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Role of Next Generation Sequencing (NGS) in Hematological Disorders

  • Sanjeev Kumar GuptaEmail author
Chapter

Abstract

Sequencing techniques are at the forefront of medical diagnostics in the current era of personalized medicine and targeted therapy. These techniques can identify the exact genetic change at the nucleotide level which aids in delineating the molecular pathogenesis and may also help in development of tailored therapy. Different sequencing approaches can be used for either the discovery of new genetic aberrations or checking the known genetic change for diagnostic purposes, depending on the requirement. Next generation sequencing (NGS) refers to the post-Sanger technologies, i.e., sequencing technologies developed after Sanger sequencing. So, NGS includes a group of technologies having the capacity to sequence large segments of genome or entire genome in high-throughput experiments to detect genetic aberrations in a much faster and reliable way [1]. The current high-throughput NGS techniques, which are also being made available at affordable costs, are gradually replacing the conventional or first generation sequencing techniques in the clinical settings. In this chapter, the basic workflow of next generation sequencing (NGS) and its application in hematological disorders has been briefly discussed.

Keywords

Next generation sequencing NGS in hematology Applications of NGS NGS workflow 

References

  1. 1.
    Singh RR, Luthra R, Routbort MJ, Patel KP, Medeiros LJ. Implementation of next generation sequencing in clinical molecular diagnostic laboratories: advantages, challenges and potential. Expert Rev Precis Med Drug Dev. 2016;1(1):109–20.CrossRefGoogle Scholar
  2. 2.
    Sulonen A, Ellonen P, Almusa H, Lepisto M, Eldfors S, Hannula S, et al. Comparison of solution-based exome capture methods for next generation sequencing. Genome Biol. 2011;12(9):R94.CrossRefGoogle Scholar
  3. 3.
    Kohlmann A, Grossmann V, Nadarahjah N, Haferlach T. Next generation sequencing—feasibility and practicality in hematology. Br J Haematol. 2013;160(6):736–53.CrossRefGoogle Scholar
  4. 4.
    Merker JD, Valouev A, Gotlib J. Next-generation sequencing in hematologic malignancies: what will be the dividends? Ther Adv Hematol. 2012;3(6):333–9.CrossRefGoogle Scholar
  5. 5.
    Shendure J, Porreca GJ, Reppas NB, Lin X, McCutcheon JP, Rosenbaum AM, et al. Accurate multiplex polony sequencing of an evolved bacterial genome. Science. 2005;309:1728–32.CrossRefGoogle Scholar
  6. 6.
    Ley TJ, Mardis ER, Ding L, Fulton B, McLellan MD, Chen K, et al. DNA sequencing of a cytogenetically normal acute myeloid leukemia genome. Nature. 2008;456:66–72.CrossRefGoogle Scholar
  7. 7.
    Ley TJ, Ding L, Walter MJ, McLellan MD, Lamprecht T, Larson DE, et al. DNMT3A mutations in acute myeloid leukemia. N Engl J Med. 2010;363:2424–33.CrossRefGoogle Scholar
  8. 8.
    Patel JP, Gonen M, Figueroa ME, Fernandez H, Sun Z, Racevskis J, et al. Prognostic relevance of integrated genetic profiling in acute myeloid leukemia. N Engl J Med. 2012;366:1079–89.CrossRefGoogle Scholar
  9. 9.
    Ding L, Ley TJ, Larson DE, Miller CA, Koboldt DC, Welch JS, et al. Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing. Nature. 2012;481:506–10.CrossRefGoogle Scholar
  10. 10.
    Walter MJ, Shen D, Ding L, Shao J, Koboldt DC, Chen K, et al. Clonal architecture of secondary acute myeloid leukemia. N Engl J Med. 2012;366:1090–8.CrossRefGoogle Scholar
  11. 11.
    Cancer Genome Atlas Research Network. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med. 2013;368:2059–74.CrossRefGoogle Scholar
  12. 12.
    Arber DA, Orazi A, Hasserjian RP, Brunning RD, Le Beau MM, Porwit A, et al. Introduction and overview of the classification of myeloid neoplasms. In: Swerdlow SH, Campo E, Harris NL, et al., editors. WHO classification of tumours of haematopoietic and lymphoid tissues. Revised 4th ed. Lyon: IARC; 2017. p. 16–27.Google Scholar
  13. 13.
    Steensma DP. The evolving role of genomic testing in assessing prognosis of patients with myelodysplastic syndromes. Best Pract Res Clin Haematol. 2017;30(4):295–300.CrossRefGoogle Scholar
  14. 14.
    Malcovati L, Papaemmanuil E, Ambaglio I, Elena C, Galli A, Della Porta MG, et al. Driver somatic mutations identify distinct disease entities within myeloid neoplasms with myelodysplasia. Blood. 2014;124(9):1513–21.CrossRefGoogle Scholar
  15. 15.
    Quesada V, Conde L, Villamor N, Ordonez GR, Jares P, Bassaganyas L, et al. Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia. Nat Genet. 2012;44:47–52.CrossRefGoogle Scholar
  16. 16.
    Wang L, Lawrence MS, Wan Y, Stojanov P, Sougnez C, Stevenson K, et al. SF3B1 and other novel cancer genes in chronic lymphocytic leukemia. N Engl J Med. 2011;365:2497–506.CrossRefGoogle Scholar
  17. 17.
    Tiacci E, Trifonov V, Schiavoni G, Holmes A, Kern W, Martelli MP, et al. BRAF mutations in hairy-cell leukemia. N Engl J Med. 2011;364:2305–15.CrossRefGoogle Scholar
  18. 18.
    Treon SP, Xu L, Yang G, et al. MYD88 L265P somatic mutation in Waldenstrom’s macroglobulinemia. N Engl J Med. 2012;367(9):826–33.CrossRefGoogle Scholar
  19. 19.
    Chapman MA, Lawrence MS, Keats JJ, Cibulskis K, Sougnez C, Schinzel AC, et al. Initial genome sequencing and analysis of multiple myeloma. Nature. 2011;471:467–72.CrossRefGoogle Scholar
  20. 20.
    Koskella HL, Eldfors S, Ellonen P, van Adrichem AJ, Kuusanmaki H, Andersson EI, et al. Somatic STAT3 mutations in large granular lymphocytic leukemia. N Engl J Med. 2012;366:1905–13.CrossRefGoogle Scholar
  21. 21.
    Roberts KG, Li Y, Payne-Turner D, Harvey RC, Yang Y-L, Pei D, et al. Targetable kinase-activating lesions in Ph-like acute lymphoblastic leukemia. N Engl J Med. 2014;371(11):1005–15.CrossRefGoogle Scholar
  22. 22.
    Shang X, Peng Z, Ye Y, Asan, Zhang X, Chen Y, et al. Rapid targeted next-generation sequencing platform for molecular screening and clinical genotyping in subjects with hemoglobinopathies. EBioMedicine. 2017;23:150–9.CrossRefGoogle Scholar
  23. 23.
    He J, Song W, Yang J, Lu S, Yuan Y, Guo J. Next-generation sequencing improves thalassemia carrier screening among premarital adults in a high prevalence population: the Dai nationality, China. Genet Med. 2017;19(9):1022–31.CrossRefGoogle Scholar
  24. 24.
    Carlberg K, Bose N, Deng J, Lal A, Erlich H, Calloway C. Towards the development of a noninvasive prenatal test for beta-thalassemia: utilization of probe capture enrichment and next generation sequencing. Blood. 2016;128(22):3622.Google Scholar
  25. 25.
    Yoshizato T, Dumitriu B, Hosokawa K, Makishima H, Yoshida K, Townsley D, et al. Somatic mutations and clonal hematopoiesis in aplastic anemia. N Engl J Med. 2015;373(1):35–47.CrossRefGoogle Scholar
  26. 26.
    Kulasekararaj AG, Jiang J, Smith AE, Mohamedali AM, Mian S, Gandhi S, et al. Somatic mutations identify a subgroup of aplastic anemia patients who progress to myelodysplastic syndrome. Blood. 2014;124(17):2698–704.CrossRefGoogle Scholar
  27. 27.
    Andolfo I, Russo R, Gambale A, Iolascon A. New insights on hereditary erythrocyte membrane defects. Haematologica. 2016;101(11):1284–94.CrossRefGoogle Scholar
  28. 28.
    Agarwal AM, Reading NS, Frizzell K, Shen W, Sorrells S, Salama ME, et al. Using a next generation sequencing panel to discover the obscure causes of hereditary hemolytic anemias. Blood. 2016;128(22):2433.Google Scholar
  29. 29.
    Russo RAI, Manna F, Gambale A, Pignataro P, De Rosa G, Iolascon A. RedPlex: a targeted next generation sequencing-based diagnosis for patients with hereditary hemolytic anemias. Haematologica. 2016;101(s1):1.Google Scholar
  30. 30.
    Lee E, Dykas DJ, Leavitt AD, Camire RM, Ebberink E, García de Frutos P, et al. Whole-exome sequencing in evaluation of patients with venous thromboembolism. Blood Adv. 2017;1:1224–37.CrossRefGoogle Scholar
  31. 31.
    McDonald CJ, Ostini L, Wallace DF, Lyons A, Crawford DH, Subramaniam VN. Next-generation sequencing: application of a novel platform to analyze atypical iron disorders. J Hepatol. 2015;63(5):1288–93.CrossRefGoogle Scholar
  32. 32.
    Kalia SS, Adelman K, Bale SJ, Chung WK, Eng C, Evans JP, et al. 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

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Lab Oncology Unit, IRCHAll India Institute of Medical Sciences (AIIMS)New DelhiIndia

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