Abstract 1218: Targeting B-RAF and checkpoint inhibitor resistant melanoma with RSK inhibitor PMD-026 in pre-clinical models
Notice bibliographique
Résumé
Abstract Cutaneous melanoma is a highly invasive skin cancer. Mortality for melanoma is low if caught before metastasis occurs, but is poor if metastasis has occurred at diagnosis. Melanomas are among the most mutated cancer genomes and have a high neoantigen load, which is related to better response to immunotherapies. A subset of melanomas contains mutations in BRAF(V600E) and respond initially to BRAF inhibitors, though they become resistant through escape pathways. Focused development of BRAF and immunotherapies has resulted in the clinical use of targeted therapies against the oncogenic BRAF/MEK/ERK pathway and immune checkpoint inhibitors for the treatment of metastatic melanoma. Although some patients with metastatic melanoma benefit from these therapies, others either do not respond or become resistant. Because of this, new targets and drugs are needed for patients who are either intrinsically resistant or have acquired resistance to targeted therapies and immunotherapies. RSKs are serine/threonine kinases downstream of BRAF/ERK that activate transcription, proliferation and cell survival. Thus RSKs are potential new targets and the availability of a RSK inhibitor called PMD-026, now in Phase 1b clinical trials for breast cancer, provides a tool to explore this possibility in pre-clinical models of melanoma. PMD-026 is an ATP-competitive inhibitor of the N-terminal kinase domain. This inhibitor is highly stable and effective in cell-based assays with an average IC50 of 2nM and 200-400 nM in soft agar and inhibits tumor growth in multiple mouse models of breast cancer given 70-100 mg/kg given orally. It is currently the only RSK inhibitor that can be given to mice orally with demonstrated in vivo activity. To explore the opportunity for RSK inhibitors in melanoma, we screened 1,959 PDx models for RSK1-4 expression, which was evaluated based on RNAseq. In melanoma, RSK1 and RSK2 were highly expressed, unlike RSK3 and RSK4. In a study of 21 cases of melanoma, RSK2 was activated in 52% of the cases based on nuclear localization using our companion diagnostic. Using FRET based assays, PMD-026 inhibited RSK2 binding with an IC50=14 nM compared to BID1870 with IC50=94 nM demonstrating competitive in vitro potency. Importantly, PMD-026 inhibits viability of melanoma cells including those that are resistant to the BRAF inhibitor. Surprisingly, we also found that it significantly reduces PD-L1 expression at the cell surface of several melanoma lines. This is through down-regulation of PD-L1 transcription and subsequent reduced PD-L1 cell surface expression. As expected, in our melanoma models, PMD-026 inhibited RSK signaling through pYB-1, a transcription factor known to bind to the PD-L1 promoter. Testing in pre-clinical mouse models is in progress. We propose that PMD-026 may therefore potentiate melanoma immunotherapy approaches and also improve response of patients to BRAFV600E targeted therapies. Citation Format: Joe William Ramos, Stephanie Si, Takeo Fujii, Brien Haun, Won Seok Yang, Aarthi Jayanthan, Sandra E. Dunn. Targeting B-RAF and checkpoint inhibitor resistant melanoma with RSK inhibitor PMD-026 in pre-clinical models [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 1218.
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) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| 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 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,002 |
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 ».