Abstract
Lung cancer is the leading cause of cancer-related death in France and in the world. It is a cancer of poor prognosis, diagnosed at the late stage III or IV, with a 5-years survival of 6% and 1%, respectively. This cancer encompass several histological types, and among them adenocarcinoma account for 40% of the diagnosis. Genetic sequencing of stage IV tumors highlights redundant mutations, and generally exclusives from each other’s, of KRAS, EGFR, BRAF and ALK genes. The identification of these mutations enable, within companion test, to make eligible patients for targeted therapies when molecules are available.Even though these targeted therapies represent a true revolution in patient’s care, the majority of them cannot benefit from these treatments because their tumors do not harbor activating mutations that are targetable (e.g. absence of EGFR, BRAF and ALK mutation, presence of KRAS mutation). Additionally, when they can be treated using an oral molecule, the benefit observed is unfortunately poor in terms of period of time, and all the patients will escape from the treatment. This is for example the case with EGFR mutations.To better understand the molecular mechanisms associated with the resistance events observed in the clinic, and to propose new therapeutics for patient not-eligible for targeted therapies, I studied at the proteome level, the impact these mutations on protein networks, using the BioID technology (proximity-dependent biotinylation identification). More particularly, I have been interested in the activating mutation of EGFR, KRAS, BRAF and ALK. Considering that proteins from the RAS family (HRAS, NRAS and KRAS) are mutated in around 30% of cancers, I have been also interested in the protein network of these proteins to highlight interaction specific to the KRAS isoform.During my thesis, I showed that the protein networks characterized using BioID are much more dense compared to those identified with the more conventional technic of AP-MS (Affinity-purification and mass spectrometry), and that they enable to identify interactors specifically deregulated upon activating mutation. Additionally, the HEK293 cell model (Human Embryonic Kidney) and BEAS2B cell model (non-cancerous lung cell line) showed a high overlapping degree of the interactors identified, suggesting that the strategy used is relevant to identify interactors specific to mutations. This thesis enabled to identify several interactors specific to the mutant KRAS, EGFR, BRAF, NRAS and EML4-ALk fusion. Thirteen interactors specific to the mutated-KRAS have been functionally validated in lung-cancer cell lines models. Finally, using BioID data I have been able to propose a model of EGFR resistance to targeted therapies. This model shows that CBL and IGH2R might be the EGFR partners responsible for therapeutic escape.Altogether, this thesis propose new perspective to determine resistance mechanisms and to identify new therapeutic targets for KRAS-mutated patients.