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PREDICT: PRoviding Effective longitudinal models of RAS DIrect inhibition to Combat Tumor resistance

Project description

Personalised treatment approach to tackle lung cancer

Lung cancer remains a significant global health challenge, particularly for patients with KRAS mutations that lead to the production of an abnormal oncogenic protein, causing the development of aggressive lung cancers. In 2022, over half a million individuals worldwide faced difficulties with therapy resistance, leading to limited treatment options. These cancers often resist standard therapies, resulting in an average survival of less than two years after treatment. The complex genetic variations in KRAS-driven lung cancer make it hard to predict responses to targeted therapies. To address this issue, the ERC-funded PREDICT project offers a personalised treatment roadmap leveraging on genetically defined cell lines to compare RAS-targeted treatments. This project might help provide indications for the choice of tailored treatment strategies.

Objective

Problem:
In 2022, more than half a million lung cancer patients worldwide carrying KRAS mutations faced therapy resistance, a trend on the rise. Such cancers resist standard treatments and targeted therapies, leading to an average survival of 1.2 years post-treatment. The heterogeneous genetic background of KRAS-driven cancer adds further complexity, hindering personalized treatment due to resistance unpredictability.

Solution:
Our Proof Of Concept (PoC) project PREDICT provides a personalized treatment roadmap for KRAS-mutant lung cancer, available through knowledge and genetic tools generated thanks to our ERC CoG grant KARMA, which was aimed at the understanding of the molecular mechanisms regulating the formation of the functional KRAS complex at the cell membrane. Using genetically-defined KRAS-mutant cell lines, our lab can facilitate direct comparisons of RAS-targeted treatments, including approved and trial drugs. This effort will empower clinicians to recommend effective strategies based on a patient's specific KRAS mutation, accounting for initial and potential acquired mutations and/or mechanisms of resistance. The model will evolve through in vitro testing, analyzing resistance mechanisms, and predicting therapies based on the patient's mutational landscape. Importantly, our approach eliminates the need for animal models.

Fields of science (EuroSciVoc)

Programme(s)

Topic(s)

Funding Scheme

HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

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Call for proposal

(opens in new window) ERC-2024-POC

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Host institution

UNIVERSITA DEGLI STUDI DI TORINO
Net EU contribution
€ 110 000,00
Address
VIA GIUSEPPE VERDI 8
10124 Torino
Italy
Region
Nord-Ovest Piemonte Torino
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data

Beneficiaries (2)