 2005;42:491-496.
26. Petersen GM, Parmigiani G, Thomas D. Missense mutations in disease genes: a Bayesian approach to evaluate causality. Am J Hum Genet 1998;62:1516- 1524.
27. Thompson D, Easton DF, Goldgar DE. A full-likelihood method for the evaluation of causality of sequence variants from family data. Am J Hum Genet 2003;73:652-655.
28. Mohammadi L, Vreeswijk MP, Oldenburg R, et al. A simple method for co-segregation analysis to evaluate the pathogenicity of unclassified variants; BRCA1 and BRCA2 as an example. BMC Cancer 2009;9:211.
29. Zhao LP, Aragaki C, Hsu L, et al. Integrated designs for gene discovery and characterization. J Natl Cancer Inst Monographs 1999;71-80.
30. Cui JS, Spurdle AB, Southey MC, et al. Regressive logistic and proportional hazards disease models for within-family analyses of measured genotypes, with application to a CYP17 polymorphism and breast cancer. Genet Epidemiol 2003;24:161-172.
31. Jenkins MA, Croitoru ME, Monga N, et al. Risk of colorectal cancer in monoallelic and biallelic carriers of MYH mutations: a population-based casefamily study. Cancer Epidemiol Biomarkers Prev 2006;15:312-314.
32. Jenkins MA, Baglietto L, Dowty JG, et al. Cancer risks for mismatch repair gene mutation carriers: a population-based early onset case-family study. Clin Gastroenterol Hepatol 2006;4:489-498.
33. Zhang Z, Ersoz E, Lai CQ, et al. Mixed linear model approach adapted for genome-wide association studies. Nat Genet 2010;42:355-360.
34. Kang HM, Sul JH, Service SK, et al. Variance component model to account for sample structure in genome-wide association studies. Nat Genet 2010;42:348- 354.
35. Project NGES. NHLBI Exome Sequencing Project (ESP). Exome Variant Server. Seattle, WA. University of Washington: Seattle, GO, 2013 (updated 7 June 2013; v.0.0.20 (Exome Variant Server). http://evs.gs.washington.edu/EVS/. Accessed20August2013.
36. Clarke E, Green RC, Green JS, et al. Inherited deleterious variants in GALNT12 are associated with CRC susceptibility. Hum Mutat 2012;33:1056-1058.
37. Guda K, Moinova H, He J, et al. Inactivating germ-line and somatic mutations in polypeptide N-acetylgalactosaminyltransferase 12 in human colon cancers. Proc Natl Acad Sci USA 2009;106:12921-12925.
38. Bouwman P, van der Gulden H, van der Heijden I et al. A high-throughput functional complementation assay for classification of BRCA1 missense variants. Cancer Discov 2013;23:23.
39. Tram E, Savas S, Ozcelik H. Missense variants of uncertain significance (VUS) altering the phosphorylation patterns of BRCA1 and BRCA2. PLoS ONE 2013;8:e62468.
40. 1000 Genomes Project Consortium; Abecasis GR, Altshuler D, Auton A,et al. A map of human genome variation from population-scale sequencing. Nature 2010;467:1061-73.