Abstract B15: Genomic and epigenomic events in arsenic-related lung squamous cell carcinomas from smokers and never smokers
Bibliographic record
Abstract
Abstract Background: Arsenic is a well-known human carcinogen. An estimated of 160 million people (∼2% of total human population) are exposed to levels above the recommended threshold (10 μg/L) in Bangladesh, Taiwan, Mongolia, India, China, Argentina, Mexico, Canada, USA, and Chile, among others countries. Skin, bladder, liver, kidney and lungs are the main targets of arsenic carcinogenicity. Lung cancer (LC) is the most deadly form of neoplasia associated to arsenic ingestion. Additionally, lung squamous cell carcinomas (SqCC) occur at higher rates than other LC subtypes following exposure to this metalloid. Both genetic and epigenetic changes (some of them related to arsenic biotransformation) have been proposed to drive carcinogenesis; however, mechanisms are not fully understood. Here, we have compiled a panel of lung tumors from a population with chronic arsenic exposure, including a rare set of lung SqCC from patients who have never smoked. We analyzed to identify whole genome arsenic associated copy-number alterations (CNAs), copy-number variations (CNVs) and global DNA methylation changes. Methods: 52 lung SqCC were analyzed by whole-genome tiling path comparative genomic hybridization for CNA. Twenty-two were from arsenic exposed patients from Chile (10 never smokers and 12 smokers), and 30 additional non-exposed cases were from North America. In addition, 22 blood samples from healthy individuals from Northern Chile were examined to identify naturally occurring germline CNVs. Global DNA methylation analyses for 5 arsenic-exposed cases from never smokers were performed using Illumina's Infinium Human Methylation 450K array. Results: We identified arsenic related CNAs occurring in lung SqCC from patients with chronic exposure to this. The most recurrent events were represented by DNA losses at chromosomes 1q21.1, 7p22.3, 9q12, and 19q13.31. Also, we observed a single arsenic-associated DNA gain at 19q13.33, which contains genes related to single strand DNA breaks repair and neoplastic processes. Interestingly, alterations in this region have been reported to be more frequent among lung adenocarcinomas from never smokers compared with smokers. Additionally, distinctive DNA methylation patterns were associated to arsenic related lung SqCC from never smokers, indicating these changes can have an impact on carcinogenic mechanisms for this subgroup of lung tumors Conclusions: Our study provides insights into the molecular mechanisms of arsenic-induced lung SqCC. Moreover, findings specifically associated to cases among never smokers contribute to understand malignant events occurring in this rare subgroup of lung tumors. The unique and recurrent set of arsenic-associated genetic and epigenetic alterations suggests that this group of tumors may be considered as a distinct disease subclass. Finally, elucidation of the mechanisms underlying the initiation and promotion of carcinogenesis related to arsenic biotransformation processes is of foremost importance to the development of early detection protocols and treatment options for affected individuals.
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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 | 0.001 | 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) | 0.003 | 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".