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Acute myeloid leukemia

Clonal dominance is an adverse prognostic factor in acute myeloid leukemia treated with intensive chemotherapy

Abstract

Intra-tumor heterogeneity portends poor outcome in many cancers. In AML, a higher number of drivers worsens prognosis. The Shannon Index is a robust metric of clonal heterogeneity that accounts for the number of clones, but also their relative abundance. We show that a Shannon Index can be estimated from bulk sequencing, which is correlated (ρ = 0.76) with clonal diversity from single-colony genotyping. In a discovery cohort of 292 patients with sequencing of 43 genes, a higher number of drivers (HR = 1.18, P = 0.028) and a lower Shannon Index (HR = 0.68, P = 0.048), the latter reflecting clonal dominance, are independently associated with worse OS independently of European LeukemiaNet 2017 risk. These findings are validated in an independent cohort of 1184 patients with 111-gene sequencing (number of drivers HR = 1.16, P = 1 × 10−5, Shannon Index HR = 0.81, P = 0.007). By re-interrogating paired diagnosis/relapse exomes from 50 cytogenetically normal AMLs, we find clonal dominance at diagnosis to be correlated with the gain of a significantly higher number of mutations at relapse (P = 6 × 10−6), hence with clonal sweeping. Our results suggest that clonal dominance at diagnosis is associated with the presence of a leukemic phenotype allowing rapid expansion of new clones and driving relapse after chemotherapy.

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Fig. 1: Estimation of clonal dominance with Shannon Index from bulk targeted sequencing of AML samples.
Fig. 2: Prognostic impact of number of drivers and clonal diversity in the discovery cohort.
Fig. 3: Prognostic impact of clonal dominance in the validation cohort.
Fig. 4: Clonal evolution at relapse based on clonal dominance at diagnosis.

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References

  1. 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;374:2209–21.

    Article  CAS  Google Scholar 

  2. 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;150:264–78.

    Article  CAS  Google Scholar 

  3. Hirsch P, Zhang Y, Tang R, Joulin V, Boutroux H, Pronier E, et al. Genetic hierarchy and temporal variegation in the clonal history of acute myeloid leukaemia. Nat Commun. 2016;7:12475.

    Article  CAS  Google Scholar 

  4. Bochtler T, Stolzel F, Heilig CE, Kunz C, Mohr B, Jauch A, et al. Clonal heterogeneity as detected by metaphase karyotyping is an indicator of poor prognosis in acute myeloid leukemia. J Clin Oncol. 2013;31:3898–905.

    Article  Google Scholar 

  5. Maley CC, Galipeau PC, Finley JC, Wongsurawat VJ, Li X, Sanchez CA, et al. Genetic clonal diversity predicts progression to esophageal adenocarcinoma. Nat Genet. 2006;38:468–73.

    Article  CAS  Google Scholar 

  6. Andor N, Graham TA, Jansen M, Xia LC, Aktipis CA, Petritsch C, et al. Pan-cancer analysis of the extent and consequences of intratumor heterogeneity. Nat Med. 2016;22:105–13.

    Article  CAS  Google Scholar 

  7. Maley CC, Aktipis A, Graham TA, Sottoriva A, Boddy AM, Janiszewska M, et al. Classifying the evolutionary and ecological features of neoplasms. Nat Rev Cancer. 2017;17:605–19.

    Article  CAS  Google Scholar 

  8. Bertucci F, Ng CKY, Patsouris A, Droin N, Piscuoglio S, Carbuccia N, et al. Genomic characterization of metastatic breast cancers. Nature. 2019;569:560–4.

    Article  CAS  Google Scholar 

  9. Casasent AK, Schalck A, Gao R, Sei E, Long A, Pangburn W, et al. Multiclonal invasion in breast tumors identified by topographic single cell sequencing. Cell. 2018;172:205–17. e212.

    Article  CAS  Google Scholar 

  10. Marusyk A, Tabassum DP, Altrock PM, Almendro V, Michor F, Polyak K. Non-cell-autonomous driving of tumour growth supports sub-clonal heterogeneity. Nature. 2014;514:54–8.

    Article  CAS  Google Scholar 

  11. Metzeler KH, Herold T, Rothenberg-Thurley M, Amler S, Sauerland MC, Gorlich D, et al. Spectrum and prognostic relevance of driver gene mutations in acute myeloid leukemia. Blood. 2016;128:686–98.

    Article  CAS  Google Scholar 

  12. Wakita S, Yamaguchi H, Ueki T, Usuki K, Kurosawa S, Kobayashi Y, et al. Complex molecular genetic abnormalities involving three or more genetic mutations are important prognostic factors for acute myeloid leukemia. Leukemia. 2016;30:545–54.

    Article  CAS  Google Scholar 

  13. Milne TA. Mouse models of MLL leukemia: recapitulating the human disease. Blood. 2017;129:2217–23.

    Article  CAS  Google Scholar 

  14. Itzykson R, Duployez N, Fasan A, Decool G, Marceau-Renaut A, Meggendorfer M, et al. Clonal interference of signaling mutations worsens prognosis in core-binding factor acute myeloid leukemia. Blood. 2018;132:187–96.

    Article  CAS  Google Scholar 

  15. Dohner H, Estey E, Grimwade D, Amadori S, Appelbaum FR, Buchner T, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood. 2017;129:424–47.

    Article  Google Scholar 

  16. 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;49:332–40.

    Article  CAS  Google Scholar 

  17. Huet S, Paubelle E, Lours C, Grange B, Courtois L, Chabane K, et al. Validation of the prognostic value of the knowledge bank approach to determine AML prognosis in real life. Blood. 2018;132:865–7.

    Article  CAS  Google Scholar 

  18. Ferret Y, Boissel N, Helevaut N, Madic J, Nibourel O, Marceau-Renaut A, et al. Clinical relevance of IDH1/2 mutant allele burden during follow-up in acute myeloid leukemia. A study by the French ALFA group. Haematologica. 2018;103:822–9.

    CAS  PubMed  Google Scholar 

  19. Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc. 1999;94:496–509. 1999/06/01.

    Article  Google Scholar 

  20. O’brien RM. A caution regarding rules of thumb for variance inflation factors. Qual Quant. 2007;41:673–90.

    Article  Google Scholar 

  21. Dohner H, Estey EH, Amadori S, Appelbaum FR, Buchner T, Burnett AK, et al. Diagnosis and management of acute myeloid leukemia in adults: recommendations from an international expert panel, on behalf of the European LeukemiaNet. Blood. 2010;115:453–74.

    Article  Google Scholar 

  22. Hirsch CM, Nazha A, Kneen K, Abazeed ME, Meggendorfer M, Przychodzen BP, et al. Consequences of mutant TET2 on clonality and subclonal hierarchy. Leukemia. 2018;32:1751–61.

    Article  CAS  Google Scholar 

  23. 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;11:396–8.

    Article  CAS  Google Scholar 

  24. Greif PA, Hartmann L, Vosberg S, Stief SM, Mattes R, Hellmann I, et al. Evolution of cytogenetically normal acute myeloid leukemia during therapy and relapse: an exome sequencing study of 50 patients. Clin Cancer Res. 2018;24:1716–26.

    Article  CAS  Google Scholar 

  25. Shlush LI, Mitchell A, Heisler L, Abelson S, Ng SWK, Trotman-Grant A, et al. Tracing the origins of relapse in acute myeloid leukaemia to stem cells. Nature. 2017;547:104–8.

    Article  CAS  Google Scholar 

  26. TCGA TCGAC. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med. 2013;368:2059–74.

    Article  Google Scholar 

  27. Pellegrino M, Sciambi A, Treusch S, Durruthy-Durruthy R, Gokhale K, Jacob J, et al. High-throughput single-cell DNA sequencing of acute myeloid leukemia tumors with droplet microfluidics. Genome Res. 2018;28:1345–52.

    Article  CAS  Google Scholar 

  28. Schlenk RF, Kayser S, Bullinger L, Kobbe G, Casper J, Ringhoffer M, et al. Differential impact of allelic ratio and insertion site in FLT3-ITD-positive AML with respect to allogeneic transplantation. Blood. 2014;124:3441–9.

    Article  CAS  Google Scholar 

  29. Prassek VV, Rothenberg-Thurley M, Sauerland MC, Herold T, Janke H, Ksienzyk B, et al. Genetics of acute myeloid leukemia in the elderly: mutation spectrum and clinical impact in intensively treated patients aged 75 years or older. Haematologica. 2018;103:1853–61.

    Article  CAS  Google Scholar 

  30. Paguirigan AL, Smith J, Meshinchi S, Carroll M, Maley C, Radich JP. Single-cell genotyping demonstrates complex clonal diversity in acute myeloid leukemia. Sci Transl Med. 2015;7:281re282.

    Article  Google Scholar 

  31. Quek L, David MD, Kennedy A, Metzner M, Amatangelo M, Shih A, et al. Clonal heterogeneity of acute myeloid leukemia treated with the IDH2 inhibitor enasidenib. Nat Med. 2018; 24:1167–77.

    Article  CAS  Google Scholar 

  32. Smith CC, Paguirigan A, Jeschke GR, Lin KC, Massi E, Tarver T, et al. Heterogeneous resistance to quizartinib in acute myeloid leukemia revealed by single-cell analysis. Blood. 2017;130:48–58.

    Article  CAS  Google Scholar 

  33. Potter N, Miraki-Moud F, Ermini L, Titley I, Vijayaraghavan G, Papaemmanuil E, et al. Single cell analysis of clonal architecture in acute myeloid leukaemia. Leukemia. 2019;33:1113–23.

    Article  CAS  Google Scholar 

  34. McMahon CM, Ferng T, Canaani J, Wang ES, Morrissette JJD, Eastburn DJ, et al. Clonal selection with RAS pathway activation mediates secondary clinical resistance to selective FLT3 inhibition in acute myeloid leukemia. Cancer Discov. 2019;9:1050–63.

    Article  CAS  Google Scholar 

  35. Turajlic S, Xu H, Litchfield K, Rowan A, Chambers T, Lopez JI, et al. Tracking cancer evolution reveals constrained routes to metastases: TRACERx Renal. Cell. 2018;173:581–94. e512.

    Article  CAS  Google Scholar 

  36. Lee JK, Wang J, Sa JK, Ladewig E, Lee HO, Lee IH, et al. Spatiotemporal genomic architecture informs precision oncology in glioblastoma. Nat Genet. 2017;49:594–9.

    Article  CAS  Google Scholar 

  37. Palm MM, Elemans M, Beltman JB. Heritable tumor cell division rate heterogeneity induces clonal dominance. PLoS Comput Biol. 2018;14:e1005954.

    Article  Google Scholar 

  38. Nagata Y, Makishima H, Kerr CM, Przychodzen BP, Aly M, Goyal A, et al. Invariant patterns of clonal succession determine specific clinical features of myelodysplastic syndromes. Nat Commun. 2019;10:5386.

    Article  Google Scholar 

  39. Baldow C, Thielecke L, Glauche I. Model based analysis of clonal developments allows for early detection of monoclonal conversion and leukemia. PLoS ONE. 2016;11:e0165129.

    Article  Google Scholar 

Download references

Acknowledgements

We are indebted to the Institut de Recherche Saint-Louis Core Facility (Niclas Setterblad, Antonio Alberdi, Simon Tournier), Emilie Gaudas, Kelly Vanoukia, Esther Dubo, Kaddour Chabane, Carole Charlot and Christine Lespinasse for help with sequencing. RI is supported by grants from Association Laurette Fugain, Association Princesse Margot, Association pour la Recherche contre le Cancer, Fondation Leucémie Espoir, and Ligue Contre le Cancer.

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MC and RI designed the study, assembled and analyzed the data and drafted the paper. PS, EC and RI supervised the study. MD performed the bioinformatic analyses. RK, MP, SQ, JP, JS, EC, and PS performed genotyping of the discovery cohort. LV, XT, FR, RR, EL, ER, ND, MS, OM, AR, KCL, LA, PF, NB, and HD provided clinical data for the discovery cohort. PH and FD performed single-colony genotyping. All authors revised the paper and accepted its final version.

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Correspondence to Raphael Itzykson.

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Cerrano, M., Duchmann, M., Kim, R. et al. Clonal dominance is an adverse prognostic factor in acute myeloid leukemia treated with intensive chemotherapy. Leukemia 35, 712–723 (2021). https://doi.org/10.1038/s41375-020-0932-8

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