Suppressing Wnt Signaling by the Hedgehog Pathway through sFRP-1
Bibliographic record
Abstract
The hedgehog (Hh) signaling pathway is essential for embryonic development and carcinogenesis. Activation of Hh signaling has been identified in several types of gastrointestinal cancers, including esophageal, gastric, pancreatic, and liver cancers. Several recent studies suggest that Hh signaling activation can inhibit Wnt signaling. However, the molecular basis underlying this inhibition remains unclear. As transcription factors in the Hh signaling pathway, Gli molecules transform cells in culture, and their expression are associated with cancer development. Here we report that expression of a secreted frizzled-related protein-sFRP-1 in mouse embryonic fibroblasts is dependent on Gli1 and Gli2. In human gastric cancer cells, inhibition of Hh signaling reduces the level of sFRP-1 transcript, whereas ectopic expression of Gli1 increases the level of sFRP-1 transcript. Results from chromatin immunoprecipitation indicate that Gli1 is involved in transcriptional regulation of sFRP-1. In 293 cells with Gli1 expression, Wnt-1-mediated beta-catenin accumulation in the cytosol and DKK1 expression are all abrogated, which can be reversed by inhibiting sFRP-1 expression. Furthermore, while SIIA cells do not respond to Wnt-1-conditioned medium, inhibition of Hh signaling by smoothened (SMO) antagonist KAAD-cyclopamine (keto-N-aminoethylaminocaproyldihydrocinnamoylcyclopamine) leads to Wnt1-mediated beta-catenin accumulation in the cytosol. These data indicate that sFRP-1, a target gene of the hedgehog pathway, is involved in cross-talk between the hedgehog pathway and the Wnt pathway.
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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".