Genetic sequence variants and the development of secondary primary cancers in patients with head and neck cancers
Bibliographic record
Abstract
BACKGROUND: Secondary primary cancers (SPCs), a major cause of morbidity and mortality in head and neck cancers (HNCs), are commonly associated with field cancerization. We comprehensively evaluated 23 germline sequence variants (from published literature) in 17 genes from 7 biological pathways associated with the HNC survival. Because cancer prognosis correlates with disease aggressiveness, the factors that determine aggressive disease may influence field cancerization process to favor SPC development. We thus hypothesized that the same sequence variants associated with HNC survival can also be associated with SPC. METHODS: Germline DNA from 531 stage I-II radiation-treated HNC patients (originally recruited for an alpha-tocopherol/beta-carotene placebo-controlled secondary prevention clinical trial) were genotyped, and analyzed using Cox proportional hazards models, stratified by treatment arm, adjusting for clinical prognostic factors. RESULTS: The majority of SPCs were of lung and HNCs. Median follow-up time was 5 years. SPCs were diagnosed in 21% of patients. The 5-year SPC-free survival was 79%. All but 1 evaluated sequence variant were not associated with SPC. There was a strong association of the DNA (cytosine-5-)-methyltransferase 3 beta (DNMT3B) sequence variant, DNMT3B:C149T (rs2424913) with SPC: the adjusted hazard ratio (aHR) for TT versus CC was 2.23 (1.32-3.78; P = .003), whereas each variant T allele was associated with an aHR of 1.49 (1.15-1.95; P = .003). CONCLUSIONS: A functional sequence variant in DNMT3B is associated with the development of SPCs in HNC early stage patients treated with radiation. Aberrant DNA methylation may be an important modulator of SPC development in at-risk individuals with HNCs.
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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".