Advertisement

Towards Personalized Medicine in Pediatric Cancer: Genome-Wide Strategies to Investigate Cancer Risk and Response to Therapy

  • Navin PintoEmail author
  • Kenan Onel
Chapter
Part of the Molecular and Translational Medicine book series (MOLEMED)

Abstract

Cancer results from the complex actions and interactions of multiple genetic, epigenetic and environmental factors that lead to the acquisition of somatic alterations abrogating the function of a variety of normal regulatory networks. While there has been considerable progress in understanding the genetic basis of cancer, only rarely has this knowledge translated to the development of rational therapeutics. In fact, the majority of children with cancer are still treated with nonspecific cytotoxic agents, and the remarkable strides made in curing these diseases have come largely from improvements in chemotherapy, radiation, cellular transplantation, and supportive care rather than from the use of targeted therapies.

Keywords

Genomics Molecular diagnostics Cytogenetics Single nucleotide polymorphisms Array comparative genomic hybridization 

References

  1. 1.
    Boveri T. Concerning the origin of malignant tumours by Theodor Boveri. Translated and annotated by Henry Harris. J Cell Sci. 2008;121 Suppl 1:1–84. doi:121/Supplement_1/1 [pii]10.1242/jcs.025742.PubMedCrossRefGoogle Scholar
  2. 2.
    Muller HJ. The production of mutations by X-rays. Proc Natl Acad Sci U S A. 1928;14:714–26.PubMedCrossRefGoogle Scholar
  3. 3.
    Muller HJ. Radiation injuries of the genetic material. Strahlentherapie. 1951;85:509–36.PubMedGoogle Scholar
  4. 4.
    Nowell PC, Hungerford DA. Chromosome studies on normal and leukemic human leukocytes. J Natl Cancer Inst. 1960;25:85–109.PubMedGoogle Scholar
  5. 5.
    Rowley JD. Letter: a new consistent chromosomal abnormality in chronic myelogenous leukaemia identified by quinacrine fluorescence and Giemsa staining. Nature. 1973;243:290–3.PubMedCrossRefGoogle Scholar
  6. 6.
    Rowley JD. Identificaton of a translocation with quinacrine fluorescence in a patient with acute leukemia. Ann Genet. 1973;16:109–12.PubMedGoogle Scholar
  7. 7.
    Knudson Jr AG. Mutation and cancer: statistical study of retinoblastoma. Proc Natl Acad Sci USA. 1971;68:820–3.PubMedCrossRefGoogle Scholar
  8. 8.
    Groffen J, et al. The human c-abl oncogene in the Philadelphia translocation. J Cell Physiol Suppl. 1984;3:179–91.PubMedCrossRefGoogle Scholar
  9. 9.
    Groffen J, et al. Philadelphia chromosomal breakpoints are clustered within a limited region, bcr, on chromosome 22. Cell. 1984;36:93–9. doi:0092-8674(84)90077-1 [pii].PubMedCrossRefGoogle Scholar
  10. 10.
    Kurzrock R, Gutterman JU, Talpaz M. The molecular genetics of Philadelphia chromosome-positive leukemias. N Engl J Med. 1988;319:990–8. doi: doi:10.1056/NEJM198810133191506.PubMedCrossRefGoogle Scholar
  11. 11.
    Lugo TG, Pendergast AM, Muller AJ, Witte ON. Tyrosine kinase activity and transformation potency of bcr-abl oncogene products. Science. 1990;247:1079–82.PubMedCrossRefGoogle Scholar
  12. 12.
    Buchdunger E, et al. Inhibition of the Abl protein-tyrosine kinase in vitro and in vivo by a 2-phenylaminopyrimidine derivative. Cancer Res. 1996;56:100–4.PubMedGoogle Scholar
  13. 13.
    Branford S, et al. Imatinib produces significantly superior molecular responses compared to interferon alfa plus cytarabine in patients with newly diagnosed chronic myeloid leukemia in chronic phase. Leukemia. 2003;17:2401–9. doi:10.1038/sj.leu.2403158 [pii].PubMedCrossRefGoogle Scholar
  14. 14.
    Hahn EA, et al. Quality of life in patients with newly diagnosed chronic phase chronic myeloid leukemia on imatinib versus interferon alfa plus low-dose cytarabine: results from the IRIS Study. J Clin Oncol. 2003;21:2138–46. doi:10.1200/JCO.2003.12.154 [pii].PubMedCrossRefGoogle Scholar
  15. 15.
    Burke MJ, Willert J, Desai S, Kadota R. The treatment of pediatric Philadelphia positive (Ph+) leukemias in the imatinib era. Pediatr Blood Cancer. 2009;53:992–5. doi: 10.1002/pbc.22172.PubMedCrossRefGoogle Scholar
  16. 16.
    Craze JL, Harrison G, Wheatley K, Hann IM, Chessells JM. Improved outcome of acute myeloid leukaemia in Down’s syndrome. Arch Dis Child. 1999;81:32–7.PubMedCrossRefGoogle Scholar
  17. 17.
    Lange BJ, et al. Distinctive demography, biology, and outcome of acute myeloid leukemia and myelodysplastic syndrome in children with Down syndrome: Children’s Cancer Group Studies 2861 and 2891. Blood. 1998;91:608–15.PubMedGoogle Scholar
  18. 18.
    George RE, et al. Relationship between histopathological features, MYCN amplification, and prognosis: a UKCCSG study. United Kingdom Children Cancer Study Group. Med Pediatr Oncol. 2001;36:169–76. doi:10.1002/1096-911X(20010101)36:1<169::AID-MPO1041>3.0.CO;2-U.PubMedCrossRefGoogle Scholar
  19. 19.
    Bown N. Neuroblastoma tumour genetics: clinical and biological aspects. J Clin Pathol. 2001;54:897–910.PubMedCrossRefGoogle Scholar
  20. 20.
    Lander ES, et al. Initial sequencing and analysis of the human genome. Nature. 2001;409:860–921. doi: 10.1038/35057062.PubMedCrossRefGoogle Scholar
  21. 21.
    Venter JC, et al. The sequence of the human genome. Science. 2001;291:1304–51. doi:10.1126/science.1058040291/5507/1304 [pii].PubMedCrossRefGoogle Scholar
  22. 22.
    The International HapMap Consortium. The International HapMap Project. Nature. 2003;426:789–96. doi:10.1038/nature02168 [pii].CrossRefGoogle Scholar
  23. 23.
    Strachan T, Read AP. Human molecular genetics. 2nd ed. New York: Wiley-Liss, BIOS Scientific Publishers; 1999.Google Scholar
  24. 24.
    Caspersson T, Zech L, Johansson C. Differential binding of alkylating fluorochromes in human chromosomes. Exp Cell Res. 1970;60:315–9.PubMedCrossRefGoogle Scholar
  25. 25.
    Pardue ML, Gall JG. Molecular hybridization of radioactive DNA to the DNA of cytological preparations. Proc Natl Acad Sci U S A. 1969;64:600–4.PubMedCrossRefGoogle Scholar
  26. 26.
    Speicher MR, Gwyn Ballard S, Ward DC. Karyotyping human chromosomes by combinatorial multi-fluor FISH. Nat Genet. 1996;12:368–75. doi: 10.1038/ng0496-368.PubMedCrossRefGoogle Scholar
  27. 27.
    Woods WG, et al. A comparison of allogeneic bone marrow transplantation, autologous bone marrow transplantation, and aggressive chemotherapy in children with acute myeloid leukemia in remission. Blood. 2001;97:56–62.PubMedCrossRefGoogle Scholar
  28. 28.
    Burnett AK, et al. The value of allogeneic bone marrow transplant in patients with acute myeloid leukaemia at differing risk of relapse: results of the UK MRC AML 10 trial. Br J Haematol. 2002;118:385–400. doi:3724 [pii].PubMedCrossRefGoogle Scholar
  29. 29.
    Cohn SL, et al. The International Neuroblastoma Risk Group (INRG) classification system: an INRG Task Force report. J Clin Oncol. 2009;27:289–97. doi:10.1200/JCO.2008.16.6785 [pii].PubMedCrossRefGoogle Scholar
  30. 30.
    Cremer T, Lichter P, Borden J, Ward DC, Manuelidis L. Detection of chromosome aberrations in metaphase and interphase tumor cells by in situ hybridization using chromosome-specific library probes. Hum Genet. 1988;80:235–46.PubMedCrossRefGoogle Scholar
  31. 31.
    Kallioniemi A, et al. Comparative genomic hybridization for molecular cytogenetic analysis of solid tumors. Science. 1992;258:818–21.PubMedCrossRefGoogle Scholar
  32. 32.
    Pinkel D, et al. High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat Genet. 1998;20:207–11. doi: 10.1038/2524.PubMedCrossRefGoogle Scholar
  33. 33.
    Mosse Y, Greshock J, Weber B, Maris J. Measurement and relevance of neuroblastoma DNA copy number changes in the post-genome era. Cancer Lett. 2005;228:83–90. doi: 10.1016/j.canlet.2005.02.052.PubMedCrossRefGoogle Scholar
  34. 34.
    Zitterbart K, et al. Low-level copy number changes of MYC genes have a prognostic impact in medulloblastoma. J Neurooncol. 2010. doi: 10.1007/s11060-010-0289-3.
  35. 35.
    Kang HJ, et al. High transcript level of FLT3 associated with high risk of relapse in pediatric acute myeloid leukemia. J Korean Med Sci. 2010;25:841–5. doi: 10.3346/jkms.2010.25.6.841.PubMedCrossRefGoogle Scholar
  36. 36.
    Kuiper RP, et al. IKZF1 deletions predict relapse in uniformly treated pediatric precursor B-ALL. Leukemia. 2010;24:1258–64. doi:10.1038/leu.2010.87 [pii].PubMedCrossRefGoogle Scholar
  37. 37.
    Pasic I, et al. Recurrent focal copy-number changes and loss of heterozygosity implicate two noncoding RNAs and one tumor suppressor gene at chromosome 3q13.31 in osteosarcoma. Cancer Res. 2010;70:160–71. doi:doi:10.1158/0008-5472.CAN-09-1902 [pii].PubMedCrossRefGoogle Scholar
  38. 38.
    Barr FG, et al. Genomic and clinical analyses of 2p24 and 12q13-q14 amplification in alveolar rhabdomyosarcoma: a report from the Children’s Oncology Group. Genes Chromosomes Cancer. 2009;48:661–72. doi: 10.1002/gcc.20673.PubMedCrossRefGoogle Scholar
  39. 39.
    Bilke S, Chen QR, Wei JS, Khan J. Whole chromosome alterations predict survival in high-risk neuroblastoma without MYCN amplification. Clin Cancer Res. 2008;14:5540–7. doi:14/17/5540 [pii] 10.1158/1078-0432.CCR-07-4461.PubMedCrossRefGoogle Scholar
  40. 40.
    Ohgaki H, Kleihues P. Population-based studies on incidence, survival rates, and genetic alterations in astrocytic and oligodendroglial gliomas. J Neuropathol Exp Neurol. 2005;64:479–89.PubMedGoogle Scholar
  41. 41.
    Sanoudou D, Tingby O, Ferguson-Smith MA, Collins VP, Coleman N. Analysis of pilocytic astrocytoma by comparative genomic hybridization. Br J Cancer. 2000;82:1218–22. doi:S0007092099910662 [pii] 10.1054/bjoc.1999.1066.PubMedCrossRefGoogle Scholar
  42. 42.
    Orr LC, et al. Cytogenetics in pediatric low-grade astrocytomas. Med Pediatr Oncol. 2002;38:173–7. doi:10.1002/mpo.1305 [pii].PubMedCrossRefGoogle Scholar
  43. 43.
    Yunoue S, et al. Neurofibromatosis type I tumor suppressor neurofibromin regulates neuronal differentiation via its GTPase-activating protein function toward Ras. J Biol Chem. 2003;278:26958–69. doi:10.1074/jbc.M209413200 [pii].PubMedCrossRefGoogle Scholar
  44. 44.
    Vose JM. Current approaches to the management of non-Hodgkin’s lymphoma. Semin Oncol. 1998;25:483–91.PubMedGoogle Scholar
  45. 45.
    A clinical evaluation of the International Lymphoma Study Group classification of non-Hodgkin’s lymphoma. The Non-Hodgkin’s Lymphoma Classification Project. Blood. 1997;89:3909–3918.Google Scholar
  46. 46.
    Alizadeh AA, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature. 2000;403:503–11. doi: 10.1038/35000501.PubMedCrossRefGoogle Scholar
  47. 47.
    Patte C, et al. Results of the randomized international FAB/LMB96 trial for intermediate risk B-cell non-Hodgkin lymphoma in children and adolescents: it is possible to reduce treatment for the early responding patients. Blood. 2007;109:2773–80. doi:10.1182/blood-2006-07-036673 [pii].PubMedGoogle Scholar
  48. 48.
    Miles RR, et al. Pediatric diffuse large B-cell lymphoma demonstrates a high proliferation index, frequent c-Myc protein expression, and a high incidence of germinal center subtype: report of the French-American-British (FAB) international study group. Pediatr Blood Cancer. 2008;51:369–74. doi: 10.1002/pbc.21619.PubMedCrossRefGoogle Scholar
  49. 49.
    Capasso M, et al. Common variations in BARD1 influence susceptibility to high-risk neuroblastoma. Nat Genet. 2009;41:718–23. doi: 10.1038/ng.374.PubMedCrossRefGoogle Scholar
  50. 50.
    Treviño LR, et al. Germline genomic variants associated with childhood acute lymphoblastic leukemia. Nat Genet. 2009;41:1001–5. doi: 10.1038/ng.432.PubMedCrossRefGoogle Scholar
  51. 51.
    Wiegand KC, et al. ARID1A mutations in endometriosis-associated ovarian carcinomas. N Engl J Med. 2010;363:1532–43. doi: 10.1056/NEJMoa1008433.PubMedCrossRefGoogle Scholar
  52. 52.
    Evans WE, Relling MV. Pharmacogenomics: translating functional genomics into rational therapeutics. Science. 1999;286:487–91. doi:7906 [pii].PubMedCrossRefGoogle Scholar
  53. 53.
    Yang JJ, et al. Genome-wide interrogation of germline genetic variation associated with treatment response in childhood acute lymphoblastic leukemia. JAMA. 2009;301:393–403. doi: doi:10.1001/jama.2009.7.PubMedCrossRefGoogle Scholar
  54. 54.
    Fruhwald MC, Witt O. The epigenetics of cancer in children. Klin Padiatr. 2008;220:333–41. doi: 10.1055/s-0028-1086026.PubMedCrossRefGoogle Scholar
  55. 55.
    Davidsson J, et al. The DNA methylome of pediatric acute lymphoblastic leukemia. Hum Mol Genet. 2009;18:4054–65. doi: 10.1093/hmg/ddp354.PubMedCrossRefGoogle Scholar
  56. 56.
    Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009;136:215–33. doi:S0092-8674(09)00008-7 [pii] 10.1016/j.cell.2009.01.002.PubMedCrossRefGoogle Scholar
  57. 57.
    Friedman RC, Farh KK, Burge CB, Bartel DP. Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 2009;19:92–105. doi:10.1101/gr.082701.108 [pii].PubMedCrossRefGoogle Scholar
  58. 58.
    McManus MT. MicroRNAs and cancer. Semin Cancer Biol. 2003;13:253–8.PubMedCrossRefGoogle Scholar
  59. 59.
    Wei JS, et al. microRNA profiling identifies cancer-specific and prognostic signatures in pediatric malignancies. Clin Cancer Res. 2009;15:5560–8. doi: 10.1158/1078-0432.ccr-08-3287.PubMedCrossRefGoogle Scholar
  60. 60.
    Chen QR, et al. Global genomic and proteomic analysis identifies biological pathways related to high-risk neuroblastoma. J Proteome Res. 2010;9:373–82. doi: 10.1021/pr900701v.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  1. 1.Department of Pediatrics, Section of Pediatric Hematology, Oncology, and Stem Cell TransplantationUniversity of ChicagoChicagoUSA

Personalised recommendations