Pancratistatin Selectively Targets Cancer Cell Mitochondria and Reduces Growth of Human Colon Tumor Xenografts
Bibliographic record
Abstract
The naturally occurring Amaryllidaceae alkaloid pancratistatin exhibits potent apoptotic activity against a large panel of cancer cells lines and has an insignificant effect on noncancerous cell lines, although with an elusive cellular target. Many current chemotherapeutics induce apoptosis via genotoxic mechanisms and thus have low selectivity. The observed selectivity of pancratistatin for cancer cells promoted us to consider the hypothesis that this alkaloid targets cancer cell mitochondria rather than DNA or its replicative machinery. In this study, we report that pancratistatin decreased mitochondrial membrane potential and induced apoptotic nuclear morphology in p53-mutant (HT-29) and wild-type p53 (HCT116) colorectal carcinoma cell lines, but not in noncancerous colon fibroblast (CCD-18Co) cells. Interestingly, pancratistatin was found to be ineffective against mtDNA-depleted (ρ(0)) cancer cells. Moreover, pancratistatin induced cell death in a manner independent of Bax and caspase activation, and did not alter β-tubulin polymerization rate nor cause double-stranded DNA breaks. For the first time we report the efficacy of pancratistatin in vivo against human colorectal adenocarcinoma xenografts. Intratumor administration of pancratistatin (3 mg/kg) caused significant reduction in the growth of subcutaneous HT-29 tumors in Nu/Nu mice (n = 6), with no apparent toxicity to the liver or kidneys as indicated by histopathologic analysis and terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling. Altogether, this work suggests that pancratistatin may be a novel mitochondria-targeting compound that selectively induces apoptosis in cancer cells and significantly reduces tumor growth.
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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".