Molecular features of T and N stage progression in laryngeal cancer
Bibliographic record
Abstract
Laryngeal squamous cell cancer (LSCC) is a common type of head and neck cancer that is typically unrelated to human papilloma virus (HPV) infection. Late-stage laryngeal cancers are associated with greater morbidity due to obstructive symptoms, and poorer overall survival. Using data from The Cancer Genome Atlas (TCGA), we analyzed 112 patient LSCC samples, comparing patient proteome, transcriptome and genome between early and late T and N samples. We observed significant differences in SNV frequency for various genes between the early and late-stage groups. Most notably we observed that NOTCH1 mutation, which was more frequent in late N-stage supraglottic cancers, was also associated with poorer patient survival in LSCCs. Methylation analysis also revealed changes in JUN gene methylation in late N glottic cancers. Transcriptomic analysis revealed differential expression in c-JUN, HOXB7 and HOXB9 transcript levels, suggesting potential involvement of these pathways in progression and nodal involvement. Our findings illustrate that LSCC undergoes distinct molecular changes associated with different stages and subsites. We observed multiple potential markers for progression, metastases and survival, including NOTCH1 mutation, which may aid as prognostic indicators in future studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".