Page 68 - 2021_12-Haematologica-web

C. Sargas et al.
weeks), ii) need to promote larger participation of PETHE- MA clinical sites, as a sizable proportion of patients are not yet benefiting from advanced laboratory centralization (especially in the relapse/refractory setting), and ii) budget- ary vulnerability.
In conclusion, the PETHEMA cooperative scientific group has adopted the reported nationwide strategy network with centralized NGS analyses. Sample and information exchange allowed us to unify analysis criteria and decrease reporting variability in order to offer reliable and consistent NGS results. This cooperative strategy has also been applied to rapid screening by conventional PCR and quan- titive real-time PCR to measure residual disease, and is being expanded to other AML diagnostic areas (e.g., biobanking and multiparametric flow cytometry). Ongoing therapeutic guidelines (NCT01296178) and clinical trials (clinicaltrials gov. Identifier: NCT04230239, NCT04107727, NCT04112589, NCT04090736) by the PETHEMA group are benefiting from this diagnostic network.
Disclosures
No conflicts of interest to disclose.
Contributions
EB and PM conceived the study; CS, EB and PM analyzed, interpreted the data and wrote the paper; CS performed the statis-
tical analyses; CS, RA, CC, MJL, EC, CB, MYR, MLL, IR, RGS, IVU, ES, YFO, KJ, CB, JS, DMC, JB, MA, PMS, MT, TB, PHP, RG, LA, MJS, LCB, EPS, IM, ELR, VN, JMA, MAS, JSG, MTGC, JAPS, MJC, MG, JML, EB and PM included data of patients treated in their institutions, reviewed the manuscript and contributed to the final draft.
Acknowledgments
The authors would like to thank María D. García, Carlos Pastorini, Rafael Vianney, and Mar Benlloch for data collection and management; and Data Science, Biostatistics and Bioinformatics Unit from IIS La Fe for its collaboration in statistical analysis.
Funding
This work was partially supported by a Celgene grant, the Subdirección General de Investigación Sanitaria (Instituto de Salud Carlos III, Spain) Spanish Ministry of Economy and Competitiveness: PI15/01706, PI16/00517 PI16/0665, PI16/01530, PI18/01340, PI18/01946 PI19/00730, PI19/01518, FI19/00059, Fundación Española de Hematología y Hemoterapia (FEHH) grant, CRIS against Cancer foundation 2018/001. CIBERONC-CB16/12/00233 and “Una manera de hacer Europa” (Innocampus; CEI-2010-1-0010), Instituto de Investigación Sanitaria La Fe (Contrato de Investigación postresi- dentes 2019-052-1)
References
1. Saultz J, Garzon R. Acute myeloid leukemia: a concise review. J Clin Med. 2016;5(3):33.
2. Arber DA, Orazi A, Hasserjian R, et al. The 2016 revision to the World Health Organization classification of myeloid neo- plasms and acute leukemia. Blood. 2016;127(20):2391-2405.
3. Döhner H, Estey E, Grimwade D, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood. 2017;129(4):424-447.
4. Hackl H, Astanina K, Wieser R. Molecular and genetic alterations associated with therapy resistance and relapse of acute myeloid leukemia. J Hematol Oncol. 2017;10(1):51.
5. Luppi M, Fabbiano F, Visani G, Martinelli G, Venditti A. Novel agents for acute myeloid leukemia. Cancers (Basel). 2018;10(11):429.
6. Riva L, Luzi L, Pelicci PG. Genomics of acute myeloid leukemia: the next genera- tion. Front Oncol. 2012;2:40.
7. Kuo FC, Mar BG, Lindsley RC, Lindeman NI. The relative utilities of genome-wide, gene panel, and individual gene sequencing in clinical practice. Blood. 2017;130(4):433- 439.
8. Bacher U, Shumilov E, Flach J, et al. Challenges in the introduction of next-gen- eration sequencing (NGS) for diagnostics of myeloid malignancies into clinical routine use. Blood Cancer J. 2018;8(11):113.
9. Macklin PS, Pillay N, Lee JL, et al. CM-Path Molecular Diagnostics Forum—consensus statement on the development and imple- mentation of molecular diagnostic tests in the United Kingdom. Br J Cancer. 2019; 121(9):738-743.
10. Ley TJ, Miller C, Ding L, et al. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med.
2013;368(22):2059-2074.
11. Tyner JW, Tognon CE, Bottomly D, et al.
Functional genomic landscape of acute myeloid leukaemia. Nature. 2018;562(7728):526-531.
12. Papaemmanuil E, Gerstung M, Bullinger L, et al. Genomic classification and prognosis in acute myeloid leukemia. N Engl J Med. 2016;374(23):2209-2221.
13. Castelli G, Pelosi E, Testa U. Targeted ther- apies in the treatment of adult acute myeloid leukemias: current status and future perspectives. Int J Hematol Oncol. 2016;5(4):143-164.
14. Gelsi-Boyer V, Brecqueville M, Devillier R, Murati A, Mozziconacci MJ, Birnbaum D. Mutations in ASXL1 are associated with poor prognosis across the spectrum of malignant myeloid diseases. J Hematol Oncol. 2012;5:12.
15. Kohlmann A, Nadarajah N, Alpermann T, et al. Monitoring of residual disease by next-generation deep-sequencing of RUNX1 mutations can identify acute myeloid leukemia patients with resistant disease. Leukemia. 2014;28(1):129-137.
16. Barbosa K, Li S, Adams PD, Deshpande AJ. The role of TP53 in acute myeloid leukemia: challenges and opportunities. Genes Chromosomes Cancer. 2019;58(12): 875-888.
17.Dinardo CD, Ravandi F, Agresta S, et al. Characteristics, clinical outcome, and prog- nostic significance of IDH mutations in AML. Am J Hematol. 2015;90(8):732-736.
18. Medeiros BC, Fathi AT, DiNardo CD, Pollyea DA, Chan SM, Swords R. Isocitrate dehydrogenase mutations in myeloid malignancies. Leukemia. 2017;31(2):272- 281.
19. Prassek VV, Rothenberg-Thurley M, Sauerland MC, 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(11):1853-1861.
20. Metzeler KH, Herold T, Rothenberg- Thurley M, et al. Spectrum and prognostic relevance of driver gene mutations in acute myeloid leukemia. Blood. 2016;128(5):686- 698.
21. Schneider F, Hoster E, Schneider S, et al. Age-dependent frequencies of NPM1 muta- tions and FLT3-ITD in patients with normal karyotype AML (NK-AML). Ann Hematol. 2012;91(1):9-18.
22. Daver N, Schlenk RF, Russell NH, Levis MJ. Targeting FLT3 mutations in AML: review of current knowledge and evidence. Leukemia. 2019;33(2):299-312.
23. Liu X, Gong Y. Isocitrate dehydrogenase inhibitors in acute myeloid leukemia. Biomark Res. 2019;7(1):22.
24.Williams AB, Nguyen B, Li L, et al. Mutations of FLT3/ITD confer resistance to multiple tyrosine kinase inhibitors. Leukemia. 2013;27(1):48-55.
25. Heidel F, Solem FK, Breitenbuecher F, et al. Clinical resistance to the kinase inhibitor PKC412 in acute myeloid leukemia by mutation of Asn-676 in the FLT3 tyrosine kinase domain. Blood. 2006;107(1):293- 300.
26. Liu SB, Dong HJ, Bao XB, et al. Impact of FLT3-ITD length on prognosis of acute myeloid leukemia. Haematologica. 2019; 104(1):e9-e12.
27.Hirsch P, Zhang Y, Tang R, et al. Genetic hierarchy and temporal variegation in the clonal history of acute myeloid leukaemia. Nat Commun. 2016;7(1):1-13.
28. Martignoles JA, Delhommeau F, Hirsch P. Genetic hierarchy of acute myeloid leukemia: from clonal hematopoiesis to molecular residual disease. Int J Mol Sci. 2018;19(12):3850.
29. Goel S, Hall J, Pradhan K, et al. High preva- lence and allele burden-independent prog- nostic importance of p53 mutations in an inner-city MDS/AML cohort. Leukemia. 2016;30(8):1793-1795.
30. Rücker FG, Schlenk RF, Bullinger L, et al.
3088
haematologica | 2021; 106(12)