Casado, Pedro;
Marfa, Santiago;
Hadi, Marym M;
Gerdes, Henry;
Martin-Guerrero, Sandra M;
Miraki-Moud, Farideh;
Rajeeve, Vinothini;
(2025)
Phosphoproteomics identifies determinants of PAK inhibitor sensitivity in leukaemia cells.
Cell Communication and Signaling
, 23
(1)
, Article 135. 10.1186/s12964-025-02107-0.
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Abstract
Background The P21 activated kinases (PAK) are frequently dysregulated in cancer and have central roles in oncogenic signalling, prompting the development of PAK inhibitors (PAKi) as anticancer agents. However, such compounds have not reached clinical use because, at least partially, there is a limited mechanistic understanding of their mode of action. Here, we aimed to characterize functional and molecular responses to PAKi (PF-3758309, FRAX-486 and IPA-3) in multiple acute myeloid leukaemia (AML) models to gain insights on the biochemical pathways affected by these inhibitors in this disease and identify determinants of response in patient samples. Methods We mined phosphoproteomic datasets of primary AML, and used proteomics and phosphoproteomics to profile PAKi impact in immortalized (P31/Fuj and MV4-11), and primary AML cells from 8 AML patients. These omics datasets were integrated with gene dependency data to identify which proteins targeted by PAKi are necessary for the proliferation of AML. We studied the effect PAKi on cell cycle progression, proliferation, differentiation and apoptosis. Finally, we used phosphoproteomics data as input for machine learning models that predicted ex vivo response in two independent datasets of primary AML cells (with 36 and 50 cases, respectively) to PF-3758309 and identify markers of response. Results We found that PAK1 activation– measured from phosphoproteomics data– was predictive of poor prognosis in primary AML cases. PF-3758309 was the most effective PAKi in reducing proliferation and inducing apoptosis in AML cell lines. In cell lines and primary cells, PF-3758309 inhibited PAK, AMPK and PKCA activities, reduced c-MYC transcriptional activity and the expression of ribosomal proteins, and targeted the FLT3 pathway in FLT3-ITD mutated cells. In primary cells, PF-3758309 reduced STAT5 phosphorylation at Tyr699. Functionally, PF-3758309 reduced cell-growth, induced apoptosis, blocked cell cycle progression and promoted differentiation in a model-dependent manner. ML modelling accurately classified primary AML samples as sensitive or resistant to PF-3758309 ex vivo treatment, and highlighted PHF2 phosphorylation at Ser705 as a robust response biomarker. Conclusions In summary, our data define the proteomic, molecular and functional responses of primary and immortalised AML cells to PF-3758309 and suggest a route to personalise AML treatments based on PAK inhibitors.
| Type: | Article |
|---|---|
| Title: | Phosphoproteomics identifies determinants of PAK inhibitor sensitivity in leukaemia cells |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1186/s12964-025-02107-0 |
| Publisher version: | https://doi.org/10.1186/s12964-025-02107-0 |
| Language: | English |
| Additional information: | Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Acute myeloid leukaemia biomarkers, Cancer, Kinase inhibitors, Lysine demethylase PHF2 Machine learning, Target therapy, PAK inhibitors, PF-3758309, Phosphoproteomics, Proteomics |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10207071 |
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