Abstract
Most types of cancers are made up of heterogeneous mixtures of genetically distinct subclones. In particular, acute myeloid leukemia (AML) has been shown to undergo substantial clonal evolution over the course of the disease. AML tends to harbor fewer mutations than solid tumors, making it challenging to infer clonal structure. Here, we present a 9-year, whole-exome sequencing study of a single case at 12 time points, from the initial diagnosis until a fourth relapse, including 6 remission samples in between. To the best of our knowledge, it covers the longest time span of any data set of its kind. We used these time series data to track the hierarchy and order of variant acquisition, and subsequently analyzed the evolution of somatic variants to infer clonal structure. From this, we postulate the development and extinction of subclones, as well as their anticorrelated expansion via varying drug responses. In particular, we show that new subclones started appearing after the first complete remission. The presence and absence of different subclones during remission and relapses implies differing drug responses among subclones. Our study shows that time series analysis contrasting remission and relapse periods provides a much more comprehensive view of clonal structure and evolution.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
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: 506–510.
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: 1090–1098.
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: 714–726.
Welch JS, Ley TJ, Link DC, Miller CA, Larson DE, Koboldt DC et al. The origin and evolution of mutations in acute myeloid leukemia. Cell 2012; 150: 264–278.
Parkin B, Ouillette P, Li Y, Keller J, Lam C, Roulston D et al. Clonal evolution and devolution after chemotherapy in adult acute myelogenous leukemia. Blood 2013; 121: 369–377.
Krönke J, Bullinger L, Teleanu V, Tschürtz F, Gaidzik VI, Kühn MWM et al. Clonal evolution in relapsed NPM1-mutated acute myeloid leukemia. Blood 2013; 122: 100–108.
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: 328–333.
Corces-Zimmerman MR, Hong W-J, Weissman IL, Medeiros BC, Majeti R . Preleukemic mutations in human acute myeloid leukemia affect epigenetic regulators and persist in remission. Proc Natl Acad Sci USA 2014; 111: 2548–2553.
Jan M, Snyder TM, Corces-Zimmerman MR, Vyas P, Weissman IL, Quake SR et al. Clonal evolution of preleukemic hematopoietic stem cells precedes human acute myeloid leukemia. Sci Transl Med 2012; 4: 149ra118–149ra118.
Nikolaev SI, Santoni F, Vannier A, Falconnet E, Giarin E, Basso G et al. Exome sequencing identifies putative drivers of progression of transient myeloproliferative disorder to AMKL in infants with Down syndrome. Blood 2013; 122: 554–561.
Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA, Kinzler KW . Cancer genome landscapes. Science 2013; 339: 1546–1558.
Roth A, Khattra J, Yap D, Wan A, Laks E, Biele J et al. PyClone: statistical inference of clonal population structure in cancer. Nat Methods 2014; 11: 396–398.
Jiao W, Vembu S, Deshwar AG, Stein L, Morris Q . Inferring clonal evolution of tumors from single nucleotide somatic mutations. BMC Bioinformatics 2014; 15: 35.
Deshwar AG, Vembu S, Yung CK, Jang GH, Stein L, Morris Q . PhyloWGS: reconstructing subclonal composition and evolution from whole-genome sequencing of tumors. Genome Biol 2015; 16: 35.
Löwenberg B, van Putten W, Theobald M, Gmür J, Verdonck L, Sonneveld P et al. Effect of priming with granulocyte colony-stimulating factor on the outcome of chemotherapy for acute myeloid leukemia. N Engl J Med 2003; 349: 743–752.
Huhmann IM, Watzke HH, Geissler K, Gisslinger H, Jäger U, Knöbl P et al. FLAG (fludarabine, cytosine arabinoside, G-CSF) for refractory and relapsed acute myeloid leukemia. Ann Hematol 1996; 73: 265–271.
Specchia G, Pastore D, Carluccio P, Liso A, Mestice A, Rizzi R et al. FLAG-IDA in the treatment of refractory/relapsed adult acute lymphoblastic leukemia. Ann Hematol 2005; 84: 792–795.
Lee J-H, Choi S-J, Lee J-H, Lee Y-S, Seol M, Ryu S-G et al. Continuous infusion intermediate-dose cytarabine, mitoxantrone, plus etoposide for refractory or early relapsed acute myelogenous leukemia. Leuk Res 2006; 30: 204–210.
Li H, Durbin R . Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 2010; 26: 589–595.
DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet 2011; 43: 491–498.
McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 2010; 20: 1297–1303.
Yoshida K, Sanada M, Shiraishi Y, Nowak D, Nagata Y, Yamamoto R et al. Frequent pathway mutations of splicing machinery in myelodysplasia. Nature 2011; 478: 64–69.
Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 2001; 29: 308–311.
Landrum MJ, Lee JM, Riley GR, Jang W, Rubinstein WS, Church DM et al. ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res 2014; 42: D980–D985.
Forbes SA, Bindal N, Bamford S, Cole C, Kok CY, Beare D et al. COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer. Nucleic Acids Res 2011; 39: D945–D950.
Sathirapongsasuti JF, Lee H, Horst BAJ, Brunner G, Cochran AJ, Binder S et al. Exome sequencing-based copy-number variation and loss of heterozygosity detection: ExomeCNV. Bioinformatics 2011; 27: 2648–2654.
Kim HS, Sung JS, Yang S-J, Kwon N-J, Jin L, Kim ST et al. Predictive efficacy of low burden EGFR mutation detected by next-generation sequencing on response to EGFR tyrosine kinase inhibitors in non-small-cell lung carcinoma. PLoS One 2013; 8: e81975.
Charrad M, Ghazzali N, Boiteau V, Niknafs A . Nbclust: an R package for determining the relevant number of clusters in a data set. J Stat Softw 2014; 61: 1–36.
Ward JH . Hierarchical grouping to optimize an objective function. J Am Stat Assoc 1963; 58: 236–244.
Cancer Genome Atlas Research Network. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med 2013; 368: 2059–2074.
Tartaglia M, Martinelli S, Iavarone I, Cazzaniga G, Spinelli M, Giarin E et al. Somatic PTPN11 mutations in childhood acute myeloid leukaemia. Br J Haematol 2005; 129: 333–339.
Sasaki M, Knobbe CB, Munger JC, Lind EF, Brenner D, Brüstle A et al. IDH1(R132H) mutation increases murine haematopoietic progenitors and alters epigenetics. Nature 2012; 488: 656–659.
Dunlap J, Beadling C, Warrick A, Neff T, Fleming WH, Loriaux M et al. Multiplex high-throughput gene mutation analysis in acute myeloid leukemia. Hum Pathol 2012; 43: 2167–2176.
Omholt K, Karsberg S, Platz A, Kanter L, Ringborg U, Hansson J . Screening of N-ras codon 61 mutations in paired primary and metastatic cutaneous melanomas: mutations occur early and persist throughout tumor progression. Clin Cancer Res 2002; 8: 3468–3474.
Havugimana PC, Hart GT, Nepusz T, Yang H, Turinsky AL, Li Z et al. A census of human soluble protein complexes. Cell 2012; 150: 1068–1081.
Will CL, Urlaub H, Achsel T, Gentzel M, Wilm M, Lührmann R . Characterization of novel SF3b and 17S U2 snRNP proteins, including a human Prp5p homologue and an SF3b DEAD-box protein. EMBO J 2002; 21: 4978–4988.
Das BK, Xia L, Palandjian L, Gozani O, Chyung Y, Reed R . Characterization of a protein complex containing spliceosomal proteins SAPs 49, 130, 145, and 155. Mol Cell Biol 1999; 19: 6796–6802.
Malcovati L, Papaemmanuil E, Bowen DT, Boultwood J, Porta Della MG, Pascutto C et al. Clinical significance of SF3B1 mutations in myelodysplastic syndromes and myelodysplastic/myeloproliferative neoplasms. Blood 2011; 118: 6239–6246.
Mayle A, Yang L, Rodriguez B, Zhou T, Chang E, Curry CV et al. Dnmt3a loss predisposes murine hematopoietic stem cells to malignant transformation. Blood 2015; 125: 629–638.
Rasmussen KD, Jia G, Johansen JV, Pedersen MT, Rapin N, Bagger FO et al. Loss of TET2 in hematopoietic cells leads to DNA hypermethylation of active enhancers and induction of leukemogenesis. Genes Dev 2015; 29: 910–922.
Bochtler T, Fröhling S, Krämer A . Role of chromosomal aberrations in clonal diversity and progression of acute myeloid leukemia. Leukemia 2015; 29: 1243–1252.
Grimwade D, Freeman SD . Defining minimal residual disease in acute myeloid leukemia: which platforms are ready for "prime time"? Blood 2014; 124: 3345–3355.
Acknowledgements
This study was supported by a grant from the National Project for Personalized Genomic Medicine, Ministry for Health & Welfare, Republic of Korea (A111218-11-GM06). This research was also supported by the Leading Foreign Research Institute Recruitment Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education, Science and Technology (MEST) (NRF-2011-0030034).
Author contributions
TK, KY, SO, GK, HK and DDK designed the study; YKK, HJP, SC, J-SA, S-HJ, D-HY, J-JL and HK collected samples and performed experiments; TK, MST, ZZ, HK and DDK analyzed data; TK, MST, ZZ, HK and DDK wrote the paper.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare no conflict of interest.
Additional information
Supplementary Information accompanies this paper on the Leukemia website
Supplementary information
Rights and permissions
About this article
Cite this article
Kim, T., Yoshida, K., Kim, Y. et al. Clonal dynamics in a single AML case tracked for 9 years reveals the complexity of leukemia progression. Leukemia 30, 295–302 (2016). https://doi.org/10.1038/leu.2015.264
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/leu.2015.264
This article is cited by
-
Allogeneic transplant can abrogate the risk of relapse in the patients of first remission acute myeloid leukemia with detectable measurable residual disease by next-generation sequencing
Bone Marrow Transplantation (2021)
-
RNA sequencing as an alternative tool for detecting measurable residual disease in core-binding factor acute myeloid leukemia
Scientific Reports (2020)
-
Single cell analysis of clonal architecture in acute myeloid leukaemia
Leukemia (2019)
-
Molecular and genetic alterations associated with therapy resistance and relapse of acute myeloid leukemia
Journal of Hematology & Oncology (2017)
-
The clonal origins of leukemic progression of myelodysplasia
Leukemia (2017)