Arsenic-related DNA copy-number alterations in lung squamous cell carcinomas
Bibliographic record
Abstract
BACKGROUND: Lung squamous cell carcinomas (SqCCs) occur at higher rates following arsenic exposure. Somatic DNA copy-number alterations (CNAs) are understood to be critical drivers in several tumour types. We have assembled a rare panel of lung tumours from a population with chronic arsenic exposure, including SqCC tumours from patients with no smoking history. METHODS: Fifty-two lung SqCCs were analysed by whole-genome tiling-set array comparative genomic hybridisation. Twenty-two were derived from arsenic-exposed patients from Northern Chile (10 never smokers and 12 smokers). Thirty additional cases were obtained for comparison from North American smokers without arsenic exposure. Twenty-two blood samples from healthy individuals from Northern Chile were examined to identify germline DNA copy-number variations (CNVs) that could be excluded from analysis. RESULTS: We identified multiple CNAs associated with arsenic exposure. These alterations were not attributable to either smoking status or CNVs. DNA losses at chromosomes 1q21.1, 7p22.3, 9q12, and 19q13.31 represented the most recurrent events. An arsenic-associated gain at 19q13.33 contains genes previously identified as oncogene candidates. CONCLUSIONS: Our results provide a comprehensive approach to molecular characteristics of the arsenic-exposed lung cancer genome and the non-smoking lung SqCC genome. The distinct and recurrent arsenic-related alterations suggest that this group of tumours may be considered as a separate disease subclass.
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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 | 0.000 | 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) | 0.000 | 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".