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KRAS Targeting in Oncogenic Systems: reconstructing the KRAS signalling network to identify optimal drug combinations

Project description

KRAS cancer resistance and precision therapies

KRAS-mutant pancreatic and lung cancers are highly aggressive and currently lack effective targeted treatments. Supported by the Marie Skłodowska-Curie Actions programme, the KRATOS project aims to develop new treatment strategies for KRAS-mutant pancreatic and lung cancers, which currently rely mainly on limited chemotherapy options. It will use a systems-level approach combining experimental biology, phosphoproteomics and protein interaction mapping to understand how cancer signalling networks adapt to drug treatment and drive resistance. AI-guided computational modelling will then be used to identify drug targets and drug combinations. Overall, the project seeks to generate mechanistically informed therapies that can improve outcomes in some of the most lethal cancer types.

Objective

KRAS-mutant pancreatic and lung cancers are among the deadliest malignancies, with most patients lacking effective targeted therapies. The most common KRAS mutations, G12D and G12V, drive aggressive disease yet remain untreatable, leaving chemotherapy as the main option despite limited survival benefits and frequent resistance. Overcoming this challenge requires a systems-level strategy that goes beyond single-target approaches.

This project combines experimental biology, computational modelling, and AI-guided drug discovery to uncover and validate new therapeutic strategies. Using phosphoproteomics under drug perturbations, we will reconstruct dynamic signalling networks in a panel of patient-relevant KRAS-mutant cell lines to reveal how oncogenic pathways adapt under treatment with both targeted RAS inhibitors and standard chemotherapies. High-resolution mass spectrometry will then map the context-specific protein interactions of key oncogenic drivers such as KRAS, TP53, and AKT, providing complementary insight into mechanisms of resistance.

These multi-layered datasets will be integrated into Rezo Therapeutics’ “Sequence to Systems to Drugs” (SSD) platform, an AI-based pipeline that predicts and prioritises novel drug targets and rational combinations. The most promising candidates will subsequently be tested in advanced 3D patient-derived organoids and spheroid models, ensuring translational relevance.

By delivering mechanistically grounded drug combinations and a comprehensive resource on KRAS signalling and resistance, this fellowship will pave the way for precision-guided therapies in high-mortality cancers. It will also equip the researcher with cutting-edge expertise in systems biology, AI-driven discovery, and translational cancer models, while providing the leadership and transferable skills needed to establish an independent career that strengthens Europe’s capacity to tackle major challenges in oncology.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global Fellowships

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Call for proposal

(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

UNIVERSITY COLLEGE DUBLIN, NATIONAL UNIVERSITY OF IRELAND, DUBLIN
Net EU contribution
€ 426 533,76
Address
BELFIELD
4 Dublin
Ireland
Region
Ireland Eastern and Midland Dublin
Activity type
Higher or Secondary Education Establishments
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Total cost
No data

Partners (2)