Abstract P3-07-03: GPNMB activates EGFR to overcome Mek-inhibition: Implications for the development of rational targeted therapy combinations in triple negative breast cancer
Notice bibliographique
Résumé
Abstract Background: TNBC is an aggressive subtype that constitutes ~15% of all BC. Currently there are no targeted therapies available for patients with. As such, there is much interest in developing targeted therapies for this disease. Recently we identified GPNMB as a transmembrane protein that promotes breast tumor growth and metastasis. CDX-011 is an antibody drug conjugate that targets GPNMB, and has recently shown promising clinical activity in patients with GPNMB+TNBC. In subset analyses of the EMERGE trial, patients with high GPNMB expressing TNBC had a median OS of 10 vs. 5.5 months for CDX011 versus chemotherapy, respectively. Response rates to CDX011 correlated with degree of GPNMB expression. These findings support the hypothesis that TNBC with high GPNMB will respond better to CDX011. As such, we sought to identify therapies with intrinsic activity against TNBC that would also induce GPNMB expression, in order to synergize with CDX-011. We have recently shown that MAPK pathway inhibition induces GPNMB expression in melanoma. Therefore we sought to determine whether Mek inhibition (Mek-i) induced GPNMB in TNBC and the targeted therapies could synergize with CDX-011. Results: We interrogated the TCGA breast datasets to determine whether the MAPK pathway is more frequently altered in TNBC. Indeed, this pathway is altered in 94% of Basal compared to 60% LumA, 83% LumB, 73% Her2 subtypes. Furthermore, we show that a Mek-activation transcriptional signature is significantly higher in basal compared to Her2 or Luminal subtypes. Indeed, we show that Fra, a downstream target of activated Erk, is most highly expressed in BC cells of the basal subtype. We used immunoblot and FACS analysis to assess GPNMB expression in response to Mek-i; trametinib and cobimetinib markedly induced GPNMB protein expression in 12 of the 14 TNBC cell lines tested. Moreover, we show that in the TCGA dataset, low expression of the Mek-activity signature correlates with higher GPNMB, specifically within the basal subtype, thus providing clinical corroboration for our in vitro observations. We go on to show that Mek-i mediated GPNMB up-regulation is regulated by TFE3. We find that EGFR is upregulated in response to Mek inhibition in several TNBC cells. GPNMB heterodimerizes with EGFR in immunoprecipitation experiments. Using siRNA to knockdown GPNMB or ectopic GPNMB overexpression, we found that GPNMB is both necessary and sufficient for enhanced EGFR activation in response to Mek-i in TNBC. Finally, we used CRISPR-CAS9 to delete genomic GPNMB from murine lung-metastatic TNBC cell lines. 533LM2 grow in syngeneic Balb/c mice. Here we show that GPNMB is required for tumor growth and metastasis in vivo. Mek-i slows tumor growth; but the combination of GPNMB deletion with Mek-i led to tumor regression, and significantly impaired tumor growth and metastasis relative to all other groups. Conclusions: Together our data show that the MAPK pathway is hyperactivated in TNBC; inhibiting this pathway impairs tumor growth, but enhances GPNMB, which facilitates mammary tumor growth and metastasis in the setting of Mek-i. These data provide rationale for combined targeting of GPNMB and the MAPK pathway in TNBC. Citation Format: Rose A, Annis M, Perkins D, Siegel P. GPNMB activates EGFR to overcome Mek-inhibition: Implications for the development of rational targeted therapy combinations in triple negative breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P3-07-03.
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 | 0,001 | 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 | 0,001 | 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) | 0,003 | 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 ».