Low expression of NSD1, NSD2, and NSD3 define a subset of human papillomavirus-positive oral squamous carcinomas with unfavorable prognosis
Bibliographic record
Abstract
BACKGROUND: Frequent mutations in the nuclear receptor binding SET domain protein 1 (NSD1) gene have been observed in head and neck squamous cell carcinomas (HNSCC). NSD1 encodes a histone 3 lysine-36 methyltransferase. NSD1 mutations are correlated with improved clinical outcomes and increased sensitivity to platinum-based chemotherapy agents in human papillomavirus-negative (HPV-) tumors, despite weak T-cell infiltration. However, the role of NSD1 and related family members NSD2 and NSD3 in human papillomavirus-positive (HPV+) HNSCC is unclear. METHODS: Using data from over 500 HNSCC patients from The Cancer Genome Atlas (TCGA), we compared the relative level of mRNA expression of NSD1, NSD2, and NSD3 in HPV+ and HPV- HNSCC. Correlation analyses were performed between T-cell infiltration and the relative level of expression of NSD1, NSD2, and NSD3 mRNA in HPV+ and HPV- HNSCC. In addition, overall survival outcomes were compared for both the HPV+ and HPV- subsets of patients based on stratification by NSD1, NSD2, and NSD3 expression levels. RESULTS: Expression levels of NSD1, NSD2 or NSD3 were not correlated with altered lymphocyte infiltration in HPV+ HNSCC. More importantly, low expression of NSD1, NSD2, or NSD3 correlated with significantly reduced overall patient survival in HPV+, but not HPV- HNSCC. CONCLUSION: These results starkly illustrate the contrast in molecular features between HPV+ and HPV- HNSCC tumors and suggest that NSD1, NSD2, and NSD3 expression levels should be further investigated as novel clinical metrics for improved prognostication and patient stratification in HPV+ HNSCC.
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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 | 0.000 | 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".