Targeted molecular characterization shows differences between primary and secondary myelofibrosis.
clinical parameters
genomic markers
next generation sequencing
primary and secondary myelofibrosis
prognosis impact
Journal
Genes, chromosomes & cancer
ISSN: 1098-2264
Titre abrégé: Genes Chromosomes Cancer
Pays: United States
ID NLM: 9007329
Informations de publication
Date de publication:
Jan 2020
Jan 2020
Historique:
revised:
07
06
2019
received:
28
01
2019
accepted:
13
06
2019
pubmed:
25
7
2019
medline:
25
7
2019
entrez:
25
7
2019
Statut:
ppublish
Résumé
In BCR-ABL1-negative myeloproliferative neoplasms, myelofibrosis (MF) is either primary (PMF) or secondary (SMF) to polycythemia vera or essential thrombocythemia. MF is characterized by an increased risk of transformation to acute myeloid leukemia (AML) and a shortened life expectancy. Because natural histories of PMF and SMF are different, we studied by targeted next generation sequencing the differences in the molecular landscape of 86 PMF and 59 SMF and compared their prognosis impact. PMF had more ASXL1 (47.7%) and SRSF2 (14%) gene mutations than SMF (respectively 27.1% and 3.4%, P = .04). Poorer survival was associated with RNA splicing mutations (especially SRSF2) and TP53 in PMF (P = .0003), and with ASXL1 and TP53 mutations in SMF (P < .0001). These mutations of poor prognosis were associated with biological features of scoring systems (DIPSS and MYSEC-PM score). Mutations in TP53/SRSF2 in PMF or TP53/ASXL1 in SMF were more frequent as the risk of these scores increased. This allowed for a better stratification of MF patients, especially within the DIPSS intermediate-1 risk group (DIPSS) or the MYSEC-PM high risk group. AML transformation occurred faster in SMF than in PMF and patients who transformed to AML were more SRSF2-mutated and less CALR-mutated at MF sampling. PMF and SMF have different but not specific molecular profiles and different prognosis depending on the molecular profile. This may be due to differences in disease history. Combining mutations and existing scores should improve prognosis assessment.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
30-39Subventions
Organisme : French Cancer Institute
ID : INCa BCB 2013
Organisme : Association Laurette Fugain
ID : LF 2013/05
Organisme : Inserm, Institut Paoli-Calmettes
Informations de copyright
© 2019 Wiley Periodicals, Inc.
Références
Tefferi A, Pardanani A. Myeloproliferative neoplasms: a contemporary review. JAMA Oncol. 2015;1(1):97-105.
Tefferi A, Mudireddy M, Mannelli F, et al. Blast phase myeloproliferative neoplasm: Mayo-AGIMM study of 410 patients from two separate cohorts. Leukemia. 2018;32(5):1200-1210.
Cervantes F, Dupriez B, Pereira A, et al. New prognostic scoring system for primary myelofibrosis based on a study of the international working Group for Myelofibrosis Research and Treatment. Blood. 2009;113(13):2895-2901.
Passamonti F, Cervantes F, Vannucchi AM, et al. Dynamic international prognostic scoring system (DIPSS) predicts progression to acute myeloid leukemia in primary myelofibrosis. Blood. 2010;116(15):2857-2858.
Gangat N, Caramazza D, Vaidya R, et al. DIPSS plus: a refined dynamic international prognostic scoring system for primary myelofibrosis that incorporates prognostic information from karyotype, platelet count, and transfusion status. J Clin Oncol off J Am Soc Clin Oncol. 2011;29(4):392-397.
Beauverd Y, Alimam S, McLornan DP, Radia DH, Harrison CN. Disease characteristics and outcomes in younger adults with primary and secondary myelofibrosis. Br J Haematol. 2016;175(1):37-42.
Tefferi A, Lasho TL, Finke CM, et al. Targeted deep sequencing in primary myelofibrosis. Blood Adv. 2016;1(2):105-111.
Vannucchi AM, Lasho TL, Guglielmelli P, et al. Mutations and prognosis in primary myelofibrosis. Leukemia. 2013;27(9):1861-1869.
Guglielmelli P, Lasho TL, Rotunno G, et al. MIPSS70: mutation-enhanced international prognostic score system for transplantation-age patients with primary myelofibrosis. J Clin Oncol. 2017;76:4886.
Tefferi A, Guglielmelli P, Nicolosi M, et al. GIPSS: genetically inspired prognostic scoring system for primary myelofibrosis. Leukemia. 2018;32(7):1631-1642.
Rotunno G, Pacilli A, Artusi V, et al. Epidemiology and clinical relevance of mutations in postpolycythemia vera and postessential thrombocythemia myelofibrosis: a study on 359 patients of the AGIMM group. Am J Hematol. 2016;91(7):681-686.
Tefferi A, Lasho TL, Finke CM, et al. CALR vs JAK2 vs MPL-mutated or triple-negative myelofibrosis: clinical, cytogenetic and molecular comparisons. Leukemia. 2014;28(7):1472-1477.
Passamonti F, Mora B, Giorgino T, et al. Driver mutations' effect in secondary myelofibrosis: an international multicenter study based on 781 patients. Leukemia. 2017;31(4):970-973.
Passamonti F, Giorgino T, Mora B, et al. A clinical-molecular prognostic model to predict survival in patients with post polycythemia vera and post essential thrombocythemia myelofibrosis. Leukemia. 2017;31(12):2726-2731.
Tefferi A, Thiele J, Vardiman JW. The 2008 World Health Organization classification system for myeloproliferative neoplasms: order out of chaos. Cancer. 2009;115(17):3842-3847.
Bertucci F, Finetti P, Guille A, et al. Comparative genomic analysis of primary tumors and metastases in breast cancer. Oncotarget. 2016;7(19):27208-27219.
Brecqueville M, Rey J, Devillier R, et al. Array comparative genomic hybridization and sequencing of 23 genes in 80 patients with myelofibrosis at chronic or acute phase. Haematologica. 2014;99(1):37-45.
Agarwal R, Blombery P, McBean M, et al. Clinicopathological differences exist between CALR and JAK2 mutated myeloproliferative neoplasms despite a similar molecular landscape: data from targeted next-generation sequencing in the diagnostic laboratory. Ann Hematol. 2017;96(5):725-732.
Delic S, Rose D, Kern W, et al. Application of an NGS-based 28-gene panel in myeloproliferative neoplasms reveals distinct mutation patterns in essential thrombocythaemia, primary myelofibrosis and polycythaemia vera. Br J Haematol. 2016;175(3):419-426.
Gill H, Ip H-W, Yim R, et al. Next-generation sequencing with a 54-gene panel identified unique mutational profile and prognostic markers in Chinese patients with myelofibrosis. Ann Hematol. 2019;98(4):869-879.
Li B, Gale RP, Xu Z, et al. Non-driver mutations in myeloproliferative neoplasm-associated myelofibrosis. J Hematol Oncol. 2017;10(1):99.
Lundberg P, Karow A, Nienhold R, et al. Clonal evolution and clinical correlates of somatic mutations in myeloproliferative neoplasms. Blood. 2014;123(14):2220-2228.
Patel KP, Newberry KJ, Luthra R, et al. Correlation of mutation profile and response in patients with myelofibrosis treated with ruxolitinib. Blood. 2015;126(6):790-797.
Tenedini E, Bernardis I, Artusi V, et al. Targeted cancer exome sequencing reveals recurrent mutations in myeloproliferative neoplasms. Leukemia. 2014;28(5):1052-1059.
Heuser M, Thol F, Ganser A. Clonal Hematopoiesis of indeterminate potential. Dtsch Ärztebl Int. 2016;113(18):317-322.
Rampal R, Ahn J, Abdel-Wahab O, et al. Genomic and functional analysis of leukemic transformation of myeloproliferative neoplasms. Proc Natl Acad Sci. 2014;111(50):E5401-E5410.
Courtier F, Carbuccia N, Garnier S, et al. Genomic analysis of myeloproliferative neoplasms in chronic and acute phases. Haematologica. 2017;102(1):e11-e14.
Venton G, Courtier F, Charbonnier A, et al. Impact of gene mutations on treatment response and prognosis of acute myeloid leukemia secondary to myeloproliferative neoplasms. Am J Hematol. 2018;93(3):330-338.
Masarova L, Bose P, Daver N, et al. Patients with post-essential thrombocythemia and post-polycythemia vera differ from patients with primary myelofibrosis. Leuk Res. 2017;59:110-116.
Mangaonkar AA, Gangat N, Al-Kali A, et al. Prognostic impact of ASXL1 mutations in patients with myelodysplastic syndromes and multilineage dysplasia with or without ring sideroblasts. Leuk Res. 2018;71:60-62.
Chou W-C, Huang H-H, Hou H-A, et al. Distinct clinical and biological features of de novo acute myeloid leukemia with additional sex comb-like 1 (ASXL1) mutations. Blood. 2010;116(20):4086-4094.
Barbui T, Barosi G, Birgegard G, et al. Philadelphia-negative classical Myeloproliferative neoplasms: critical concepts and management recommendations from European LeukemiaNet. J Clin Oncol. 2011;29(6):761-770.
Amatangelo MD, Quek L, Shih A, et al. Enasidenib induces acute myeloid leukemia cell differentiation to promote clinical response. Blood. 2017;130(6):732-741.
Fiskus W, Wang Y, Sreekumar A, et al. Combined epigenetic therapy with the histone methyltransferase EZH2 inhibitor 3-deazaneplanocin a and the histone deacetylase inhibitor panobinostat against human AML cells. Blood. 2009;114(13):2733-2743.
Lee SC-W, Dvinge H, Kim E, et al. Modulation of splicing catalysis for therapeutic targeting of leukemia with mutations in genes encoding spliceosomal proteins. Nat Med. 2016;22(6):672-678.
Andreeff M, Kelly KR, Yee K, et al. Results of the phase I trial of RG7112, a small-molecule MDM2 antagonist in leukemia. Clin Cancer Res. 2016;22(4):868-876.
Welch JS, Petti AA, Miller CA, et al. TP53 and decitabine in acute myeloid leukemia and myelodysplastic syndromes. N Engl J Med. 2016;375(21):2023-2036.