Toll-like receptor 7 regulates pancreatic carcinogenesis in mice and humans
Bibliographic record
Abstract
Pancreatic ductal adenocarcinoma is an aggressive cancer that interacts with stromal cells to produce a highly inflammatory tumor microenvironment that promotes tumor growth and invasiveness. The precise interplay between tumor and stroma remains poorly understood. TLRs mediate interactions between environmental stimuli and innate immunity and trigger proinflammatory signaling cascades. Our finding that TLR7 expression is upregulated in both epithelial and stromal compartments in human and murine pancreatic cancer led us to postulate that carcinogenesis is dependent on TLR7 signaling. In a mouse model of pancreatic cancer, TLR7 ligation vigorously accelerated tumor progression and induced loss of expression of PTEN, p16, and cyclin D1 and upregulation of p21, p27, p53, c-Myc, SHPTP1, TGF-β, PPARγ, and cyclin B1. Furthermore, TLR7 ligation induced STAT3 activation and interfaced with Notch as well as canonical NF-κB and MAP kinase pathways, but downregulated expression of Notch target genes. Moreover, blockade of TLR7 protected against carcinogenesis. Since pancreatic tumorigenesis requires stromal expansion, we proposed that TLR7 ligation modulates pancreatic cancer by driving stromal inflammation. Accordingly, we found that mice lacking TLR7 exclusively within their inflammatory cells were protected from neoplasia. These data suggest that targeting TLR7 holds promise for treatment of human pancreatic cancer.
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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 | 0.004 | 0.003 |
| 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".