Disrupting Ectopic Super-Enhancers to Treat Multiple Myeloma
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".