Cross-ancestral GWAS identifies 29 novel variants across Head and Neck Cancer subsites
Bibliographic record
Abstract
Abstract In this multi-ancestry genome-wide association study (GWAS) and fine mapping study of head and neck squamous cell carcinoma (HNSCC) subsites, we analysed 19,073 cases and 38,857 controls and identified 29 independent novel loci. We provide robust evidence that a 3’ UTR variant in TP53 (rs78378222, T>G) confers a 40% reduction in odds of developing overall HNSCC. We further examine the gene-environment relationship of BRCA2 and ADH1B variants demonstrating their effects act through both smoking and alcohol use. Through analyses focused on the human leukocyte antigen (HLA) region, we highlight that although human papilloma virus (HPV)(+) oropharyngeal cancer (OPC), HPV(-) OPC and oral cavity cancer (OC) all show GWAS signal at 6p21, each subsite has distinct associations at the variant, amino acid, and 4-digit allele level. We also defined the specific amino acid changes underlying the well-known DRB1*13:01-DQA1*01:03-DQB1*06:03 protective haplotype for HPV(+) OPC. We show greater heritability of HPV(+) OPC compared to other subsites, likely to be explained by HLA effects. These findings advance our understanding of the genetic architecture of head and neck squamous cell carcinoma, providing important insights into the role of genetic variation across ancestries, tumor subsites, and gene-environment interactions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".