Advertisement

Reporting Clinical Genomic Assay Results and the Role of the Pathologist

  • Janina A. LongtineEmail author
Chapter

Abstract

Next-generation sequencing is a disruptive technology that significantly impacts pathologists’ role in analyzing, interpreting, and reporting clinical laboratory results. Clinical laboratory personnel must develop procedures and policies for assay validation, generating and managing the vast amount of data, integrating bioinformatics analyses and filters, and annotating variants to create clear, informative, and timely reports. Professional societies and organizations assist with recommendations and guidelines. This chapter delineates current challenges to generating next-generation sequencing clinical reports and emerging solutions.

Keywords

Next-generation sequencing Clinical genomics Sequence variants Interpretation and reporting 

References

  1. 1.
    Watson MS, Cutting GR, Desnick RJ, Driscoll DA, Klinger K, Mennuti M, Palomaki GE, Popovich BW, Pratt VM, Rohlfs EM, Strom CM, Richards CS, Witt DR, Grody WW. Cystic fibrosis population carrier screening: 2004 revision of American College of Medical Genetics mutation panel. Genet Med. 2004;6(5):387–91.CrossRefGoogle Scholar
  2. 2.
    Teekakirikul P, Kelly MA, Rehm HL, Lakdawala NK, Funke BH. Inherited cardiomyopathies: Molecular genetics and clinical genetic testing in the postgenomic era. J Mol Diagn. 2013;15(2):158–70.CrossRefGoogle Scholar
  3. 3.
    Burke MA, Cook SA, Seidman JG, Seidman CE. Clinical and Genetic Insights into the Genetics of Cardiomyopathy. J Am Coll Cardiol. 2016;68(25):2871–86.CrossRefGoogle Scholar
  4. 4.
    Cardarella S, Ortiz TM, Joshi VA, Butaney M, Jackman DM, Kwiatkowski DJ, Yeap BY, Janne PA, Lindeman NI, Johnson BA. The introduction of systemic genomic testing for patients with non-small-cell lung cancer. J Thorac Oncol. 2012;7(12):1767–74.CrossRefGoogle Scholar
  5. 5.
    Sequist LV, Heist RS, Shaw AT, Fidias P, Rosovsky R, Temel JS, Lennes IT, Digumarthy S, Waltman BA, Bast E, Tammireddy S, Morrissey L, Muzikansky A, Goldberg SB, Gainor J, Channick CL, Wain JC, Gaissert H, Donahue DM, Muniappan A, Wright C, Willers H, Mathisen DJ, Ellisen LW, Mino-Kenudson M, Lanuti M, Borger DR, Iafrate AJ, Engelman JA, Dias-Santagata D. Implementing multiplexed genotyping of non-small cell lung cancers into routine clinical practice. Ann Oncol. 2011;22(12):2616–24.CrossRefGoogle Scholar
  6. 6.
    Zehir A, Benayed R, Shah RH, Syed A, Middha S, Kim HR, Srinivasan P, Gao J, Chakravarty D, Devlin SM, Hellmann MD, Barron DA, Schram AM, Hameed M, Dogan S, Ross DS, Hechtman JF, DeLair DF, Yao J, Mandelker DL, Cheng DT, Chandramohan R, Mohanty AS, Ptashkin RN, Jayakumaran G, Prasad M, Syed MH, Rema AB, Liu ZY, Nafa K, Borsu L, Sadowska J, Casanova J, Bacares R, Kiecka IJ, Razumova A, Son JB, Stewart L, Baldi T, Mullaney KA, al-Ahmadie H, Vakiani E, Abeshouse AA, Penson AV, Jonsson P, Camacho N, Chang MT, Won HH, Gross BE, Kundra R, Heins Z, Chen HW, Phillips S, Zhang H, Wang J, Ochoa A, Wills J, Eubank M, Thomas SB, Gardos SM, Reales DN, Galle J, Durany R, Cambria R, Abida W, Cercek A, Feldman DR, Grounder MM, Hakimi AA, Harding JJ, Iyer G, Janjigian YY, Jordan EJ, Kelly CM, Lowery MA, LGT M, Omuro AM, Raj N, Razavi P, Shoushtari AN, Shukla N, Soumerai TE, Varghese AM, Yaeger R, Coleman J, Bochner B, Riely GJ, Saltz LB, Scher HI, Sabbatini PJ, Robson ME, Klimstra DS, Taylor BS, Baselga J, Schultz N, Hyman DM, Arcila ME, Sofit DB, Ladanyi M, Berger MF. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat Med. 2017;23(6):703–13.CrossRefGoogle Scholar
  7. 7.
    Hartmaier RJ, Albacker LA, Chmielecki J, Bailey M, He J, Goldberg ME, Ramkissoon S, Suh J, Elvin JA, Chiacchia S, Frampton GM, Ross JS, Miller V, Stephens PJ, Lipson D. High-throughput genomic profiling of adult solid tumors reveals novel insights into cancer pathogenesis. Cancer Res. 2017;77(9):2464–75.CrossRefGoogle Scholar
  8. 8.
    Gulley ML, Braziel RM, Halling HC, Hsi ED, Kant JA, Nikiforova MN, Nowak JA, Ogino S, Oliveira A, Polesky HF, Silverman L, Tubbs RR, Van Deerlin VM, Vance GH, Versalovic J, Molecular Pathology Resource Committee, College of American Pathologists. Clinical laboratory reports in molecular pathology. Arch Pathol Lab Med. 2007;131(6):852–63.PubMedGoogle Scholar
  9. 9.
    Gray KA, Yates B, Seal RL, Wright MW, Bruford EA. Genenames.org: the HGNC resources in 2015. Nucleic Acids Res. 2015;43(Database issue):D1079–85.CrossRefGoogle Scholar
  10. 10.
    den Dunnen JT, Dalgleish R, Maglott DR, Hart RK, Greenblatt MS, McGowan-Jordan J, Roux AF, Smith T, Antonarakis SE. Tascher PEM on behalf of the Human Genome Variation Society (HGVS), the Human Variome Project (HVP), and the Human Genome Organisation (HUGO). HGVS recommendations for the description of sequence variants: 2016 update. Hum Mutat. 2016;37(6):564–9.CrossRefGoogle Scholar
  11. 11.
    Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, Sunyaev SR. A method and server for predicting damaging missense mutations. Nat Methods. 2010;7(4):248–9.CrossRefGoogle Scholar
  12. 12.
    Sim NL, Kumar P, Hu J, Henikoff S, Schneider G, Ng PC. SIFT web server: predicting effects of amino acid substitutions on proteins. Nucleic Acids Res. 2012;40(Web Server issue):W452–257.CrossRefGoogle Scholar
  13. 13.
    Choi Y, Chan AP. PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics. 2015;31(16):2745–7.CrossRefGoogle Scholar
  14. 14.
    Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody W, Hedge M, Lyon E, Spector E, Voelkerding K, Rehm H, ACMG Laboratory Quality Assurance Committee. 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. 2015;17(5):405–24.CrossRefGoogle Scholar
  15. 15.
    Drmanac R. The advent of personal genomic sequencing. Genet Med. 2011;13(3):188–90.CrossRefGoogle Scholar
  16. 16.
    Lek M, Karczewski KJ, Minikei EV, Samocha KE, Banks E, Fennell T, O’Donnell-Luria AH, Ware JS, Hill AJ, Cummings BB, Tukiainen T, Birmbaum DP, Kosmicki JA, Duncan LE, Estrada K, Zhao F, Zou J, Pierce-Hoffman E, Berghout J, Cooper DN, Deflaux N, DePristo M, Do R, Flannick J, Fromer M, Gautheir L, Goldstein J, Gupta N, Howrigan D, Kiezun A, Kurki MI, Moonshine AL, Natarajan P, Orozco L, Peloso GM, Poplin R, Rivas MA, Ruano-Rubio V, Rose SA, Ruderfer DM, Shakir K, Stenson PD, Stevens C, Thomas BP, Tiao G, Tusie-Luna MT, Weisburd B, Won HH, Yu D, Altshuler DM, Ardissino D, Boehnke M, Danesh J, Donnelly S, Elosua R, Florez JC, Gabriel SB, Getz G, Glatt SJ, Hultman CM, Kathiresan S, Laakso M, McCarroll S, McCarthy MI, McGovern D, McPherson R, Neale BM, Palotie A, Purcell SM, Saleheen D, Scharf JM, Sklar P, Sullivan PF, Tuomilehto J, Tsuang MT, Watkins HC, Wilson JG, Daly MJ, MacArthur DG. Exome Aggregation Consortium. Nature. 2016;536:285–91.CrossRefGoogle Scholar
  17. 17.
    Kobayashi Y, Yang S, Nykamp K, Garcia J, Lincoln SE, Topper SE. Pathogenic variant burden in the ExAC database: an empirical approach to evaluating population data for clinical variant interpretation. Genome Med. 2017;9(1):13.CrossRefGoogle Scholar
  18. 18.
    NCBI Resource Coordinators. Database resources of the National Center for Biotechnology Information. Nucleci Acids Res. 2017;45(D1):D12–7.CrossRefGoogle Scholar
  19. 19.
    Green RC, Berg JS, Grody WW, Kalia SS, Korf BR, Martin CL, McGuire AL, Nussbaum RL, O’Daniel JM, Rehm HL, Watson MS, Williams MS, Biesecker LG, American College of Medical and Genomics. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med. 2013;15(7):565–74.CrossRefGoogle Scholar
  20. 20.
    ACMG Board of Directors. ACMG policy statement: updated recommendations regarding analysis and reporting of secondary findings in clinical genome-scale sequencing. Genet Med. 2015;17(1):68–9.CrossRefGoogle Scholar
  21. 21.
    Kalia SS, Adelman K, Bale SJ, Chung WK, Eng C, Evans JP, Herman GE, Hufnagel SK, Klein TE, Korf BR, McKelvey KD, Ormand KE, Richards CS, Vlangos CN, Watson M, Martin CL, Miller DT. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet Med. 2017;19(2):249–55.CrossRefGoogle Scholar
  22. 22.
    Wenger AM, Guturu H, Bernstein JA, Bejerano G. Systematic reanalysis of clinical exome data yields additional diagnoses: implications for providers. Genet Med. 2017;19(2):209–14.CrossRefGoogle Scholar
  23. 23.
    Biesecker LG. Opportunities and challenges for the integration of massively parallel genomic sequencing into clinical practice: lessons from the ClinSeq project. Genet Med. 2012;14(4):393–8.CrossRefGoogle Scholar
  24. 24.
    Arber DA, Brunning RD, Le Beau MM, Falini B, Vardiman JW, Porwit A, Thiele J, Bloomfield CD. Acute myeloid leukaemia with recurrent genetic abnormalities. In: Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, Thiele J, Vardiman J, editors. WHO classification of tumours of Haematopoietic and Lymphoid tissues. Lyon: International Agency for Research on Cancer; 2008.Google Scholar
  25. 25.
    Lynch TJ, Bell DS, Sordella R, Gurubhagavatula S, Okimoto RA, Brannigan BW, Harris PL, Haserlat SM, Supko JG, Haluska FG, Louis DN, Christiani DC, Settleman J, Haber DA. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med. 2004;350(21):2129–39.CrossRefGoogle Scholar
  26. 26.
    Paez JG, Jänne PA, Lee JC, Tracy S, Greulich H, Gabriel S, Herman P, Kaye FJ, Lindeman N, Boggon TJ, Naoki K, Sasaki H, Fujii Y, Eck MJ, Sellers WR, Johnson BE, Meyerson M. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science. 2004;304(5676):1497–500.CrossRefGoogle Scholar
  27. 27.
    Pao W, Miller V, Zakowski M, Doherty J, Politi K, Sarkaria I, Singh B, Heelan R, Rusch V, Fulton L, Mardis E, Kupfer D, Wilson R, Kris M, Varmus H. EGF receptor gene mutations are common in lung cancers from “never smokers” and are associated with sensitivity of tumors to gefitinib and erlotinib. Proc Natl Acad Sci U S A. 2004;101(36):13306–11.CrossRefGoogle Scholar
  28. 28.
    Dias-Santagata D, Akhavanfard S, David SS, Vernovsky K, Kuhlmann G, Boisvert SL, Stubbs H, McDermott U, Settleman J, Kwak EL, Clark JW, Isakoff SJ, Sequist LV, Engelman JA, Lynch TJ, Haber DA, Louis DN, Ellisen LW, Borger DR, Iafrate AJ. Rapid targeted mutational analysis of human tumours: a clinical platform to guide personalized cancer medicine. EMBO Mol Med. 2010;2(5):146–58.CrossRefGoogle Scholar
  29. 29.
    MacConaill LE, Campbell CD, Kehoe SM, Bass AJ, Hatton C, Niu L, Davis M, Yao K, Hanna M, Mondal C, Luongo L, Emery CM, Baker AC, Philips J, Goff DJ, Fiorentino M, Rubin MA, Polyak K, Chan J, Wang Y, Fletcher JA, Santagata S, Corso G, Roviello F, Shivdasani R, Kieran MW, Ligon KL, Stiles CD, Hahn WC, Meyerson ML, Garraway LA. Profiling critical cancer gene mutations in clinical tumor samples. PLoS One. 2009;4(11):e7887.CrossRefGoogle Scholar
  30. 30.
    Pao W, Kris MG, Iafrate AJ, Ladanyi M, Jänne PA, Wistuba II, Miake-Lye R, Herbst RS, Carbone DP, Johnson BE, Lynch TJ. Integration of molecular profiling into the lung cancer clinic. Clin Cancer Res. 2009;15(17):5317–22.CrossRefGoogle Scholar
  31. 31.
    Jennings LJ, Arcila ME, Corless C, Kamel-Reid S, Lubin I, Pfeifer J, Temple-Smolkin RL, Voelkerding KV, Nikiforova MN. Guidelines for validation of next-generation sequencing-based oncology panels. A joint consensus recommendation of the Association for Molecular Pathology and College of American Pathologists. J Mol Diagn. 2017;19(3):341–65.CrossRefGoogle Scholar
  32. 32.
    Oxnard GR, Jänne P. Power in numbers: Meta-analysis to identify inhibitor-sensitive tumor genotypes. Clin Cancer Res. 2013;19(7):1634–6.  https://doi.org/10.1158/1078-0432.CCR-13-0169.CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Flaherty KT, Puzanov I, Kim KB, Ribas A, McArthur GA, Sosman JA, O’Dwyer PJ, Lee RJ, Grippo JF, Nolop K, Chapman PB. Inhibition of mutated, activated BRAF in metastatic melanoma. N Engl J Med. 2010;363(9):809–19.CrossRefGoogle Scholar
  34. 34.
    Sundar R, Hong DS, Kopetz S, Yap TA. Targeting BRAF-mutant colorectal cancer: Progress in combination strategies. Cancer Discov. 2017;7(6):558–60.CrossRefGoogle Scholar
  35. 35.
    Li MM, Datto M, Duncavage EJ, Kulkarni S, Lindeman NI, Roy S, Tsimberidou AM, Vnencak-Jones CL, Wolff DJ, Younes A, Nikiforova MN. Standards and guidelines for the interpretation and reporting of sequence variants in cancer: A joint consensus recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and the College of American Pathologists. J Mol Diagn. 2017;19(1):4–23.CrossRefGoogle Scholar
  36. 36.
    Chene P. The role of tetramerization in p53 function. Oncogene. 2001;20(21):2611–7.CrossRefGoogle Scholar
  37. 37.
    Mehrvarz Sarshekeh A, Advani S, Overman MJ, Manyam G, Kee BK, Fogelman DR, Dasari A, Raghav K, Vilar E, Manuel S, Shureiqi I, Wolff RA, Patel KP, Luthra R, Shaw K, Eng C, Maru DM, Routbort MJ, Meric-Bernstam F, Kopetz S. Association of SMAD4 mutation with patient demographics, tumor characteristics, and clinical outcomes in colorectal cancer. PLoS One. 2017;12(3):e0173345.CrossRefGoogle Scholar
  38. 38.
    Pilarski R, Rai K, Cebulla C, Abdel-Rahman. BAP1 tumor predisposition syndrome, 2016 Oct 13. In: Pagon RA, Adam MP, Ardinger HH, et al., editors. GeneReviews® [Internet]. Seattle: University of Washington, Seattle; 1993–2017. https://www.ncbi.nlm.nih.gov/books/NBK390611/.
  39. 39.
    Schrijver I, Aziz N, Farkas DH, Furtado M, Gonzalez AF, Grenier TC, Grody WW, Hambuch T, Kalman L, Kant JA, Klein RD, Leonard DG, Lubin IM, Mao R, Nagan N, Pratt VM, Sobel ME, Voelkerding KV, Gibson JS. Opportunities and challenges associated with clinical diagnostic genome sequencing: a report of the Association for Molecular Pathology. J Mol Diagn. 2012;14(6):525–40.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Departments of Pathology and Laboratory MedicineYale University School of Medicine, Pathology and Laboratory Medicine, Yale New Haven Hospital and Smilow Cancer HospitalNew HavenUSA

Personalised recommendations