PREDICT PRoviding Effective longitudinal models of RAS DIrect inhibition to Com...
PREDICT PRoviding Effective longitudinal models of RAS DIrect inhibition to Combat Tumor resistance
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...
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Información proyecto PREDICT
Duración del proyecto: 20 meses
Fecha Inicio: 2024-10-07
Fecha Fin: 2026-06-30
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
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.