3-Bromopyruvate potentiates TRAIL-induced apoptosis in human colon cancer cells through a reactive oxygen species- and caspase-dependent mitochondrial pathway
Bibliographic record
Abstract
Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is a promising anticancer cytokine with minimal toxicity towards normal cells. Nevertheless, most primary cancers are often intrinsically TRAIL-resistant or can acquire resistance after TRAIL therapy. This study aimed to investigate the inhibitory effect of co-treatment of 3-bromopyruvate (3-BP) as a potent anticancer agent with TRAIL on colon cancer cells (HT-29). The results of present study indicated that combined treatment with 3-BP and TRAIL inhibited the proliferation of HT-29 cells to a greater extent (88.4%) compared with 3-BP (54%) or TRAIL (11%) treatment alone. In contrast, the combination of 3-BP and TRAIL had no significant inhibitory effect on the proliferation of normal cells (HEK-293) (8.4%). At a cellular mechanistic level, the present study showed that 3-BP sensitized human colon cancer cells to TRAIL-induced apoptosis via reactive oxygen species generation, upregulation of Bax, downregulation of Bcl-2 and survivin, release of cytochrome c into the cytosol, and activation of caspase-3. In normal cells, 3-BP, TRAIL, or combination of both had no significant effect on the reactive oxygen species levels, release of cytochrome c, and caspase-3 activity. Therefore, the combination of 3-BP and TRAIL can be a promising therapeutic strategy for treatment of colon cancer.
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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".