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Mapping the Mutational Landscape of Myeloproliferative Neoplasms: An Indian Cohort of 1,000 Patients

Sep 2026 · Indian Journal of Medical and Paediatric Oncology · 0 citations · 47 references

TL;DR

This large NGS-based study highlights the genetic heterogeneity of MPNs in an Indian population and supports the clinical utility of integrated genomic profiling for molecular diagnosis and risk stratification.

Abstract

Abstract Introduction Myeloproliferative neoplasms (MPNs) are clonal hematopoietic stem cell disorders characterized by overproduction of myeloid lineages. Driver mutations in JAK2 , CALR , and MPL account for most cases; however, additional somatic mutations contribute to disease heterogeneity, prognosis, and therapeutic response. Next-generation sequencing (NGS) enables comprehensive genomic profiling of these alterations. Objectives This article ails to characterize the mutational landscape of MPNs in a large Indian cohort using targeted NGS. Materials and Methods A total of 1,000 patients with clinically suspected MPNs were analyzed using DNA- and RNA-based NGS assays. Genomic DNA from peripheral blood or bone marrow samples underwent targeted library preparation and sequencing on Illumina and Thermo Fisher platforms. Bioinformatic analysis identified single-nucleotide variants, insertion–deletions, and clinically relevant gene fusions. Results Somatic alterations were detected in 490 patients. JAK2  V617F was the most frequent mutation (256 cases; 52.9%), followed by CALR exon 9 indels (50 cases; 11.1%) and MPL mutations (24 cases; 5.3%). Rare JAK2 exon 12 variants were identified in seven cases. Additional mutations included TET2 (94 cases; 20.9%), ASXL1 (53 cases; 11.8%), and SRSF2 (44 cases; 9.8%). RNA sequencing detected clinically relevant fusions including BCR::ABL1 , FIP1L1::PDGFRA , and ETV6::PDGFRB . Conclusion This large NGS-based study highlights the genetic heterogeneity of MPNs in an Indian population and supports the clinical utility of integrated genomic profiling for molecular diagnosis and risk stratification.

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