Advertisement

Genomic Applications in Hematologic Oncology

  • Kevin E. Fisher
  • Linsheng Zhang
  • Charles E. HillEmail author
Chapter

Abstract

Molecular applications for the diagnosis and treatment of hematologic malignancies are front and center in the field of genomic medicine. Single-gene and whole-chromosome assays are currently used in routine clinical practice to diagnose and monitor hematologic malignancies, and newer testing modalities such as array comparative genomic hybridization, single-nucleotide polymorphism arrays, and next-generation sequencing are rapidly being adopted for clinical testing. This chapter focuses on traditional and cutting-edge diagnostic molecular applications in hematologic oncology and addresses some of the assay limitations and diagnostic challenges of which pathologists, laboratory directors, molecular technologists and technicians, and clinicians should be aware.

Keywords

Leukemia Lymphoma Molecular SNP arrays Array CGH Next-generation sequencing Hematopathology Diagnostics 

References

  1. 1.
    Jung D, Giallourakis C, Mostoslavsky R, Alt FW. Mechanism and control of V(D)J recombination at the immunoglobulin heavy chain locus. Annu Rev Immunol. 2006;24:541–70.PubMedCrossRefGoogle Scholar
  2. 2.
    Bruns DE, Ashwood ER, Burtis CA. Fundamentals of molecular diagnostics. St. Louis: Saunders Elsevier; 2007.Google Scholar
  3. 3.
    Nikiforova MN, Hsi ED, Braziel RM, Gulley ML, Leonard DGB, Nowak JA, et al. Detection of clonal IGH gene rearrangements: summary of molecular oncology surveys of the College of American Pathologists. Arch Pathol Lab Med. 2007;131(2):185–9.PubMedGoogle Scholar
  4. 4.
    Mannu C, Gazzola A, Bacci F, Sabattini E, Sagramoso C, Roncolato F, et al. Use of IGK gene rearrangement analysis for clonality assessment of lymphoid malignancies: a single center experience. Am J Blood Res. 2011;1(2):167–74.PubMedPubMedCentralGoogle Scholar
  5. 5.
    Tapia G, Sanz C, Mate JL, Munoz-Marmol AM, Ariza A. Improved clonality detection in Hodgkin lymphoma using the BIOMED-2-based heavy and kappa chain assay: a paraffin-embedded tissue study. Histopathology. 2012;60(5):768–73.PubMedCrossRefGoogle Scholar
  6. 6.
    Jevremovic D, Viswanatha DS. Molecular diagnosis of hematopoietic and lymphoid neoplasms. Hematol Oncol Clin North Am. 2009;23(4):903–33.PubMedCrossRefGoogle Scholar
  7. 7.
    Swerdlow SH, Cancer IAfRo, Organization WH. WHO classification of tumours of haematopoietic and lymphoid tissues. Lyon: International Agency for Research on Cancer; 2008.Google Scholar
  8. 8.
    van Dongen JJ, Langerak AW, Bruggemann M, Evans PA, Hummel M, Lavender FL, et al. Design and standardization of PCR primers and protocols for detection of clonal immunoglobulin and T-cell receptor gene recombinations in suspect lymphoproliferations: report of the BIOMED-2 concerted action BMH4-CT98-3936. Leukemia. 2003;17(12):2257–317.PubMedCrossRefGoogle Scholar
  9. 9.
    Leonard DGB. Diagnostic molecular pathology. Philadelphia: W.B. Saunders; 2003.Google Scholar
  10. 10.
    Patnaik MM, Tefferi A. Molecular diagnosis of myeloproliferative neoplasms. Expert Rev Mol Diagn. 2009;9(5):481–92.PubMedCrossRefGoogle Scholar
  11. 11.
    Tefferi A, Skoda R, Vardiman JW. Myeloproliferative neoplasms: contemporary diagnosis using histology and genetics. Nat Rev Clin Oncol. 2009;6(11):627–37.PubMedCrossRefGoogle Scholar
  12. 12.
    Hammond E, Shaw K, Carnley B, P'ng S, James I, Herrmann R. Quantitative determination of JAK2 V617F by TaqMan: an absolute measure of averaged copies per cell that may be associated with the different types of myeloproliferative disorders. J Mol Diagn. 2007;9(2):242–8.PubMedPubMedCentralCrossRefGoogle Scholar
  13. 13.
    Lippert E, Girodon F, Hammond E, Jelinek J, Reading NS, Fehse B, et al. Concordance of assays designed for the quantification of JAK2V617F: a multicenter study. Haematologica. 2009;94(1):38–45.PubMedCrossRefGoogle Scholar
  14. 14.
    Barosi G, Birgegard G, Finazzi G, Griesshammer M, Harrison C, Hasselbalch HC, et al. Response criteria for essential thrombocythemia and polycythemia vera: result of a European LeukemiaNet consensus conference. Blood. 2009;113(20):4829–33.PubMedCrossRefGoogle Scholar
  15. 15.
    Tefferi A, Barbui T. Polycythemia vera and essential thrombocythemia: 2017 update on diagnosis, risk-stratification, and management. Am J Hematol. 2017;92(1):94–108. Frohling S, Scholl C, Gilliland DG, Levine RL. Genetics of myeloid malignancies: pathogenetic and clinical implications. J Clin Oncol 2005;23(26):6285–95.PubMedCrossRefGoogle Scholar
  16. 16.
    Murphy KM, Levis M, Hafez MJ, Geiger T, Cooper LC, Smith BD, et al. Detection of FLT3 internal tandem duplication and D835 mutations by a multiplex polymerase chain reaction and capillary electrophoresis assay. J Mol Diagn. 2003;5(2):96–102.PubMedPubMedCentralCrossRefGoogle Scholar
  17. 17.
    Dekking E, van der Velden VHJ, Böttcher S, Brüggemann M, Sonneveld E, Koning-Goedheer A, et al. Detection of fusion genes at the protein level in leukemia patients via the flow cytometric immunobead assay. Best practice & amp. Res Clin Haematol. 2010;23(3):333–45.CrossRefGoogle Scholar
  18. 18.
    O'Brien SG, Guilhot F, Larson RA, Gathmann I, Baccarani M, Cervantes F, et al. Imatinib compared with interferon and low-dose cytarabine for newly diagnosed chronic-phase chronic myeloid leukemia. N Engl J Med. 2003;348(11):994–1004.PubMedCrossRefGoogle Scholar
  19. 19.
    Druker BJ, Guilhot F, O'Brien SG, Gathmann I, Kantarjian H, Gattermann N, et al. Five-year follow-up of patients receiving imatinib for chronic myeloid leukemia. N Engl J Med. 2006;355(23):2408–17.PubMedCrossRefGoogle Scholar
  20. 20.
    White HE, Matejtschuk P, Rigsby P, Gabert J, Lin F, Lynn Wang Y, et al. Establishment of the first World Health Organization International Genetic Reference Panel for quantitation of BCR-ABL mRNA. Blood. 2010;116(22):e111–7.PubMedCrossRefGoogle Scholar
  21. 21.
    Wang N. Methodologies in cancer cytogenetics and molecular cytogenetics. Am J Med Genet. 2002;115(3):118–24.PubMedCrossRefGoogle Scholar
  22. 22.
    Bejjani BA, Saleki R, Ballif BC, Rorem EA, Sundin K, Theisen A, et al. Use of targeted array-based CGH for the clinical diagnosis of chromosomal imbalance: is less more? Am J Med Genet A. 2005;134(3):259–67.PubMedCrossRefGoogle Scholar
  23. 23.
    Sharathkumar A, DeCamillo D, Bhambhani K, Cushing B, Thomas R, Mohamed AN, et al. Children with hyperdiploid but not triple trisomy (+4,+10,+17) acute lymphoblastic leukemia have an increased incidence of extramedullary relapse on current therapies: a single institution experience. Am J Hematol. 2008;83(1):34–40.PubMedCrossRefGoogle Scholar
  24. 24.
    Marschalek R. Mechanisms of leukemogenesis by MLL fusion proteins. Br J Haematol. 2011;152(2):141–54.PubMedCrossRefGoogle Scholar
  25. 25.
    Jacoby MA, Walter MJ. Detection of copy number alterations in acute myeloid leukemia and myelodysplastic syndromes. Expert Rev Mol Diagn. 2012;12(3):253–64.PubMedCrossRefGoogle Scholar
  26. 26.
    Shinawi M, Cheung SW. The array CGH and its clinical applications. Drug Discov Today. 2008;13(17–18):760–70.PubMedCrossRefGoogle Scholar
  27. 27.
    Shaikh TH. Oligonucleotide arrays for high-resolution analysis of copy number alteration in mental retardation/multiple congenital anomalies. Genet Med. 2007;9(9):617–25.PubMedCrossRefGoogle Scholar
  28. 28.
    Shao L, Kang S-HL, Li J, Hixson P, Taylor J, Yatsenko SA, et al. Array comparative genomic hybridization detects chromosomal abnormalities in hematological cancers that are not detected by conventional cytogenetics. J Mol Diagn. 2010;12(5):670–9.PubMedPubMedCentralCrossRefGoogle Scholar
  29. 29.
    Kolquist KA, Schultz RA, Furrow A, Brown TC, Han J-Y, Campbell LJ, et al. Microarray-based comparative genomic hybridization of cancer targets reveals novel, recurrent genetic aberrations in the myelodysplastic syndromes. Cancer Genet. 2011;204(11):603–28.PubMedCrossRefGoogle Scholar
  30. 30.
    Paulsson K, Heidenblad M, Strombeck B, Staaf J, Jonsson G, Borg A, et al. High-resolution genome-wide array-based comparative genome hybridization reveals cryptic chromosome changes in AML and MDS cases with trisomy 8 as the sole cytogenetic aberration. Leukemia. 2006;20(5):840–6.PubMedCrossRefGoogle Scholar
  31. 31.
    Thiel A, Beier M, Ingenhag D, Servan K, Hein M, Moeller V, et al. Comprehensive array CGH of normal karyotype myelodysplastic syndromes reveals hidden recurrent and individual genomic copy number alterations with prognostic relevance. Leukemia. 2011;25(3):387–99.PubMedCrossRefGoogle Scholar
  32. 32.
    Vercauteren SM, Sung S, Starczynowski DT, Lam WL, Bruyere H, Horsman DE, et al. Array comparative genomic hybridization of peripheral blood granulocytes of patients with myelodysplastic syndrome detects karyotypic abnormalities. American Journal of Clinical Pathology. 2010;134(1):119–26.PubMedCrossRefGoogle Scholar
  33. 33.
    Dawson AJ, Yanofsky R, Vallente R, Bal S, Schroedter I, Liang L, et al. Array comparative genomic hybridization and cytogenetic analysis in pediatric acute leukemias. Curr Oncol. 2011;18(5):e210–7.PubMedPubMedCentralGoogle Scholar
  34. 34.
    Lucioni M, Novara F, Fiandrino G, Riboni R, Fanoni D, Arra M, et al. Twenty-one cases of blastic plasmacytoid dendritic cell neoplasm: focus on biallelic locus 9p21.3 deletion. Blood. 2011;118(17):4591–4.PubMedCrossRefGoogle Scholar
  35. 35.
    Higgins RA, Gunn SR, Robetorye RS. Clinical application of array-based comparative genomic hybridization for the identification of prognostically important genetic alterations in chronic lymphocytic leukemia. Mol Diagn Ther. 2008;12(5):271–80.PubMedCrossRefGoogle Scholar
  36. 36.
    Okada M, Suto Y, Hirai M, Shiseki M, Usami A, Okajima K, et al. Microarray CGH analyses of chromosomal 20q deletions in patients with hematopoietic malignancies. Cancer Genet. 2012;205(1–2):18–24.PubMedCrossRefGoogle Scholar
  37. 37.
    Sachidanandam R, Weissman D, Schmidt SC, Kakol JM, Stein LD, Marth G, et al. A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms. Nature. 2001;409(6822):928–33.CrossRefGoogle Scholar
  38. 38.
    Ersland KM, Christoforou A, Stansberg C, Espeseth T, Mattheisen M, Mattingsdal M, et al. Gene-based analysis of regionally enriched cortical genes in GWAS data sets of cognitive traits and psychiatric disorders. PLoS One. 2012;7(2):e31687.PubMedPubMedCentralCrossRefGoogle Scholar
  39. 39.
    Kidd KK, Pakstis AJ, Speed WC, Grigorenko EL, Kajuna SL, Karoma NJ, et al. Developing a SNP panel for forensic identification of individuals. Forensic Sci Int. 2006;164(1):20–32.PubMedCrossRefGoogle Scholar
  40. 40.
    Tzvetkov M, von Ahsen N. Pharmacogenetic screening for drug therapy: from single gene markers to decision making in the next generation sequencing era. Pathology. 2012;44(2):166–80.PubMedCrossRefGoogle Scholar
  41. 41.
    Sato-Otsubo A, Sanada M, Ogawa S. Single-nucleotide polymorphism array karyotyping in clinical practice: where, when, and how? Semin Oncol. 2012;39(1):13–25.PubMedCrossRefGoogle Scholar
  42. 42.
    Fan JB, Gunderson KL, Bibikova M, Yeakley JM, Chen J, Wickham Garcia E, et al. [3] Illumina Universal Bead Arrays. In: Alan K, Brian O, editors. Methods in enzymology. New York: Academic Press; 2006. p. 57–73.Google Scholar
  43. 43.
    Murray SS, Oliphant A, Shen R, McBride C, Steeke RJ, Shannon SG, et al. A highly informative SNP linkage panel for human genetic studies. Nat Meth. 2004;1(2):113–7.  https://doi.org/10.1038/nmeth712.CrossRefGoogle Scholar
  44. 44.
    Maciejewski JP, Tiu RV, O'Keefe C. Application of array-based whole genome scanning technologies as a cytogenetic tool in haematological malignancies. Br J Haematol. 2009;146(5):479–88.PubMedCrossRefGoogle Scholar
  45. 45.
    Maciejewski JP, Mufti GJ. Whole genome scanning as a cytogenetic tool in hematologic malignancies. Blood. 2008;112(4):965–74.PubMedPubMedCentralCrossRefGoogle Scholar
  46. 46.
    Kawamata N, Ogawa S, Zimmermann M, Niebuhr B, Stocking C, Sanada M, et al. Cloning of genes involved in chromosomal translocations by high-resolution single nucleotide polymorphism genomic microarray. Proc Natl Acad Sci U S A. 2008;105(33):11921–6.PubMedPubMedCentralCrossRefGoogle Scholar
  47. 47.
    Mullighan CG, Goorha S, Radtke I, Miller CB, Coustan-Smith E, Dalton JD, et al. Genome-wide analysis of genetic alterations in acute lymphoblastic leukaemia. Nature. 2007;446(7137):758–64.PubMedCrossRefGoogle Scholar
  48. 48.
    Pfeifer D, Pantic M, Skatulla I, Rawluk J, Kreutz C, Martens UM, et al. Genome-wide analysis of DNA copy number changes and LOH in CLL using high-density SNP arrays. Blood. 2007;109(3):1202–10.PubMedCrossRefGoogle Scholar
  49. 49.
    Edelmann J, Holzmann K, Miller F, Winkler D, Buhler A, Zenz T, et al. High-resolution genomic profiling of chronic lymphocytic leukemia reveals new recurrent genomic alterations. Blood. 2012;120(24):4783–94.PubMedCrossRefGoogle Scholar
  50. 50.
    Jenner MW, Leone PE, Walker BA, Ross FM, Johnson DC, Gonzalez D, et al. Gene mapping and expression analysis of 16q loss of heterozygosity identifies WWOX and CYLD as being important in determining clinical outcome in multiple myeloma. Blood. 2007;110(9):3291–300.PubMedCrossRefGoogle Scholar
  51. 51.
    Parkin B, Erba H, Ouillette P, Roulston D, Purkayastha A, Karp J, et al. Acquired genomic copy number aberrations and survival in adult acute myelogenous leukemia. Blood. 2010;116(23):4958–67.PubMedPubMedCentralCrossRefGoogle Scholar
  52. 52.
    Tiu RV, Gondek LP, O'Keefe CL, Elson P, Huh J, Mohamedali A, et al. Prognostic impact of SNP array karyotyping in myelodysplastic syndromes and related myeloid malignancies. Blood. 2011;117(17):4552–60.PubMedPubMedCentralCrossRefGoogle Scholar
  53. 53.
    Yi JH, Huh J, Kim HJ, Kim SH, Kim YK, Sohn SK, et al. Adverse prognostic impact of abnormal lesions detected by genome-wide single nucleotide polymorphism array-based karyotyping analysis in acute myeloid leukemia with normal karyotype. J Clin Oncol. 2011;29(35):4702–8.PubMedCrossRefGoogle Scholar
  54. 54.
    Heinrichs S, Li C, Look AT. SNP array analysis in hematologic malignancies: avoiding false discoveries. Blood. 2010;115(21):4157–61.PubMedPubMedCentralCrossRefGoogle Scholar
  55. 55.
    Ishkanian AS, Malloff CA, Watson SK, DeLeeuw RJ, Chi B, Coe BP, et al. A tiling resolution DNA microarray with complete coverage of the human genome. Nat Genet. 2004;36(3):299–303.PubMedCrossRefGoogle Scholar
  56. 56.
    Zhang J, Feuk L, Duggan GE, Khaja R, Scherer SW. Development of bioinformatics resources for display and analysis of copy number and other structural variants in the human genome. Cytogenet Genome Res. 2006;115(3–4):205–14.PubMedCrossRefGoogle Scholar
  57. 57.
    Le Scouarnec S, Gribble SM. Characterising chromosome rearrangements: recent technical advances in molecular cytogenetics. Heredity (Edinb). 2012;108(1):75–85.CrossRefGoogle Scholar
  58. 58.
    LaFramboise T. Single nucleotide polymorphism arrays: a decade of biological, computational and technological advances. Nucleic Acids Res. 2009;37(13):4181–93.PubMedPubMedCentralCrossRefGoogle Scholar
  59. 59.
    Venter JC. Multiple personal genomes await. Nature. 2010;464(7289):676–7.  https://doi.org/10.1038/464676a.PubMedCrossRefGoogle Scholar
  60. 60.
    https://www.genome.gov/27565109/the-cost-of-sequencing-a-human-genome/. Accessed 10 Mar 2018; Metzker ML. Sequencing technologies [mdash] the next generation. Nat Rev Genet.  https://doi.org/10.1038/nrg2626. 2010;11(1):31–46.
  61. 61.
    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.  https://doi.org/10.1038/nature10242.PubMedCrossRefGoogle Scholar
  62. 62.
    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.PubMedPubMedCentralCrossRefGoogle Scholar
  63. 63.
    Dressman D, Yan H, Traverso G, Kinzler KW, Vogelstein B. Transforming single DNA molecules into fluorescent magnetic particles for detection and enumeration of genetic variations. Proc Natl Acad Sci U S A. 2003;100(15):8817–22.PubMedPubMedCentralCrossRefGoogle Scholar
  64. 64.
    Leamon JH, Lee WL, Tartaro KR, Lanza JR, Sarkis GJ, deWinter AD, et al. A massively parallel PicoTiterPlate based platform for discrete picoliter-scale polymerase chain reactions. Electrophoresis. 2003;24(21):3769–77.PubMedCrossRefGoogle Scholar
  65. 65.
    Ronaghi M, Uhlén M, Nyrén P. A sequencing method based on real-time pyrophosphate. Science. 1998;281(5375):363–5.PubMedCrossRefGoogle Scholar
  66. 66.
    Liu L, Li Y, Li S, Hu N, He Y, Pong R, et al. Comparison of next-generation sequencing systems. J Biomed Biotechnol. 2012;2012:251364.PubMedPubMedCentralGoogle Scholar
  67. 67.
    Loman NJ, Misra RV, Dallman TJ, Constantinidou C, Gharbia SE, Wain J, et al. Performance comparison of benchtop high-throughput sequencing platforms. Nat Biotech. 2012;30(5):434–9.  https://doi.org/10.1038/nbt.2198.CrossRefGoogle Scholar
  68. 68.
    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.PubMedPubMedCentralCrossRefGoogle Scholar
  69. 69.
    Welch Js WPDL, et al. Use of whole-genome sequencing to diagnose a cryptic fusion oncogene. JAMA. 2011;305(15):1577–84.PubMedPubMedCentralCrossRefGoogle Scholar
  70. 70.
    Ley TJ, Mardis ER, Ding L, Fulton B, McLellan MD, Chen K, et al. DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome. Nature. 2008;456(7218):66–72.PubMedPubMedCentralCrossRefGoogle Scholar
  71. 71.
    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(12):1079–89.PubMedPubMedCentralCrossRefGoogle Scholar
  72. 72.
    Bejar R, Stevenson K, Abdel-Wahab O, Galili N, Nilsson B, Garcia-Manero G, et al. Clinical effect of point mutations in myelodysplastic syndromes. N Engl J Med. 2011;364(26):2496–506.PubMedPubMedCentralCrossRefGoogle Scholar
  73. 73.
    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(7339):467–72.  https://doi.org/10.1038/nature09837.PubMedPubMedCentralCrossRefGoogle Scholar
  74. 74.
    Campana D. Minimal residual disease monitoring in childhood acute lymphoblastic leukemia. Curr Opin Hematol. 2012;19(4):313–8.PubMedCrossRefGoogle Scholar
  75. 75.
    Gawad C, Pepin F, Carlton VE, Klinger M, Logan AC, Miklos DB, et al. Massive evolution of the immunoglobulin heavy chain locus in children with B precursor acute lymphoblastic leukemia. Blood. 2012;120(22):4407–17.PubMedPubMedCentralCrossRefGoogle Scholar
  76. 76.
    Ramsay AJ, Martinez-Trillos A, Jares P, Rodriguez D, Kwarciak A, Quesada V. Next-generation sequencing reveals the secrets of the chronic lymphocytic leukemia genome. Clin Transl Oncol, 2013;15(1):3–8;Google Scholar
  77. 77.
    Benichou J, Ben-Hamo R, Louzoun Y, Efroni S. Rep-Seq: uncovering the immunological repertoire through next-generation sequencing. Immunology. 2012;135(3):183–91.PubMedPubMedCentralCrossRefGoogle Scholar
  78. 78.
    Kohlmann A, Grossmann V, Haferlach T. Integration of next-generation sequencing into clinical practice: are we there yet? Semin Oncol. 2012;39(1):26–36.PubMedCrossRefGoogle Scholar
  79. 79.
    Shaffer LG, Schultz RA, Ballif BC. The use of new technologies in the detection of balanced translocations in hematologic disorders. Curr Opin Genet Dev. 2012;22(3):264–71.PubMedCrossRefGoogle Scholar
  80. 80.
    Wren D, Walker BA, Brüggemann M, Catherwood MA, Pott C, Stamatopoulos K, et al. Comprehensive translocation and clonality detection in lymphoproliferative disorders by next-generation sequencing. Haematologica. 2017;102(2):e57–60.PubMedPubMedCentralCrossRefGoogle Scholar
  81. 81.
    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(7382):506–10.  https://doi.org/10.1038/nature10738.PubMedPubMedCentralCrossRefGoogle Scholar
  82. 82.
    Soverini S, De Benedittis C, Machova Polakova K, Brouckova A, Horner D, Iacono M, et al. Unraveling the complexity of tyrosine kinase inhibitor-resistant populations by ultra-deep sequencing of the BCR-ABL kinase domain. Blood. 2013;21:2013.Google Scholar
  83. 83.
    Landau Dan A, Carter Scott L, Stojanov P, McKenna A, Stevenson K, Lawrence Michael S, et al. Evolution and impact of subclonal mutations in chronic lymphocytic leukemia. Cell. 2013;152(4):714–26.PubMedPubMedCentralCrossRefGoogle Scholar
  84. 84.
    Gullapalli RR, Lyons-Weiler M, Petrosko P, Dhir R, Becich MJ, LaFramboise WA. Clinical integration of next-generation sequencing technology. Clin Lab Med. 2012;32(4):585–99.PubMedPubMedCentralCrossRefGoogle Scholar
  85. 85.
    Gargis AS, Kalman L, Berry MW, Bick DP, Dimmock DP, Hambuch T, et al. Assuring the quality of next-generation sequencing in clinical laboratory practice. Nat Biotech. 2012;30(11):1033–6.  https://doi.org/10.1038/nbt.2403.CrossRefGoogle Scholar
  86. 86.
    Spencer DH, Abel HJ, Lockwood CM, Payton JE, Szankasi P, Kelley TW, et al. Detection of FLT3 internal tandem duplication in targeted, short-read-length, next-generation sequencing data. J Mol Diagn. 2013;15(1):81–93.PubMedCrossRefGoogle Scholar
  87. 87.
    Shen R, Fan JB, Campbell D, Chang W, Chen J, Doucet D, Yeakley J, Bibikova M, Garcia EW, McBride C, Steemers F, Garcia F, Kermani BG, Gunderson K, Oliphant A. High throughput SNP genotyping on universal bead arrays. Mutat Res. 2005;573(1–2):70–82.PubMedCrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Kevin E. Fisher
    • 1
  • Linsheng Zhang
    • 2
  • Charles E. Hill
    • 2
    Email author
  1. 1.Pathology and ImmunologyBaylor College of Medicine, Texas Children’s HospitalHoustonUSA
  2. 2.Pathology and Laboratory MedicineEmory University HospitalAtlantaUSA

Personalised recommendations