Abstract
Background : In primary myelofibrosis (PMF), ̴ 88% of patients harbor one of three "driver" mutations, with mutational frequencies of approximately 60%, 22% and 6% for JAK2, CALR and MPL, respectively. Other "non-driver" mutations have also been described in PMF and some of them and their number have been associated with inferior survival (Leukemia. 2014;28:1804). We applied next generation sequencing (NGS) with a broader panel of MPN-relevant genes, in order to identify additional mutations of prognostic relevance as well as obtain additional information regarding the prognostic value of 'number of mutations'.
Methods: Targeted capture assays were carried out on bone marrow or whole blood DNA specimens obtained at time of referral for the following genes: TET2, DNMT3A, IDH1, IDH2, ASXL1, EZH2, SUZ12, SRSF2, SF3B1, ZRSR2, U2AF1, PTPN11, Tp53, SH2B3, RUNX1, CBL, NRAS, JAK2, CSF3R, FLT3, KIT, CALR, MPL, NPM1, CEBPA, IKZF, and SETBP1. Paired-end indexed libraries were prepared from individual patient DNA using the NEB Next Ultra Library prep protocol on the Agilent Bravo liquid handler (NEB, Ipswich, MA/Agilent Technologies Inc, Santa Clara, CA). Capture libraries were assembled according to Nimblegen standard library protocol (Roche Nimblegen, Inc, Basel, Switzerland). Base-calling was performed using Illumina's RTA version 1.17.21.3. Genesifter® software was utilized (PerkinElmer, Danvers, Massachusetts) to analyze targeted sequence data. Nucleotide variants were called using the Genome Analysis Toolkit (GATK-Broad Institute, Cambridge, MA). Specific variants were deemed as mutations if they are associated with a hematologic malignancy (as identified by COSMIC database), or if they have not been associated with a dbSNP.
Results: 180 PMF patients were evaluated (median age 63 years; 65% males). DIPSS-plus risk distribution was 32% high, 38% intermediate-2, 17% intermediate-1 and 13% low. Driver mutation distribution was 62% JAK2, 22% CALR, 9% triple-negative and 7% MPL. Karyotype was abnormal in 41% of patients and unfavorable in 12%.
Mutations other than JAK2, CALR or MPL (i.e. "non-driver" mutations) were seen in 150 (83%) patients including 88% of "triple-negative" cases. 62 (34%) patients harbored one, 55 (31%) two, 16 (9%) three and 17 (10%) four or more. Mutational frequencies were: ASXL1 36%, TET2 18%, SRSF2 17%, U2AF1 17%, ZRSR2 11%, SF3B1 10%, DNMT3A 9%, CEBPA (9%), Tp53 7%, SETBP1 6%, CBL 5%, IDH1/2 5%, SH2B3 4%, CSF3R 4%, NRAS 4%, RUNX1 3% and ≤2% for SUZ12, KIT, PTPN11, NPM1 and EZH2. DIPSS-plus high/intermediate-2 risk patients displayed higher number of mutations (p=0.0004) and higher mutational frequencies for ASXL1 (p=0.02), SRSF2 (p=0.004) and CBL (p=0.02). Associations noted included JAK2 with U2AF1 (p=0.03), unfavorable karyotype with CBL (p=0.01) and normal karyotype with ZRSR2 mutations (p=0.04).
At a median follow-up of 4 years, 111 (62%) deaths were documented. For examination of impact on survival, we considered 'number of mutations' and specific mutations with >2% frequency. Accordingly, in univariate analysis, survival was adversely affected by 'number of mutations' (Figure 1) and presence of ASXL1, SRSF2, IDH1/2, U2AF1, RUNX1 and CBL mutations. For multivariable analysis, we considered three categories (zero, 1-3 and ≥4) for number of mutations based on the results from univariate analysis (Figure 1); the results showed ≥4 mutations, 1-3 mutations, RUNX1, CBL, ASXL1 and SRSF2 mutations were independently associated with shortened survival; the respective HR (95% CI) were 4 (1.4-11.1), 3 (1.3-6.8), 2.9 (1.1-8.1), 2.8 (1.3-6.3), 1.8 (1.2-2.7) AND 1.7 (1.03-2.7). When the multivariable analysis was repeated including only the 150 patients with at least one non-driver mutation, the 'number of mutations' was no longer significant (p=0.35) but ASXL1, CBL, RUNX1 and SRSF2 mutations retained their significance. The prognostic relevance of ASXL1 and CBL continued to be apparent even after the addition of DIPSS-plus and driver mutation profile to the multivariable model.
Conclusions: Mutations other than JAK2, CALR or MPL occur in more than 80% of patients with PMF, including those with "triple-negative" driver mutational status. The absence of such mutations is independently favorable for survival while the prognostic effect of their presence is influenced by ASXL1, CBL, RUNX1 and SRSF2 mutations.
Figure 1. Figure 1.
Disclosures
Pardanani: Stemline: Research Funding.
A 27-Gene NGS Panel in Primary Myelofibrosis Identifies ASXL1, CBL, RUNX1 and SRSF2 Mutations As Being Unfavorable and Absence of Any Non-Driver Mutation As Being Favorable to Survival
