Resistance to Bleomycin in Cancer Cell Lines Is Characterized by Prolonged Doubling Time, Reduced DNA Damage and Evasion of G2/M Arrest and Apoptosis
Bibliographic record
Abstract
BACKGROUND: To establish, characterize and elucidate potential mechanisms of acquired bleomycin (BLM) resistance using human cancer cell lines. Seven BLM-resistant cell lines were established by exposure to escalating BLM concentrations over a period of 16-24 months. IC50 values and cell doubling times were quantified using a real time cytotoxicity assay. COMET and γ-H2AX assays, cell cycle analysis, and apoptosis assessment further investigated the mechanisms of BLM resistance in these cell lines. RESULTS: Compared with parental cell lines, real time cytotoxicity assays revealed 7 to 49 fold increases in IC50 and a mean doubling time increase of 147 % (range 64 %-352%) in BLM-resistant sub-clones (p<0.05 for both). Higher maintenance BLM concentrations were associated with higher IC50 and increased doubling times (p<0.05). Significantly reduced DNA damage (COMET and γ-H2AX assays), G2/M arrest, and apoptosis (p<0.05 for each set of comparison) following high-dose acute BLM exposure was observed in resistant sub-clones, compared with their BLM-sensitive parental counterparts. Three weeks of BLM-free culturing resulted in a partial return to BLM sensitivity in 3/7 BLM-resistant sub-clones (p<0.05). CONCLUSION: Bleomycin resistance may be associated with reduced DNA damage after bleomycin exposure, resulting in reduced G2/M arrest, and reduced apoptosis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".