The dietary isothiocyanate sulforaphane targets pathways of apoptosis, cell cycle arrest, and oxidative stress in human pancreatic cancer cells and inhibits tumor growth in severe combined immunodeficient mice
Bibliographic record
Abstract
Anticancer effects of the dietary isothiocyanate sulforaphane were investigated in the human pancreatic cancer cell lines MIA PaCa-2 and PANC-1. Sulforaphane-treated cells accumulated in metaphase as determined by flow cytometry [4C DNA content, cyclin A(-), cyclin B1(+), and phospho-histone H3 (Ser(10))(+)]. In addition, treated cells showed nuclear apoptotic morphology that coincided with an activation of caspase-8, loss of mitochondrial membrane potential, and loss of plasma membrane integrity. The initial detection of caspase-3 cleavage occurring in G(2)-M arrest was independent of a change in phospho-cdc2 (Tyr(15)) protein; consequently, sulforaphane treatment combined with UCN-01 had no significant impact on cellular toxicity. Incubations at higher sulforaphane doses (>10 micromol/L) resulted in cleavage of caspase-3 in the G(1) subpopulation, suggesting that the induction of apoptosis and the sulforaphane-induced mitosis delay at the lower dose are independently regulated. Cellular toxicity in MIA PaCa-2, and to a greater extent in PANC-1, was positively correlated with a decrease in cellular glutathione levels, whereas sustained increases in glutathione observed in MIA PaCa-2 cells or the simultaneous incubation with N-acetyl-L-cysteine in PANC-1 cells were associated with resistance to sulforaphane-induced apoptosis. Daily sulforaphane i.p. injections (375 micromol/kg/d for 3 weeks) in severe combined immunodeficient mice with PANC-1 s.c. tumors resulted in a decrease of mean tumor volume by 40% compared with vehicle-treated controls. Our findings suggest that, in addition to the known effects on cancer prevention, sulforaphane may have activity in established pancreatic 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".