A survivin-driven, tumor-activatable minicircle system for prostate cancer theranostics
Bibliographic record
Abstract
Gene vectors regulated by tumor-specific promoters to express transgenes specifically in cancer cells are an emerging approach for cancer diagnosis and treatment. Minicircles are shortened plasmids stripped of prokaryotic sequences that have potency and safety characteristics beneficial for clinical translation. Previously, we developed minicircles driven by the tumor-specific survivin promoter, which exhibits elevated transcriptional activity in aggressive cancers, to express a secreted reporter for blood-based cancer detection. Here we present the first activatable, cancer theranostic minicircle system featuring a pair of diagnostic and therapeutic minicircles expressing Gaussia luciferase for urine-based cancer detection or cytosine deaminase:uracil phosphoribosyltransferase for gene-directed enzyme prodrug therapy. Diagnostic minicircles revealed urinary reporter output related to cellular survivin levels. Notably, mice with aggressive prostate tumors exhibited significantly higher urine reporter activity than mice with non-aggressive tumors and healthy mice after intratumoral minicircle administration. Therapeutic minicircles displayed specific cytotoxicity in survivin-rich cancer cells and significantly attenuated growth of aggressive orthotopic prostate tumors in mice. Use of these minicircles together creates a theranostic system that can first identify individuals carrying aggressive prostate cancer via a urinary test, followed by stringent control of tumor progression in stratified individuals who carry high-risk prostate lesions.
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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) | 0.001 | 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 | 0.001 | 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".