Acute myeloid leukemia (AML) remains one of the most difficult blood cancers to treat. Although drug combinations are often more effective than single agents, their true mechanisms of action have been poorly understood.
A new study published in Nature Communications introduces CoPISA – the Combinatorial Proteome Integral Solubility/Stability Alteration analysis, a powerful high‑throughput proteomics workflow that uncovers how drug combinations reshape the soluble proteome in ways that single drugs cannot.
The research team, led by Senior Research Fellow Mohieddin Jafari from Tampere University, applied CoPISA to two highly promising AML drug combinations: LY3009120 + sapanisertib (LS) and Ruxolitinib + ulixertinib (RU).
“These combinations had previously shown excellent efficacy with low toxicity across AML cell lines, patient samples and zebrafish xenograft models. The goal was to uncover the mechanistic basis behind their success, Jafari explains.
In oncology, combination therapies are still largely selected empirically. Existing methods reveal whether two drugs are synergistic but do not explain how they work together at the molecular level.
CoPISA fills this gap by providing a comprehensive way to track how drugs reshape the proteome. The method captures changes in protein solubility and stability across the entire proteome, allowing researchers to see both direct and indirect protein targets affected by treatment.
“At the same time, it uncovers emergent effects that arise only when drugs are used in combination—effects that cannot be predicted from single‑agent data alone. Through this approach, CoPISA offers a much deeper mechanistic understanding of drug interactions”, Jafari says.
The study uncovered proteins whose solubility or stability changed only when both drugs were present, a phenomenon described as “conjunctional targeting”. These so-called AND-gate effects mean that both drugs must act together to produce a specific outcome, much like a system that only responds when two conditions are met. As a result, the combination creates biological effects that cannot be predicted from single drug data.
Notably, the combinations uniquely targeted several AML‑critical proteins, including DNMT3A, NPM1 and TP53, revealing vulnerabilities that single drugs fail to expose.
Each drug combination produced its own distinct mechanistic signature. The LS combination (LY3009120 + sapanisertib) influenced cellular processes related to SUMOylation, chromatin condensation, mitosis, and VEGF‑linked adhesion.
In contrast, the RU combination (ruxolitinib + ulixertinib) disrupted DNA‑damage checkpoint regulation, mitochondrial bioenergetics, and RNA splicing, revealing a mechanistic profile clearly different from that of LS.
These findings show that each drug combination reshapes cellular networks in a distinct way, disrupting multiple processes that leukemia cells depend on for survival.
“The results position CoPISA as a powerful new tool for the precision‑guided design of combination therapies. By revealing how drugs interact at a mechanistic level, the method makes it possible to identify drug pairs that are optimally compatible, uncover resistance pathways and previously unrecognized therapeutic targets, and enhance treatment safety by supporting the selection of combinations with minimal toxicity”, Jafari says.
Moreover, CoPISA provides a valuable foundation for advancing precision medicine in genetically heterogeneous cancers such as AML, where tailored treatment strategies are essential for improving patient outcomes.
“We are now applying CoPISA to additional drug combinations in AML and extending the approach to acute lymphoblastic leukemia (ALL). Our preliminary results are consistent with these findings and highly promising”, Jafari says.
Because CoPISA relies on a general physicochemical readout, it is broadly applicable across diseases and drug classes—not limited to leukemia.
Nature Communications
Solubility based mechanistic profiling of combinatorial drug therapy
25-Mar-2026