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December 8, 2025BloodOpen Access

Multiomics-guided ex vivo drug sensitivity testing in Relapsed/Refractory Acute Myeloid Leukemia

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Authors

SCSikander ChohanYSYang ShiJYJay Yang

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Overview

Observational analysis finds gene expression patterns predict drug responses in R/R AML patients, suggesting personalized treatments.

Key Points

  • Response prediction was established using genomic characteristics and drug sensitivity testing in R/R AML patients, enhancing clinical decision-making.
  • The study found a relationship between drug sensitivity and specific genomic features, notably IC50 thresholds across various anti-cancer drugs.
  • Participants showed variable responses to 64 anti-cancer agents, with significant findings for kinase and HDAC inhibitors relevant to treatment outcomes.
  • Integrating multiomics with drug sensitivity tests may offer significant insights for tailoring therapies to meet the needs of R/R AML patients.

Cite This Study

Chohan et al. (2025) studied this question.

synapsesocial.com/papers/69362f574fa91c937236da1fhttps://doi.org/10.1182/blood-2025-3496
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Also Consider

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

  1. 1Ex vivo drug sensitivity testing in Korean AML patients: Integration of functional and genomic profiles for predicting clinical response and survival2025
  2. 2A rapid gene expression profiler predicts tumor responsiveness and patient outcome for standard-of-care therapies in acute myeloid leukemia2025 · 1 citations
  3. 3The transition from myelodysplastic neoplasm to secondary acute myeloid leukemia is revealed by molecular analysis, while functional drug screening demonstrates novel sensitivity patterns with clinical implication2025
  4. 4Multi-omics integration reveals therapeutic vulnerabilities and immune microenvironment subtypes in Acute Myeloid Leukemia2025 · 1 citations
  5. 5Longitudinal single-cell spatial proteomics reveals predictive immune and stem cell signatures in Relapsed/Refractory AML2025