Observational analysis identified gene expression signatures linked to treatment responses in AML, highlighting machine-learning's role in therapeutic strategy predictions.
Key Points
AML shows significant heterogeneity in response to induction therapy, affecting patient outcomes.
Machine-learning model achieved 87% alignment with clinical treatment in complete remission patients.
Single-cell RNA sequencing and whole-genome sequencing used to profile 306 bone marrow samples from newly diagnosed patients.
Immune dysfunction pathways are linked to treatment resistance, emphasizing the need for personalized therapy.