Thirdhand smoke exposure promotes gastric tumor development in mouse and human
Bibliographic record
Abstract
The pollution of indoor environments and the consequent health risks associated with thirdhand smoke (THS) are increasingly recognized in recent years. However, the carcinogenic potential of THS and its underlying mechanisms have yet to be thoroughly explored. In this study, we examined the effects of short-term THS exposure on the development of gastric cancer (GC) in vitro and in vivo. In a mouse model of spontaneous GC, CC036, we observed a significant increase in gastric tumor incidence and a decrease in tumor-free survival upon THS exposure as compared to control. RNA sequencing of primary gastric epithelial cells derived from CC036 mice showed that THS exposure increased expression of genes related to the extracellular matrix and cytoskeletal protein structure. We then identified a THS exposure-induced 91-gene expression signature in CC036 and a homologous 84-gene signature in human GC patients that predicted the prognosis, with secreted phosphoprotein 1 (SPP1) and tribbles pseudokinase 3 (TRIB3) emerging as potential targets through which THS may promote gastric carcinogenesis. We also treated human GC cell lines in vitro with media containing various concentrations of THS, which, in some exposure dose range, significantly increased their proliferation, invasion, and migration. We showed that THS exposure could activate the epithelial-mesenchymal transition (EMT) pathway at the transcript and protein level. We conclude that short-term exposure to THS is associated with an increased risk of GC and that activation of the EMT program could be one potential mechanism. Increased understanding of the cancer risk associated with THS exposure will help identify new preventive and therapeutic strategies for tobacco-related disease as well as provide scientific evidence and rationale for policy decisions related to THS pollution control to protect vulnerable subpopulations such as children.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".