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Myelodysplastic syndrome

Prognostic significance of serial molecular annotation in myelodysplastic syndromes (MDS) and secondary acute myeloid leukemia (sAML)

Leukemia volume 35, pages 1145–1155 (2021)Cite this article

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Abstract

The implementation of next-generation sequencing (NGS) has influenced diagnostic, prognostic, and therapeutic decisions in myeloid malignancies. However, the clinical relevance of serial molecular annotation in patients with myelodysplastic syndrome (MDS) undergoing active treatment is unknown. MDS or secondary acute myeloid leukemia (sAML) patients who had at least two NGS assessments were identified. Outcomes according to mutation clearance (NGS-) on serial assessment were investigated. Univariate and multivariate Cox regression models were used to evaluate the prognostic impact of NGS trajectory on overall survival (OS). A total of 157 patients (MDS [n = 95]; sAML [n = 52]; CMML [n = 10]) were identified, with 93% of patients receiving treatment between NGS assessments. Magnitude of VAF delta from baseline was significantly associated with quality of response to treatment. Patients achieving NGS- had significantly improved OS compared to patients with mutation persistence (median OS not reached vs. 18.5 months; P = 0.002), which was confirmed in multivariate analysis (HR,0.14; 95%CI = 0.03–0.56; P = 0.0064). Serial TP53 VAF evaluation predicts outcomes with TP53 clearance representing an independent covariate for superior OS (HR,0.22; 95%CI = 0.05–0.99; P = 0.048). Collectively, our study highlights the clinical value of serial NGS during treatment and warrants prospective validation of NGS negativity as a biomarker for treatment outcome.

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Fig. 1: Dynamics of VAF changes of dominant clone before and after treatment.
Fig. 2: Mutational spectrum in patients who achieved NGS negativity on serial analyses.
Fig. 3: Prognostic impact of serial NGS results on overall survival.
Fig. 4: Prognostic impact of TP53 VAF changes on overall survival.

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References

  1. Tefferi A, Vardiman JW. Myelodysplastic syndromes. N Engl J Med. 2009;361:1872–85.

    Article  CAS  Google Scholar 

  2. Löwenberg B, Downing JR, Burnett A. Acute myeloid leukemia. N Engl J Med. 1999;341:1051–62.

    Article  Google Scholar 

  3. Kayser S, Döhner K, Krauter J, Köhne CH, Horst HA, Held G, et al. The impact of therapy-related acute myeloid leukemia (AML) on outcome in 2853 adult patients with newly diagnosed AML. Blood. 2011;117:2137–45.

    Article  CAS  Google Scholar 

  4. Hulegårdh E, Nilsson C, Lazarevic V, Garelius H, Antunovic P, Rangert Derolf Å, et al. Characterization and prognostic features of secondary acute myeloid leukemia in a population-based setting: a report from the Swedish Acute Leukemia Registry. Am J Hematol. 2015;90:208–14.

    Article  Google Scholar 

  5. Renaud L, Nibourel O, Berthon C, Roumier C, Rodriguez C, Frimat C, et al. De Novo and secondary acute myeloid leukemia, real world data on outcomes from the french nord-pas-de-calais picardie acute myeloid leukemia observatory. Blood. 2016;128:4013.

    Article  Google Scholar 

  6. Döhner H, Estey E, Grimwade D, Amadori S, Appelbaum FR, Büchner 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 

  7. 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;364:2496–506.

    Article  CAS  Google Scholar 

  8. 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;122:3616–27. quiz 3699.

    Article  CAS  Google Scholar 

  9. 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 

  10. Bally C, Ades L, Renneville A, Sebert M, Eclache V, Preudhomme C, et al. Prognostic value of TP53 gene mutations in myelodysplastic syndromes and acute myeloid leukemia treated with azacitidine. Leuk Res. 2014;38:751–5.

    Article  CAS  Google Scholar 

  11. Bejar R, Lord A, Stevenson K, Bar-Natan M, Perez-Ladaga A, Zaneveld J, et al. TET2 mutations predict response to hypomethylating agents in myelodysplastic syndrome patients. Blood. 2014;124:2705–12.

    Article  CAS  Google Scholar 

  12. Bejar R, Stevenson KE, Caughey B, Lindsley RC, Mar BG, Stojanov P, et al. Somatic mutations predict poor outcome in patients with myelodysplastic syndrome after hematopoietic stem-cell transplantation. J Clin Oncol. 2014;32:2691–8.

    Article  Google Scholar 

  13. Della Porta MG, Galli A, Bacigalupo A, Zibellini S, Bernardi M, Rizzo E, et al. Clinical effects of driver somatic mutations on the outcomes of patients with myelodysplastic syndromes treated with allogeneic hematopoietic stem-cell transplantation. J Clin Oncol. 2016;34:3627–37.

    Article  Google Scholar 

  14. Lindsley RC, Saber W, Mar BG, Redd R, Wang T, Haagenson MD, et al. Prognostic mutations in myelodysplastic syndrome after stem-cell transplantation. N Engl J Med. 2017;376:536–47.

    Article  CAS  Google Scholar 

  15. Yoshizato T, Nannya Y, Atsuta Y, Shiozawa Y, Iijima-Yamashita Y, Yoshida K, et al. Genetic abnormalities in myelodysplasia and secondary acute myeloid leukemia: impact on outcome of stem cell transplantation. Blood. 2017;129:2347–58.

    Article  CAS  Google Scholar 

  16. Takahashi K, Patel K, Bueso-Ramos C, Zhang J, Gumbs C, Jabbour E, et al. Clinical implications of TP53 mutations in myelodysplastic syndromes treated with hypomethylating agents. Oncotarget. 2016;7:14172–87.

    Article  Google Scholar 

  17. Sallman DA, Komrokji R, Vaupel C, Cluzeau T, Geyer SM, McGraw KL, et al. Impact of TP53 mutation variant allele frequency on phenotype and outcomes in myelodysplastic syndromes. Leukemia. 2016;30:666–73.

    Article  CAS  Google Scholar 

  18. Bejar R, Papaemmanuil E, Haferlach T, Garcia-Manero G, Maciejewski JP, Sekeres MA, et al. TP53 mutation status divides MDS patients with complex karyotypes into distinct prognostic risk groups: analysis of combined datasets from the international working group for MDS-molecular prognosis committee. Blood. 2014;124:532.

    Article  Google Scholar 

  19. Belickova M, Vesela J, Jonasova A, Pejsova B, Votavova H, Merkerova MD, et al. TP53 mutation variant allele frequency is a potential predictor for clinical outcome of patients with lower-risk myelodysplastic syndromes. Oncotarget. 2016;7:36266–79.

    Article  Google Scholar 

  20. Makishima H, Yoshizato T, Yoshida K, Sekeres MA, Radivoyevitch T, Suzuki H, et al. Dynamics of clonal evolution in myelodysplastic syndromes. Nat Genet. 2017;49:204–12.

    Article  CAS  Google Scholar 

  21. da Silva-Coelho P, Kroeze LI, Yoshida K, Koorenhof-Scheele TN, Knops R, van de Locht LT, et al. Clonal evolution myelodysplastic syndromes. Nat Commun. 2017;8:15099.

    Article  Google Scholar 

  22. Uy GL, Duncavage EJ, Chang GS, Jacoby MA, Miller CA, Shao J, et al. Dynamic changes in the clonal structure of MDS and AML in response to epigenetic therapy. Leukemia. 2017;31:872–81.

    Article  CAS  Google Scholar 

  23. Mossner M, Jann J-C, 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;128:1246–59.

    Article  CAS  Google Scholar 

  24. Pellagatti A, Roy S, Di Genua C, Burns A, McGraw K, Valletta S, et al. Targeted resequencing analysis of 31 genes commonly mutated in myeloid disorders in serial samples from myelodysplastic syndrome patients showing disease progression. Leukemia. 2016;30:247–50.

    Article  CAS  Google Scholar 

  25. Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016;127:2391–405.

    Article  CAS  Google Scholar 

  26. Cheson BD, Bennett JM, Kantarjian H, Pinto A, Schiffer CA, Nimer SD, et al. Report of an international working group to standardize response criteria for myelodysplastic syndromes. Blood. 2000;96:3671–4.

    CAS  PubMed  Google Scholar 

  27. Greenberg PL, Tuechler H, Schanz J, Sanz G, Garcia-Manero G, Solé F, et al. Revised international prognostic scoring system for myelodysplastic syndromes. Blood. 2012;120:2454–65.

    Article  CAS  Google Scholar 

  28. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17:405–23.

    Article  Google Scholar 

  29. Komrokji RS, DeZern AE, Zell K, Al Ali NH, Estling C, Zimmerman C, et al. Validation of International Working Group (IWG) Response Criteria in Higher-Risk Myelodysplastic Syndromes (MDS): A Report on Behalf of the MDS Clinical Research Consortium (MDS CRC). Blood. 2015;126:909.

    Article  Google Scholar 

  30. Duncavage EJ, Jacoby MA, Chang GS, Miller CA, Edwin N, Shao J. et al. Mutation Clearance after Transplantation for Myelodysplastic Syndrome. N Engl J Med. 2018;379:1028–41.

    Article  CAS  Google Scholar 

  31. Ganzel C, Sun Z, Gonen M, Patel JP, Abdel-Wahab O, Fernandez HF, et al. Minimal residual disease assessment by flow cytometry in AML Is an independant prognostic factor even after adjusting for cytogenetic/molecular abnormalities. Blood. 2014;124:1016.

    Article  Google Scholar 

  32. Minetto P, Guolo F, Clavio M, Kunkl A, Ballerini F, Colombo N, et al. Minimal residual disease assessment may drive post remission therapy in acute myeloid leukemia. It’s time for MRD-driven therapy. Blood. 2016;128:2895.

    Article  Google Scholar 

  33. Sebert M, Vidal V, Eclache V, Thepot S, Braun T, Gardin C, et al. Impact cytogenetics cytogenetic response outcome MDS treat azacitidine (AZA). Blood. 2012;120:2807.

    Article  Google Scholar 

  34. Ivey A, Hills RK, Simpson MA, Jovanovic JV, Gilkes A, Grech A, et al. Assessment of minimal residual disease in standard-risk AML. N. Engl J Med. 2016;374:422–33.

    Article  CAS  Google Scholar 

  35. Balsat M, Renneville A, Thomas X, de Botton S, Caillot D, Marceau A, et al. Postinduction minimal residual disease predicts outcome and benefit from allogeneic stem cell transplantation in acute myeloid leukemia with npm1 mutation: a study by the acute leukemia french association group. J Clin Oncol. 2017;35:185–93.

    Article  CAS  Google Scholar 

  36. Freeman SD, Hills RK, Virgo P, Khan N, Couzens S, Dillon R, et al. Measurable residual disease at induction redefines partial response in acute myeloid leukemia and stratifies outcomes in patients at standard risk without NPM1 mutations. J Clin Oncol. 2018;36:1486–97.

    Article  CAS  Google Scholar 

  37. 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;378:1189–99.

    Article  CAS  Google Scholar 

  38. 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;36:1788–97.

    Article  CAS  Google Scholar 

  39. Welch JS, Petti AA, Miller CA, Fronick CC, O’Laughlin M, Fulton RS, et al. TP53 and decitabine in acute myeloid leukemia and myelodysplastic syndromes. N Engl J Med. 2016;375:2023–36.

    Article  CAS  Google Scholar 

  40. Sallman DA, DeZern AE, Garcia-Manero G, Steensma DP, Roboz GJ, et al. Phase 1b/2 combination study of APR-246 and azacitidine (AZA) in patients with TP53 mutant myelodysplastic syndromes (MDS) and acute myeloid. Leuk (AML). Blood. 2019;132(Suppl 1):676.

    Google Scholar 

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Acknowledgements

This work was supported in part by a research grant from the Graduate Medical Education (GME) at the University of South Florida (SY), Research Training Award for Fellow (RTAF) from the American Society of Hematology (SY), Scholar Award from the American Society of Hematology (SY), NIH grant K08 CA237627 (SY), MDS Foundation Young Investigator Grant (DAS), Early Career Award of the Dresner Foundation (DAS), and Edward P. Evans Foundation Award (DAS).

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Authors and Affiliations

  1. Malignant Hematology Department, H. Lee Moffitt Cancer Center, Tampa, FL, USA

    Seongseok Yun, Rami S. Komrokji, Najla H. Al Ali, Kendra L. Sweet, Jeffrey E. Lancet, Alan F. List, Eric Padron & David A. Sallman

  2. Health Informatics Institute, University of South Florida, Tampa, FL, USA

    Susan M. Geyer

  3. Hematopathology and Laboratory Medicine Department, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA

    Jinming Song & Mohammad Hussaini

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Contributions

Conception and design: SY, DAS. Collection and assembly of data: SY, NHA, MH, KS, JL, JH, AL, EP, RK, DAS. Data analysis and interpretation: SY, SMG, JS, CV, DAS. Manuscript writing: SY, NHA, MH, KS, SMG, JL, JH, AL, EP, RK, DAS.

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Correspondence to David A. Sallman.

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Yun, S., Geyer, S.M., Komrokji, R.S. et al. Prognostic significance of serial molecular annotation in myelodysplastic syndromes (MDS) and secondary acute myeloid leukemia (sAML). Leukemia 35, 1145–1155 (2021). https://doi.org/10.1038/s41375-020-0997-4

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