PPARgamma ligand 15-deoxy-delta 12,14-prostaglandin J2 sensitizes human colon carcinoma cells to TWEAK-induced apoptosis.
Bibliographic record
Abstract
BACKGROUND: Tumor necrosis factor-like weak inducer of apoptosis (TWEAK) has been shown to induce colon cancer cell apoptosis in the presence of interferon-gamma. We hypothesized that co-treatment using TWEAK with other pro-apoptosis agents could sensitize death receptor-resistant colon cancer cells. MATERIALS AND METHODS: The effects of chemopreventive agents and TWEAK on cell death and apoptosis were determined using propidium iodide (PI) exclusion and M30 CytoDEATH. RESULTS: We found that 15d-PGJ(2) sensitizes colon cancer cells to TWEAK-induced apoptosis. Caspase inhibition reduced 15d-PGJ(2)-, but not 15d-PGJ(2)+TWEAK-induced apoptosis. 15d-PGJ(2) promoted reactive oxygen species (ROS) production and dissipation of mitochondrial potential (DeltaPsi(m)) that were more marked with combined treatment. ROS, DeltaPsi(m) and cell death were partially normalized by the antioxidant N-acetylcysteine. TWEAK induced nuclear factor-kappa B activation, which was attenuated by 15d-PGJ(2). 15d-PGJ(2) reduced the expression of the anti-apoptotic proteins BCL-X(L) and MCL-1, while increasing BAX and translocation of cytochrome c and apoptosis-inducing factor. CONCLUSION: 15d-PGJ(2) sensitized cancer cells to TWEAK-induced apoptosis through an ROS-dependent cell death pathway and may have chemotherapeutic utility as an apoptosis-enhancing agent.
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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) | 0.002 | 0.001 |
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".