Acute myeloid leukemia (AML) is a deadly blood cancer with poor long-term survival, and current treatments often fail due to relapse and limitations in model accuracy. To better reflect disease heterogeneity, we developed a diverse panel of patient-derived AML models. By integrating proteomics and drug-response data, we generated a deep learning–based map of therapeutic sensitivity that guides treatment positioning for upcoming clinical trials.

American Society for Mass Spectrometry www.hupo.org