Methylation of viral and host genes and severity of cervical lesions associated with human papillomavirus type 16
Bibliographic record
Abstract
Methylation of human papillomavirus (HPV) and host genes may predict cervical cancer risk. We examined the methylation status of selected sites in HPV16 and human genes in DNA extracted from exfoliated cervical cell samples of 244 women harboring HPV16-positive cancer or cervical intraepithelial neoplasia (CIN) or negative for intraepithelial lesions or malignancy (NILM). We quantified the methylation of CpG sites in the HPV16 L1 gene (CpG 6367 and 6389) and in the human genes EPB41L3 (CpG 438, 427, 425) and LMX1 (CpG 260, 262, 266, 274) following bisulfite treatment and pyrosequencing. Receiver operating characteristic (ROC) curves were used to analyze the diagnostic utility of methylation level for the different sites and for a joint predictor score. Methylation in all sites significantly increased with lesion severity (p < 0.0001). Area under the curve (AUC) was highest among the CIN2/3 vs. cancer ranging from 0.786 to 0.853 among the different sites. Site-specific methylation levels strongly discriminated CIN2/3 from NILM/CIN1 and cancer from CIN2/3 (range of odds ratios [OR]: 3.69-12.76, range of lower 95% confidence bounds: 1.03-4.01). When methylation levels were mutually adjusted for each other EPB41L3 was the only independent predictor of CIN2/3 vs. NILM/CIN1 contrasts (OR = 9.94, 95%CI: 2.46-40.27). High methylation levels of viral and host genes are common among precancerous and cancer lesions and can serve as independent risk biomarkers. Methylation of host genes LMX1 and EPB41L3 and of the viral HPV16 L1 sites has the potential to distinguish among precancerous lesions and to distinguish the latter from invasive disease.
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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 | 0.000 | 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) | 0.000 | 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".