Abstract
Hereditary cancer diagnostics is rapidly evolving with the increased availability and uptake of next-generation sequencing (NGS)-based multigene panels. Multigene panels offer several advantages such as time- and cost-effectiveness, and have been shown to be a useful diagnostic tool, particularly for cases suggestive of multiple different hereditary cancer conditions and for atypical phenotypes. However, there are many important considerations in the clinical use of multigene panels in hereditary cancer predisposition testing, from both clinic and laboratory perspectives. There are currently limited resources to guide clinicians in ordering multigene panels and managing patients with significant findings in lesser known genes. In addition, the development of clinical grade NGS-based panels is complex, and laboratories differ in various aspects of testing methodology. In this chapter, we review the various aspects of multigene panel workflow including target enrichment, NGS, bioinformatics, and interpretation of results. Results from our laboratory’s experience with over 20,000 hereditary cancer panel cases are also summarized, with a focus on frequently mutated moderate penetrance genes, atypical phenotypes, and mosaic results.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Pagon, R. GeneTests. 2014. Accessed on September 2, 2014, from: http://www.genetests.org/
Pritchard CC, et al. ColoSeq provides comprehensive lynch and polyposis syndrome mutational analysis using massively parallel sequencing. J Mol Diagn. 2012;14(4):357–66.
Walsh T, et al. Detection of inherited mutations for breast and ovarian cancer using genomic capture and massively parallel sequencing. Proc Natl Acad Sci U S A. 2010;107(28):12629–33.
Castera L, et al. Next-generation sequencing for the diagnosis of hereditary breast and ovarian cancer using genomic capture targeting multiple candidate genes. Eur J Hum Genet. 2014;22:1305.
Chong HK, et al. The validation and clinical implementation of BRCAplus: a comprehensive high-risk breast cancer diagnostic assay. PLoS One. 2014;9(5):e97408.
Morgan JE, et al. Genetic diagnosis of familial breast cancer using clonal sequencing. Hum Mutat. 2010;31(4):484–91.
Kurian AW, et al. Clinical evaluation of a multiple-gene sequencing panel for hereditary cancer risk assessment. J Clin Oncol. 2014;32(19):2001–9.
Lam CW, Mak CM. Allele dropout in PCR-based diagnosis of Wilson disease: mechanisms and solutions. Clin Chem. 2006;52(3):517–20.
Landsverk ML, et al. Diagnostic approaches to apparent homozygosity. Genet Med. 2012;14(10):877–82.
Sulonen AM, et al. Comparison of solution-based exome capture methods for next generation sequencing. Genome Biol. 2011;12(9):R94.
Elliott AM, et al. Rapid detection of the ACMG/ACOG-recommended 23 CFTR disease-causing mutations using ion torrent semiconductor sequencing. J Biomol Tech. 2012;23(1):24–30.
Nord AS, et al. Accurate and exact CNV identification from targeted high-throughput sequence data. BMC Genomics. 2011;12:184.
Xie C, Tammi MT. CNV-seq, a new method to detect copy number variation using high-throughput sequencing. BMC Bioinform. 2009;10:80.
Plon SE, et al. Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results. Hum Mutat. 2008;29(11):1282–91.
Richards CS, et al. ACMG recommendations for standards for interpretation and reporting of sequence variations: revisions 2007. Genet Med. 2008;10(4):294–300.
Tavtigian SV, et al. Assessing pathogenicity: overview of results from the IARC Unclassified Genetic Variants Working Group. Hum Mutat. 2008;29(11):1261–4.
Thompson BA, et al. Application of a 5-tiered scheme for standardized classification of 2,360 unique mismatch repair gene variants in the InSiGHT locus-specific database. Nat Genet. 2014;46(2):107–15.
Freidlin B, et al. Trend tests for case-control studies of genetic markers: power, sample size and robustness. Hum Hered. 2002;53(3):146–52.
Hennekam RC. Care for patients with ultra-rare disorders. Eur J Med Genet. 2011;54(3):220–4.
Eggington JM, et al. A comprehensive laboratory-based program for classification of variants of uncertain significance in hereditary cancer genes. Clin Genet. 2014;86(3):229–37.
Exome Variant Server, NHLBI GO Exome Sequencing Project (ESP). 2013; Seattle, WA.
Abecasis GR, et al. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491(7422):56–65.
Consortium IH. The International HapMap Project. Nature. 2003;426(6968):789–96.
Sherry ST, et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001;29(1):308–11.
Oddoux C, et al. The carrier frequency of the BRCA2 6174delT mutation among Ashkenazi Jewish individuals is approximately 1 %. Nat Genet. 1996;14(2):188–90.
Struewing JP, et al. The carrier frequency of the BRCA1 185delAG mutation is approximately 1 percent in Ashkenazi Jewish individuals. Nat Genet. 1995;11(2):198–200.
Morton NE. Sequential tests for the detection of linkage. Am J Hum Genet. 1955;7(3):277–318.
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(3):652–5.
Domchek SM, et al. Biallelic deleterious BRCA1 mutations in a woman with early-onset ovarian cancer. Cancer Discov. 2013;3(4):399–405.
Judkins T, et al. Application of embryonic lethal or other obvious phenotypes to characterize the clinical significance of genetic variants found in trans with known deleterious mutations. Cancer Res. 2005;65(21):10096–103.
Bakry D, et al. Genetic and clinical determinants of constitutional mismatch repair deficiency syndrome: report from the constitutional mismatch repair deficiency consortium. Eur J Cancer. 2014;50(5):987–96.
Meyer S, et al. Fanconi anaemia, BRCA2 mutations and childhood cancer: a developmental perspective from clinical and epidemiological observations with implications for genetic counselling. J Med Genet. 2014;51(2):71–5.
Myers K, et al. The clinical phenotype of children with Fanconi anemia caused by biallelic FANCD1/BRCA2 mutations. Pediatr Blood Cancer. 2012;58(3):462–5.
Wimmer K, et al. Diagnostic criteria for constitutional mismatch repair deficiency syndrome: suggestions of the European consortium ‘care for CMMRD’ (C4CMMRD). J Med Genet. 2014;51(6):355–65.
Laduca H, et al. Utilization of multigene panels in hereditary cancer predisposition testing: analysis of more than 2,000 patients. Genet Med. 2014;16:830.
Adank MA, et al. CHEK2*1100delC homozygosity is associated with a high breast cancer risk in women. J Med Genet. 2011;48(12):860–3.
Huijts PE, et al. CHEK2*1100delC homozygosity in the Netherlands–prevalence and risk of breast and lung cancer. Eur J Hum Genet. 2014;22(1):46–51.
Thusberg J, Vihinen M. Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods. Hum Mutat. 2009;30(5):703–14.
Ng PC, Henikoff S. Predicting the effects of amino acid substitutions on protein function. Annu Rev Genomics Hum Genet. 2006;7:61–80.
Adzhubei IA, et al. A method and server for predicting damaging missense mutations. Nat Methods. 2010;7(4):248–9.
Kircher M, et al. A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet. 2014;46(3):310–5.
Mathe E, et al. Computational approaches for predicting the biological effect of p53 missense mutations: a comparison of three sequence analysis based methods. Nucleic Acids Res. 2006;34(5):1317–25.
Tavtigian SV, et al. Comprehensive statistical study of 452 BRCA1 missense substitutions with classification of eight recurrent substitutions as neutral. J Med Genet. 2006;43(4):295–305.
Chao EC, et al. Accurate classification of MLH1/MSH2 missense variants with multivariate analysis of protein polymorphisms-mismatch repair (MAPP-MMR). Hum Mutat. 2008;29(6):852–60.
Association for Molecular Pathology et al. v. Myriad Genetics Inc., et al. in 569 U. S. ____ (2013). 2013.
Loveday C, et al. Germline mutations in RAD51D confer susceptibility to ovarian cancer. Nat Genet. 2011;43(9):879–82.
Gutierrez-Enriquez S, et al. About 1 % of the breast and ovarian Spanish families testing negative for BRCA1 and BRCA2 are carriers of RAD51D pathogenic variants. Int J Cancer. 2014;134(9):2088–97.
Osher DJ, et al. Mutation analysis of RAD51D in non-BRCA1/2 ovarian and breast cancer families. Br J Cancer. 2012;106(8):1460–3.
Thompson ER, et al. Analysis of RAD51D in ovarian cancer patients and families with a history of ovarian or breast cancer. PLoS One. 2013;8(1):e54772.
Wickramanayake A, et al. Loss of function germline mutations in RAD51D in women with ovarian carcinoma. Gynecol Oncol. 2012;127(3):552–5.
Vaughn CP, et al. The frequency of previously undetectable deletions involving 3′ Exons of the PMS2 gene. Genes Chromosomes Cancer. 2013;52(1):107–12.
Pennington KP, Swisher EM. Hereditary ovarian cancer: beyond the usual suspects. Gynecol Oncol. 2012;124(2):347–53.
Walsh T, et al. Mutations in 12 genes for inherited ovarian, fallopian tube, and peritoneal carcinoma identified by massively parallel sequencing. Proc Natl Acad Sci U S A. 2011;108(44):18032–7.
The NCCN Clinical Practice Guidelines in Oncologyâ„¢ Genetic/Familial High-Risk Assessment: Breast and Ovarian V3.2013. National Comprehensive Cancer Network, Inc. 2013; Available from: http://www.nccn.org/
McCabe N, et al. Deficiency in the repair of DNA damage by homologous recombination and sensitivity to poly(ADP-ribose) polymerase inhibition. Cancer Res. 2006;66(16):8109–15.
National Cancer Institute, Clinical Trials. 2014.
Behjati S, et al. A pathogenic mosaic TP53 mutation in two germ layers detected by next generation sequencing. PLoS One. 2014;9(5):e96531.
Chen Z, et al. Enhanced sensitivity for detection of low-level germline mosaic RB1 mutations in sporadic retinoblastoma cases using deep semiconductor sequencing. Hum Mutat. 2014;35(3):384–91.
Coppin L, et al. VHL mosaicism can be detected by clinical next-generation sequencing and is not restricted to patients with a mild phenotype. Eur J Hum Genet. 2014;22(9):1149–52.
Pritchard CC, et al. A mosaic PTEN mutation causing Cowden syndrome identified by deep sequencing. Genet Med. 2013;15(12):1004–7.
Narod SA, et al. Should all BRCA1 mutation carriers with stage I breast cancer receive chemotherapy? Breast Cancer Res Treat. 2013;138(1):273–9.
Rebbeck TR, et al. Bilateral prophylactic mastectomy reduces breast cancer risk in BRCA1 and BRCA2 mutation carriers: the PROSE Study Group. J Clin Oncol. 2004;22(6):1055–62.
Vasen HF, et al. Revised guidelines for the clinical management of Lynch syndrome (HNPCC): recommendations by a group of European experts. Gut. 2013;62(6):812–23.
The NCCN Clinical Practice Guidelines in Oncologyâ„¢ Colorectal Cancer Screening V1.2013. 2013; Available from: http://www.nccn.org/
Robson ME, et al. American Society of Clinical Oncology policy statement update: genetic and genomic testing for cancer susceptibility. J Clin Oncol. 2010;28(5):893–901.
Riley BD, et al. Essential elements of genetic cancer risk assessment, counseling, and testing: updated recommendations of the National Society of Genetic Counselors. J Genet Couns. 2012;21(2):151–61.
Fecteau H, et al. The evolution of cancer risk assessment in the era of next generation sequencing. J Genet Couns. 2014;23(4):633–9.
Mauer CB, et al. The integration of next-generation sequencing panels in the clinical cancer genetics practice: an institutional experience. Genet Med. 2014;16:407.
Spurdle AB, et al. ENIGMA–evidence-based network for the interpretation of germline mutant alleles: an international initiative to evaluate risk and clinical significance associated with sequence variation in BRCA1 and BRCA2 genes. Hum Mutat. 2012;33(1):2–7.
Liang J, et al. APC polymorphisms and the risk of colorectal neoplasia: a HuGE review and meta-analysis. Am J Epidemiol. 2013;177(11):1169–79.
Tung N, et al. Frequency of mutations in individuals with breast cancer referred for BRCA1 and BRCA2 testing using next-generation sequencing with a 25-gene panel. Cancer. 2015;121:25.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
LaDuca, H. et al. (2015). Utilization of Multigene Panels in Hereditary Cancer Predisposition Testing. In: Wu, W., Choudhry, H. (eds) Next Generation Sequencing in Cancer Research, Volume 2. Springer, Cham. https://doi.org/10.1007/978-3-319-15811-2_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-15811-2_26
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-15810-5
Online ISBN: 978-3-319-15811-2
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)