Inhibiting BCL2L1 preferentially targets aneuploid cells in acute myeloid leukemia

Refractory acute myeloid leukemia (AML) is frequently associated with high rates of aneuploidy, a hallmark of intratumoral heterogeneity (ITH) that promotes chemoresistance and is linked to poor prognosis. ITH enables the competitive expansion of subclones harboring diverse advantageous drug resistance mutations, ultimately causing conventional single-target/pathway therapies to fail. Aneuploidy, however, represents a subclone-independent cellular feature shared across heterogeneous tumor populations, thereby emerging as a rational yet underexplored therapeutic target. Using machine-learning approaches, we identify a selective inhibitor of the anti-apoptotic protein BCL2L1 as a potential therapeutic agent for aneuploid AML. We further analyze both RNA interference screening data from AML cell lines and single-cell RNA sequencing data from AML patients, revealing the dependence of high-aneuploid AML cells on BCL2L1 for survival. Subsequent investigations using paired low- and high-aneuploid AML models confirm that high-aneuploid AML cells are more sensitive to both pharmacological and genetic inhibition of BCL2L1 than their low-aneuploid counterparts. Additionally, we develop an integrated gene signature to predict aneuploidy extent, prognosis, and drug response in AML, facilitating the clinical application of aneuploidy level as a therapeutic guide. Our findings establish the therapeutic efficacy of BCL2L1 inhibitors in high-aneuploid AML and propose aneuploidy targeting as a promising strategy to overcome ITH-driven chemoresistance.