Disrupting Ectopic Super-Enhancers to Treat Multiple Myeloma
Notice bibliographique
Résumé
Abstract Multiple myeloma (MM) is an incurable form of plasma cell cancer in which primary and secondary chromosomal translocations routinely juxtapose oncogenes to plasma cell-specific super-enhancers. Coincidentally, drugs which target super-enhancers have had success clinically. For example, immunomodulatory imide drugs (IMiDs) degrade super-enhancer-binding pioneer factors IKAROS and AIOLOS, while glucocorticoids (Dexamethasone) and proteasome inhibitors (Bortezomib) have the ability to transrepress or block the processing of super-enhancer-forming NF-κB proteins, respectively. Currently, alternative enhancer-targeting drugs are also in clinical development, like p300 inhibitors which target the acetyl-binding bromodomains and/or histone acetyl transferase activity of the chromatin-regulating coactivator homologs CBP and EP300. Despite showing therapeutic promise, our understanding of how these drugs function, alone or together, remains incomplete. Case in point, we find that IMiD-induced degradation of its target proteins IKAROS and AIOLOS does not guarantee a therapeutic response in vitro, and patients successfully treated with IMiDs eventually relapse; meanwhile, coactivator-targeting therapies like p300 inhibitors are often too toxic in vivo, and lack a therapeutic window. To improve the outcomes of MM patients we need to understand the heterogeneous genetics and transcription-factor milieus of the myeloma enhancer landscape, as well as how to increase the precision of enhancer-disrupting drugs. To accomplish this, our lab utilizes more than 60 human myeloma cell lines that have been extensively characterized at the genetic, proteomic, and drug-therapeutic-response levels. Additionally, we have generated a highly-predictive immunocompetent mouse model (Vk*MYC hCRBN+) that develops human-like MM and is sensitive to both IMiDs and a new class of therapeutics termed "degronimids" (normal mice do not respond to IMiDs or degronimids). Our central hypothesis is that combining a broad coactivator-targeting drug (e.g., the p300 inhibitor GNE-781), with a MM-specific transcription factor-targeting drug (e.g., IMiDs) restricts toxicities to myeloma cells and thus improves the therapeutic window. Currently, we are testing a variety of coactivator-targeting compounds alongside traditional IMiD therapies and other preclinical transcription factor-targeting drugs both in vivo and in vitro. We show that Vk*MYC hCRBN+ mice are exquisitely sensitive to GNE-781, requiring one fourth of the dose needed to treat other cancers and therefore avoiding the neutropenia and thrombocytopenia seen at higher doses. Second, we show that although IMiDs and GNE-781 induce an effective but transient response in vivo as single agents, the combination of the two drugs proved curative, with a progressive deepening of the anti-tumor response occurring even after therapy is discontinued. Ongoing experiments aim to determine how this drug combination, and other coactivator + transcription factor-targeting combinations, permanently disrupt myeloma-specific super-enhancers. Disclosures Neri: BMS: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Bahlis: Sanofi: Consultancy, Honoraria; GlaxoSmithKline: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; BMS/Celgene: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Genentech: Consultancy. Boise: AstraZeneca: Honoraria, Research Funding; AbbVie/Genentech: Membership on an entity's Board of Directors or advisory committees. Chesi: Abcuro: Patents & Royalties: Genetically engineered mouse model of myeloma; Pi Therapeutics: Patents & Royalties: Genetically engineered mouse model of myeloma; Pfizer: Consultancy; Novartis: Consultancy, Patents & Royalties: human CRBN transgenic mouse; Palleon Pharmaceuticals: Patents & Royalties: Genetically engineered mouse model of myeloma.
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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) | 0,002 | 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 ».