Chromosome 22q a frequent site of allele loss in head and neck carcinoma
Bibliographic record
Abstract
BACKGROUND: Loss of heterozygosity (LOH) correlates with inactivated tumor suppressor genes. LOH at chromosome arm 22q has been found in a variety of human neoplasms, suggesting that this region contains a tumor suppressor gene(s) other than NF2 important to tumorigenesis. The aim of this study was to evaluate the presence of LOH on chromosome 22q11.2-13 and determine whether there was a relationship between loss in this genomic region and tumor histologic parameters, anatomic site, and survival in patients with squamous cell carcinoma of the head and neck (HNSCC). METHODS: Fifty matched blood and HNSCC tumor samples taken at the time of surgical treatment were evaluated for LOH by use of four microsatellite markers mapping to 22q11.2-q13. Clinical information was available for all patients. The frequency and distribution of LOH was correlated with clinical (age, sex, use of tobacco and alcohol, site of primary tumor, clinical stage, adjuvant therapy and overall survival) and histologic parameters (histopathologic stage, tumor differentiation). RESULTS: LOH at 22q was found in 19 of 50 (38%) informative tumors. The respective incidence of allelic loss for the patients was as follows: 28% at D22S421, 10% at D22S277, 8% at D22S446, and 4% at D22S280. No statistical differences were apparent with a mean follow-up of 30 months. Laryngeal tumors showed a higher incidence of LOH compared with oral tumors. CONCLUSIONS: These results suggest that the D22S277 locus may be closely linked to a tumor suppressor gene (TSG) and involved in upper aerodigestive tract carcinogenesis. In particular, laryngeal tumors may harbor another putative TSG on 22q11.2-q12.3 that may play a role in aggressive stage III/IV disease.
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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 | 0.001 | 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".