Characterization of 5-Fluorouracil-Resistant Cholangiocarcinoma Cell Lines
Bibliographic record
Abstract
BACKGROUND: Although 5-fluorouracil (5-FU) is the drug of choice for the palliative treatment of cholangiocarcinoma (CCA), resistance to the drug is a therapeutic obstacle. The aim of this study was to explore the mechanisms underlying 5-FU resistance of CCA using cell lines derived from CCA associated with liver fluke infection. METHODS: A stepwise exposure was used for inducing 5-FU-resistant CCA cell lines, and the expression of nine genes associated with 5-FU resistance was analyzed using real-time (RT)-PCR. RESULTS: Altered expression of several genes involved in 5-FU resistance in CCA cell lines was observed. The expression levels of almost all target genes investigated including TP, DPD, ENT1, UNG1, TOP2A, BIRC5, TP73 and DeltaNp73 appeared to be significantly altered in these resistant strains. The expression of the TS gene tended to be increased but the fold change was not significantly different from their parental cell lines. UNG1 (a DNA repairing enzyme) and BIRC5 (an apoptotic inhibitor) expressions were increased whereas TP73 (a proapoptotic factor) expression levels decreased concomitantly. CONCLUSION: Our study showed that increases in UNG1 and BIRC5 expression and concomitant decreases in TP73 expression may be associated with development of acquired 5-FU resistance in CCA lines and their phenotypes.
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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 | 0.001 | 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".