Exploiting Cancer Cell Mitochondria as a Therapeutic Strategy: Structure Activity Relationship Analysis of Synthetic Analogues of Pancratistatin
Bibliographic record
Abstract
Distinct characteristics, including decreased dependence on mitochondrial respiration and high levels of oxygen radicals, provide opportunities for cancer targeting. We have shown the compound pancratistatin (PST) to selectively induce apoptosis in cancers by mitochondrial targeting. However, its low availability in nature was limiting its preclinical development. Various PST analogues were synthesized to circumvent this limitation. In this dissertation, these analogues were screened and several had comparable or greater anti-cancer activity compared to PST. The analogue, SVTH-7, demonstrated the most potent anti-cancer activity, followed by SVTH-6 and -5 in vitro and in vivo. These compounds had greater efficacy than PST, 7-deoxyPST analogues, and multiple standard chemotherapeutics, and were found to induce apoptosis in cancer cells by acting on cancer cell mitochondria. Furthermore, the anti-cancer effects of PST analogues were enhanced when used with agents known to target cancer cell mitochondria and oxidative vulnerabilities, including tamoxifen, curcumin, and piperlongumine. Interestingly, functional complex II and III of the electron transport chain were required for SVTH-7 to inflict its pro-apoptotic effects on cancer cells, suggesting exploitation of a mitochondrial vulnerability by SVTH-7. Therefore, these findings demonstrate a novel approach to treat cancer by exploiting cancer cell mitochondria with PST analogues alone or in combination with other compounds. These PST analogues have high therapeutic potential and this work will lay the groundwork for the identification and characterization of distinct mitochondrial features of cancer cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".