Sequence dependence of MEK inhibitor AZD6244 combined with gemcitabine for treatment of biliary cancer.
Bibliographic record
Abstract
196 Background: MEK inhibition has clinical activity against biliary tract cancers, and might therefore be successfully combined with gemcitabine; one of the most active chemotherapy agents for these cancers. As gemcitabine is active in S-phase, and the ERK pathway has a major role driving cell cycle progression, concurrent use of a MEK inhibitor could potentially antagonize the effect of gemcitabine. We therefore tested the sequence dependence of the combination of gemcitabine and the MEK inhibitor AZD6244 in vitro and in vivo. Methods: Two biliary tract cancer cell lines and 4 xenografts established from patients were used in this study. In vitro, cell cycle effects of AZD6244 and their impact on gemcitabine sensitivity were detected by Flow cytometry, EdU uptake assay, MTS assay and Clonogenic survival assay. In vivo, tumor-bearing SCID mice were treated for 48hr with AZD6244 and then monitored for 48hr off treatment. Plasma and tumor drug levels were assessed by LC-MS. The time course for recovery of ERK signaling, cell cycle distribution and cell proliferation were measured by Immunofluorescence staining, Flow cytometry, EdU uptake assay and 18F-FLT PET imaging. Based on these results, two different treatment schedules combining AZD6244 with gemcitabine were tested in four different biliary tract cancer models. Results: DNA synthesis was suppressed during treatment with AZD6244, and re-entry into S-phase was delayed by 15hr in vitro and 48hr post-treatment in vivo. Concurrent treatment showed antagonistic effect (IC50=2.02±0.91uM) compared to gemcitabine alone (IC50=0.09±0.04uM) whereas when gemcitabine treatment was delayed for 24 hr after AZD6244 removal, enhanced cytotoxic effect was observed (IC50=0.051± 0.012uM). Consistantly, strong schedule dependence was seen in all four biliary cancer models tested: combined treatment with AZD6244 plus gemcitabine exerts enhanced antitumor effect when gemcitabine is given following a 48hr interruption in AZD6244 dosing, rather than concurrently. Conclusions: The combination of AZD6244 plus gemcitabine is highly schedule dependent, and predicted to be more effective in the clinic using sequential rather than simultaneous dosing protocols.
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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".