Abstract 3069: Investigation of pharmacodynamic and predictive biomarkers to define response to proteasome inhibitor marizomib in glioma
Notice bibliographique
Résumé
Abstract Proteasome inhibitors (PIs) have been employed with clinical success in multiple myeloma, but have been much less effective in solid tumors, despite the central role of the proteasome in controlling cellular metabolism. Marizomib (MRZ) is a novel second generation proteasome inhibitor which binds irreversibly to and inhibits the enzymatic activity of all three subunits of the proteasome. The unique ability of MRZ among PIs to cross the blood-brain barrier, combined with its pan-proteasome activity, suggest that MRZ may have distinct therapeutic advantages over the approved PIs in the treatment of glioma. Preclinical studies with MRZ have demonstrated anti-tumor activity in intracranial glioma studies, and MRZ is currently being evaluated in a Phase I clinical trial in WHO Grade IV recurrent glioma in combination with bevacizumab (NCT02330562). The aim of this study was to identify pharmacodynamic and predictive biomarkers of response to marizomib in glioma patients. Analysis of the pharmacodynamic profile of MRZ in packed whole blood from MRZ-treated glioma patients demonstrated >70% inhibition of the chymotrypsin-like (CT-L) activity as early as day 1 of cycle1 at 1 hr post-infusion, with 100% inhibition post-infusion in all patients by the end of cycle 1. Pre-infusion data demonstrate a prolonged effect, with >60% inhibition of CT-L persistent between day 15 of each cycle and day 1 of the next cycle. Trypsin-like (T-L) and caspase-like (C-L) activities increased after the first 1-2 MRZ doses, presumably due to compensatory hyperactivation of these subunits triggered by CT-L inhibition, which was subsequently overcome by repeated MRZ infusion, resulting in 40-60% inhibition of T-L and 10-30% inhibition of C-L evident through cycle 5. Analysis of proteasome enzymatic activity in archival glioma tumor tissue revealed that levels of all three proteasome activities are variable between high grade glioma samples, suggesting the potential for differential sensitivity to proteasome inhibition in glioma patients. Further, there is a linear correlation between CT-L activity (the rate limiting enzyme for proteasomal proteolysis) and C-L activity in these samples, suggesting that a PI such as MRZ with pan-proteasome specificity could potentially exhibit more activity in glioma compared to CT-L specific PIs. The data are currently being expanded to evaluate both proteasome enzymatic activity and subunit mRNA levels, to establish whether these endpoints might serve as a proteasome based biomarker. In conclusion, this study demonstrates that packed whole blood may be suitable as a pharmacodynamic biomarker for proteasome inhibition. This biomarker strategy may be crucial to stratify MRZ responsive patients in glioma. Citation Format: Daniela Bota, Annick Desjardins, Warren Mason, Kaijun Di, Ann P. MacLaren, Nancy Levin, Mohit Trikha. Investigation of pharmacodynamic and predictive biomarkers to define response to proteasome inhibitor marizomib in glioma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3069.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».