Abstract C232: B-raf/Mek/Erk Pathway inhibition induces GPNMB expression and sensitizes melanoma cells to the antibody-drug conjugate glembatumumab vedotin.
Notice bibliographique
Résumé
Abstract Background: Recent advances with B-raf and Mek targeted therapies have transformed the therapeutic landscape for metastatic melanoma and improved survival times for patients. Despite this progress, resistance to targeted therapies remains a universal problem that limits treatment efficacy. Combination therapy strategies represent a viable option to overcome the problem of therapeutic resistance. Glycoprotein Non-Metastatic B (GPNMB) is a cell surface protein that is highly expressed in a wide variety of cancer types, and regulates: tumor growth, cancer cell migration, invasion and metastasis. Glembatumumab vedotin (CDX-011) is a GPNMB-targeted antibody-drug conjugate that is in clinical trials for the treatment of melanoma and breast cancer. Interestingly, a wide spectrum of kinase inhibitors (KI) has been reported to induce GPNMB expression in a variety of cell types. Here we investigate the mechanism(s) responsible for elevated GPNMB levels in melanoma cells treated with clinically relevant KI, determine whether KI-mediated induction of GPNMB expression synergizes with CDX-011 in the treatment of melanoma. Methods: B-raf mutant (A375, WM-2664) and N-ras mutant (SkMel2) melanoma cells were exposed to inhibitors of B-raf (vemurafenib, dabrafenib), or Mek (trametinib, selumetinib). Immunoblot analysis or fluorescence-activated cell sorting was used to assess GPNMB expression. B-raf mutant cells were passaged in the presence of vemurafenib over the course of several weeks to months to generate vemurafenib-resistant cells. Transient siRNA knockdown studies were used to assess the requirement for the transcription factor, MiTF, in KI-mediated induction of GPNMB. To assess the interaction between individual KI and CDX011, dose response curves for the KI and CDX-011 alone or in combination in melanoma cells in vitro were generated. Melanoma cells were either 1) pretreated or 2) pre and co-treated with KI for 48 hours prior to treatment with CDX011 for 96 hours. Cell viability was assessed by XTT assay. Results: B-raf inhibition led to an induction of total and cell surface GPNMB protein in B-raf mutant, but not in B-raf WT melanoma cells. Mek inhibition induced GPNMB expression in all three melanoma cell lines. In addition to acute inhibitor treatment, Vemurafenib-resistant cells also expressed higher levels of GPNMB when compared to parental cells (inhibitor sensitive). Knock-down of the MiTF transcription factor abrogated the vemurafenib-mediated induction of GPNMB. Pretreatment of melanoma cells with Mek inhibitors led to a reduction in cell viability, compared to untreated cells, that was further exacerbated by exposure to CDX-011, in a dose-dependent manner. Interestingly, sub-optimal doses with B-raf inhibitors did not significantly affect cell viability of WM-2664 cells when used in isolation, but did enhance the sensitivity of melanoma cells to CDX-011. Conclusions: Induction of GPNMB in response to B-raf/Mek inhibition is a MiTF-dependent process that occurs in both B-raf mutant and WT cells. In this context, induction of GPNMB expression sensitizes cells to CDX-011 mediated cell killing. As such, the combination of B-raf/Mek inihibitors with CDX-011 represents an intriguing new combination therapy strategy for the treatment of melanoma, and warrants further validation in in vivo mouse models. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):C232. Citation Format: April A.N. Rose, Peter M. Siegel. B-raf/Mek/Erk Pathway inhibition induces GPNMB expression and sensitizes melanoma cells to the antibody-drug conjugate glembatumumab vedotin. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr C232.
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) | 0,004 | 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 ».