Small Molecule Disruption of a Protein Disulfide Isomerase-Containing Multi-Protein Complex Causes Broad Cancer Selective Metabolic Collapse and Tumor Inhibition <i>in vivo</i>
Bibliographic record
Abstract
Abstract PAV-620, and PAV-805 are chemical analogs from a protein assembly modulating small molecule lead series that displays broad anti-cancer activity. These compounds are active against all cancers in the NCI-60 cancer cell line screen, which is representative of diverse blood, brain, breast, colon, lung, ovarian, prostate, renal, and skin cancers. Safety in mice is observed up to doses of 10 mg/kg daily and nontoxicity to healthy human peripheral blood mononuclear cells at doses up to 20uM. The compounds are as efficacious as Paclitaxel in reducing tumor growth and metastasis in the aggressive 4T1 mouse allograft model for triple negative breast cancer. The mechanism of action of PAV-620 and PAV-805 in primary carcinoma cells under conditions inducing programmed cell death was found to be distinct from the cytotoxic mechanisms of Staurosporine, Paclitaxel, and Etoposide. PAV-805 was shown to target a small subset of protein disulfide isomerase (PDI) in a dynamic multi-protein complex enriched in the cancer hallmark proteins involved in reprogramming energy metabolism. These data suggest a new approach to cancer therapeutics, with selectivity arising not from targeting PDI itself, an abundant cellular protein, but from targeting a disease-associated assembly state of PDI-containing complexes as a therapeutically exploitable dimension of cancer biology.
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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".