A cellular hierarchy framework for understanding heterogeneity and predicting drug response in AML
The treatment landscape of AML is evolving with promising therapies entering clinical translation, yet patient responses remain heterogeneous and biomarkers for tailoring treatment are lacking. To understand how disease heterogeneity links with therapy response, we determined the leukemia cell hierarchy make-up from bulk transcriptomes of over 1000 patients through deconvolution using single-cell reference profiles of leukemia stem, progenitor, and mature cell types. Leukemia hierarchy composition was associated with functional, genomic, and clinical properties and converged into four overall classes, spanning Primitive, Mature, GMP, and Intermediate. Critically, variation in hierarchy composition along the Primitive vs GMP or Primitive vs Mature axes were associated with response to chemotherapy or drug sensitivity profiles of targeted therapies, respectively. A 7-gene biomarker derived from the Primitive vs Mature axis was predictive of patient response to 105 investigational drugs. Thus, hierarchy composition constitutes a novel framework for understanding disease biology and advancing precision medicine in AML.