Impact of the Chemotherapy Cocktail Used to Treat Testicular Cancer on the Gene Expression Profile of Germ Cells from Male Brown-Norway Rats1
Bibliographic record
Abstract
Advances in treatment for testicular cancer that include the coadministration of bleomycin, etoposide, and cisplatin (BEP) have brought the cure rate to higher than 90%%. The goal of this study was to elucidate the impact of BEP treatment on gene expression in male germ cells. Brown-Norway rats were treated for 9 wk with vehicle (0x) or BEP at doses equivalent to 0.3x and 0.6x the human dose. At the end of treatment, spermatogenesis was affected, showing altered histology and a decreased sperm count; spermatozoa had a higher number of DNA breaks. After 9 wk of treatment, round spermatids were isolated, and RNA was extracted and probed on Rat230-2.0 Affymetrix arrays. Of the 31 099 probe sets present on the array, 59%% were expressed in control round spermatids. BEP treatment significantly altered the expression of 221 probe sets, with at least a 1.5-fold change compared with controls; 80% were upregulated. We observed a dose-dependent increase in the expression of oxidative stress response genes and no change in the expression of genes involved in DNA repair. BEP upregulated genes were implicated in pathways related to Jun and Junb protooncogenes. Increased mRNA levels of Jun and Junb were confirmed by quantitative RT-PCR; furthermore, JUN protein was increased in elongating spermatids. Thus, BEP exposure triggers an oxidative stress response in round spermatids and induces many pathways that may lead to the survival of damaged cells and production of abnormal sperm.
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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) | 0.002 | 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".