CYTOGENOMIC PROFILING OF LARGE COHORT OF INDIAN MYELODYSPLASTIC SYNDROMES

Abstract

Introduction: About 40% - 50% of Myelodysplastic syndromes (MDS) patients present with a normal karyotype whereas 50% - 60% of patients are of low risk, however, they tend to have worse outcomes and a higher chance of disease progression. Hence, we aim to study the genomic pathophysiology of disease and their association with overall survival in MDS. Methods: The study cohort included 200 MDS patients. The molecular cytogenetic and mutation profiling was carried out in all MDS patients. The patients were clinically followed up. The Kaplan-Meier survival and multivariate analysis was performed using GraphPad Prism 5.00 Results: The WHO 2016 classification revealed a high frequency of MDS – MLD (33%) followed by MDS – SLD (25%), MDS – EB-1/2 (24%). The chromosomal aberrations were identified in 35% of MDS patients by CK/FISH. The NGS identified gene mutations in 75% of the cohort. The survival analysis revealed that the mutations in TP53, JAK2/3, KRAS, NRAS, and ASXL1 are significantly (P < 0.05) associated with poor survival. SNP array analysis (n=77), revealed, patients with chromosome 2 aberrations have a poor prognosis. SNP array combined with NGS confirmed the biallelic loss of function of the TP53 gene (3/7), a clinically relevant biomarker and new genetic-based MDS entity i.e. MDS-biTP53 as per the new WHO classification 2022. The univariate and multivariate analysis suggested that genetic lesions (mutations/CNVs/LOH) with IPSS-R could be prognosticating markers in MDS patients. Conclusions: Our study strongly supports that the genome profiling by combined CGH+SNP array and NGS improves prognostication and hence personalized disease management