HPV and methylation indicators in paired tumor and saliva in HNSCC
Bibliographic record
Abstract
Human papilloma virus type 16 (HPV16) is a causative agent for some head and neck squamous cell carcinoma (HNSCC) and an independent risk factor for oropharyngeal SCC. The goal of this study was to examine HPV16 associated gene methylation in paired saliva and tumor DNA with assessment of the sensitivity, specificity, positive predictive, and negative predictive value for saliva HPV as a test for HNSCC. HPV16 status was determined by quantitative PCR (qPCR) in 35 primary HNSCC paired tumor and saliva specimens. Tumor cut points >=0.03 and >=0.1 and saliva cut points >0 and ?0.001 were used to classify results as HPV positive or negative. Aberrant methylation was determined by the methylation-specific multiplex ligation probe amplification (MS-MLPA) assay. The frequency of promoter hypermethylation in tumor samples was 66% (23/35) versus 17% (6/35) in saliva. Two of 35 paired tumor and saliva samples had commonly methylated genes. HPV and methylation were correlated for IGSF4 (p=0.01) in tumor samples (cut point ?0.03) and for ESR1 in saliva samples (cut point >0). Although the sensitivity of HPV detection in saliva was significantly reduced when saliva cut points were increased from >0 to >=0.001, the specificity and positive predictive values were 100% at saliva cut point of >=0.001, regardless of tumor cut points. Within clearly defined parameters, HPV detection in saliva DNA shows promise as a non invasive approach for tumor HPV status. Methylated genes detected in saliva may be useful in early detection and as potential predictive markers of HNSCC. Further confirmation and validation in larger cohorts is required.
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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) | 0.001 | 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".