Related Experiment Video
Updated: Mar 27, 2026
07:51
High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method
Published on: May 21, 2018
12.8K
Solubility based mechanistic profiling of combinatorial drug therapy
Elham Gholizadeh1, Ehsan Zangene1, Uladzislau Vadadokhau1
1Department of Biochemistry and Developmental Biology, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Nature Communications
|March 26, 2026
Summary
Combinatorial Proteome Integral Solubility/Stability Alteration analysis (CoPISA) reveals combination-exclusive protein targets in acute myeloid leukemia (AML) drug pairs. This approach enables precision-guided design of novel combinatorial therapies for heterogeneous cancers.
Area of Science:
- Proteomics
- Cancer Biology
- Drug Discovery
Background:
- Acute myeloid leukemia (AML) presents significant treatment challenges due to genetic diversity, frequent relapses, and toxic side effects.
- Current drug combination selection for AML is often empirical, lacking mechanistic insight.
- Novel approaches are needed to rationally design effective and less toxic AML combination therapies.
Purpose of the Study:
- Introduce Combinatorial Proteome Integral Solubility/Stability Alteration analysis (CoPISA), a high-throughput proteomics method.
- Characterize protein alterations induced by specific AML drug combinations.
- Uncover emergent mechanisms of combinatorial drug action for precision therapy development.
Main Methods:
- Applied CoPISA to two validated AML drug pairs: LY3009120-sapanisertib (LS) and ruxolitinib-ulixertinib (RU).
- Validated drug pairs in AML cell lines, patient-derived samples, and zebrafish xenograft models.
- Performed post-translational modification and network analyses on identified protein targets.
Main Results:
- CoPISA identified combination-exclusive protein targets, termed "conjunctional targeting," operating under AND-gate logic.
- LS combination targeted SUMOylation, chromatin condensation, and VEGF-linked adhesion.
- RU combination disrupted DNA-damage checkpoints, mitochondrial bioenergetics, and RNA splicing.
- Combination-induced post-translational modifications (acetylation, methylation, phosphorylation) were observed in key AML proteins like NPM1.
- Network analysis revealed combination-specific targeting of AML-associated proteins including DNMT3A, NPM1, and TP53.
Conclusions:
- CoPISA uncovers a mechanistic layer of combinatorial drug action beyond classical synergy.
- This proteomics framework facilitates the precision-guided design of combinatorial therapies for heterogeneous cancers like AML.
- CoPISA offers a robust strategy for developing more effective and targeted cancer treatments.
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