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December 8, 2025Blood

Determining sensitivity to FLT3 inhibitors prior to therapy in FLT3 mutant acute myelogenous leukemia

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Authors

ÉMÉlodie De MagalhaesMAMahan AbbasianSKSteven Kornblau

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Overview

Assessment identifies FLT3 mutations predict sensitivity to inhibitors in AML, suggesting biomarkers may improve therapy selection.

Key Points

  • Differential FLT3i sensitivity was observed in acute myelogenous leukemia samples, indicating potential for better treatment outcomes.
  • Using Mass Spectrometry, we identified distinct patterns in protein expression associated with sensitivity to Sorafenib and Midostaurin.
  • Machine learning model coupled with Consensus Clustering was employed to categorize patient samples based on proteomics and sensitivity.
  • Our findings support further validation of biomarkers for guiding FLT3 inhibitor therapy selection in FLT3 mutant AML patients.

Cite This Study

Magalhaes et al. (2025) studied this question.

synapsesocial.com/papers/69362f574fa91c937236da44https://doi.org/10.1182/blood-2025-3507
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  1. 1Machine learning-powered integration of global proteomics and ex vivo sensitivity unveils a protein signature predictive of treatment success to AML therapy: Validation in patients treated with FHD-286, a SMARCA2/4 dual inhibitor2025
  2. 2Prognostic impact of co-occurring FLT3 mutations across molecular subgroups in intensively treated acute myeloid leukemia: Insights from real-world genomic data2025
  3. 3A blood-based protein signature adds to genomic prognostication of survival in TP53-mutated Acute Myeloid Leukemia2025
  4. 4Changing dogma regarding mutation primacy in acute myelogenous leukemia : Protein expression supersedes mutation status2025
  5. 5Proteogenomic analysis of NPM1-mutated AML reveals clinical heterogeneity related to differentiation states and mitochondrial metabolism2025