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Updated: Jul 1, 2026

A New Approach for the Comparative Analysis of Multiprotein Complexes Based on 15N Metabolic Labeling and Quantitative Mass Spectrometry

A New Approach for the Comparative Analysis of Multiprotein Complexes Based on ¹⁵N Metabolic Labeling and Quantitative Mass Spectrometry

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A dataset supporting Combinatorial Proteome Integral Solubility/Stability Alteration Analysis (CoPISA).

Ehsan Zangene¹, Elham Gholizadeh¹, Uladzislau Vadadokhau¹

¹Department of Biochemistry and Developmental Biology, Faculty of Medicine, University of Helsinki, Helsinki, Finland.

Scientific Data

|June 29, 2026

Summary

This summary is machine-generated.

We developed CoPISA, a proteomics assay to study drug combination effects in acute myeloid leukemia (AML). This dataset reveals proteome-wide responses to drug pairs, aiding in understanding combination therapy in AML.

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Area of Science:

Proteomics
Cancer Biology
Pharmacology

Background:

Combination therapies are crucial for acute myeloid leukemia (AML) treatment.
Limited systematic datasets exist for proteome-wide responses to multi-drug perturbations in AML.

Purpose of the Study:

To present CoPISA, a quantitative proteomics assay for profiling protein solubility and stability responses to single and combined drug treatments in AML.
To generate a comprehensive dataset of proteome-wide responses to AML drug combinations.

Main Methods:

Utilized Combinatorial Proteome Integral Solubility/Stability Alteration (CoPISA) assay.
Applied two AML drug pairs to four AML cell lines under various treatment conditions.
Employed thermal solubility profiling with TMT-based multiplexed LC-MS/MS.

Main Results:

Generated 16 TMT16-plex experiments with deep proteome coverage.
Enabled identification of proteins with unique responses to combination treatments.
Demonstrated reproducible quantification across multiplex experiments and assay formats.

Conclusions:

The CoPISA dataset provides a benchmark for studying drug combination proteome responses in AML.
Facilitates comparison of lysate and intact-cell perturbation profiles.
Supports development of computational approaches for combinatorial target inference and training in computational proteomics.