Abstract LB104: Detecting protein cleavage events in living cells using IMPRINTS-CETSA data
Abstract The cell machinery is composed of a range of intricate and complex network of different regulatory pathways. Functionalities and interactions of this network are depending on proteins which are regulated by interactions, but also different posttranslational modifications (PTM) such as phosphorylation and proteolysis. Proteolysis is an irreversible posttranslational modification that hydrolyzes a peptide bond in a peptide or protein substrate thanks to several families of specialized proteases (Barrett et al. 2013). Proteolysis or proteolytic cleavage is a key step in different degradation processes as in the proteasome or during apoptosis but also for cell cycle regulation (Fatima, Fazili and Bhat 2022). Hence, identifying and understanding proteolytic events in the cell is essential to explain the cell machinery. Recently in (Ramos et al. 2024) we established that we could detect such proteolytic events in intact cells by using the Cellular Thermal Shift Assay (CETSA) (Martinez Molina et al. 2013). More precisely, by using a specific format of CETSA coupled with mass spectrometry, IMPRINTS-CETSA (Integrated Modulation of Protein Interaction States -CETSA) reported by our lab in (Dai et al. 2018). IMPRINTS-CETSA has been used to address complex biological questions such as the study of sensitiveness and resistance of cancer cell lines (Liang et al. 2022) or uncover new insights in main biological events such as the cell cycle (Dai et al. 2018) or apoptosis (Ramos et al. 2024). Following our work in (Ramos et al. 2024), we present a new and robust algorithm to detect and follow proteolytic events in living cells by analyzing IMPRINTS-CETSA data. Not only are we able to follow caspase cleavage cascades, but also cleavage from other proteases occurring in the cell such as cathepsins, meprins or granzymes. Moreover, by filtering the candidates obtained by our algorithm, we can also differentiate protein cleavage from PTMs and/or alternative splicing forms by using databases such as Uniprot and PhosphoSitePlus. Together this approach gives an unprecedented stringency in following proteolysis in the cell, e.g. during cancer drug action. To support this, we applied our newly developed method on the data from (Ramos et al. 2024) and (Dai et al. 2018). Additionally, to increase the coverage of potential cleavage sites, we’ve leveraged on increased data acquisition rate of Orbitrap Astral mass-spectrometer for enhanced IMPRINTS-CETSA time course profiling after apoptosis induction by the BCL2 inhibitor venetoclax drug in acute myeloblastic leukemia cells. Citation Format: Marc-Antoine Gerault Nicolas Gerault, Anderson Daniel Ramos, Sara Lööf, Alexey Chernobrovkin, Pär Nordlund. Detecting protein cleavage events in living cells using IMPRINTS-CETSA data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB104.
Authors
- Sara Lööf
- Alexey Chernobrovkin (ORCID: https://orcid.org/0000-0001-7709-0161)
- P. Nordlund (ORCID: https://orcid.org/0000-0002-7794-702X)
- Marc-Antoine Gerault (ORCID: https://orcid.org/0009-0000-7430-3467)
- Anderson Daniel Ramos
Institutions
- Karolinska Institutet (SE)
- Svenska Örtmedicinska Institute (SE)
Publication Details
- Journal
- Cancer Research
- Published
- 2025-04-25
- DOI
- https://doi.org/10.1158/1538-7445.am2025-lb104
- Primary Topic
- Machine Learning in Bioinformatics
- Type
- article
- Field-Weighted Citation Impact
- 0.00