Targeted Next-Generation Sequencing in Polycythemia Vera and Essential Thrombocythemia

Background : Polycythemia Vera (PV) is associated with JAK2 mutations. In essential thrombocythemia (ET), 85% of patients harbor one of 3 "driver" mutations, with frequencies of 58%, 23% and 4%, for JAK2 , CALR and MPL , respectively; 15% are wild type for all three mutations and are referred to as "triple negative". We applied next-generation sequencing (NGS) with a 27-gene panel of myeloid malignancy-relevant genes, in order to describe the prevalence of "non-driver" mutations and their prognostic relevance in PV and ET. Methods : Targeted capture assays were carried out on bone marrow or whole blood DNA 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 using the NEBNext Ultra Library prep protocol (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 (PerkinElmer, Danvers, Massachusetts) was utilized 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 (COSMIC database), or if they have not been associated with a dbSNP. Results: 314 patients with PV ( n =133; median age 64 years, 53% females) or ET ( n =181; median age 58 years, 59% females) were evaluated. Median follow-up was 9.8 years for PV and 9.2 years for ET. During this time 59 (44%) deaths, 15 (11%) fibrotic and 5 (4%) leukemic transformations were documented for PV and the corresponding percentages for ET were approximately 33%, 8% and 2%. Driver mutation distribution was 98% JAK2 for PV and 52% JAK2 , 24% CALR , 20% triple-negative and 4% MPL for ET. Polycythemia Vera Mutations other than JAK2 , CALR or MPL were seen in 58 (44%) patients; 29% harbored one, 14% two and one 3 mutations. None of 3 JAK2 -unmutated cases expressed non-driver mutations. Mutational frequencies were 18% TET2 , 11% ASXL1 , 5% SH2B3 , 3% SF3B1 and ≤2% SETBP1 , IDH2 , DNMT3A , CEBPA , CSF3R and SUZ12 , SRSF2 , ZRSR2 , TP53 , CBL , NRAS , RUNX1 , KIT , PTPN11 and FLT3 . "Number of mutations" significantly affected overall (OS; Figure 1) and myelofibrosis-free (MFS) survival; respective HR (95% CI) were 2.6 (1.3-5.2) and 1.7 (0.97-3.1) and 13.7 (2.9-63.4) and 5.1 (1.5-17.6) for ≥2 mutations and one mutation, respectively. OS was also adversely affected by SRSF2 (p=0.006) and RUNX1 (p=0.04) and borderline affected by TET2 (p=0.06), IDH2 (p=0.08), ASXL1 (p=0.19) and SF3B1 (p=0.19) mutations. In multivariable analysis, SRSF2 and RUNX1 retained significance whereas the others remained borderline significant. In both univariate and multivariable analyses, leukemia-free survival (LFS) was adversely affected by IDH2 and RUNX1 mutations. In univariate analysis, ASXL1 , IDH2 , RUNX1 and KIT mutations predicted fibrotic progression, whereas SETBP1 was of borderline significance (p=0.07); all, including SETBP1 , were significant during multivariable analysis. Essential thrombocythemia Mutations other than JAK2 , CALR or MPL were seen in 83 (46%) patients; 35% harbored one, 7% two and 4% three mutations; prevalence in JAK2 , CALR , MPL mutated and triple-negative cases was 52%, 43%, 43% and 35%, respectively (p=0.52). Mutational frequencies were: 13% TET2 , 11% ASXL1 , 6% DNMT3A , 5% SF3B1, 4% CEBPA, 2% TP53, SH2B3 , EZH2 and CSF3R and <2% for SETBP1 , IDH2 , SRSF2 , ZRSR2 , CBL , NRAS , RUNX1 , U2AF1 , KIT , PTPN11 and FLT3 . "Number of mutations" significantly affected OS (Figure 2) but not MFS or LFS; HR (95% CI) for OS were 6.6 (2.5-17.8) for 3 mutations and 2.2 (1.3-3.9) for one or two mutations. In univariate analysis, survival was adversely affected by CBL , EZH2 , SF3B1 , SRSF2 and IDH2 mutations. In multivariable analysis, EZH2 and SF3B1 remained significant. Univariate analysis identified SETBP1 and SF3B1 mutations as risk factors for fibrotic progression and EZH2 , TP53 and CSF3R mutations for leukemic transformation. Conclusions: "Non-driver" mutations occur in more than 40% of patients with PV or ET; the number of such mutations and presence of certain specific ones likely predict OS, MFS or LFS. [Figure 1. ][1] Figure 1. [Figure 2. ][1] Figure 2. Disclosures Pardanani: Stemline: Research Funding. [1]: pending:yes