ArticleMolecular systems biology2024
Network integration of thermal proteome profiling with multi-omics data decodes PARP inhibition.
Article in Molecular systems biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Cell painting and thermal proteome profiling for inference of drug targets and mechanism of action.Molecular systems biology · 2026Article
- DORSSAA: Drug-Target interactOmics Resource Based on Stability/Solubility Alteration Assay.Molecular & cellular proteomics : MCP · 2026Article
- Benchmarking EGF signaling pathway inference using phosphoproteomics and kinase-substrate interactions.Nature communications · 2026Article
- Proteome-Wide Profiling of Olaparib Interactors Using a Biotinylated Photoaffinity Probe.Chembiochem : a European journal of chemical biology · 2025Article
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Authors and funding
14 authors.
Funding
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Abstract
Complex disease phenotypes often span multiple molecular processes. Functional characterization of these processes can shed light on disease mechanisms and drug effects. Thermal Proteome Profiling (TPP) is a mass-spectrometry (MS) based technique assessing changes in thermal protein stability that can serve as proxies of functional protein changes. These unique insights of TPP can complement those obtained by other omics technologies. Here, we show how TPP can be integrated with phosphoproteomics and transcriptomics in a network-based approach using COSMOS, a multi-omics integration framework, to provide an integrated view of transcription factors, kinases and proteins with altered thermal stability. This allowed us to recover consequences of Poly (ADP-ribose) polymerase (PARP) inhibition in ovarian cancer cells on cell cycle and DNA damage response as well as interferon and hippo signaling. We found that TPP offers a complementary perspective to other omics data modalities, and that its integration allowed us to obtain a more complete molecular overview of PARP inhibition. We anticipate that this strategy can be used to integrate functional proteomics with other omics to study molecular processes.
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