DNAzyme Targeting c- <i>jun</i> Suppresses Skin Cancer Growth
Bibliographic record
Abstract
Worldwide, one in three cancers is skin-related, with increasing incidence in many populations. Here, we demonstrate the capacity of a DNAzyme-targeting c-jun mRNA, Dz13, to inhibit growth of two common skin cancer types-basal cell and squamous cell carcinomas-in a therapeutic setting with established tumors. Dz13 inhibited tumor growth in both immunodeficient and immunocompetent syngeneic mice and reduced lung nodule formation in a model of metastasis. In addition, Dz13 suppressed neovascularization in tumor-bearing mice and zebrafish and increased apoptosis of tumor cells. Dz13 inhibition of tumor growth, which required an intact catalytic domain, was due in part to the induction of tumor immunity. In a series of good laboratory practice-compliant toxicology studies in cynomolgus monkeys, minipigs, and rodents, the DNAzyme was found to be safe and well tolerated. It also did not interfere in more than 70 physiologically relevant in vitro bioassays, suggesting a reduced propensity for off-target effects. If these findings hold true in clinical trials, Dz13 may provide a safe, effective therapy for human skin cancer.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".