Abstract A013: NF1 loss is syntetic lethal with Trastuzumab emtansine
Notice bibliographique
Résumé
Abstract There is great interest in the identification of biomarkers to guide development of antibody-drug conjugates (ADC). Most research has focused on target expression, but key predictors of payload efficacy have not been indeitifed. NF1 is a tumor suppressor classically considered as an inhibitor of RAS signaling, and often mutated in metastatic HER2+ breast cancer (BC). We screened multiple approved drugs for differential sensitivityin CRISPR-engineeredf NF1 KO cells. HER2-targeted agents (small molecules or antibodies) were found to be less effective upon NF1 loss; surprisingly, we identified increased sensitivity to the approved ADC T-DM1, but not to Trastuzumab Deruxtecan (T-Dxd). We then elucidated the underlying molecular cause employing in vivo, in vitro and in vitro reductionist systems. To measure in vivo MT dynamics, we transiently transfected the MT end-binding protein EB3- GFP and reconstructed MT trajectories by live-cell imaging. Upon DM1 treatment, KO cells showed a highly significant reduction in MT speed, demonstrating a direct role for NF1 on MT dynamics in cells. In tubulin polymerization assays, recombinant NF1 greatly accelerated polymerization and completely rescued DM1-induced inhibition. NF1 induced significant MT bundling, a defining feature of many MT-associated proteins, which generates signal indistinguishable from true MT polymerization in turbidity assays. To follow the dynamics of individual microtubules, we applied Total Internal Reflection (TIRF) microscopy on glass-immobilized MTs. As expected, polymerization in the presence of NF1 led to a dose-dependent significant increase in MT dynamics (fraction of elongating MTs, elongation speed, catastrophe rate). Expectedly, DM1 led to significant reduction in the fraction of elongating MTs and speed, but these defects were completely or partially rescued by NF1. Importantly, DM1 did not only lead to MT shortening (as proposed by the current model), but also to clear and frequent MT fracturing, indicating that the drug is not only engaging MT ends but also intra-tubular binding sites. This is consistent with recent models of MT formation which incorporate the frequent presence of areas of discontinuity or damage induced by mechanical stress, exposing intratubular DM1 binding sites. Interestingly, adding NF1 to DM1-treated MTs generated areas of de novo intra-tubular tubulin insertion, coincident with damaged sites, suggesting an entirely novel role for NF1 in MT repair. In conclusion, we provide evidence for a model in which maytansinoids bind not only to soluble tubulin dimers and MT ends, but also to intratubular damaged sites. Thus, the number of binding sites in cells would be proportional to MT damage, suggesting a mechanism for differential efficacy across tumor types and a potential avenue for combinatorial drug development. These results prompt the use of NF1 as a biomarker to select patients for ADC treatment. Funding: FIEO fellowship 2023, AIRC (n25791), Italian MoH-Ricerca Corrente di Rete (ACCORD) 2022, Next Generation EU – PNRR M6C2 – PNRR-MAD-2022-12376934 Citation Format: Eleonora Messuti, Bruno Achutti Duso, Alessia Castiglioni, Giulia Tini, Emanuele Bonetti, Giuseppe Ciossani, Silvia Monzani, Daria Khuntsariya, Marcus Braun, Zdenek Lansky, Luigi Scietti, Luca Mazzarella. NF1 loss is syntetic lethal with Trastuzumab emtansine [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr A013.
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 | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 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 ».