Skip to main content
SpringerLink
Log in

Leukemia’s Clonal Evolution in Development, Progression, and Relapse

  • Mathematical Models of Stem Cell Behavior (M Kohandel, Section Editor)
  • Published:
Current Stem Cell Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

Advances in high-throughput methods have enabled the molecular characterization of leukemias and have improved our understanding of their clonal evolution from leukemogenesis in hematopoietic stem/progenitor cells to overt diagnosable disease.

Recent Findings

It has now been revealed that during leukemia’s development and progression, genetic alterations accumulate according to the principles of Darwinian evolution. Drug resistance often emerges from changes in evolutionary trajectories of disease through selection of subpopulations that have greater fitness under therapy. In this manuscript, we will review recent data on prevalence of highly branched evolutionary patterns in myeloid and lymphoid leukemias and discuss how different treatment strategies differentially shape leukemia’s clonal architecture.

Summary

Increasing evidence on clinical impact of small pre-malignant clones prior to diagnosis and small resistant clones during treatment strongly suggests that highly sensitive experimental and mathematical models are necessary for accurate dissection of hematopoietic populations and robust identification of predictive markers for disease transformation and relapse.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Busque L, Patel JP, Figueroa ME, Vasanthakumar A, Provost S, Hamilou Z, et al. Recurrent somatic TET2 mutations in normal elderly individuals with clonal hematopoiesis. Nat Genet. 2012;44(11):1179–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Genovese G, Kahler AK, Handsaker RE, Lindberg J, Rose SA, Bakhoum SF, et al. Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. N Engl J Med. 2014;371(26):2477–87.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. Jaiswal S, Fontanillas P, Flannick J, Manning A, Grauman PV, Mar BG, et al. Age-related clonal hematopoiesis associated with adverse outcomes. N Engl J Med. 2014;371(26):2488–98.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Kwok B, Hall JM, Witte JS, Xu Y, Reddy P, Lin K, et al. MDS-associated somatic mutations and clonal hematopoiesis are common in idiopathic cytopenias of undetermined significance. Blood. 2015;126(21):2355–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Young AL, Challen GA, Birmann BM, Druley TE. Clonal haematopoiesis harbouring AML-associated mutations is ubiquitous in healthy adults. Nat Commun. 2016;7:12484.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. • Papaemmanuil E, Gerstung M, Bullinger L, Gaidzik VI, Paschka P, Roberts ND, et al. Genomic classification and prognosis in acute myeloid leukemia. N Engl J Med. 2016;374(23):2209–21 A large-scale genomic study of more than 1500 AML patients showing prognostic power of genomic classification.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Shlush LI, Zandi S, Mitchell A, Chen WC, Brandwein JM, Gupta V, et al. Identification of pre-leukaemic haematopoietic stem cells in acute leukaemia. Nature. 2014;506(7488):328–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Mossner M, Jann JC, Wittig J, Nolte F, Fey S, Nowak V, et al. Mutational hierarchies in myelodysplastic syndromes dynamically adapt and evolve upon therapy response and failure. Blood. 2016;128(9):1246–59.

    Article  CAS  PubMed  Google Scholar 

  9. •• Abelson S, Collord G, Ng SWK, Weissbrod O, Mendelson Cohen N, Niemeyer E, et al. Prediction of acute myeloid leukaemia risk in healthy individuals. Nature. 2018 One of the first studies to directly link CHIP to development of AML.

  10. •• Desai P, Mencia-Trinchant N, Savenkov O, Simon MS, Cheang G, Lee S, et al. Somatic mutations precede acute myeloid leukemia years before diagnosis. Nature Medicine. 2018;24(7):1015–23 One of the first studies to directly link CHIP to development of AML.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. • Bowman RL, Busque L, Levine RL. Clonal hematopoiesis and evolution to hematopoietic malignancies. Cell Stem Cell. 2018;22(2):157–70 A comprehensive review on CHIP and its evolution to hematological malignancies.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Coombs CC, Zehir A, Devlin SM, Kishtagari A, Syed A, Jonsson P, et al. Therapy-related clonal hematopoiesis in patients with non-hematologic cancers is common and associated with adverse clinical outcomes. Cell Stem Cell. 2017.

  13. Severson EA, Riedlinger GM, Connelly CF, Vergilio JA, Goldfinger M, Ramkissoon S, et al. Detection of clonal hematopoiesis of indeterminate potential in clinical sequencing of solid tumor specimens. Blood. 2018;131(22):2501–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Xie M, Lu C, Wang J, McLellan MD, Johnson KJ, Wendl MC, et al. Age-related mutations associated with clonal hematopoietic expansion and malignancies. Nat Med. 2014;20(12):1472–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Arends CM, Galan-Sousa J, Hoyer K, Chan W, Jager M. Yoshida K, et al. Leukemia: Hematopoietic lineage distribution and evolutionary dynamics of clonal hematopoiesis; 2018.

    Google Scholar 

  16. Tiacci E, Pettirossi V, Schiavoni G, Falini B. Genomics of hairy cell leukemia. J Clin Oncol. 2017;35(9):1002–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Chung SS, Kim E, Park JH, Chung YR, Lito P, Teruya-Feldstein J, et al. Hematopoietic stem cell origin of BRAFV600E mutations in hairy cell leukemia. Sci Transl Med. 2014;6(238):238ra71.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Damm F, Mylonas E, Cosson A, Yoshida K, Della Valle V, Mouly E, et al. Acquired initiating mutations in early hematopoietic cells of CLL patients. Cancer Discov. 2014;4(9):1088–101.

    Article  CAS  PubMed  Google Scholar 

  19. Kikushige Y, Ishikawa F, Miyamoto T, Shima T, Urata S, Yoshimoto G, et al. Self-renewing hematopoietic stem cell is the primary target in pathogenesis of human chronic lymphocytic leukemia. Cancer Cell. 2011;20(2):246–59.

    Article  CAS  PubMed  Google Scholar 

  20. Marsilio S, Khiabanian H, Fabbri G, Vergani S, Scuoppo C, Montserrat E, et al. Somatic CLL mutations occur at multiple distinct hematopoietic maturation stages: documentation and cautionary note regarding cell fraction purity. Leukemia. 2018;32(4):1041–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Alpar D, Wren D, Ermini L, Mansur MB, van Delft FW, Bateman CM, et al. Clonal origins of ETV6-RUNX1(+) acute lymphoblastic leukemia: studies in monozygotic twins. Leukemia. 2015;29(4):839–46.

    Article  CAS  PubMed  Google Scholar 

  22. Hong D, Gupta R, Ancliff P, Atzberger A, Brown J, Soneji S, et al. Initiating and cancer-propagating cells in TEL-AML1-associated childhood leukemia. Science. 2008;319(5861):336–9.

    Article  CAS  PubMed  Google Scholar 

  23. Sanjuan-Pla A, Bueno C, Prieto C, Acha P, Stam RW, Marschalek R, et al. Revisiting the biology of infant t(4;11)/MLL-AF4+ B-cell acute lymphoblastic leukemia. Blood. 2015;126(25):2676–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Zhang J, Ding L, Holmfeldt L, Wu G, Heatley SL, Payne-Turner D, et al. The genetic basis of early T-cell precursor acute lymphoblastic leukaemia. Nature. 2012;481(7380):157–63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Corces-Zimmerman MR, Hong WJ, Weissman IL, Medeiros BC, Majeti R. Preleukemic mutations in human acute myeloid leukemia affect epigenetic regulators and persist in remission. Proc Natl Acad Sci U S A. 2014;111(7):2548–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Heath EM, Chan SM, Minden MD, Murphy T, Shlush LI, Schimmer AD. Biological and clinical consequences of NPM1 mutations in AML. Leukemia. 2017;31(4):798–807.

    Article  CAS  PubMed  Google Scholar 

  27. Gerstung M, Papaemmanuil E, Martincorena I, Bullinger L, Gaidzik VI, Paschka P, et al. Precision oncology for acute myeloid leukemia using a knowledge bank approach. Nat Genet. 2017;49(3):332–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. • Ferrando AA, Lopez-Otin C. Clonal evolution in leukemia. Nat Med. 2017;23(10):1135–45 A comprehensive review of clonal evolution in acute and chronic leukemias.

    Article  CAS  PubMed  Google Scholar 

  29. Landau DA, Carter SL, Stojanov P, McKenna A, Stevenson K, Lawrence MS, et al. Evolution and impact of subclonal mutations in chronic lymphocytic leukemia. Cell. 2013;152(4):714–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Landau DA, Tausch E, Taylor-Weiner AN, Stewart C, Reiter JG, Bahlo J, et al. Mutations driving CLL and their evolution in progression and relapse. Nature. 2015;526(7574):525–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. • Ortmann CA, Kent DG, Nangalia J, Silber Y, Wedge DC, Grinfeld J, et al. Effect of mutation order on myeloproliferative neoplasms. N Engl J Med. 2015;372(7):601–12 This study showed the differential dynamics of TET2-first-mutated vs. JAK2-first-mutated myeloproliferative neoplasms.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Papaemmanuil E, Gerstung M, Malcovati L, Tauro S, Gundem G, Van Loo P, et al. Clinical and biological implications of driver mutations in myelodysplastic syndromes. Blood. 2013;122(22):3616–27 quiz 99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Wang L, Fan J, Francis JM, Georghiou G, Hergert S, Li S, et al. Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia. Genome Res. 2017;27(8):1300–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Wang J, Khiabanian H, Rossi D, Fabbri G, Gattei V, Forconi F, et al. Tumor evolutionary directed graphs and the history of chronic lymphocytic leukemia. Elife. 2014;3.

  35. Holyoake TL, Vetrie D. The chronic myeloid leukemia stem cell: stemming the tide of persistence. Blood. 2017;129(12):1595–606.

    Article  CAS  PubMed  Google Scholar 

  36. Cortes J, Jabbour E, Kantarjian H, Yin CC, Shan J, O'Brien S, et al. Dynamics of BCR-ABL kinase domain mutations in chronic myeloid leukemia after sequential treatment with multiple tyrosine kinase inhibitors. Blood. 2007;110(12):4005–11.

    Article  CAS  PubMed  Google Scholar 

  37. Falini B, Martelli MP, Tiacci E. BRAF V600E mutation in hairy cell leukemia: from bench to bedside. Blood. 2016;128(15):1918–27.

    Article  CAS  PubMed  Google Scholar 

  38. Tiacci E, Park JH, De Carolis L, Chung SS, Broccoli A, Scott S, et al. Targeting mutant BRAF in relapsed or refractory hairy-cell leukemia. N Engl J Med. 2015;373(18):1733–47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Nadeu F, Delgado J, Royo C, Baumann T, Stankovic T, Pinyol M, et al. Clinical impact of clonal and subclonal TP53, SF3B1, BIRC3, NOTCH1, and ATM mutations in chronic lymphocytic leukemia. Blood. 2016;127(17):2122–30.

    Article  CAS  PubMed  Google Scholar 

  40. • Rossi D, Khiabanian H, Spina V, Ciardullo C, Bruscaggin A, Fama R, et al. Clinical impact of small TP53 mutated subclones in chronic lymphocytic leukemia. Blood. 2014;123(14):2139–47 The first systematic study to uncover the impact of small TP53-mutated clones on CLL prognosis.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Rasi S, Khiabanian H, Ciardullo C, Terzi-di-Bergamo L, Monti S, Spina V, et al. Clinical impact of small subclones harboring NOTCH1, SF3B1 or BIRC3 mutations in chronic lymphocytic leukemia. Haematologica. 2016;101(4):e135–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Woyach JA, Johnson AJ, Byrd JC. The B-cell receptor signaling pathway as a therapeutic target in CLL. Blood. 2012;120(6):1175–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Landau DA, Sun C, Rosebrock D, Herman SEM, Fein J, Sivina M, et al. The evolutionary landscape of chronic lymphocytic leukemia treated with ibrutinib targeted therapy. Nat Commun. 2017;8(1):2185.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. • Ahn IE, Underbayev C, Albitar A, Herman SE, Tian X, Maric I, et al. Clonal evolution leading to ibrutinib resistance in chronic lymphocytic leukemia. Blood. 2017;129(11):1469–79 This study provided strong evidence for the role of subclonal heterogeneity and timing the rise of resistant disease in CLLs treated with ibrutinib.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Meyer JA, Wang J, Hogan LE, Yang JJ, Dandekar S, Patel JP, et al. Relapse-specific mutations in NT5C2 in childhood acute lymphoblastic leukemia. Nat Genet. 2013;45(3):290–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Tzoneva G, Perez-Garcia A, Carpenter Z, Khiabanian H, Tosello V, Allegretta M, et al. Activating mutations in the NT5C2 nucleotidase gene drive chemotherapy resistance in relapsed ALL. Nat Med. 2013;19(3):368–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Dieck CL, Tzoneva G, Forouhar F, Carpenter Z, Ambesi-Impiombato A, Sanchez-Martin M, et al. Structure and mechanisms of NT5C2 mutations driving thiopurine resistance in relapsed lymphoblastic leukemia. Cancer Cell. 2018;34(1):136–47 e6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. •• Tzoneva G, Dieck CL, Oshima K, Ambesi-Impiombato A, Sanchez-Martin M, Madubata CJ, et al. Clonal evolution mechanisms in NT5C2 mutant-relapsed acute lymphoblastic leukaemia. Nature. 2018;553(7689):511–4 Systematic demonstration of clonal evolution in relapsed ALL and of the rise of resistant mutations at the cost of impaired leukemia cell growth.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Aries IM, van den Dungen RE, Koudijs MJ, Cuppen E, Voest E, Molenaar JJ, et al. Towards personalized therapy in pediatric acute lymphoblastic leukemia: RAS mutations and prednisolone resistance. Haematologica. 2015;100(4):e132–6.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Irving J, Matheson E, Minto L, Blair H, Case M, Halsey C, et al. Ras pathway mutations are prevalent in relapsed childhood acute lymphoblastic leukemia and confer sensitivity to MEK inhibition. Blood. 2014;124(23):3420–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Irving JA, Enshaei A, Parker CA, Sutton R, Kuiper RP, Erhorn A, et al. Integration of genetic and clinical risk factors improves prognostication in relapsed childhood B-cell precursor acute lymphoblastic leukemia. Blood. 2016;128(7):911–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Ma X, Edmonson M, Yergeau D, Muzny DM, Hampton OA, Rusch M, et al. Rise and fall of subclones from diagnosis to relapse in pediatric B-acute lymphoblastic leukaemia. Nat Commun. 2015;6:6604.

    Article  CAS  PubMed  Google Scholar 

  53. Oshima K, Khiabanian H, da Silva-Almeida AC, Tzoneva G, Abate F, Ambesi-Impiombato A, et al. Mutational landscape, clonal evolution patterns, and role of RAS mutations in relapsed acute lymphoblastic leukemia. Proc Natl Acad Sci U S A. 2016;113(40):11306–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Schuurhuis GJ, Heuser M, Freeman S, Bene MC, Buccisano F, Cloos J, et al. Minimal/measurable residual disease in AML: a consensus document from the European LeukemiaNet MRD working party. Blood. 2018;131(12):1275–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Thompson PA, Wierda WG. Eliminating minimal residual disease as a therapeutic end point: working toward cure for patients with CLL. Blood. 2016;127(3):279–86.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Ojamies PN, Kontro M, Edgren H, Ellonen P, Lagstrom S, Almusa H, et al. Monitoring therapy responses at the leukemic subclone level by ultra-deep amplicon resequencing in acute myeloid leukemia. Leukemia. 2017;31(5):1048–58.

    Article  CAS  PubMed  Google Scholar 

  57. • Jongen-Lavrencic M, Grob T, Hanekamp D, Kavelaars FG, Al Hinai A, Zeilemaker A, et al. Molecular minimal residual disease in acute myeloid leukemia. N Engl J Med. 2018;378(13):1189–99 Persistence of mutations during complete remission was associated with a significant rate of relapse, and it showed lack of correlation for CHIP-associated mutations with AML prognosis.

    Article  CAS  PubMed  Google Scholar 

  58. Morita K, Kantarjian HM, Wang F, Yan Y, Bueso-Ramos C, Sasaki K, et al. Clearance of somatic mutations at remission and the risk of relapse in acute myeloid leukemia. J Clin Oncol. 2018;36(18):1788–97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Salk JJ, Schmitt MW, Loeb LA. Enhancing the accuracy of next-generation sequencing for detecting rare and subclonal mutations. Nat Rev Genet. 2018;19(5):269–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Altrock PM, Liu LL, Michor F. The mathematics of cancer: integrating quantitative models. Nat Rev Cancer. 2015;15(12):730–45.

    Article  CAS  PubMed  Google Scholar 

  61. •• Beerenwinkel N, Schwarz RF, Gerstung M, Markowetz F. Cancer evolution: mathematical models and computational inference. Syst Biol. 2015;64(1):e1–25 A comprehensive review on methods to infer population dynamics and phylogenetic relationships in cancer.

    Article  CAS  PubMed  Google Scholar 

  62. Clapp G, Levy D. A review of mathematical models for leukemia and lymphoma. Drug Discov Today Dis Models. 2015;16:1–6.

    Article  PubMed  Google Scholar 

  63. Michor F, Beal K. Improving cancer treatment via mathematical modeling: surmounting the challenges is worth the effort. Cell. 2015;163(5):1059–63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Rodriguez-Brenes IA, Wodarz D. Preventing clonal evolutionary processes in cancer: insights from mathematical models. Proc Natl Acad Sci U S A. 2015;112(29):8843–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Zhao B, Hemann MT, Lauffenburger DA. Modeling tumor clonal evolution for drug combinations design. Trends Cancer. 2016;2(3):144–58.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Komarova NL, Burger JA, Wodarz D. Evolution of ibrutinib resistance in chronic lymphocytic leukemia (CLL). Proc Natl Acad Sci U S A. 2014;111(38):13906–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Messmer BT, Messmer D, Allen SL, Kolitz JE, Kudalkar P, Cesar D, et al. In vivo measurements document the dynamic cellular kinetics of chronic lymphocytic leukemia B cells. J Clin Invest. 2005;115(3):755–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Wodarz D, Garg N, Komarova NL, Benjamini O, Keating MJ, Wierda WG, et al. Kinetics of CLL cells in tissues and blood during therapy with the BTK inhibitor ibrutinib. Blood. 2014;123(26):4132–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Burger JA, Li KW, Keating MJ, Sivina M, Amer AM, Garg N, et al. Leukemia cell proliferation and death in chronic lymphocytic leukemia patients on therapy with the BTK inhibitor ibrutinib. JCI Insight. 2017;2(2):e89904.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Chen LS, Bose P, Cruz ND, Jiang Y, Wu Q, Thompson PA, et al. A pilot study of lower doses of ibrutinib in patients with chronic lymphocytic leukemia. Blood. 2018.

  71. McGranahan N, Swanton C. Clonal heterogeneity and tumor evolution: past, present, and the future. Cell. 2017;168(4):613–28.

    Article  CAS  PubMed  Google Scholar 

  72. Caravagna G, Giarratano Y, Ramazzotti D, Tomlinson I, Graham TA, Sanguinetti G, et al. Detecting repeated cancer evolution from multi-region tumor sequencing data. Nat Methods. 2018;15(9):707–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Somarelli JA, Ware KE, Kostadinov R, Robinson JM, Amri H, Abu-Asab M, et al. PhyloOncology: understanding cancer through phylogenetic analysis. Biochim Biophys Acta Rev Cancer. 2017;1867(2):101–8.

    Article  CAS  PubMed  Google Scholar 

  74. Billera LJ, Holmes SP, Vogtmann K. Geometry of the space of phylogenetic trees. Adv Appl Math. 2001;27(4):733–67.

    Article  Google Scholar 

  75. Zairis S, Khiabanian H, Blumberg A, Rabadan R. Moduli spaces of phylogenetic trees describing tumor evolutionary patterns. Lect Notes Comput Sci. 2014;8609:528–39.

    Article  Google Scholar 

  76. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Li S, Garrett-Bakelman FE, Chung SS, Sanders MA, Hricik T, Rapaport F, et al. Distinct evolution and dynamics of epigenetic and genetic heterogeneity in acute myeloid leukemia. Nat Med. 2016;22(7):792–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Schuh A, Becq J, Humphray S, Alexa A, Burns A, Clifford R, et al. Monitoring chronic lymphocytic leukemia progression by whole genome sequencing reveals heterogeneous clonal evolution patterns. Blood. 2012;120(20):4191–6.

    Article  CAS  PubMed  Google Scholar 

  79. Zairis S, Khiabanian, H., Blumberg A, Rabadan R. Genomic data analysis in tree spaces. arXiv:1607.075032016.

  80. Andrew J. Blumberg, Prithwish Bhaumik, Walker SG. Testing to distinguish measures on metric spaces. arXiv:1802.011522018.

  81. Luria SE, Delbruck M. Mutations of bacteria from virus sensitivity to virus resistance. Genetics. 1943;28(6):491–511.

    CAS  PubMed  PubMed Central  Google Scholar 

  82. Batlle E, Clevers H. Cancer stem cells revisited. Nat Med. 2017;23(10):1124–34.

    Article  CAS  PubMed  Google Scholar 

  83. Rosenbloom DIS, Camara PG, Chu T, Rabadan R. Evolutionary scalpels for dissecting tumor ecosystems. Biochim Biophys Acta Rev Cancer. 2017;1867(2):69–83.

    Article  CAS  PubMed  Google Scholar 

  84. Nowell PC. The clonal evolution of tumor cell populations. Science. 1976;194(4260):23–8.

    Article  CAS  PubMed  Google Scholar 

  85. Emmett KJ, Lee A, Khiabanian H, Rabadan R. High-resolution genomic surveillance of 2014 Ebolavirus using shared subclonal variants. PLoS Curr 2015;7.

  86. Sobel Leonard A, Weissman DB, Greenbaum B, Ghedin E, Koelle K. Transmission bottleneck size estimation from pathogen deep-sequencing data, with an application to human influenza A virus. J Virol. 2017;91(14).

  87. • Bozic I, Reiter JG, Allen B, Antal T, Chatterjee K, Shah P, et al. Evolutionary dynamics of cancer in response to targeted combination therapy. Elife. 2013;2:e00747 A mathematical model showing that simultaneous therapy with two drugs is more effective than sequential therapy.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

J-WL is a pre-doctoral fellow of the New Jersey Commission on Cancer Research (DFS18PPC017). HK acknowledges support from Rutgers Cancer Institute of New Jersey (P30CA072720).

Author information

Authors and Affiliations

  1. Rutgers Cancer Institute of New Jersey, Rutgers University, 195 Little Albany Street, New Brunswick, NJ, 08903-2681, USA

    Jui Wan Loh & Hossein Khiabanian

  2. Center for Systems and Computational Biology, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA

    Jui Wan Loh & Hossein Khiabanian

  3. Graduate Program in Microbiology and Molecular Genetics, Rutgers University, Piscataway, NJ, USA

    Jui Wan Loh

  4. Department of Pathology and Laboratory Medicine, Rutgers Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA

    Hossein Khiabanian

Authors
  1. Jui Wan Loh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hossein Khiabanian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hossein Khiabanian.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Mathematical Models of Stem Cell Behavior

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Loh, J.W., Khiabanian, H. Leukemia’s Clonal Evolution in Development, Progression, and Relapse. Curr Stem Cell Rep 5, 73–81 (2019). https://doi.org/10.1007/s40778-019-00157-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40778-019-00157-y

Keywords

Search

Navigation