Cytochrome P450 1B1 Overexpression in Cervical Cancers: Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: Current standard treatments for patients with recurrent cervical cancer are not very effective and are associated with severe toxicity. Recently, the rational approach for the discovery of new therapies for cervical cancer is based on the alterations in the molecular biology of cancer cells. One of the emerging molecular changes in cancer cells is the aberrant expression of cytochrome P450 1B1 (CYP1B1). This unique enzyme has been reported to be selectively overexpressed in several cancers. OBJECTIVE: The aim of this study was to examine CYP1B1 expression in cervical cancers and to assess the enzyme's relationship with several clinicopathological features. METHODS: Immunohistochemistry was performed to examine CYP1B1 expression in 100 patient samples with cervical cancer and 10 patient samples with normal healthy cervical tissues. RESULTS: CYP1B1 was expressed in the majority of the cervical cancer samples (91/100, 91.0%) but not in normal healthy cervical samples. The difference in the expression of CYP1B1 between healthy and tumorous cervical tissues was significant (P=.01). Moreover, the frequency of CYP1B1 expression was found to be significantly higher in patients with advanced grades of the disease (P=.03) and in patients having metastasis to the lymph nodes (P=.01). Surprisingly, there was a significantly higher expression of CYP1B1 in patients with a high prevalence of human papilloma virus 16/18 (P=.04). CONCLUSIONS: The differential profile of CYP1B1 expression between cervical cancer tissues and normal cervical tissues suggests that CYP1B1 may be used as a target for future therapeutic exploitations.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| 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 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".