Molecular alterations associated with chronic exposure to cigarette smoke and chewing tobacco in normal oral keratinocytes
Bibliographic record
Abstract
Tobacco usage is a known risk factor associated with development of oral cancer. It is mainly consumed in two different forms (smoking and chewing) that vary in their composition and methods of intake. Despite being the leading cause of oral cancer, molecular alterations induced by tobacco are poorly understood. To investigate the adverse effects of cigarette smoke/chewing tobacco exposure in oral keratinocytes, we developed two cellular models where normal oral keratinocytes were chronically exposed to cigarette smoke and chewing tobacco for a period of 8 months. Cellular assays reveal that OKF6/TERT1 cells acquire an oncogenic phenotype after chronic exposure to cigarette smoke/chewing tobacco. We employed both whole exome sequencing (WES) and quantitative proteomics approaches to investigate the molecular alterations in oral keratinocytes (OKF6/TERT1) chronically exposed to smoke and chewing tobacco. Exome sequencing revealed a much higher rate of C>A transversions in smoke exposed cells in conjunction with previous studies. In contrast, C>G transversions were observed to be higher in chewing tobacco exposed cells. Diverse mutations in both treated cells further highlight the distinct effects of each exposure. Distinct proteomic alterations were observed in smoke and chewing tobacco exposed cells compared to parental cells. In addition, we observe enrichment of different signaling cascades in transformed oral cells upon chronic exposure to either cigarette smoke or chewing tobacco. Current analysis defines a clear distinction in the molecular dysregulation in oral cells in response to different tobacco-based insults. Future studies are needed to validate some of the genetic and proteomic alterations unique to each form of tobacco exposure. This study can serve as a reference for fundamental damage on oral cells as a consequence of exposure to different forms of tobacco.
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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 | 0.000 | 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) | 0.001 | 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".