Effects of Four Chemotherapeutic Agents, Bleomycin, Etoposide, Cisplatin, and Cyclophosphamide, on DNA Damage and Telomeres in a Mouse Spermatogonial Cell Line1
Bibliographic record
Abstract
Treatment with chemotherapeutics agents may induce persistent DNA damage in male germ cells with the possibility of long-term consequences on fertility and progeny outcome. Telomeres, specialized structures at the physical ends of chromosomes, play an important role in the maintenance of genetic stability and in the response of somatic cells to anticancer drugs. Our objective was to test the hypothesis that exposure to bleomycin, etoposide, or cisplatin (the drugs used to treat testicular cancer) or cyclophosphamide (an anticancer agent and immunosuppressant) targets telomeres in the male germ line. C18-4 spermatogonial cells were exposed to bleomycin, etoposide, cisplatin, or 4-hydroperoxycyclophosphamide (4OOH-CPA, a preactivated analog of cyclophosphamide). All four anticancer drugs induced a significant increase in DNA damage in C18-4 cells, as assessed by gamma-H2AX immunofluorescence. Interestingly, the gamma-H2AX signal was localized to telomeres after treatment with bleomycin, cisplatin, and 4OOH-CPA, but not etoposide. Mean telomere lengths, the intensity of the telomere fluorescence in situ hybridization signal, telomerase activity, and the expression of the telomerase enzyme mRNA components, Tert and Terc, were reduced by exposure to cisplatin and 4OOH-CPA, but not by bleomycin or etoposide. Thus, although all four anticancer drugs induced DNA damage in this spermatogonial cell line, telomeres were not specifically affected by etoposide and only the two alkylating agents, cisplatin and 4OOH-CPA, induced telomere dysfunction. This telomere dysfunction may contribute to infertility and developmental defects in the offspring.
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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".