RESISTANCE TO FAS‐MEDIATED APOPTOSIS IN MALIGNANT TUMOURS IS RESCUED BY KN‐93 AND CISPLATIN VIA DOWNREGULATION OF c‐FLIP EXPRESSION AND PHOSPHORYLATION
Bibliographic record
Abstract
1. The purpose of the present study was to investigate the molecular mechanisms that control tumour cell resistance and to search for molecules that could overcome Fas ligand (FasL) or CH-11 resistance in certain tumours, including glioma and melanoma. 2. Twelve tumour cell lines were examined for their sensitivity to CH-11-induced apoptosis and then two of each of the CH-11-sensitive and -resistant tumour cell lines were analysed for Fas-mediated death-inducing signalling complex (DISC). The calmodulin kinase II (CaMKII) inhibitor KN-93 and the chemotherapeutic drug cisplatin were used to treat resistant cells; the effects of these two drugs on CH-11-resistant tumour cells were investigated. 3. In CH-11-sensitive tumour cells, apoptosis-initiating caspase 8 and caspase 10 were recruited to the DISC, where they became activated through autocatalytic cleavage, leading to apoptosis through cleavage of downstream substrates, such as caspase 3 and DNA fragmentation factor 45. 4. In CH-11-resistant cells, cellular Fas-associated death domain-like interleukin-1b-converting enzyme inhibitory protein (c-FLIP) proteins were recruited to the DISC, resulting in inhibition of caspase 8 and caspase 10 cleavage. The c-protein expression and phosphorylation of FLIP and CaMKII protein and enzyme activity were upregulated in resistant cells. Treatment of resistant cells with 100 micromol/L KN-93 and 10 microg/mL cisplatin downregulated c-FLIP expression, inhibited c-FLIP phosphorylation and rescued CH-11 sensitivity. 5. In conclusion, KN-93 and cisplatin inhibit c-FLIP protein expression and phosphorylation restores CH-11-induced apoptosis in tumour cells. tHe present study provides evidence for the use of a new combination therapeutic strategy in the treatment of malignant tumours.
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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".