Over the past decade NGS has expanded our understanding of the genomic landscape of hematological malignancies. New biomarkers discovered during NGS are now widely used in clinical practice to improve diagnosis, stratify patients into prognostic groups, and select targeted therapy for Ph-MPN patients. To assess possibilities of NGS in diagnosis and determination of prognostic features of disease course in Ph-MPN patients. The study included 36 patients from clinics in Moscow and St. Petersburg (17 men and 19 women), the median age was 55 (IQR 27-79) with diagnosed PV, ET, PMF, MDS, AML. A panel of 116 genes with an average reading depth of 200x or 1000x on MiSeq (Illumina) was used. NGS panel had a detection limit of 3% variant allele frequency. The clinical significance of mutations was determined using COSMIC and ClinVar. Genetic abnormalities were detected in all patients. On average, 10 mutations per one patient were revealed, including 4 somatic mutations in 92% (33/36) patients. In 70% (25/36), from 1 to 3 mutations with known clinical significance were found. In all patients without driver and somatic mutations (ASXL1, EZH2, etc.) and chromosomal aberrations, somatic mutations (both clinically significant and unknown clinical significance) were detected, that served as clonality confirmation. All patients were divided into two groups: 1) driver mutations, normal karyotype (16/36) (favorable prognosis) and 2) triple-negative mutational status (20/36) with additional patients having mutations in epigenetic regulators genes (4/36) (unfavorable prognosis). In the first group, NGS revealed additional mutations in 8/16 (50%) patients (ASXL1, EZH2, IDH1) and in 3/16 (19%) were noted mutations in TET2 gene. In an unfavorable group, additional mutations were also found in genes of epigenetic regulation (ASXL1, IDH1, SRSF2) and in signal transduction genes (RAS genes, PTPN11) and TET2. NGS data can confirm disease clonal nature, assess disease prognosis, and select target therapy for patients with Ph-negative myeloproliferative neoplasms. To get new information it is possible to expand the panel of sequenced genes, as well as study other genetic mechanisms underlying disease pathogenesis (e.g., changes in gene expression level, microRNAs, or transcription factors).
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