» Articles » PMID: 24695057

ASXL1 and SETBP1 Mutations and Their Prognostic Contribution in Chronic Myelomonocytic Leukemia: a Two-center Study of 466 Patients

Overview
Journal Leukemia
Specialties Hematology
Oncology
Date 2014 Apr 4
PMID 24695057
Citations 134
Authors
Affiliations
Soon will be listed here.
Abstract

In a cohort of 466 patients, we sought to clarify the prognostic relevance of ASXL1 and SETBP1 mutations, among others, in World Health Organization-defined chronic myelomonocytic leukemia (CMML) and its added value to the Mayo prognostic model. In univariate analysis, survival was adversely affected by ASXL1 (nonsense and frameshift) but not SETBP1 mutations. In multivariable analysis, ASXL1 mutations, absolute monocyte count >10 × 10(9)/l, hemoglobin <10 g/dl, platelets <100 × 10(9)/l and circulating immature myeloid cells were independently predictive of shortened survival: hazard ratio (95% confidence interval (CI)) values were 1.5 (1.1-2.0), 2.2 (1.6-3.1), 2.0 (1.6-2.6), 1.5 (1.2-1.9) and 2.0 (1.4-2.7), respectively. A regression coefficient-based prognostic model based on these five risk factors delineated high (≥3 risk factors; HR 6.2, 95% CI 3.7-10.4) intermediate-2 (2 risk factors; HR 3.4, 95% CI 2.0-5.6) intermediate-1 (one risk factor; HR 1.9, 95% CI 1.1-3.3) and low (no risk factors) risk categories with median survivals of 16, 31, 59 and 97 months, respectively. Neither ASXL1 nor SETBP1 mutations predicted leukemic transformation. The current study confirms the independent prognostic value of nonsense/frameshift ASXL1 mutations in CMML and signifies its added value to the Mayo prognostic model, as had been shown previously in the French consortium model.

Citing Articles

Survival Outcomes of U.S. Patients with CMML: A Two-Decade Analysis from the SEER Database.

Bangolo A, Amoozgar B, Thapa A, Bajwa W, Nagesh V, Nyzhnyk Y Med Sci (Basel). 2024; 12(4).

PMID: 39584910 PMC: 11587058. DOI: 10.3390/medsci12040060.


Chronic myelomonocytic leukemia: molecular pathogenesis and therapeutic innovations.

Marando L, Csizmar C, Patnaik M Haematologica. 2024; 110(1):22-36.

PMID: 39415698 PMC: 11694134. DOI: 10.3324/haematol.2024.286061.


Distinct clinical profiles and patient outcomes in aCML and CNL.

Sun Y, Wang Q, Zhang Z, Wang Q, Cen J, Zhu M Ann Hematol. 2024; 103(12):5325-5332.

PMID: 39375227 DOI: 10.1007/s00277-024-06032-z.


Genomic Landscape of Myelodysplastic/Myeloproliferative Neoplasms: A Multi-Central Study.

Fei F, Jariwala A, Pullarkat S, Loo E, Liu Y, Tizro P Int J Mol Sci. 2024; 25(18).

PMID: 39337700 PMC: 11431978. DOI: 10.3390/ijms251810214.


genotype-based risk stratification outperforms mutational impact and is independent of mutant variant allele fractions in chronic myelomonocytic leukemia.

Csizmar C, Gurney M, Kanagal-Shamanna R, Chien K, Hammond D, Lasho T Haematologica. 2024; 109(10):3419-3425.

PMID: 38899337 PMC: 11443373. DOI: 10.3324/haematol.2024.285410.


References
1.
Shen Y, Zhu Y, Fan X, Shi J, Wang Q, Yan X . Gene mutation patterns and their prognostic impact in a cohort of 1185 patients with acute myeloid leukemia. Blood. 2011; 118(20):5593-603. DOI: 10.1182/blood-2011-03-343988. View

2.
Vannucchi A, Lasho T, Guglielmelli P, Biamonte F, Pardanani A, Pereira A . Mutations and prognosis in primary myelofibrosis. Leukemia. 2013; 27(9):1861-9. DOI: 10.1038/leu.2013.119. View

3.
Onida F, Kantarjian H, Smith T, Ball G, Keating M, Estey E . Prognostic factors and scoring systems in chronic myelomonocytic leukemia: a retrospective analysis of 213 patients. Blood. 2002; 99(3):840-9. DOI: 10.1182/blood.v99.3.840. View

4.
Itzykson R, Kosmider O, Renneville A, Gelsi-Boyer V, Meggendorfer M, Morabito M . Prognostic score including gene mutations in chronic myelomonocytic leukemia. J Clin Oncol. 2013; 31(19):2428-36. DOI: 10.1200/JCO.2012.47.3314. View

5.
Yoshida K, Sanada M, Shiraishi Y, Nowak D, Nagata Y, Yamamoto R . Frequent pathway mutations of splicing machinery in myelodysplasia. Nature. 2011; 478(7367):64-9. DOI: 10.1038/nature10496. View