Toxicogenomic outcomes predictive of forestomach carcinogenesis following exposure to benzo(a)pyrene: Relevance to human cancer risk
Bibliographic record
Abstract
Forestomach tumors are observed in mice exposed to environmental carcinogens. However, the relevance of this data to humans is controversial because humans lack a forestomach. We hypothesize that an understanding of early molecular changes after exposure to a carcinogen in the forestomach will provide mode-of-action information to evaluate the applicability of forestomach cancers to human cancer risk assessment. In the present study we exposed mice to benzo(a)pyrene (BaP), an environmental carcinogen commonly associated with tumors of the rodent forestomach. Toxicogenomic tools were used to profile gene expression response in the forestomach. Adult Muta™Mouse males were orally exposed to 25, 50, and 75 mgBaP/kg-body-weight/day for 28 consecutive days. The forestomach was collected three days post-exposure. DNA microarrays, real-time RT-qPCR arrays, and protein analyses were employed to characterize responses in the forestomach. Microarray results showed altered expression of 414 genes across all treatment groups (± 1.5 fold; false discovery rate adjusted P ≤ 0.05). Significant downregulation of genes associated with phase II xenobiotic metabolism and increased expression of genes implicated in antigen processing and presentation, immune response, chemotaxis, and keratinocyte differentiation were observed in treated groups in a dose-dependent manner. A systematic comparison of the differentially expressed genes in the forestomach from the present study to differentially expressed genes identified in human diseases including human gastrointestinal tract cancers using the NextBio Human Disease Atlas showed significant commonalities between the two models. Our results provide molecular evidence supporting the use of the mouse forestomach model to evaluate chemically-induced gastrointestinal carcinogenesis in humans.
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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) | 0.001 | 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".