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bioRxiv · 10.64898/2026.03.20.713131

CoPISA: Combinatorial Proteome Integral Solubility/Stability Alteration analysis

zangene, e.·gholizadeh, e.·Vadadokhau, U.·Ritz, D.·Saei, A.·JAFARI, M.
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Abstract

Combination therapies are widely used in acute myeloid leukemia (AML), but systematic datasets capturing proteome-wide responses to multi-drug perturbations remain limited. Here we present CoPISA (Combinatorial Proteome Integral Solubility/Stability Alteration), a quantitative proteomics assay designed to profile protein solubility and stability responses to single and combined drug treatments. The dataset includes two AML drug pairs (LY3009120-sapanisertib and ruxolitinib-ulixertinib) applied to four AML cell lines (MOLM-13, MOLM-16, SKM-1, and NOMO-1) under control, single-agent, and combination conditions in both lysate and intact-cell formats. Thermal solubility profiling coupled with TMT-based multiplexed LC-MS/MS generated 16 TMT16-plex experiments comprising 192 LC-MS/MS raw files, providing deep proteome coverage across treatments and biological contexts. The resource includes raw and processed proteomics data, detailed experimental metadata in Sample and Data Relationship Format (SDRF), and reproducible analysis scripts for reporter normalization, protein-level aggregation, statistical modeling, and classification of combinatorial response patterns. The experimental design enables identification of proteins responding uniquely to combination treatments as well as overlapping single-agent effects. Technical validation demonstrates reproducible quantification across multiplex experiments and assay formats. All data are publicly available through the PRIDE repository (PXD066812) together with analysis code, enabling independent reanalysis and method development. This dataset provides a benchmark resource for studying proteome responses to drug combinations, comparing lysate and intact-cell perturbation profiles, developing computational approaches for combinatorial target inference, and supporting training in computational proteomics.

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zangene, e., gholizadeh, e., Vadadokhau, U., Ritz, D., Saei, A., JAFARI, M.. 2026-03-23. CoPISA: Combinatorial Proteome Integral Solubility/Stability Alteration analysis. https://doi.org/10.64898/2026.03.20.713131

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