Wnt5a Signals through DVL1 to Repress Ribosomal DNA Transcription by RNA Polymerase I
Bibliographic record
Abstract
Ribosome biogenesis is essential for cell growth and proliferation and is commonly elevated in cancer. Accordingly, numerous oncogene and tumor suppressor signaling pathways target rRNA synthesis. In breast cancer, non-canonical Wnt signaling by Wnt5a has been reported to antagonize tumor growth. Here, we show that Wnt5a rapidly represses rDNA gene transcription in breast cancer cells and generates a chromatin state with reduced transcription of rDNA by RNA polymerase I (Pol I). These effects were specifically dependent on Dishevelled1 (DVL1), which accumulates in nucleolar organizer regions (NORs) and binds to rDNA regions of the chromosome. Upon DVL1 binding, the Pol I transcription activator and deacetylase Sirtuin 7 (SIRT7) releases from rDNA loci, concomitant with disassembly of Pol I transcription machinery at the rDNA promoter. These findings reveal that Wnt5a signals through DVL1 to suppress rRNA transcription. This provides a novel mechanism for how Wnt5a exerts tumor suppressive effects and why disruption of Wnt5a signaling enhances mammary tumor growth in vivo.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".