Incorporation of Clinical Information to Decipher Driver Mutations in Myeloproliferative Neoplasms

Introduction: Mutations in the epigenetic regulators are commonly found in myeloid disorders including Myeloproliferative Neoplasm (MPN). Primary myelofibrosis, dysplastic changes and severity of the disease were associated with the mutation load. Most of the studies had a limited number of targeted genes and included a mixture of JAK2 positive and negative disease. The objective of this study is to assess the impact of mutations in the epigenetic regulators on the presentation of patients with JAK2 V617F positive MPN.

Methods: We retrieved the clinical and laboratory information on 61 consecutive eligible patients. Mutation analysis of the entire coding regions of ASXL1, ASXL2, CBL, CEBPA, CSF3R, DNMT3A, EZH2, IDH2, TET1 and TET2 genes was performed using next generation sequencing (NGS; Ion PGM Sequencer; Thermo Fisher ScientificÒ). The library was constructed and the templates were prepared using the PGM tool. The variants were annotated using the ClinVar database and the prediction from the Scale-Invariant Feature Transform (SIFT) and or Polymorphism Phenotyping (Polyphen) algorithms. Alignment, variant filtering and annotation were performed using Ion Torrent Suite. Standard descriptive and analytical statistics were used as appropriate to describe and compare different groups. The MPN subtype, bleeding, thrombosis, hemoglobin, platelet count, White Cell Count (WBC), Lactate Dehydrogenase (LDH) and erythropoietin level were compared for each candidate variant. An alpha threshold of 0.05 was used with no adjustment for multiple comparisons as the analyses were considered exploratory. All statistics were performed using R program. Variants were selected for further experimentation based on their frequency and association with the clinical information at diagnosis.

Results: Sixty-one patients were included (Polycythemia Vera: 29, Essential Thrombocythemia: 21, Primary Myelofibrosis: 9, MPN unclassifiable: 2) with a median age of 62 years (Interquartile Range [IQR]: 44 - 70). Male to female ratio was 35:26. The median hemoglobin, WBC, platelet count, LDH and erythropoietin were 14.6 g/dL (IQR: 12.8 - 16.8), 11.5 *10⁹/L (IQR: 11.5 - 14.4), 507 *10⁹/L (IQR: 391 - 779), 265 mU/mL (IQR: 231 - 409) and 1.2 mU/mL (IQR: 1.0 - 4.8) respectively. At presentation, 54% had splenomegaly, 23% had an arterial or venous thrombosis, and 5% had bleeding. Sixty-three variants were found in the samples tested. The median mutation load was 13 variants (Range: 11-14). Patients with higher than the median mutation load had higher mean erythropoietin (7.8 vs. 0.9 g/dL; p = 0.02016). ASXL1 p.Leu815Pro variant was found in all patients. Only three variants were found in the ClinVar database. Seven variants were predicted to be pathogenic (ASXL1: 1, EZH2: 1, IHD1: 1, TET1: 1 and TET2: 3). Patients with TET2: p.Leu1721Trp variant had 6.4 higher odds of bleeding (p = 0.04345). Patients with TET2: p.His1778Arg variant had a lower WBC (9.1 vs. 13.9 *10⁹/L; p = 0.01699) and LDH (213 vs. 348 mU/mL; p = 0.0006528) while those with TET1: p.Lle1123Met variant had a higher WBC (13.5 vs. 8.3 *10⁹/L; p = 0.02756). None of the remaining comparisons were statistically significant.

Conclusions: Incorporation of clinical information facilitates the prioritization of variants from DNA sequencing experiments. In MPN, we recommend ASXL1: p.Leu815Pro (expressed in all patients), TET2: p.Leu1721Trp (associated with bleeding), TET2: p.His1778Arg (correlated with the WBC and LDH) and TET1: p.Lle1123Met (correlated with LDH) for further functional experimentation.