The Presence of ASXL1 Mutations As Well As a Total Number of Myeloid Driver Mutations Higher Than Two Is Strongly Associated with the Diagnosis of Primary Myelofibrosis As Opposed to Essential Thrombocythemia

Introduction: Primary Myelofibrosis (PMF) and Essential Thrombocythemia (ET) are myeloproliferative neoplasms with similar genetic backgrounds. Both diseases are characterized, at the molecular level, by mutations in the genes JAK2, MPL and CALR. In addition recurring mutations is several other genes have been described in myeloid malignancies in general. Although the differential diagnosis between PMF and ET may be straight forward in most cases, there is a significant clinical and pathologic overlap between these two conditions, making the differential diagnosis difficult sometimes, mostly between early PMF and ET. With the goal of utilizing genomic information to better differentiate ET from PMF we decided to identify and compare all genomic alterations present in patients with ET and PMF, through whole exome / genome sequencing of paired granulocytes and skin.

Methods: A total of 84 patients with either PMF (N=48) or ET (N=36) were analyzed. DNA was extracted from CD66b+ magnetic bead selected granulocytes (EasySep, Stem Cell Technologies) and matched skin biopsies with QiaAmp DNA Mini kit (Qiagen). Whole-exome targeted capture was carried out on 3 μg of genomic DNA, using the SureSelect Human Exome Kit 51Mb version 4 (Agilent Technologies, Inc., Santa Clara, CA, USA). The exome library was sequenced with 100 bp paired-end reads on an Illumina HiSeq2000. Somatic variants calls were generated by combining the output of Somatic Sniper (Washington University), Mutect (Broad Institute) and Pindel (Washington University). Tumor coverage was 150x and germline was 60x. The combined output of these 3 softwares was further filtered by in-house criteria in order to reduce false-positive calls (minimum coverage at both tumor/germline ≥8 reads; fraction of reads supporting alternate allele ≥5% in tumor and ≤10% in germline; ratio of allele fraction tumor:germline >2). All JAK2 and CALR mutations were validated through Sanger sequencing. Validations of other somatic mutations are under way at this point. For this work, other myeloid driver mutations were defined as mutations occurring recurrently in myeloid malignancies in the medical literature, and in this cohort of patients these mutations were present in the following genes: ASXL1, ATM, CALR, CBL, CUX1, DNMT3A, EZH2, GATA2, GNAS, IDH1, IDH2, JAK2, MPL, NRAS, SH2B3, SF3B1, STAG2, TET2, NFE2, SMC3, SUZ12, PRPF8, SRSF2, U2AF1, TP53. Fisherxs exact test was used for statistical comparisons.

Results: The most common mutated genes after JAK2 and CALR were ASXL1 (n=16), TET2 (n=9) and DNMT3A (n=9). After data analysis, the patients could be divided in 7 groups based on the genomic profile:

A – JAK2 mutation as the single genetic abnormality (JAK2_Single) (N=24), B – JAK2 plus other myeloid driver mutations (JAK2_Plus) (N=25), C - CALR mutation as the single genetic abnormality (CALR_Single) (N=11), D – CALR plus other myeloid driver mutations (CALR_Plus) (N=9), E – MPL mutation (N=1), F – Triple negative without other myeloid driver mutations (TN_Single) (N=8), G – No JAK2, CALR or MPL (triple negative) but with other myeloid driver mutations (TN_plus) (N=6)

1 – The presence of 3 or more total myeloid driver mutations was strongly associated with a diagnosis of PMF

2 – The presence of ASXL1 mutations was strongly associated with a diagnosis of PMF

P=0.0007

In order to validate our findings in an independent cohort of patients, we performed the same analysis using data from 2 published studies that evaluated myeloid multi-gene panels in ET and PMF (Nangalia J, NEJM 2013) (Lundberg P, Blood, 2014). We pooled together all patients with ET (N=117) and PMF (N=56) from both studies and repeated the two previous analyses, that confirmed the previous results:

Conclusions: We have demonstrated that ASXL1 mutations as well as a number of myeloid driver mutations higher than two is strongly associated with PMF. This information may be useful in the near future to improve the differential diagnosis between ET and PMF.