Transforming Growth Factor β1 Promotes Chromosomal Instability in Human Papillomavirus 16 E6E7–Infected Cervical Epithelial Cells
Bibliographic record
Abstract
Uterine cervical cancer, the second most frequently occurring cancer in women worldwide, is tightly associated with the expression of high-risk human papillomavirus [mainly human papillomavirus (HPV)-16 and HPV18] oncogenes E6 and E7 and characteristically exhibits chromosomal instability. However, the mechanisms underlying chromosomal instability in cervical cancer are still not fully understood. In this study, we observed that two of three human cervical epithelial cell lines expressing HPV16 E6E7 became immortalized without extensive chromosomal instability and crisis. The introduction of transforming growth factor (TGF)-beta1, a multiple functional cytokine/growth factor, in the culture medium induced crisis, which was associated with massive chromosomal end-to-end fusions and other structural aberrations. The distributions of structural aberrations on individual chromosomes were significantly correlated with the profiles of telomere signal-free ends. The immortalized cells that emerged from the TGF-beta1-induced crisis showed multiple clonal structural aberrations that were not observed in cells without TGF-beta1 treatment. Overexpression of the catalytic subunit of telomerase (hTERT) abolished the effects of TGF-beta1 on chromosomal instability. Interestingly, another HPV16 E6E7-expressing cervical cell line that experienced crisis and telomere dysfunction under ordinary culture condition had a higher level of autocrine TGF-beta1 production than the other two crisis-free immortalized cell lines. Blocking the TGF-beta1 pathway by an inhibitor of TGF-beta1 receptor type I prevented the crisis and telomere-mediated chromosomal instability. In addition, more dramatic telomere shortening was observed in cervical intraepithelial neoplasias having higher expression of TGF-beta1 in vivo. These results together suggest an important role of TGF-beta1 in the early process of cervical carcinogenesis.
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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".