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  • Title: Impact of TET2, SRSF2, ASXL1 and SETBP1 mutations on survival of patients with chronic myelomonocytic leukemia.
    Author: Cui Y, Tong H, Du X, Li B, Gale RP, Qin T, Liu J, Xu Z, Zhang Y, Huang G, Jin J, Fang L, Zhang H, Pan L, Hu N, Qu S, Xiao Z.
    Journal: Exp Hematol Oncol; 2015; 4():14. PubMed ID: 26019984.
    Abstract:
    BACKGROUND: Chronic myelomonocytic leukemia (CMML) is a myeloid neoplasm classified in the myelodysplastic syndrome/myeloproliferative neoplasm (MDS/MPN) category. Molecular abnormalities are reported in about 90 % of patients with CMML. ASXL1 and SETBP1 mutations, but not TET2 or SFRS2 mutations are reported to be associated with prognosis. METHODS: We studied frequency of TET2, SRSF2, ASXL1 and SETBP1 mutations in 145 patients with CMML using Sanger sequencing, and determined the prognostic factors for OS. We also identified the predictive value of ASXL1 mutations (frameshift and nonsense mutations) through comparing the Mayo Prognostic Model with the Mayo Molecular Model. RESULTS: Forty-seven (32 %) had a mutation in TET2, 42 (29 %), a mutation in SRSF2, 65 (45 %), a mutation (nonsense and frame-shift) in ASXL1 and 26 (18 %), a mutation in SETBP1. Significant variables in multivariable analysis of survival included ASXL1 (HR = 1.99 [1.20-3.28]; P = 0.007), hemoglobin <100 g/L (HR = 2.42 [1.40-4.19]; P = 0.002) and blood immature myeloid cells (IMCs) (HR = 2.08 [1.25-3.46]; P = 0.005). When our patients were analyzed using the Mayo Prognostic Model median OS were not reached, 26 months and 15 months (P = 0.014). An analysis using the Mayo Molecular Model identified 4 cohorts with median OS of not reached, 70 months, 26 months and 11 months (P < 0.001). Data fitting using our patients suggest the Molecular Mayo Model has significantly higher survival predictive power compared with Mayo Prognostic Model (P < 0.001, -2 log-likelihood ratios of 538.070 and 552.260). CONCLUSIONS: There were high frequencies of mutations in TET2, SRSF2, ASXL1 and SETBP1 in patients with CMML. With the addition of ASXL1 frameshift and nonsense mutations, the Mayo Molecular Model fitted better than Mayo Prognostic Model of our patients.
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