Sensitization of human melanoma cells by tamoxifen to apoptosis induction by pancratistatin, a nongenotoxic natural compound
Bibliographic record
Abstract
The objective of this study was to determine the efficacy of the natural compound pancratistatin (PST), isolated from the Hymenocallis littoralis, in human melanoma cells. Melanoma is an aggressive form of skin cancer that is commonly fatal if not diagnosed in its early stage of development. Melanoma is resistant to many treatments, thus drastically limiting chemotherapy options for this cancer. We have shown that exposure to PST induces apoptosis in human melanoma within 72 h using Hoechst staining. Interestingly tamoxifen (TAM), an estrogen receptor antagonist, sensitizes these cells to apoptosis induction by PST as observed with Hoechst and annexin-V staining. This cotreatment did not affect the viability of normal noncancerous human fibroblasts. Both of these compounds have been shown to target the mitochondria synergistically, as indicated by higher levels of reactive oxygen species generation from isolated mitochondria. PST alone and in combination with TAM shows depolarization of the mitochondrial membrane potential as shown by JC-1 staining. Melanoma drug resistance was not observed after posttreatment recuperation, as cells displayed apoptotic morphology up to 96 h after drug-free media replacement. Our results indicate that TAM alone does not induce apoptosis in this cell line, but sensitizes the mitochondria, thereby enhancing the effect of PST exposure. In conclusion, combination of two nongenotoxic compounds offers a novel treatment regime for this notoriously resilient form of skin cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".