CE17 - Recherche translationnelle en santé

Translational integration of PIK3CA- and MAP3K3-mutant sporadic cerebral cavernous malformations – PIMACA

Submission summary

Cerebral cavernous malformations (CCMs) are common inherited and sporadic vascular malformations of the central nervous system. While CCMs have been linked to mutations in one of three genetic loci, CCM1, CCM2 and CCM3 in 80% of inherited cases, the genetics of sporadic CCMs were poorly understood until recently. Over the past year, oncogenic mutations in PIK3CA and MAP3K3 have been discovered in more than 50% of sporadic cerebral cavernous malformations.
We have published the most important series to date establishing this result and developed an unique genetically engineered mouse model demonstrating the capacity of PIK3CA alone to promote cavernoma formation in the mouse brain and sheding new light on the potential cell of origin of these malformations.
This project will follow up on our previous effort on several aspects. In the mouse, we will develop a new MAP3K3-mutant genetically engineered mouse model that will lead to a pre-clinical study on the efficacy of clinically available PI3K and mTor inhibitors in our PIK3CA-driven and MAP3K3-driven mouse CCM models. In humans, we will use machine-learning techniques in an extended cohort of more than 200 human cavernomas to identify radiomic features of PIK3CA mutant cavernomas. We will also perform single cell RNA sequencing on fresh samples of cavernomas to identify the cell of origin of those lesions and assess the translational relevance of our models. This project could open therapeutic perspectives for cavernoma patients.

Project coordinator

Monsieur Matthieu Peyre (Institut du Cerveau)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

ICM Institut du Cerveau

Help of the ANR 320,999 euros
Beginning and duration of the scientific project: December 2022 - 36 Months

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