Solubility based mechanistic profiling of combinatorial drug therapy.

Abstract

Acute myeloid leukemia (AML) remains challenging to treat due to extensive genetic heterogeneity, high relapse rates, and treatment-related toxicity. Although drug combinations offer therapeutic promise, their selection is often empirical. Here, we introduce Combinatorial Proteome Integral Solubility/Stability Alteration analysis (CoPISA), a high-throughput proteomics workflow that captures protein solubility/stability alterations uniquely induced by drug combinations. We applied CoPISA to two rationally designed AML drug pairs, LY3009120-sapanisertib (LS) and ruxolitinib-ulixertinib (RU), previously identified as the most effective and least toxic combinations among many candidates and validated in AML cell lines, patient-derived samples and zebrafish xenograft models. We uncovered an emergent mechanism termed "conjunctional targeting", in which combinatorial drug action induces combination-exclusive protein targets consistent with an AND-gate logic model. LS-specific converged on SUMOylation, chromatin condensation, and VEGF-linked adhesion, while RU-specific targets disrupted DNA-damage checkpoints, mitochondrial bioenergetics, and RNA-splicing. Post-translational modification analysis revealed combination-induced acetylation, methylation, and phosphorylation of key AML proteins, including NPM1. Network analysis demonstrated that a substantial fraction of AML-associated proteins targeted by CoPISA are unique to combinations, including DNMT3A, NPM1, and TP53. By uncovering a mechanistic layer beyond classical synergy, CoPISA provides a robust framework for the precision-guided design of combinatorial therapies in heterogeneous cancers.