Nonpromoter methylation of the CDKN2A gene with active transcription is associated with improved locoregional control in laryngeal squamous cell carcinoma
Bibliographic record
Abstract
We previously reported a novel association between CDKN2A nonpromoter methylation and transcription (ARF/INK4a) in human papillomavirus associated oropharyngeal tumors. In this study we assessed whether nonpromoter CDKN2A methylation in laryngeal squamous cell carcinomas (LXSCC) conferred a similar association with transcription that predicted patient outcome. We compared DNA methylation and ARF/INK4a RNA expression levels for the CDKN2A locus using the Illumina HumanMethylation27 beadchip and RT-PCR in 43 LXSCC tumor samples collected from a prospective study of head and neck cancer patients treated at Montefiore Medical Center (MMC). Validation was performed using RNAseq data on 111 LXSCC tumor samples from the Cancer Genome Atlas (TCGA). The clinical relevance of combined nonpromoter CDKN2A methylation and transcription was assessed by multivariate Cox regression for locoregional recurrence on a subset of 69 LXSCC patients with complete clinicopathologic data from the MMC and TCGA cohorts. We found evidence of CDKN2A nonpromoter hypermethylation in a third of LXSCC from our MMC cohort, which was significantly associated with increased ARF and INK4a RNA expression (Wilcoxon rank-sum, P = 0.007 and 0.003, respectively). A similar association was confirmed in TCGA samples (Wilcoxon rank-sum test P < 0.0001 for ARF and INK4a). Patients with CDKN2A hypermethylation or high ARF/INK4a expression were significantly less likely to develop a locoregional recurrence compared to those with neither of the features, independent of other clinicopatholgic risk factors (adjusted hazard ratio=0.21, 95% confidence interval:0.05-0.81). These results support the conclusion that CDKN2A nonpromoter methylation is associated with increased ARF and INK4a RNA expression, and improved locoregional control in LXSCC.
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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".