Multi-Omics Analysis to Characterize Cigarette Smoke Induced Molecular Alterations in Esophageal Cells
Bibliographic record
Abstract
Though smoking remains one of the established risk factors of esophageal squamous cell carcinoma, there is limited data on molecular alterations associated with cigarette smoke exposure in esophageal cells. To investigate molecular alterations associated with chronic exposure to cigarette smoke, non-neoplastic human esophageal epithelial cells were treated with cigarette smoke condensate (CSC) for up to 8 months. Chronic treatment with CSC increased cell proliferation and invasive ability of non-neoplastic esophageal cells. Whole exome sequence analysis of CSC treated cells revealed several mutations and copy number variations. This included loss of high mobility group nucleosomal binding domain 2 (HMGN2) and a missense variant in mediator complex subunit 1 (MED1). Both these genes play an important role in DNA repair. Global proteomic and phosphoproteomic profiling of CSC treated cells lead to the identification of 38 differentially expressed and 171 differentially phosphorylated proteins. Bioinformatics analysis of differentially expressed proteins and phosphoproteins revealed that most of these proteins are associated with DNA damage response pathway. Proteomics data revealed decreased expression of HMGN2 and hypophosphorylation of MED1. Exogenous expression of HMGN2 and MED1 lead to decreased proliferative and invasive ability of smoke exposed cells. Immunohistochemical labeling of HMGN2 in primary ESCC tumor tissue sections (from smokers) showed no detectable expression while strong to moderate staining of HMGN2 was observed in normal esophageal tissues. Our data suggests that cigarette smoke perturbs expression of proteins associated with DNA damage response pathways which might play a vital role in development of ESCC.
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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 | 0.001 |
| 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) | 0.000 | 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".