Selective Cytotoxicity against Human Osteosarcoma Cells by a Novel Synthetic C-1 Analogue of 7-Deoxypancratistatin Is Potentiated by Curcumin
Bibliographic record
Abstract
The natural compound pancratistatin (PST) is a non-genotoxic inducer of apoptosis in a variety of cancers. It exhibits cancer selectivity as non-cancerous cells are markedly less sensitive to PST. Nonetheless, PST is not readily synthesized and is present in very low quantities in its natural source to be applied clinically. We have previously synthesized and evaluated several synthetic analogues of 7-deoxypancratistatin, and found that JC-TH-acetate-4 (JCTH-4), a C-1 acetoxymethyl analogue, possessed similar apoptosis inducing activity compared to PST. In this study, notoriously chemoresistant osteosarcoma (OS) cells (Saos-2, U-2 OS) were substantially susceptible to JCTH-4-induced apoptosis through mitochondrial targeting; JCTH-4 induced collapse of mitochondrial membrane potential (MMP), increased reactive oxygen species (ROS) production in isolated mitochondria, and caused release of apoptosis inducing factor (AIF) and endonuclease G (EndoG) from isolated mitochondria. Furthermore, JCTH-4 selectively induced autophagy in OS cells. Additionally, we investigated the combinatory effect of JCTH-4 with the natural compound curcumin (CC), a compound found in turmeric spice, previously shown to possess antiproliferative properties. CC alone had no observable effect on Saos-2 and U-2 OS cells. However, when present with JCTH-4, CC was able to enhance the cytotoxicity of JCTH-4 selectively in OS cells. Such cytotoxicity by JCTH-4 alone and in combination with CC was not observed in normal human osteoblasts (HOb) and normal human fetal fibroblasts (NFF). Therefore, this report illustrates a new window in combination therapy, utilizing a novel synthetic analogue of PST with the natural compound CC, for the treatment of OS.
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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".