MDB-26. Omomyc is a promising anti-MYC therapy for pediatric medulloblastoma
Bibliographic record
Abstract
Abstract A leading cause of cancer-related mortality in children is brain cancer, with medulloblastoma (MB) being the most common malignant type. Despite scientific advances in the field, surgery, radio- and chemotherapy still represent the current standard of care (SoC). Approximately 30% of patients relapse or develop secondary tumors, and survivors present debilitating neurocognitive impairments from SoC. Novel therapeutic approaches are needed to address the existing unmet medical need. MYC is one of the most dysregulated proteins in cancer, including MB. MYC is a master regulator of cellular processes that, when overactivated, drives tumorigenesis and tumor maintenance. However, MYC has been considered undruggable until recently. Here, we investigate the use of Omomyc as a potential therapy for pediatric MB. Omomyc is a MYC dominant negative inhibitor, currently in clinical trials for adults with advanced solid tumors as OMO-103, an Omomyc-based mini-protein. We show that Omomyc selectively targets MB brain tumor initiating cells, impairing proliferation and self-renewal, while sparing the human neural stem cells. Treatment with Omomyc downregulates MYC regulated genes, cell cycle pathways, and other oncogenic pathways specific to MB. Moreover, the half-maximal inhibitory concentration required was sustained for primary and matched SoC-recurrent samples, and a significant survival advantage was observed from our preliminary results in MB patient-derived orthotopic xenograft in vivo model. Altogether, Omomyc may be a promising therapy for MB patients, particularly at recurrence.
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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 | 0.000 |
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".