Advertisement

Genetic Testing in Hereditary Colorectal Cancer

  • Conxi Lázaro
  • Lidia Feliubadaló
  • Jesús del Valle
Chapter

Abstract

Genetic testing for hereditary disorders has suffered a dramatic change in the last decade with the incorporation of next-generation sequencing (NGS) technologies in the clinical diagnostics routine. Consequently, mutation detection yield in hereditary cancer in general, and in colorectal cancer in particular, has increased due to the fact that more genes are screened at the same time with a similar cost and turnaround time. This chapter summarizes previous methodologies used to address genetic causes of hereditary colorectal cancer and tackles important issues regarding NGS implementation for clinical testing. Analytical validity and clinical validity and utility together with ELSI aspects are briefly addressed. Somatic versus germline testing is also discussed due to its relevance in new clinical scenarios where novel target therapies are introduced for particular genetic conditions. Altogether, we highlight the importance of creating multidisciplinary committees to interpret genetic and genomic results and translate them into good laboratory practice and clinical guidelines.

Keywords

Genetic testing Mutation detection Next generation sequencing Gene panels Germline mutations Somatic mutations Lynch syndrome Familial adenomatous polyposis Microsatellite instability (MSI) Variants of unknown significance (VUS) Multilocus inherited neoplasia alleles syndrome (MINAS) Moderate risk genes 

Notes

Acknowledgments

We thank all patients who contributed to our studies and have helped us to better understand the molecular basis underlying colorectal cancer and other hereditary cancer syndromes. The authors would also like to thank all current and former members of the Hereditary Cancer Program at the Catalan Institute of Oncology (ICO). The authors would like to particularly acknowledge the support of the Asociación Española Contra el Cáncer (AECC), the Instituto de Salud Carlos III (organismo adscrito al Ministerio de Economía y Competitividad) and “Fondo Europeo de Desarrollo Regional (FEDER), una manera de hacer Europa” (PI10/01422, PI13/00285, PIE13/00022, PI16/00563, and CIBERONC), and the Institut Català de la Salut and Autonomous Government of Catalonia (2017SGR1282, 2017SGR496 and PERIS Project MedPerCan).

References

  1. 1.
    Ionov Y, Peinado MA, Malkhosyan S, Shibata D, Perucho M. Ubiquitous somatic mutations in simple repeated sequences reveal a new mechanism for colonic carcinogenesis. Nature. 1993;363(6429):558–61.CrossRefGoogle Scholar
  2. 2.
    Aaltonen LA, Peltomaki P, Leach FS, Sistonen P, Pylkkanen L, Mecklin JP, et al. Clues to the pathogenesis of familial colorectal cancer. Science (New York, NY). 1993;260(5109):812–6.CrossRefGoogle Scholar
  3. 3.
    Verstrepen KJ, Jansen A, Lewitter F, Fink GR. Intragenic tandem repeats generate functional variability. Nat Genet. 2005;37(9):986–90.CrossRefGoogle Scholar
  4. 4.
    Cicek MS, Lindor NM, Gallinger S, Bapat B, Hopper JL, Jenkins MA, et al. Quality assessment and correlation of microsatellite instability and immunohistochemical markers among population- and clinic-based colorectal tumors results from the colon cancer family registry. J Mol Diagn: JMD. 2011;13(3):271–81.CrossRefGoogle Scholar
  5. 5.
    Boland CR, Thibodeau SN, Hamilton SR, Sidransky D, Eshleman JR, Burt RW, et al. A National Cancer Institute Workshop on Microsatellite Instability for cancer detection and familial predisposition: development of international criteria for the determination of microsatellite instability in colorectal cancer. Cancer Res. 1998;58(22):5248–57.PubMedPubMedCentralGoogle Scholar
  6. 6.
    Suraweera N, Duval A, Reperant M, Vaury C, Furlan D, Leroy K, et al. Evaluation of tumor microsatellite instability using five quasimonomorphic mononucleotide repeats and pentaplex PCR. Gastroenterology. 2002;123(6):1804–11.CrossRefGoogle Scholar
  7. 7.
    Yamamoto H, Imai K. Microsatellite instability: an update. Arch Toxicol. 2015;89(6):899–921.CrossRefGoogle Scholar
  8. 8.
    Vasen HF, Moslein G, Alonso A, Bernstein I, Bertario L, Blanco I, et al. Guidelines for the clinical management of Lynch syndrome (hereditary non-polyposis cancer). J Med Genet. 2007;44(6):353–62.CrossRefGoogle Scholar
  9. 9.
    Pineda M, Gonzalez S, Lazaro C, Blanco I, Capella G. Detection of genetic alterations in hereditary colorectal cancer screening. Mutat Res. 2010;693(1–2):19–31.CrossRefGoogle Scholar
  10. 10.
    Deng G, Bell I, Crawley S, Gum J, Terdiman JP, Allen BA, et al. BRAF mutation is frequently present in sporadic colorectal cancer with methylated hMLH1, but not in hereditary nonpolyposis colorectal cancer. Clin Cancer Res: Off J Am Assoc Cancer Res. 2004;10(1 Pt 1):191–5.CrossRefGoogle Scholar
  11. 11.
    Gausachs M, Mur P, Corral J, Pineda M, Gonzalez S, Benito L, et al. MLH1 promoter hypermethylation in the analytical algorithm of Lynch syndrome: a cost-effectiveness study. Eur J Hum Genet: EJHG. 2012;20(7):762–8.CrossRefGoogle Scholar
  12. 12.
    Parsons MT, Buchanan DD, Thompson B, Young JP, Spurdle AB. Correlation of tumour BRAF mutations and MLH1 methylation with germline mismatch repair (MMR) gene mutation status: a literature review assessing utility of tumour features for MMR variant classification. J Med Genet. 2012;49(3):151–7.CrossRefGoogle Scholar
  13. 13.
    Moreira L, Munoz J, Cuatrecasas M, Quintanilla I, Leoz ML, Carballal S, et al. Prevalence of somatic mutl homolog 1 promoter hypermethylation in Lynch syndrome colorectal cancer. Cancer. 2015;121(9):1395–404.CrossRefGoogle Scholar
  14. 14.
    Newton K, Jorgensen NM, Wallace AJ, Buchanan DD, Lalloo F, McMahon RF, et al. Tumour MLH1 promoter region methylation testing is an effective prescreen for Lynch syndrome (HNPCC). J Med Genet. 2014;51(12):789–96.CrossRefGoogle Scholar
  15. 15.
    Bellido F, Pineda M, Aiza G, Valdes-Mas R, Navarro M, Puente DA, et al. POLE and POLD1 mutations in 529 kindred with familial colorectal cancer and/or polyposis: review of reported cases and recommendations for genetic testing and surveillance. Genetics in medicine : Off J Am Coll Med Genet. 2016;18(4):325–32.CrossRefGoogle Scholar
  16. 16.
    Shinbrot E, Henninger EE, Weinhold N, Covington KR, Goksenin AY, Schultz N, et al. Exonuclease mutations in DNA polymerase epsilon reveal replication strand specific mutation patterns and human origins of replication. Genome research. 2014;24(11):1740–50.CrossRefGoogle Scholar
  17. 17.
    Mertz TM, Baranovskiy AG, Wang J, Tahirov TH, Shcherbakova PV. Nucleotide selectivity defect and mutator phenotype conferred by a colon cancerassociated DNA polymerase delta mutation in human cells. Oncogene. 2017;36(31):4427–33.CrossRefGoogle Scholar
  18. 18.
    Bellizzi AM, Frankel WL. Colorectal cancer due to deficiency in DNA mismatch repair function: a review. Adv Anat Pathol. 2009;16(6):405–17.CrossRefGoogle Scholar
  19. 19.
    Etzler J, Peyrl A, Zatkova A, Schildhaus HU, Ficek A, Merkelbach-Bruse S, et al. RNA-based mutation analysis identifies an unusual MSH6 splicing defect and circumvents PMS2 pseudogene interference. Hum Mutat. 2008;29(2):299–305.CrossRefGoogle Scholar
  20. 20.
    van der Klift HM, Tops CM, Bik EC, Boogaard MW, Borgstein AM, Hansson KB, et al. Quantification of sequence exchange events between PMS2 and PMS2CL provides a basis for improved mutation scanning of Lynch syndrome patients. Hum Mutat. 2010;31(5):578–87.PubMedGoogle Scholar
  21. 21.
    Vaughn CP, Robles J, Swensen JJ, Miller CE, Lyon E, Mao R, et al. Clinical analysis of PMS2: mutation detection and avoidance of pseudogenes. Hum Mutat. 2010;31(5):588–93.PubMedGoogle Scholar
  22. 22.
    Kovacs ME, Papp J, Szentirmay Z, Otto S, Olah E. Deletions removing the last exon of TACSTD1 constitute a distinct class of mutations predisposing to lynch syndrome. Hum Mutat. 2009;30(2):197–203.CrossRefGoogle Scholar
  23. 23.
    Ligtenberg MJ, Kuiper RP, Chan TL, Goossens M, Hebeda KM, Voorendt M, et al. Heritable somatic methylation and inactivation of MSH2 in families with Lynch syndrome due to deletion of the 3′ exons of TACSTD1. Nat Genet. 2009;41(1):112–7.CrossRefGoogle Scholar
  24. 24.
    Nielsen M, Morreau H, Vasen HF, Hes FJ. MUTYH-associated polyposis (MAP). Crit Rev Oncol Hematol. 2011;79(1):1–16.CrossRefGoogle Scholar
  25. 25.
    Grover S, Kastrinos F, Steyerberg EW, Cook EF, Dewanwala A, Burbidge LA, et al. Prevalence and phenotypes of APC and MUTYH mutations in patients with multiple colorectal adenomas. JAMA. 2012;308(5):485–92.CrossRefGoogle Scholar
  26. 26.
    Castillejo A, Vargas G, Castillejo MI, Navarro M, Barbera VM, Gonzalez S, et al. Prevalence of germline MUTYH mutations among lynch-like syndrome patients. Eur J Cancer. 2014;50(13):2241–50.CrossRefGoogle Scholar
  27. 27.
    Morak M, Heidenreich B, Keller G, Hampel H, Laner A, de la Chapelle A, et al. Biallelic MUTYH mutations can mimic lynch syndrome. Eur J Hum Genet : EJHG. 2014;22(11):1334–7.CrossRefGoogle Scholar
  28. 28.
    Segui N, Navarro M, Pineda M, Koger N, Bellido F, Gonzalez S, et al. Exome sequencing identifies MUTYH mutations in a family with colorectal cancer and an atypical phenotype. Gut. 2015;64(2):355–6.CrossRefGoogle Scholar
  29. 29.
    van Puijenbroek M, Nielsen M, Tops CM, Halfwerk H, Vasen HF, Weiss MM, et al. Identification of patients with (atypical) MUTYH-associated polyposis by KRAS2 c.34G > T prescreening followed by MUTYH hotspot analysis in formalin-fixed paraffin-embedded tissue. Clin Cancer Res : Off J Am Assoc Cancer Res. 2008;14(1):139–42.CrossRefGoogle Scholar
  30. 30.
    Knopperts AP, Nielsen M, Niessen RC, Tops CM, Jorritsma B, Varkevisser J, et al. Contribution of bi-allelic germline MUTYH mutations to early-onset and familial colorectal cancer and to low number of adenomatous polyps: case-series and literature review. Familial Cancer. 2013;12(1):43–50.CrossRefGoogle Scholar
  31. 31.
    Bentley DR, Balasubramanian S, Swerdlow HP, Smith GP, Milton J, Brown CG, et al. Accurate whole human genome sequencing using reversible terminator chemistry. Nature. 2008;456(7218):53–9.CrossRefGoogle Scholar
  32. 32.
    Rothberg JM, Hinz W, Rearick TM, Schultz J, Mileski W, Davey M, et al. An integrated semiconductor device enabling non-optical genome sequencing. Nature. 2011;475(7356):348–52.CrossRefGoogle Scholar
  33. 33.
    Aziz N, Zhao Q, Bry L, Driscoll DK, Funke B, Gibson JS, et al. College of American Pathologists' laboratory standards for next-generation sequencing clinical tests. Arch Pathol Lab Med. 2015;139(4):481–93.CrossRefGoogle Scholar
  34. 34.
    Rehm HL, Bale SJ, Bayrak-Toydemir P, Berg JS, Brown KK, Deignan JL, et al. ACMG clinical laboratory standards for next-generation sequencing. Genet Med : Off J Am Coll Med Genet. 2013;15(9):733–47.CrossRefGoogle Scholar
  35. 35.
    Strom SP, Lee H, Das K, Vilain E, Nelson SF, Grody WW, et al. Assessing the necessity of confirmatory testing for exome-sequencing results in a clinical molecular diagnostic laboratory. Genet Med : Off J Am Coll Med Genet. 2014;16(7):510–5.CrossRefGoogle Scholar
  36. 36.
    Baudhuin LM, Lagerstedt SA, Klee EW, Fadra N, Oglesbee D, Ferber MJ. Confirming variants in next-generation sequencing panel testing by Sanger sequencing. J Mol Diagn : JMD. 2015;17(4):456–61.CrossRefGoogle Scholar
  37. 37.
    Mu W, Lu HM, Chen J, Li S, Elliott AM. Sanger confirmation is required to achieve optimal sensitivity and specificity in next-generation sequencing panel testing. J Mol Diagn : JMD. 2016;18(6):923–32.CrossRefGoogle Scholar
  38. 38.
    Feliubadaló L, Tonda R, Gausachs M, Trotta JR, Castellanos E, Lopez-Doriga A, et al. Benchmarking of whole exome sequencing and ad hoc designed panels for genetic testing of hereditary cancer. Sci Rep. 2017;7:37984.CrossRefGoogle Scholar
  39. 39.
    Campbell PJ, Stephens PJ, Pleasance ED, O'Meara S, Li H, Santarius T, et al. Identification of somatically acquired rearrangements in cancer using genome-wide massively parallel paired-end sequencing. Nat Genet. 2008;40(6):722–9.CrossRefGoogle Scholar
  40. 40.
    Yoon S, Xuan Z, Makarov V, Ye K, Sebat J. Sensitive and accurate detection of copy number variants using read depth of coverage. Genome Res. 2009;19(9):1586–92.CrossRefGoogle Scholar
  41. 41.
    Ye K, Schulz MH, Long Q, Apweiler R, Ning Z. Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads. Bioinformatics. 2009;25(21):2865–71.CrossRefGoogle Scholar
  42. 42.
    Chen K, Wallis JW, McLellan MD, Larson DE, Kalicki JM, Pohl CS, et al. BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat Methods. 2009;6(9):677–81.CrossRefGoogle Scholar
  43. 43.
    Bartenhagen C, Dugas M. Robust and exact structural variation detection with paired-end and soft-clipped alignments: SoftSV compared with eight algorithms. Brief Bioinform. 2016;17(1):51–62.CrossRefGoogle Scholar
  44. 44.
    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 : JMD. 2015;17(5):545–53.CrossRefGoogle Scholar
  45. 45.
    Kim TM, Laird PW, Park PJ. The landscape of microsatellite instability in colorectal and endometrial cancer genomes. Cell. 2013;155(4):858–68.CrossRefGoogle Scholar
  46. 46.
    Salipante SJ, Scroggins SM, Hampel HL, Turner EH, Pritchard CC. Microsatellite instability detection by next generation sequencing. Clin Chem. 2014;60(9):1192–9.CrossRefGoogle Scholar
  47. 47.
    Glen T. 2016 NGS field guide. 2016. The Molecular Ecologist. 2017, March. Available from: http://www.molecularecologist.com/next-gen-fieldguide-2016/.
  48. 48.
    Feliubadaló L, Lopez-Doriga A, Castellsague E, del Valle J, Menendez M, Tornero E, et al. Next-generation sequencing meets genetic diagnostics: development of a comprehensive workflow for the analysis of BRCA1 and BRCA2 genes. Eur J Hum Genet : EJHG. 2013;21(8):864–70.CrossRefGoogle Scholar
  49. 49.
    Susswein LR, Marshall ML, Nusbaum R, Vogel Postula KJ, Weissman SM, 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. 2016;18(8):823–32.CrossRefGoogle Scholar
  50. 50.
    LaDuca H, Farwell KD, Vuong H, Lu HM, Mu W, Shahmirzadi L, et al. Exome sequencing covers >98% of mutations identified on targeted next generation sequencing panels. PLoS One. 2017;12(2):e0170843.CrossRefGoogle Scholar
  51. 51.
    Yurgelun MB, Allen B, Kaldate RR, Bowles KR, Judkins T, Kaushik P, et al. Identification of a variety of mutations in cancer predisposition genes in patients with suspected lynch syndrome. Gastroenterology. 2015;149(3):604–13 e20.CrossRefGoogle Scholar
  52. 52.
    Yurgelun MB, Kulke MH, Fuchs CS, Allen BA, Uno H, Hornick JL, et al. Cancer susceptibility gene mutations in individuals with colorectal cancer. J Clin Oncol. 2017;35(10):1086–95.CrossRefGoogle Scholar
  53. 53.
    Chubb D, Broderick P, Frampton M, Kinnersley B, Sherborne A, Penegar S, et al. Genetic diagnosis of high-penetrance susceptibility for colorectal cancer (CRC) is achievable for a high proportion of familial CRC by exome sequencing. J Clin Oncol. 2015;33(5):426–32.CrossRefGoogle Scholar
  54. 54.
    Cragun D, Radford C, Dolinsky JS, Caldwell M, Chao E, Pal T. Panel-based testing for inherited colorectal cancer: a descriptive study of clinical testing performed by a US laboratory. Clin Genet. 2014;86(6):510–20.CrossRefGoogle Scholar
  55. 55.
    Ricker C, Culver JO, Lowstuter K, Sturgeon D, Sturgeon JD, Chanock CR, et al. Increased yield of actionable mutations using multi-gene panels to assess hereditary cancer susceptibility in an ethnically diverse clinical cohort. Cancer Genet. 2016;209(4):130–7.CrossRefGoogle Scholar
  56. 56.
    Pearlman R, Frankel WL, Swanson B, Zhao W, Yilmaz A, Miller K, et al. Prevalence and spectrum of germline cancer susceptibility gene mutations among patients with early-onset colorectal cancer. JAMA Oncol. 2017;3(4):464–471. doi: 10.1001/jamaoncol.2016.5194.CrossRefPubMedPubMedCentralGoogle Scholar
  57. 57.
    Slavin TP, Niell-Swiller M, Solomon I, Nehoray B, Rybak C, Blazer KR, et al. Clinical application of multigene panels: challenges of next-generation counseling and cancer risk management. Front Oncol. 2015;5:208.PubMedPubMedCentralGoogle Scholar
  58. 58.
    Hermel DJ, McKinnon WC, Wood ME, Greenblatt MS. Multi-gene panel testing for hereditary cancer susceptibility in a rural Familial Cancer Program. Familial Cancer. 2017;16(1):159–66.CrossRefGoogle Scholar
  59. 59.
    Howarth DR, Lum SS, Esquivel P, Garberoglio CA, Senthil M, Solomon NL. Initial results of multigene panel testing for hereditary breast and ovarian cancer and lynch syndrome. Am Surg. 2015;81(10):941–4.Google Scholar
  60. 60.
    Rohlin A, Rambech E, Kvist A, Torngren T, Eiengard F, Lundstam U, et al. Expanding the genotype-phenotype spectrum in hereditary colorectal cancer by gene panel testing. Familial Cancer. 2017;16(2):195–203.CrossRefGoogle Scholar
  61. 61.
  62. 62.
  63. 63.
    Castellanos E, Gel B, Rosas I, Tornero E, Santin S, Pluvinet R, et al. A comprehensive custom panel design for routine hereditary cancer testing: preserving control, improving diagnostics and revealing a complex variation landscape. Sci Rep. 2017;7:39348.CrossRefGoogle Scholar
  64. 64.
    Eccles DM, Mitchell G, Monteiro AN, Schmutzler R, Couch FJ, Spurdle AB, et al. BRCA1 and BRCA2 genetic testing-pitfalls and recommendations for managing variants of uncertain clinical significance. Ann oncol : Off J Eur Soc Med Oncol. 2015;26(10):2057–65.CrossRefGoogle Scholar
  65. 65.
    Balmana J, Digiovanni L, Gaddam P, Walsh MF, Joseph V, Stadler ZK, et al. Conflicting interpretation of genetic variants and cancer risk by commercial laboratories as assessed by the prospective registry of multiplex testing. J Clin Oncol. 2016;34(34):4071–8.CrossRefGoogle Scholar
  66. 66.
    Whitworth J, Skytte AB, Sunde L, Lim DH, Arends MJ, Happerfield L, et al. Multilocus inherited Neoplasia alleles syndrome: a case series and review. JAMA Oncol. 2016;2(3):373–9.CrossRefGoogle Scholar
  67. 67.
    Wimmer K, Kratz CP. Constitutional mismatch repair-deficiency syndrome. Haematologica. 2010;95(5):699–701.CrossRefGoogle Scholar
  68. 68.
    Gallego CJ, Shirts BH, Bennette CS, Guzauskas G, Amendola LM, Horike-Pyne M, et al. Next-generation sequencing panels for the diagnosis of colorectal cancer and polyposis syndromes: a cost-effectiveness analysis. J Clin Oncol. 2015;33(18):2084–91.CrossRefGoogle Scholar
  69. 69.
    Ng SB, Turner EH, Robertson PD, Flygare SD, Bigham AW, Lee C, et al. Targeted capture and massively parallel sequencing of 12 human exomes. Nature. 2009;461(7261):272–6.CrossRefGoogle Scholar
  70. 70.
    Choi M, Scholl UI, Ji W, Liu T, Tikhonova IR, Zumbo P, et al. Genetic diagnosis by whole exome capture and massively parallel DNA sequencing. Proc Natl Acad Sci U S A. 2009;106(45):19096–101.CrossRefGoogle Scholar
  71. 71.
    Harding KE, Robertson NP. Applications of next-generation whole exome sequencing. J Neurol. 2014;261(6):1244–6.CrossRefGoogle Scholar
  72. 72.
    Warr A, Robert C, Hume D, Archibald A, Deeb N, Watson M. Exome sequencing: current and future perspectives. G3 (Bethesda). MD. 2015;5(8):1543–50.Google Scholar
  73. 73.
    Chilamakuri CS, Lorenz S, Madoui MA, Vodak D, Sun J, Hovig E, et al. Performance comparison of four exome capture systems for deep sequencing. BMC Genomics. 2014;15:449.CrossRefGoogle Scholar
  74. 74.
    Meienberg J, Zerjavic K, Keller I, Okoniewski M, Patrignani A, Ludin K, et al. New insights into the performance of human whole-exome capture platforms. Nucleic Acids Res. 2015;43(11):e76.CrossRefGoogle Scholar
  75. 75.
    Wang JL, Yang X, Xia K, Hu ZM, Weng L, Jin X, et al. TGM6 identified as a novel causative gene of spinocerebellar ataxias using exome sequencing. Brain. 2010;133(Pt 12):3510–8.CrossRefGoogle Scholar
  76. 76.
    Vissers LE, de Ligt J, Gilissen C, Janssen I, Steehouwer M, de Vries P, et al. A de novo paradigm for mental retardation. Nat Genet. 2010;42(12):1109–12.CrossRefGoogle Scholar
  77. 77.
    Ng SB, Buckingham KJ, Lee C, Bigham AW, Tabor HK, Dent KM, et al. Exome sequencing identifies the cause of a mendelian disorder. Nat Genet. 2010;42(1):30–5.CrossRefGoogle Scholar
  78. 78.
    Lee H, Deignan JL, Dorrani N, Strom SP, Kantarci S, Quintero-Rivera F, et al. Clinical exome sequencing for genetic identification of rare Mendelian disorders. JAMA. 2014;312(18):1880–7.CrossRefGoogle Scholar
  79. 79.
    Yang Y, Muzny DM, Xia F, Niu Z, Person R, Ding Y, et al. Molecular findings among patients referred for clinical whole-exome sequencing. JAMA. 2014;312(18):1870–9.CrossRefGoogle Scholar
  80. 80.
    Jones S, Hruban RH, Kamiyama M, Borges M, Zhang X, Parsons DW, et al. Exomic sequencing identifies PALB2 as a pancreatic cancer susceptibility gene. Science (New York, NY). 2009;324(5924):217.CrossRefGoogle Scholar
  81. 81.
    Nieminen TT, O'Donohue MF, Wu Y, Lohi H, Scherer SW, Paterson AD, et al. Germline mutation of RPS20, encoding a ribosomal protein, causes predisposition to hereditary nonpolyposis colorectal carcinoma without DNA mismatch repair deficiency. Gastroenterology. 2014;147(3):595–8 e5.CrossRefGoogle Scholar
  82. 82.
    Lupski JR, Reid JG, Gonzaga-Jauregui C, Rio Deiros D, Chen DC, Nazareth L, et al. Whole-genome sequencing in a patient with Charcot-Marie-tooth neuropathy. N Engl J Med. 2010;362(13):1181–91.CrossRefGoogle Scholar
  83. 83.
    Sobreira NL, Cirulli ET, Avramopoulos D, Wohler E, Oswald GL, Stevens EL, et al. Whole-genome sequencing of a single proband together with linkage analysis identifies a Mendelian disease gene. PLoS Genet. 2010;6(6):e1000991.CrossRefGoogle Scholar
  84. 84.
    Rios J, Stein E, Shendure J, Hobbs HH, Cohen JC. Identification by whole-genome resequencing of gene defect responsible for severe hypercholesterolemia. Hum Mol Genet. 2010;19(22):4313–8.CrossRefGoogle Scholar
  85. 85.
    Yokoyama S, Woods SL, Boyle GM, Aoude LG, MacGregor S, Zismann V, et al. A novel recurrent mutation in MITF predisposes to familial and sporadic melanoma. Nature. 2011;480(7375):99–103.CrossRefGoogle Scholar
  86. 86.
    Roberts NJ, Jiao Y, Yu J, Kopelovich L, Petersen GM, Bondy ML, et al. ATM mutations in patients with hereditary pancreatic cancer. Cancer Discov. 2012;2(1):41–6.CrossRefGoogle Scholar
  87. 87.
    Comino-Mendez I, Gracia-Aznarez FJ, Schiavi F, Landa I, Leandro-Garcia LJ, Leton R, et al. Exome sequencing identifies MAX mutations as a cause of hereditary pheochromocytoma. Nat Genet. 2011;43(7):663–7.CrossRefGoogle Scholar
  88. 88.
    Rafnar T, Gudbjartsson DF, Sulem P, Jonasdottir A, Sigurdsson A, Jonasdottir A, et al. Mutations in BRIP1 confer high risk of ovarian cancer. Nat Genet. 2011;43(11):1104–7.CrossRefGoogle Scholar
  89. 89.
    Palles C, Cazier JB, Howarth KM, Domingo E, Jones AM, Broderick P, et al. Germline mutations affecting the proofreading domains of POLE and POLD1 predispose to colorectal adenomas and carcinomas. Nat Genet. 2013;45(2):136–44.CrossRefGoogle Scholar
  90. 90.
    Belkadi A, Bolze A, Itan Y, Cobat A, Vincent QB, Antipenko A, et al. Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants. Proc Natl Acad Sci U S A. 2015;112(17):5473–8.CrossRefGoogle Scholar
  91. 91.
    Lelieveld SH, Spielmann M, Mundlos S, Veltman JA, Gilissen C. Comparison of exome and genome sequencing Technologies for the Complete Capture of protein-coding regions. Hum Mutat. 2015;36(8):815–22.CrossRefGoogle Scholar
  92. 92.
    Meynert AM, Ansari M, FitzPatrick DR, Taylor MS. Variant detection sensitivity and biases in whole genome and exome sequencing. BMC bioinformatics. 2014;15:247.CrossRefGoogle Scholar
  93. 93.
    Abdel-Rahman MH, Rai K, Pilarski R, Davidorf FH, Cebulla CM. Germline BAP1 mutations misreported as somatic based on tumor-only testing. Familial Cancer. 2016;15(2):327–30.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Conxi Lázaro
    • 1
  • Lidia Feliubadaló
    • 1
  • Jesús del Valle
    • 1
  1. 1.Hereditary Cancer Program, Genetic Diagnostics Unit, Catalan Institute of Oncology (ICO-IDIBELL), CIBERONC, Hospitalet de LlobregatBarcelonaSpain

Personalised recommendations