• Conventional cytogenetic methods frequently fail to fully capture the genomic complexity of myelofibrosis.

  • OGM overcomes these limitations by revealing clinically relevant SVs, CNVs, and CN‑LOH, enabling more accurate risk stratification.

Accurate genomic stratification is essential for guiding therapeutic decisions in myelofibrosis (MF), particularly regarding allogeneic stem-cell transplantation. Conventional chromosome banding (CBA) analysis, however, has limited resolution and provides an informative karyotype in only about half of MF patients. In a prospective series of 107 patients with primary or secondary MF, we compared optical genome mapping (OGM) plus targeted next-generation sequencing with CBA. OGM generated interpretable cytogenetic data for every sample, whereas CBA succeeded in fewer than half. In addition, OGM revealed structurally complex alterations and copy-neutral loss of heterozygosity that conventional methods missed. Integration of OGM results into contemporary prognostic models, including DIPSS-plus, GIPSS and MIPSS70-plus version 2.0 (MIPSS70v2), refined risk allocation across the cohort. The greatest impact was observed for the transplant-oriented MIPSS70v2: the proportion of patients assigned to high or very-high risk categories rose from 19% with CBA alone to 36% after incorporating OGM findings. Incorporation of OGM data enabled full risk stratification of all 57 individuals with non-evaluable CBA karyotypes; 16 were assigned directly to the high or very-high MIPSS70v2 risk categories, a reclassification with immediate implications for transplant referral and follow-up intensity. This study represents the largest prospective evaluation of OGM in MF, demonstrating that OGM overcomes the limitations of CBA, uncovers clinically relevant cryptic alterations, and refines prognostic stratification. These findings support integrating OGM with targeted sequencing as a step toward precision medicine in MF.

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First page of OPTICAL GENOME MAPPING IN MYELOFIBROSIS: ENHANCING PROGNOSTIC ACCURACY THROUGH HIGH-RESOLUTION GENOMIC PROFILING.

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