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Diagnosing Hereditary Cancer Susceptibility Through Multigene Panel Testing

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Next Generation Sequencing Based Clinical Molecular Diagnosis of Human Genetic Disorders

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Abstract

Hereditary cancer diagnostics has considerably evolved with the clinical availability of multigene hereditary cancer panels. Over the past few years, multigene hereditary cancer panels have contributed to a growing number of diagnoses of hereditary cancer syndromes, including patients who would likely have been missed with a traditional testing approach. While panels are largely based on next generation sequencing (NGS), panel design is not always straightforward as there are a number of factors that need to be considered to correctly and reliably diagnose hereditary cancer syndromes. In this chapter, assay design and the interpretation/reporting of multigene panel results are reviewed from the perspective of a commercial genetic testing laboratory. Key observations in multigene panel cohorts are also presented, including the identification of atypical and expanding phenotypes, carriers of pathogenic variants in moderate penetrance genes, and individuals harboring pathogenic variants in multiple cancer susceptibility genes. Such observations have highlighted the need for data sharing and collaborative efforts, which is also discussed.

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Abbreviations

ACMG:

American College of Medical Genetics and Genomics

ASCO:

American Society of Clinical Oncology

CAP:

College of American Pathologists

ClinGen:

Clinical Genome Resource

CMMR-D:

Constitutional mismatch repair deficiency syndrome

CRC:

Colorectal cancer

ESP:

Exome Sequencing Project

ExAC:

Exome Aggregation Consortium

GTR:

Genetic Testing Registry

IARC:

International Agency for Research on Cancer

LOG:

Log of likelihood ratio

NCCN:

National Comprehensive Cancer Network

NGS:

Next generation sequencing

PGL-PCC:

Paraganglioma-pheochromocytoma

References

  1. The NCCN Clinical Practice Guidelines in Oncologyâ„¢ Genetic/Familial High-Risk Assessment: Breast and Ovarian V2.2015. In: National Comprehensive Cancer Network, Inc. http://www.nccn.org/ (2015)

  2. Kapoor, N.S., Curcio, L.D., Blakemore, C., Bremner, A.K., McFarland, R., West, J.G., Banks, K.C.: Multi-Gene panel testing detects equal rates of pathogenic BRCA1/2 mutations and has a higher diagnostic yield compared to limited BRCA1/2 analysis alone in patients at risk for hereditary breast cancer. Ann. Surg. Oncol. 22(10), 3282–3288 (2015)

    Article  PubMed  Google Scholar 

  3. Rehm, H.L., Bale, S.J., Bayrak-Toydemir, P., Berg, J.S., Brown, K.K., Deignan, J.L., et al.: ACMG clinical laboratory standards for next-generation sequencing. Genet. Med. Off. J. Am. Coll. Med. Genet. 15(9), 733–747 (2013). doi:10.1038/gim.2013.92

    Google Scholar 

  4. Easton, D.F., Pharoah, P.D., Antoniou, A.C., Tischkowitz, M., Tavtigian, S.V., Nathanson, K.L., et al.: Gene-panel sequencing and the prediction of breast-cancer risk. N. Engl. J. Med. 372(23), 2243–2257 (2015). doi:10.1056/NEJMsr1501341

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Laduca, H., Stuenkel, A.J., Dolinsky, J.S., Keiles, S., Tandy, S., Pesaran, T., et al.: Utilization of multigene panels in hereditary cancer predisposition testing: analysis of more than 2,000 patients. Genet. Med. Off. J. Am. Coll. Med. Genet. (2014). doi:10.1038/gim.2014.40

    Google Scholar 

  6. Chek Breast Cancer Case-Control Consortium: CHEK2*1100delC and susceptibility to breast cancer: a collaborative analysis involving 10,860 breast cancer cases and 9,065 controls from 10 studies. Am. J. Hum. Genet. 74(6), 1175–1182 (2004). doi:10.1086/421251

    Article  Google Scholar 

  7. Janin, N., Andrieu, N., Ossian, K., Lauge, A., Croquette, M.F., Griscelli, C., et al.: Breast cancer risk in ataxia telangiectasia (AT) heterozygotes: haplotype study in French AT families. Br. J. Cancer. 80(7), 1042–1045 (1999). doi:10.1038/sj.bjc.6690460

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Kilpivaara, O., Vahteristo, P., Falck, J., Syrjakoski, K., Eerola, H., Easton, D., et al.: CHEK2 variant I157T may be associated with increased breast cancer risk. Int. J. Cancer J. Int. du Cancer. 111(4), 543–547 (2004). doi:10.1002/ijc.20299

    Article  CAS  Google Scholar 

  9. Meijers-Heijboer, H., van den Ouweland, A., Klijn, J., Wasielewski, M., de Snoo, A., Oldenburg, R., et al.: Low-penetrance susceptibility to breast cancer due to CHEK2(*)1100delC in noncarriers of BRCA1 or BRCA2 mutations. Nat. Genet. 31(1), 55–59 (2002). doi:10.1038/ng879

    Article  CAS  PubMed  Google Scholar 

  10. Olsen, J.H., Hahnemann, J.M., Borresen-Dale, A.L., Tretli, S., Kleinerman, R., Sankila, R., et al.: Breast and other cancers in 1445 blood relatives of 75 Nordic patients with ataxia telangiectasia. Br. J. Cancer. 93(2), 260–265 (2005). doi:10.1038/sj.bjc.6602658

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Renwick, A., Thompson, D., Seal, S., Kelly, P., Chagtai, T., Ahmed, M., et al.: ATM mutations that cause ataxia-telangiectasia are breast cancer susceptibility alleles. Nat. Genet. 38(8), 873–875 (2006). doi:10.1038/ng1837

    Article  CAS  PubMed  Google Scholar 

  12. Thompson, D., Duedal, S., Kirner, J., McGuffog, L., Last, J., Reiman, A., et al.: Cancer risks and mortality in heterozygous ATM mutation carriers. J. Natl. Cancer Inst. 97(11), 813–822 (2005). doi:10.1093/jnci/dji141

    Article  CAS  PubMed  Google Scholar 

  13. Weischer, M., Heerfordt, I.M., Bojesen, S.E., Eigentler, T., Garbe, C., Rocken, M., et al.: CHEK2*1100delC and risk of malignant melanoma: Danish and German studies and meta-analysis. J. Invest. Dermatol. 132(2), 299–303 (2012). doi:10.1038/jid.2011.303

    Article  CAS  PubMed  Google Scholar 

  14. Mauer, C.B., Pirzadeh-Miller, S.M., Robinson, L.D., Euhus, D.M.: The integration of next-generation sequencing panels in the clinical cancer genetics practice: an institutional experience. Genet. Med. Off. J. Am. Coll. Med. Genet. (2013). doi:10.1038/gim.2013.160

    Google Scholar 

  15. Richards, S., Aziz, N., Bale, S., Bick, D., Das, S., Gastier-Foster, J., et al.: Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. Off. J. Am. Coll. Med. Genet. 17(5), 405–424 (2015). doi:10.1038/gim.2015.30

    Google Scholar 

  16. Mu, W., Lu, H.M., Chen, J., Li, S., Elliott, A.M.: Sanger confirmation is required to achieve optimal sensitivity and specificity in next-generation sequencing panel testing. J. Mol. Diagn. 18(6), 923–932 (2016). doi:10.1016/j.jmoldx.2016.07.006

    Article  CAS  PubMed  Google Scholar 

  17. Vaughn, C.P., Robles, J., Swensen, J.J., Miller, C.E., Lyon, E., Mao, R., et al.: Clinical analysis of PMS2: mutation detection and avoidance of pseudogenes. Hum. Mutat. 31(5), 588–593 (2010). doi:10.1002/humu.21230

    CAS  PubMed  Google Scholar 

  18. Li, J., Dai, H., Feng, Y., Tang, J., Chen, S., Tian, X., et al.: A comprehensive strategy for accurate mutation detection of the highly homologous PMS2. J. Mol. Diagn. 17(5), 545–553 (2015). doi:10.1016/j.jmoldx.2015.04.001

    Article  CAS  PubMed  Google Scholar 

  19. Invitae. Sequencing exons 12-15 of PMS2 using next-generation sequencing (NGS). http://marketing.invitae.com/acton/attachment/7098/f-0139/1/-/-/-/-/WP103-1_PMS2%20Sequencing%20NGS%20Validation%20Summary.pdf (2015). Accessed July 2015

  20. Wu, W., Choudhry, H. (eds.): Next generation sequencing in cancer research, volume 2. Springer International Publishing, Switzerland (2015)

    Google Scholar 

  21. Duan, J., Zhang, J.G., Deng, H.W., Wang, Y.P.: Comparative studies of copy number variation detection methods for next-generation sequencing technologies. PLoS One. 8(3), e59128 (2013). doi:10.1371/journal.pone.0059128

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Feng, Y., Chen, D., Wang, G.L., Zhang, V.W., Wong, L.J.: Improved molecular diagnosis by the detection of exonic deletions with target gene capture and deep sequencing. Genet. Med. Off. J. Am. Coll. Med. Genet. 17(2), 99–107 (2015). doi:10.1038/gim.2014.80

    CAS  Google Scholar 

  23. Association for Molecular Pathology et al. v. Myriad Genetics Inc., et al 569 U. S. ____ (2013), Supreme Court of the United States (June 13, 2013)

    Google Scholar 

  24. Jaeger, E., Leedham, S., Lewis, A., Segditsas, S., Becker, M., Cuadrado, P.R., et al.: Hereditary mixed polyposis syndrome is caused by a 40-kb upstream duplication that leads to increased and ectopic expression of the BMP antagonist GREM1. Nat. Genet. 44(6), 699–703 (2012). doi:10.1038/ng.2263

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Palles, C., Cazier, J.B., Howarth, K.M., Domingo, E., Jones, A.M., Broderick, P., et al.: Germline mutations affecting the proofreading domains of POLE and POLD1 predispose to colorectal adenomas and carcinomas. Nat. Genet. 45(2), 136–144 (2013). doi:10.1038/ng.2503

    Article  CAS  PubMed  Google Scholar 

  26. Valle, L., Hernandez-Illan, E., Bellido, F., Aiza, G., Castillejo, A., Castillejo, M.I., et al.: New insights into POLE and POLD1 germline mutations in familial colorectal cancer and polyposis. Hum. Mol. Genet. 23(13), 3506–3512 (2014). doi:10.1093/hmg/ddu058

    Article  CAS  PubMed  Google Scholar 

  27. Pesaran, T., Karam, R., Huether, R., Li, S., Farber-Katz, S., Chamberlin, A., et al.: Beyond DNA: an integrated and functional approach for classifying germline variants in breast cancer genes. Int. J. Breast Cancer. 2016, 2469523 (2016). doi:10.1155/2016/2469523

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Plon, S.E., Eccles, D.M., Easton, D., Foulkes, W.D., Genuardi, M., Greenblatt, M.S., et al.: Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results. Hum. Mutat. 29(11), 1282–1291 (2008). doi:10.1002/humu.20880

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Goldgar, D.E., Easton, D.F., Byrnes, G.B., Spurdle, A.B., Iversen, E.S., Greenblatt, M.S., et al.: Genetic evidence and integration of various data sources for classifying uncertain variants into a single model. Hum. Mutat. 29(11), 1265–1272 (2008). doi:10.1002/humu.20897

    Article  PubMed  PubMed Central  Google Scholar 

  30. Petersen, G.M., Parmigiani, G., Thomas, D.: Missense mutations in disease genes: a Bayesian approach to evaluate causality. Am. J. Hum. Genet. 62(6), 1516–1524 (1998). doi:10.1086/301871

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Thompson, D., Easton, D.F., Goldgar, D.E.: A full-likelihood method for the evaluation of causality of sequence variants from family data. Am. J. Hum. Genet. 73(3), 652–655 (2003). doi:10.1086/378100

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Mohammadi, L., Vreeswijk, M.P., Oldenburg, R., van den Ouweland, A., Oosterwijk, J.C., van der Hout, A.H., et al.: A simple method for co-segregation analysis to evaluate the pathogenicity of unclassified variants; BRCA1 and BRCA2 as an example. BMC Cancer. 9, 211 (2009). doi:10.1186/1471-2407-9-211

    Article  PubMed  PubMed Central  Google Scholar 

  33. Ott, J., Wang, J., Leal, S.M.: Genetic linkage analysis in the age of whole-genome sequencing. Nat. Rev. Genet. 16(5), 275–284 (2015). doi:10.1038/nrg3908

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. 1000 Genomes Project [database on the Internet]. Available from: http://www.1000genomes.org/. Accessed 11 Nov 2016

  35. Exome Variant Server, NHLBI GO Exome Sequencing Project (ESP) [database on the Internet] 2013. Available from: http://evs.gs.washington.edu/EVS/. Accessed 11 Nov 2016

  36. Abecasis, G.R., Auton, A., Brooks, L.D., DePristo, M.A., Durbin, R.M., Handsaker, R.E., et al.: An integrated map of genetic variation from 1,092 human genomes. Nature. 491(7422), 56–65 (2012). doi:10.1038/nature11632

    Article  PubMed  Google Scholar 

  37. Lek, M., Karczewski, K.J., Minikel, E.V., Samocha, K.E., Banks, E., Fennell, T., et al.: Analysis of protein-coding genetic variation in 60,706 humans. Nature. 536(7616), 285–291 (2016). doi:10.1038/nature19057

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Exome Aggregation Consortium (ExAC) [database on the Internet]. Available from: http://exac.broadinstitute.org. Accessed 11 Nov 2016

  39. Genome Aggregation Database (GnomAD) [database on the Internet] 2016. Available from: http://gnomad.broadinstitute.org/. Accessed 11 Nov 2016

  40. Loveday, C., Turnbull, C., Ramsay, E., Hughes, D., Ruark, E., Frankum, J.R., et al.: Germline mutations in RAD51D confer susceptibility to ovarian cancer. Nat. Genet. 43(9), 879–882 (2011). doi:10.1038/ng.893

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Meindl, A., Hellebrand, H., Wiek, C., Erven, V., Wappenschmidt, B., Niederacher, D., et al.: Germline mutations in breast and ovarian cancer pedigrees establish RAD51C as a human cancer susceptibility gene. Nat. Genet. 42(5), 410–414 (2010). doi:10.1038/ng.569

    Article  CAS  PubMed  Google Scholar 

  42. Comino-Mendez, I., Gracia-Aznarez, F.J., Schiavi, F., Landa, I., Leandro-Garcia, L.J., Leton, R., et al.: Exome sequencing identifies MAX mutations as a cause of hereditary pheochromocytoma. Nat. Genet. 43(7), 663–667 (2011). doi:10.1038/ng.861

    Article  CAS  PubMed  Google Scholar 

  43. Antoniou, A.C., Foulkes, W.D., Tischkowitz, M.: Breast-cancer risk in families with mutations in PALB2. N. Engl. J. Med. 371(17), 1651–1652 (2014). doi:10.1056/NEJMc1410673

    PubMed  Google Scholar 

  44. Xiang, H.P., Geng, X.P., Ge, W.W., Li, H.: Meta-analysis of CHEK2 1100delC variant and colorectal cancer susceptibility. Eur. J. Cancer. 47(17), 2546–2551 (2011). doi:10.1016/j.ejca.2011.03.025

    Article  CAS  PubMed  Google Scholar 

  45. Jasperson, K.W.: Genetic testing by cancer site: colon (polyposis syndromes). Cancer J. 18(4), 328–333 (2012). doi:10.1097/PPO.0b013e3182609300

    Article  PubMed  Google Scholar 

  46. Savitsky, K., Bar-Shira, A., Gilad, S., Rotman, G., Ziv, Y., Vanagaite, L., et al.: A single ataxia telangiectasia gene with a product similar to PI-3 kinase. Science. 268(5218), 1749–1753 (1995)

    Article  CAS  PubMed  Google Scholar 

  47. Levitus, M., Waisfisz, Q., Godthelp, B.C., de Vries, Y., Hussain, S., Wiegant, W.W., et al.: The DNA helicase BRIP1 is defective in Fanconi anemia complementation group J. Nat. Genet. 37(9), 934–935 (2005). doi:10.1038/ng1625

    Article  CAS  PubMed  Google Scholar 

  48. Levran, O., Attwooll, C., Henry, R.T., Milton, K.L., Neveling, K., Rio, P., et al.: The BRCA1-interacting helicase BRIP1 is deficient in Fanconi anemia. Nat. Genet. 37(9), 931–933 (2005). doi:10.1038/ng1624

    Article  CAS  PubMed  Google Scholar 

  49. Litman, R., Peng, M., Jin, Z., Zhang, F., Zhang, J., Powell, S., et al.: BACH1 is critical for homologous recombination and appears to be the Fanconi anemia gene product FANCJ. Cancer Cell. 8(3), 255–265 (2005). doi:10.1016/j.ccr.2005.08.004

    Article  CAS  PubMed  Google Scholar 

  50. Adank, M.A., Jonker, M.A., Kluijt, I., van Mil, S.E., Oldenburg, R.A., Mooi, W.J., et al.: CHEK2*1100delC homozygosity is associated with a high breast cancer risk in women. J. Med. Genet. 48(12), 860–863 (2011). doi:10.1136/jmedgenet-2011-100380

    Article  CAS  PubMed  Google Scholar 

  51. Stewart, G.S., Maser, R.S., Stankovic, T., Bressan, D.A., Kaplan, M.I., Jaspers, N.G., et al.: The DNA double-strand break repair gene hMRE11 is mutated in individuals with an ataxia-telangiectasia-like disorder. Cell. 99(6), 577–587 (1999)

    Article  CAS  PubMed  Google Scholar 

  52. Carney, J.P., Maser, R.S., Olivares, H., Davis, E.M., Le Beau, M., Yates 3rd, J.R., et al.: The hMre11/hRad50 protein complex and Nijmegen breakage syndrome: linkage of double-strand break repair to the cellular DNA damage response. Cell. 93(3), 477–486 (1998)

    Article  CAS  PubMed  Google Scholar 

  53. Matsuura, S., Tauchi, H., Nakamura, A., Kondo, N., Sakamoto, S., Endo, S., et al.: Positional cloning of the gene for Nijmegen breakage syndrome. Nat. Genet. 19(2), 179–181 (1998). doi:10.1038/549

    Article  CAS  PubMed  Google Scholar 

  54. Varon, R., Vissinga, C., Platzer, M., Cerosaletti, K.M., Chrzanowska, K.H., Saar, K., et al.: Nibrin, a novel DNA double-strand break repair protein, is mutated in Nijmegen breakage syndrome. Cell. 93(3), 467–476 (1998)

    Article  CAS  PubMed  Google Scholar 

  55. Vaz, F., Hanenberg, H., Schuster, B., Barker, K., Wiek, C., Erven, V., et al.: Mutation of the RAD51C gene in a Fanconi anemia-like disorder. Nat. Genet. 42(5), 406–409 (2010). doi:10.1038/ng.570

    Article  CAS  PubMed  Google Scholar 

  56. Howlett, N.G., Taniguchi, T., Olson, S., Cox, B., Waisfisz, Q., De Die-Smulders, C., et al.: Biallelic inactivation of BRCA2 in Fanconi anemia. Science. 297(5581), 606–609 (2002). doi:10.1126/science.1073834

    Article  CAS  PubMed  Google Scholar 

  57. Reid, S., Schindler, D., Hanenberg, H., Barker, K., Hanks, S., Kalb, R., et al.: Biallelic mutations in PALB2 cause Fanconi anemia subtype FA-N and predispose to childhood cancer. Nat. Genet. 39(2), 162–164 (2007). doi:10.1038/ng1947

    Article  CAS  PubMed  Google Scholar 

  58. Xia, B., Dorsman, J.C., Ameziane, N., de Vries, Y., Rooimans, M.A., Sheng, Q., et al.: Fanconi anemia is associated with a defect in the BRCA2 partner PALB2. Nat. Genet. 39(2), 159–161 (2007). doi:10.1038/ng1942

    Article  CAS  PubMed  Google Scholar 

  59. Wimmer, K., Etzler, J.: Constitutional mismatch repair-deficiency syndrome: have we so far seen only the tip of an iceberg? Hum. Genet. 124(2), 105–122 (2008). doi:10.1007/s00439-008-0542-4

    Article  PubMed  Google Scholar 

  60. Bourgeron, T., Chretien, D., Poggi-Bach, J., Doonan, S., Rabier, D., Letouze, P., et al.: Mutation of the fumarase gene in two siblings with progressive encephalopathy and fumarase deficiency. J. Clin. Invest. 93(6), 2514–2518 (1994). doi:10.1172/JCI117261

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Zinn, A.B., Kerr, D.S., Hoppel, C.L.: Fumarase deficiency: a new cause of mitochondrial encephalomyopathy. N. Engl. J. Med. 315(8), 469–475 (1986). doi:10.1056/NEJM198608213150801

    Article  CAS  PubMed  Google Scholar 

  62. Bourgeron, T., Rustin, P., Chretien, D., Birch-Machin, M., Bourgeois, M., Viegas-Pequignot, E., et al.: Mutation of a nuclear succinate dehydrogenase gene results in mitochondrial respiratory chain deficiency. Nat. Genet. 11(2), 144–149 (1995). doi:10.1038/ng1095-144

    Article  CAS  PubMed  Google Scholar 

  63. Felton, K.E., Gilchrist, D.M., Andrew, S.E.: Constitutive deficiency in DNA mismatch repair. Clin. Genet. 71(6), 483–498 (2007). doi:10.1111/j.1399-0004.2007.00803.x

    Article  CAS  PubMed  Google Scholar 

  64. Gatti, R.A., Tward, A., Concannon, P.: Cancer risk in ATM heterozygotes: a model of phenotypic and mechanistic differences between missense and truncating mutations. Mol. Genet. Metab. 68(4), 419–423 (1999). doi:10.1006/mgme.1999.2942

    Article  CAS  PubMed  Google Scholar 

  65. Goldgar, D.E., Healey, S., Dowty, J.G., Da Silva, L., Chen, X., Spurdle, A.B., et al.: Rare variants in the ATM gene and risk of breast cancer. Breast Cancer Res. BCR. 13(4), R73 (2011). doi:10.1186/bcr2919

    Article  CAS  PubMed  Google Scholar 

  66. Tavtigian, S.V., Oefner, P.J., Babikyan, D., Hartmann, A., Healey, S., Le Calvez-Kelm, F., et al.: Rare, evolutionarily unlikely missense substitutions in ATM confer increased risk of breast cancer. Am. J. Hum. Genet. 85(4), 427–446 (2009). doi:10.1016/j.ajhg.2009.08.018

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Antoniou, A., Pharoah, P.D., Narod, S., Risch, H.A., Eyfjord, J.E., Hopper, J.L., 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. 72(5), 1117–1130 (2003). doi:10.1086/375033

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. American College of Medical Genetics and Genomics. Standards and guidelines for clinical genetics laboratories. www.acmg.net (2008)

  69. Alterman, N., Fattal-Valevski, A., Moyal, L., Crawford TO, Lederman, H.M., Ziv, Y., et al.: Ataxia-telangiectasia: mild neurological presentation despite null ATM mutation and severe cellular phenotype. Am. J. Med. Genet. A. 143A(16), 1827–1834 (2007). doi:10.1002/ajmg.a.31853

    Article  CAS  PubMed  Google Scholar 

  70. Mitui, M., Nahas, S.A., Du, L.T., Yang, Z., Lai, C.H., Nakamura, K., et al.: Functional and computational assessment of missense variants in the ataxia-telangiectasia mutated (ATM) gene: mutations with increased cancer risk. Hum. Mutat. 30(1), 12–21 (2009). doi:10.1002/humu.20805

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Saviozzi, S., Saluto, A., Taylor, A.M., Last, J.I., Trebini, F., Paradiso, M.C., et al.: A late onset variant of ataxia-telangiectasia with a compound heterozygous genotype, A8030G/7481insA. J. Med. Genet. 39(1), 57–61 (2002)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Trimis, G.G., Athanassaki, C.K., Kanariou, M.M., Giannoulia-Karantana, A.A.: Unusual absence of neurologic symptoms in a six-year old girl with ataxia-telangiectasia. J. Postgrad. Med. 50(4), 270–271 (2004)

    CAS  PubMed  Google Scholar 

  73. Eliade, M., Skrzypski, J., Baurand, A., Jacquot, C., Bertolone, G., Loustalot, C., et al.: The transfer of multigene panel testing for hereditary breast and ovarian cancer to healthcare: what are the implications for the management of patients and families? Oncotarget. (2016). doi:10.18632/oncotarget.12699

    PubMed Central  Google Scholar 

  74. Susswein, L.R., Marshall, M.L., Nusbaum, R., Vogel Postula, K.J., Weissman, S.M., Yackowski, L., et al.: Pathogenic and likely pathogenic variant prevalence among the first 10,000 patients referred for next-generation cancer panel testing. Genet. Med. Off. J. Am. Coll. Med. Genet. 18(8), 823–832 (2016). doi:10.1038/gim.2015.166

    CAS  Google Scholar 

  75. Thompson, E.R., Rowley, S.M., Li, N., McInerny, S., Devereux, L., Wong-Brown, M.W., et al.: Panel testing for familial breast cancer: calibrating the tension between research and clinical care. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 34(13), 1455–1459 (2016). doi:10.1200/JCO.2015.63.7454

    Article  CAS  Google Scholar 

  76. Walsh, T., Casadei, S., Lee, M.K., Pennil, C.C., Nord, A.S., Thornton, A.M., 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. 108(44), 18032–18037 (2011). doi:10.1073/pnas.1115052108

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Yurgelun, M.B., Masciari, S., Joshi, V.A., Mercado, R.C., Lindor, N.M., Gallinger, S., et al.: Germline TP53 mutations in patients with early-onset colorectal cancer in the Colon cancer family registry. JAMA Oncol. 1(2), 214–221 (2015). doi:10.1001/jamaoncol.2015.0197

    Article  PubMed  Google Scholar 

  78. Cragun, D., Radford, C., Dolinsky, J., Caldwell, M., Chao, E., Pal, T.: Panel-based testing for inherited colorectal cancer: a descriptive study of clinical testing performed by a U.S. laboratory. Clin. Genet. (2014). doi:10.1111/cge.12359

    Google Scholar 

  79. Kurian, A.W., Hare, E.E., Mills, M.A., Kingham, K.E., McPherson, L., Whittemore, A.S., et al.: Clinical evaluation of a multiple-gene sequencing panel for hereditary cancer risk assessment. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 32(19), 2001–2009 (2014). doi:10.1200/JCO.2013.53.6607

    Article  CAS  Google Scholar 

  80. Tung, N., Battelli, C., Allen, B., Kaldate, R., Bhatnagar, S., Bowles, K., 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. 121(1), 25–33 (2015). doi:10.1002/cncr.29010

    Article  CAS  PubMed  Google Scholar 

  81. Minion, L.E., Dolinsky, J.S., Chase, D.M., Dunlop, C.L., Chao, E.C., Monk, B.J.: Hereditary predisposition to ovarian cancer, looking beyond BRCA1/BRCA2. Gynecol. Oncol. 137(1), 86–92 (2015). doi:10.1016/j.ygyno.2015.01.537

    Article  CAS  PubMed  Google Scholar 

  82. Fitzgerald, R.C., Hardwick, R., Huntsman, D., Carneiro, F., Guilford, P., Blair, V., et al.: Hereditary diffuse gastric cancer: updated consensus guidelines for clinical management and directions for future research. J. Med. Genet. 47(7), 436–444 (2010). doi:10.1136/jmg.2009.074237

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. National Institutes of Health Consensus Development Conference Statement: neurofibromatosis. Bethesda, Md., USA, July 13–15, 1987. Neurofibromatosis. 1(3), 172–178 (1988)

    Google Scholar 

  84. Castera, L., Krieger, S., Rousselin, A., Legros, A., Baumann, J.J., Bruet, O., 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. EJHG. (2014). doi:10.1038/ejhg.2014.16

    PubMed  Google Scholar 

  85. Akbari, M.R., Tonin, P., Foulkes, W.D., Ghadirian, P., Tischkowitz, M., Narod, S.A.: RAD51C germline mutations in breast and ovarian cancer patients. Breast Cancer Res. BCR. 12(4), 404 (2010). doi:10.1186/bcr2619

    Article  PubMed  Google Scholar 

  86. Osorio, A., Endt, D., Fernandez, F., Eirich, K., de la Hoya, M., Schmutzler, R., et al.: Predominance of pathogenic missense variants in the RAD51C gene occurring in breast and ovarian cancer families. Hum. Mol. Genet. 21(13), 2889–2898 (2012). doi:10.1093/hmg/dds115

    Article  CAS  PubMed  Google Scholar 

  87. Pelttari, L.M., Heikkinen, T., Thompson, D., Kallioniemi, A., Schleutker, J., Holli, K., et al.: RAD51C is a susceptibility gene for ovarian cancer. Hum. Mol. Genet. 20(16), 3278–3288 (2011). doi:10.1093/hmg/ddr229

    Article  CAS  PubMed  Google Scholar 

  88. Romero, A., Perez-Segura, P., Tosar, A., Garcia-Saenz, J.A., Diaz-Rubio, E., Caldes, T., et al.: A HRM-based screening method detects RAD51C germ-line deleterious mutations in Spanish breast and ovarian cancer families. Breast Cancer Res. Treat. 129(3), 939–946 (2011). doi:10.1007/s10549-011-1543-x

    Article  CAS  PubMed  Google Scholar 

  89. Vuorela, M., Pylkas, K., Hartikainen, J.M., Sundfeldt, K., Lindblom, A., von Wachenfeldt, W.A., et al.: Further evidence for the contribution of the RAD51C gene in hereditary breast and ovarian cancer susceptibility. Breast Cancer Res. Treat. 130(3), 1003–1010 (2011). doi:10.1007/s10549-011-1677-x

    Article  CAS  PubMed  Google Scholar 

  90. Thompson, E.R., Boyle, S.E., Johnson, J., Ryland, G.L., Sawyer, S., Choong, D.Y., et al.: Analysis of RAD51C germline mutations in high-risk breast and ovarian cancer families and ovarian cancer patients. Hum. Mutat. 33(1), 95–99 (2012). doi:10.1002/humu.21625

    Article  CAS  PubMed  Google Scholar 

  91. Catenacci, D.V., Amico, A.L., Nielsen, S.M., Geynisman, D.M., Rambo, B., Carey, G.B., et al.: Tumor genome analysis includes germline genome: are we ready for surprises? Int. J. Cancer J. Int. du Cancer. 136(7), 1559–1567 (2015). doi:10.1002/ijc.29128

    Article  CAS  Google Scholar 

  92. Varga, E., Chao, E.C., Yeager, N.D.: The importance of proper bioinformatics analysis and clinical interpretation of tumor genomic profiling: a case study of undifferentiated sarcoma and a constitutional pathogenic BRCA2 mutation and an MLH1 variant of uncertain significance. Familial Cancer. (2015). doi:10.1007/s10689-015-9790-3

    PubMed  PubMed Central  Google Scholar 

  93. Speare, V., Dolinsky, J.S., LaDuca, H., Horton, C., Panos, L., Mason, C., Dalton, E., Chao, E.: Germline testing in hereditary cancer genes subsequent to the identification of mutations in tumor specimens. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 33(15_suppl), abstr 1527 (2015)

    Google Scholar 

  94. Hall, M.J., Beryl Daly, M., Ross, E.A., Boyd, J., Sanford, E.M., Sun, J., Stephens, P., Liss, D., Chen, S., Miller, V.I., Yelensky, R., Giri, V.N.: Germline variants in cancer risk genes detected by NGS-based comprehensive tumor genomic profiling (CGP). J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 33(15_suppl), abstr 11084 (2015)

    Google Scholar 

  95. Rubinstein, W.S., Maglott, D.R., Lee, J.M., Kattman, B.L., Malheiro, A.J., Ovetsky, M., et al.: The NIH genetic testing registry: a new, centralized database of genetic tests to enable access to comprehensive information and improve transparency. Nucleic Acids Res. 41(Database issue), D925–D935 (2013). doi:10.1093/nar/gks1173

    Article  CAS  PubMed  Google Scholar 

  96. GTR: The Genetic Testing Registry [database on the Internet] 2012. Available from: http://www.ncbi.nlm.nih.gov/gtr/. Accessed 11 Nov 2016

  97. ACMG Board of Directors: ACMG policy statement: updated recommendations regarding analysis and reporting of secondary findings in clinical genome-scale sequencing. Genet. Med. Off. J. Am. Coll. Med. Genet. 17(1), 68–69 (2015). doi:10.1038/gim.2014.151

    Google Scholar 

  98. ACMG Board of Directors: Clinical utility of genetic and genomic services: a position statement of the American College of Medical Genetics and Genomics. Genet. Med. Off. J. Am. Coll. Med. Genet. 17(6), 505–507 (2015). doi:10.1038/gim.2015.41

    Google Scholar 

  99. Statement of the American Society of Clinical Oncology: genetic testing for cancer susceptibility, adopted on February 20, 1996. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 14(5), 1730–1736 (1996); discussion 7–40

    Google Scholar 

  100. American Society of Clinical O: American Society of Clinical Oncology policy statement update: genetic testing for cancer susceptibility. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 21(12), 2397–2406 (2003). doi:10.1200/JCO.2003.03.189

    Article  Google Scholar 

  101. Robson, M.E., Storm, C.D., Weitzel, J., Wollins, D.S., Offit, K., American Society of Clinical O: American Society of Clinical Oncology policy statement update: genetic and genomic testing for cancer susceptibility. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 28(5), 893–901 (2010). doi:10.1200/JCO.2009.27.0660

    Article  Google Scholar 

  102. Lu, K.H., Wood, M.E., Daniels, M., Burke, C., Ford, J., Kauff, N.D., et al.: American Society of Clinical Oncology Expert Statement: collection and use of a cancer family history for oncology providers. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 32(8), 833–840 (2014). doi:10.1200/JCO.2013.50.9257

    Article  Google Scholar 

  103. Bradbury, A.R., Patrick-Miller, L., Domchek, S.: Multiplex genetic testing: reconsidering utility and informed consent in the era of next-generation sequencing. Genet. Med. Off. J. Am. Coll. Med. Genet. 17(2), 97–98 (2015). doi:10.1038/gim.2014.85

    CAS  Google Scholar 

  104. Robson, M.: Multigene panel testing: planning the next generation of research studies in clinical cancer genetics. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 32(19), 1987–1989 (2014). doi:10.1200/JCO.2014.56.0474

    Article  CAS  Google Scholar 

  105. Kurian, A.W., Ford, J.M.: Multigene panel testing in oncology practice: how should we respond? JAMA Oncol. 1(3), 277–278 (2015). doi:10.1001/jamaoncol.2015.28

    Article  PubMed  Google Scholar 

  106. Landrum, M.J., Lee, J.M., Riley, G.R., Jang, W., Rubinstein, W.S., Church, D.M., et al.: ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res. 42(Database issue), D980–D985 (2014). doi:10.1093/nar/gkt1113

    Article  CAS  PubMed  Google Scholar 

  107. Rehm, H.L., Berg, J.S., Brooks, L.D., Bustamante, C.D., Evans, J.P., Landrum, M.J., et al.: ClinGen – the clinical genome resource. N. Engl. J. Med. 372(23), 2235–2242 (2015). doi:10.1056/NEJMsr1406261

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. National Society of Genetic Counselors. Clinical Data Sharing. Position Statements. www.nsgc.org (2015)

  109. Spurdle, A.B., Healey, S., Devereau, A., Hogervorst, F.B., Monteiro, A.N., Nathanson, K.L., 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. 33(1), 2–7 (2012). doi:10.1002/humu.21628

    Article  CAS  PubMed  Google Scholar 

  110. Ou, J., Niessen, R.C., Vonk, J., Westers, H., Hofstra, R.M., Sijmons, R.H.: A database to support the interpretation of human mismatch repair gene variants. Hum. Mutat. 29(11), 1337–1341 (2008). doi:10.1002/humu.20907

    Article  CAS  PubMed  Google Scholar 

  111. Karam, R., Pesaran, T., Chao, E.: ClinGen and genetic testing. N. Engl. J. Med. 373, 1376–1379 (2015). doi:10.1056/NEJMc1508700

    Article  PubMed  Google Scholar 

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  1. Department of Clinical Diagnostics, Ambry Genetics, Inc., 15 Argonaut, Aliso Viejo, CA, 92656, USA

    Holly LaDuca, Shuwei Li, A. J. Stuenkel, Virginia Speare, Jill S. Dolinsky & Elizabeth C. Chao

  2. Department of Pediatrics, Division of Genetics and Genomics, University of California, Irvine, Irvine, CA, USA

    Elizabeth C. Chao

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  1. Holly LaDuca
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    Lee-Jun C. Wong

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LaDuca, H., Li, S., Stuenkel, A.J., Speare, V., Dolinsky, J.S., Chao, E.C. (2017). Diagnosing Hereditary Cancer Susceptibility Through Multigene Panel Testing. In: Wong, LJ. (eds) Next Generation Sequencing Based Clinical Molecular Diagnosis of Human Genetic Disorders. Springer, Cham. https://doi.org/10.1007/978-3-319-56418-0_8

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