Abstract LB187: EGFR signaling and pharmacology in oncology revealed with an innovative RTK biosensor technology
Notice bibliographique
Résumé
Abstract EGFR is involved in key biological processes and its deregulation is associated with the development of many cancers. EGFR is implicated in tumor invasion, metastasis and angiogenesis. Moreover, intrinsic and acquired mutations of EGFR have been described to modify receptor signaling and be responsible for the appearance of drug resistance during treatment in a clinical setting. Development of tools providing new insight into RTK complex mechanisms is crucial to develop more effective RTK-targeting drugs. In this study, we present a live-cell ebBRET-based biosensor platform which includes 12 distinct biosensors for monitoring SH2-domain containing proteins-mediated downstream signaling of RTKs, hence following the activation of MAPK, Akt and PKC pathways. These biosensors are designed to measure receptor proximal events that are engaged upon receptor activation at the plasma membrane (PM) and early endosomal compartments (EE). Using EGFR and two of its ligands as a model system, we showed the capacity of these biosensors to differentiate unique signaling signatures of EGFR, at the PM or the EE, with EGF and Epiregulin ligands displaying differences of efficacy and potency. Indeed, EGF was more potent and efficacious than Epiregulin on all the studied pathways. Also, we detected activities at the EE with EGF stimulation but not with Epiregulin. Our data highlight the platform's capacity to follow the trafficking of RTK biosensors into different compartments and to reveal internalization selectivity and bias which can be observed with different ligands. Overcoming resistance has become an important challenge when developing new therapeutics for the treatment of cancer. We further demonstrated that EGFR deletions or single point mutations, found in Gliobastoma or NSCLC, have an impact on the constitutive activity of EGFR and the signaling profiles but also on inhibitor efficacies which could impact receptor trafficking from the PM to the EE. In addition, the sensitivity of the RTK platform allowed us to measure the signaling of endogenously expressed EGFR in pathophysiologically-relevant cell lines commonly used for their oncogenic properties, such as A431 human epidermoid carcinoma cells, N87 gastric carcinoma cells and T47D, MCF7 and SK-BR-3 breast adenocarcinoma cells. Finally, we illustrated, using BRET-based imaging, the recruitment of SH2 effectors at the PM or at the EE after a 10-minute or 60-minute incubation respectively with EGF, highlighting the translatability of the biosensor platform to microscopy. The ebBRET-based biosensor technology displayed new insights in RTK biology and revealed different modes of action, extensive RTK signal profiling, and trafficking of RTK effectors. It represents a powerful tool for the analysis of RTK mutations and for the identification of novel generation of TKIs and antibodies directed against RTKs. Citation Format: Florence Gross, Guilhem Dugast, Arturo Mancini, Hiroyuki Kobayashi, Michel Bouvier, Stephan Schann, Xavier Leroy, Laurent Sabbagh. EGFR signaling and pharmacology in oncology revealed with an innovative RTK biosensor technology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB187.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».