Abstract PR10: Preclinical validation of Myc inhibition by a new generation of Omomyc-based cell penetrating peptides
Bibliographic record
Abstract
Abstract Deregulated Myc is associated with most human cancers suggesting that its inhibition would be a useful therapeutic strategy. Indeed, we have shown that Myc inhibition displays extraordinary therapeutic benefit in various transgenic mouse models of cancer (i.e skin, lung, pancreatic cancer and glioma) and causes only mild, well-tolerated and reversible side effects in normal tissues. For these studies we employed a dominant negative inhibitor of Myc, called Omomyc, which proved to be the most effective inhibitor of Myc transactivation function both in vitro and in vivo. Omomyc has so far been utilized exclusively as a transgene and served as a proof of principle. Here we report the exciting finding that Omomyc-based Cell Penetrating Peptides (CPPs) are a novel, state-of-the-art method for directly utilizing Omomyc itself (and similar peptides) to treat tumors in the lung and brain, where the peptides biodistribute after intranasal administration. We provide a comprehensive preclinical validation of this innovative therapeutic approach for pharmacological inhibition of Myc in cancer cell lines of different origin and genetic make-up, as well as in a mouse model of Non-Small-Cell Lung Cancer (NSCLC), where the Omomyc-CPPs, like their transgenic counterpart before, display a dramatic therapeutic impact. Citation Format: Marie-eve Beaulieu, Jonathan Whitfield, Daniel Massó-Vallés, Toni Jauset, Erika Serrano, Martin Montagne, Loika Maltais, Cynthia Tremblay, Pierre Lavigne, Laura Soucek. Preclinical validation of Myc inhibition by a new generation of Omomyc-based cell penetrating peptides. [abstract]. In: Proceedings of the AACR Special Conference on Myc: From Biology to Therapy; Jan 7-10, 2015; La Jolla, CA. Philadelphia (PA): AACR; Mol Cancer Res 2015;13(10 Suppl):Abstract nr PR10.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".