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December 8, 2025Blood

CMML2AML: Machine-learning discovery of co-mutations predictive of blast transformation in chronic myelomonocytic leukemia

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Authors

MPMatteo Giovanni Della Porta

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Overview

Machine-learning uncovers genomic alterations linked to blast transformation in chronic myelomonocytic leukemia, suggesting they may improve risk assessment for allogeneic stem cell transplantation.

Key Points

  • This research explores the role of concurrent mutations in predicting blast transformation in chronic myelomonocytic leukemia.
  • Development of machine-learning algorithms for patient stratification based on genomic alterations.
  • Use of competing risk analysis and cumulative incidence functions for survival outcomes evaluation.
  • Cohorts included 605 patients from the Mayo Clinic and 501 patients from Humanitas Cancer Center.
  • Machine-learning algorithms identified five molecular clusters with varying 3-year blast transformation rates.
  • Significant survival differences were observed among mutation combinations like RUNX1MUT/ASXL1MUT.
  • Independent prognostic contributions were confirmed via Cox regression analysis for several mutations.

Cite This Study

Matteo Giovanni Della Porta (2025) studied this question.

synapsesocial.com/papers/69362f4e4fa91c937236d839https://doi.org/10.1182/blood-2025-3844
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1CMML2AML: machine-learning discovery of co-mutations and specific single mutations predictive of blast transformation in chronic myelomonocytic leukemia2026 · 1 citations
  2. 2Myeloproliferative neoplasm driver mutations (JAK2/CALR/MPL) in chronic myelomonocytic leukemia are associated with an increased risk of blast transformation2025
  3. 3Risk-adjusted comparison of survival in chronic myelomonocytic leukemia with and without allogeneic stem cell transplant: Mayo Clinic experience in 775 consecutive patients2025
  4. 4Machine learning accurately predicts mortality in adult NPM1-mutant Acute Myeloid Leukemia using baseline clinical and genomic features2025
  5. 5Frequency and Impact of Somatic Co-occurring Mutations on Post-Transplant Outcomes in Acute Myeloid Leukemia: A Multicenter Registry Analysis on Behalf of the EBMT ALWP2025