Intrinsic cell-penetrating activity propels Omomyc from proof of concept to viable anti-MYC therapy
Bibliographic record
Abstract
Inhibiting MYC has long been considered unfeasible, although its key role in human cancers makes it a desirable target for therapeutic intervention. One reason for its perceived undruggability was the fear of catastrophic side effects in normal tissues. However, we previously designed a dominant-negative form of MYC called Omomyc and used its conditional transgenic expression to inhibit MYC function both in vitro and in vivo. MYC inhibition by Omomyc exerted a potent therapeutic impact in various mouse models of cancer, causing only mild, well-tolerated, and reversible side effects. Nevertheless, Omomyc has been so far considered only a proof of principle. In contrast with that preconceived notion, here, we show that the purified Omomyc mini-protein itself spontaneously penetrates into cancer cells and effectively interferes with MYC transcriptional activity therein. Efficacy of the Omomyc mini-protein in various experimental models of non-small cell lung cancer harboring different oncogenic mutation profiles establishes its therapeutic potential after both direct tissue delivery and systemic administration, providing evidence that the Omomyc mini-protein is an effective MYC inhibitor worthy of clinical development.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".