Classic and Molecular Cytogenetic Analyses Reveal Chromosomal Gains and Losses Correlated with Survival in Head and Neck Cancer Patients
Bibliographic record
Abstract
PURPOSE: Genetic biomarkers of head and neck tumors could be useful for distinguishing among patients with similar clinical and histopathologic characteristics but having differential probabilities of survival. The purpose of this study was to investigate chromosomal alterations in head and neck carcinomas and to correlate the results with clinical and epidemiologic variables. EXPERIMENTAL DESIGN: Cytogenetic analysis of short-term cultures from 64 primary untreated head and neck squamous cell carcinomas was used to determine the overall pattern of chromosome aberrations. A representative subset of tumors was analyzed in detail by spectral karyotyping and/or confirmatory fluorescence in situ hybridization analysis. RESULTS: Recurrent losses of chromosomes Y (26 cases) and 19 (14 cases), and gains of chromosomes 22 (23 cases), 8 and 20 (11 cases each) were observed. The most frequent structural aberration was del(22)(q13.1) followed by rearrangements involving 6q and 12p. The presence of specific cytogenetic aberrations was found to correlate significantly with an unfavorable outcome. There was a significant association between survival and gains in chromosomes 10 (P = 0.008) and 20 (P = 0.002) and losses of chromosomes 15 (P = 0.005) and 22 (P = 0.021). Univariate analysis indicated that acquisition of monosomy 17 was a significant (P = 0.0012) factor for patients with a previous family history of cancer. CONCLUSIONS: The significant associations found in this study emphasize that alterations of distinct regions of the genome may be genetic biomarkers for a poor prognosis. Losses of chromosomes 17 and 22 can be associated with a family history of cancer.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".