Characterization of a Gemcitabine-Resistant Murine Leukemic Cell Line
Bibliographic record
Abstract
Resistance to cytotoxic nucleoside analogues is a major problem in cancer treatment. The cellular mechanisms involved in this phenomenon have been studied for several years, and some factors have been identified. Various strategies to overcome resistance have been suggested, but none has yet shown efficacy in vivo. We developed a gemcitabine-resistant cell line (L1210 10K) from the murine leukemic L1210 strain (L1210 wt) by continuous exposure to increasing concentrations of gemcitabine. L1210 10K is highly resistant to gemcitabine (14,833-fold), 1-beta-D-arabinofuranosylcytosine (ara-C; 2,100-fold), troxacitabine (>200-fold), and cladribine (160-fold) and slightly resistant to trimidox (7.22-fold), but does not display cross-resistance to fludarabine or nonnucleoside anticancer drugs. Deoxycytidine kinase mRNA was not detected by quantitative real-time reverse transcription-PCR in L1210 10K cells, whereas expression of thymidine kinase 1 and ribonucleotide reductase subunit R2 gene was moderately reduced. L1210 10K cells also demonstrated in vivo resistance to nucleoside analogues: gemcitabine- or ara-C-treated mice carrying L1210 10K had significantly shorter survival than gemcitabine- or ara-C-treated mice carrying L1210 wt (P < 0.05). UA911, a mononucleotide prodrug (pronucleotide) of ara-C was found to significantly sensitize L1210 10K cells in vitro. These results suggest that reduced deoxycytidine kinase expression is a mechanism of resistance to gemcitabine that is relevant in vivo and can be circumvented by a prodrug approach.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".