Impact of Integrated Genetic Information on Diagnosis and Prognostication for Myeloproliferative Neoplasms in the Next-Generation Sequencing Era

Abstract Background: Since next-generation sequencing has been widely used in clinical laboratory, diagnosis and risk stratification of hematologic malignancies are greatly dependent on genetic aberrations.Methods: In this study, we analyzed the genomic landscape of 200 patients with myeloproliferative neoplasms (MPNs) using targeted panel sequencing covering including 86 genes. Conventional bone marrow karyotyping was also performed to determine chromosomal aberration. We analyzed relationships between genetic profiles and clinical outcomes including acute transformation, bone marrow fibrosis and death.Results: Mutations in JAK2, CALR, and MPL were detected in 76.4% of MPNs. The proportion of patients with clonal genetic markers increased up to 86.4% when all detectable genetic aberrations were included. Significant co-occurring genetic aberrations potentially associated with phenotype and/or disease progression, including those in JAK2/SF3B1 (P = 0.017) and TP53/del(13q), del(5q), -7/del(7q) and complex karyotypes (P = 0.038, P < 0.001, P < 0.001 and P < 0.001, respectively) were detected. We also identified genetic aberrations associated with patient outcomes: TP53 and -7/del(7q) for inferior survival (HR, 95% CI: 64.2, 3.8-1096.5, P = 0.0041, HR, 95% CI: 14.0, 1.5-132.7, P = 0.0219), RUNX1, TP53 and IDH1/2 for leukemic transformation (HR, 95% CI: 68.1, 3.6-1300.4, P = 0.005, HR, 95% CI: 16.3, 1.2-222.7, P = 0.0364, HR, 95% CI: 32.5, 2.8-371.1, P = 0.0051), SF3B1, IDH1/2, ASXL1 and del(20q) for fibrotic progression (HR, 95% CI: 31.5, 4.1-243.3, P = 0.0009, HR, 95% CI: 21.2, 3.4-132.2, P = 0.0011, HR, 95% CI: 4.3, 1.1-16.4, P = 0.0358, HR, 95% CI: 44.5, 6.1-323.0, P = 0.0002). We compared risk stratification systems and found that mutation-enhanced prognostic scoring systems could identify lower risk polycythemia vera and essential thrombocythemia and higher risk primary myelofibrosis (P < 0.001, P < 0.001 and P < 0.001, respectively). Furthermore, the new risk stratification systems showed better predictive capacity of patient outcome. Conclusions: These results collectively indicate that integrated genetic information can enhance diagnosis and prognostication in patients with myeloproliferative neoplasms.