Association of an intact E2 gene with higher HPV viral load, higher viral oncogene expression, and improved clinical outcome in HPV16 positive head and neck squamous cell carcinoma
Bibliographic record
Abstract
To assess the relationship of E2 gene disruption with viral gene expression and clinical outcome in human papillomavirus (HPV) positive head and neck squamous cell carcinoma, we evaluated 31 oropharyngeal and 17 non-oropharyngeal HPV16 positive carcinomas using two PCR-based methods to test for disruption of E2, followed by Sanger sequencing. Expression of HPV16 E6, E7 and E2 transcripts, along with cellular ARF and INK4A, were also assessed by RT-qPCR. Associations between E2 disruption, E2/E6/E7 expression, and clinical outcome were evaluated by Kaplan-Meier analysis for loco-regional recurrence and disease-specific survival. The majority (n = 21, 68%) of HPV16 positive oropharyngeal carcinomas had an intact E2 gene, whereas the majority of HPV16 positive non-oropharyngeal carcinomas (n = 10, 59%) had a disrupted E2 gene. Three of the oropharyngeal tumors and two of the non-oropharyngeal tumors had deletions within E2. Detection of an intact E2 gene was associated with a higher DNA viral load and increased E2/E6/E7, ARF and INK4A expression in oropharyngeal tumors. Oropharyngeal carcinomas with an intact E2 had a lower risk of loco-regional recurrence (log-rank p = 0.04) and improved disease-specific survival (p = 0.03) compared to tumors with disrupted E2. In addition, high E7 expression was associated with lower risk of loco-regional recurrence (p = 0.004) as was high E6 expression (p = 0.006). In summary, an intact E2 gene is more common in HPV16 positive oropharyngeal than non-oropharyngeal carcinomas; the presence of an intact E2 gene is associated with higher HPV viral load, higher viral oncogene expression, and improved clinical outcome compared to patients with a disrupted E2 gene in oropharyngeal cancer.
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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 | 0.001 |
| 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".