Identification and In Vivo Validation of Unique Anti-Oncogenic Mechanisms Involving Protein Kinase Signaling and Autophagy Mediated by the Investigational Agent PV-10
Bibliographic record
Abstract
PV-10 is a 10% formulation of rose bengal sodium that has potent immunotherapeutic and anti-cancer activity against various tumors, including metastatic melanoma and refractory neuroblastoma. Currently, PV-10 is undergoing clinical testing for refractory metastatic neuroendocrine cancer and melanomas. However, preclinical investigation of PV-10 activity and its mechanisms against phenotypically and molecularly diverse adult solid tumors had not been conducted. In a panel of human cell lines derived from breast, colorectal, head and neck, and testicular cancers, we demonstrated that PV-10 induces cytotoxicity by apoptotic and autophagic pathways involving caspase-mediated PARP cleavage, downregulation of SQSTM1/p62, and upregulation of beclin-1. Treatment with PV-10 also consistently reduced phosphorylation of WNK1, which has been implicated in cancer cell migration and autophagy inhibition. By wound healing assay, PV-10 treatment inhibited the migration of cancer cells. Finally, significant inhibition of tumor growth was also noted in tumor-bearing mice treated with PV-10 by intralesional or systemic administration. In addition to known PV-10-mediated tumor-specific cytotoxic effects, we identified the mechanisms of PV-10 and provide new insights into its effect on autophagy and metastasis. Our data provide essential mechanism-based evidence and biomarkers of activity to formulate clinical studies of PV-10 in the future.
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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) | 0.001 | 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".