Interaction of Nuclear Receptors with the Wnt/β-Catenin/Tcf Signaling Axis: Wnt You Like to Know?
Bibliographic record
Abstract
The cross-regulation of Wnt/beta-catenin/Tcf ligands, kinases, and transcription factors with members of the nuclear receptor (NR) family has emerged as a clinically and developmentally important area of endocrine cell biology. Interactions between these signaling pathways result in a diverse array of cellular effects including altered cellular adhesion, tissue morphogenesis, and oncogenesis. Analyses of NR interactions with canonical Wnt signaling reveal two broad themes: Wnt/beta-catenin modulation of NRs (theme I), and ligand-dependent NR inhibition of the Wnt/beta-catenin/Tcf cascade (theme II). Beta-catenin, a promiscuous Wnt signaling member, has been studied intensively in relation to the androgen receptor (AR). Beta-catenin acts as a coactivator of AR transcription and is also involved in co-trafficking, increasing cell proliferation, and prostate pathogenesis. T cell factor, a transcriptional mediator of beta-catenin and AR, engages in a dynamic reciprocity of nuclear beta-catenin, p300/CREB binding protein, and transcriptional initiation factor 2/GC receptor-interaction protein, thereby facilitating hormone-dependent coactivation and transrepression. Beta-catenin responds in an equally dynamic manner with other NRs, including the retinoic acid (RA) receptor (RAR), vitamin D receptor (VDR), glucocorticoid receptor (GR), progesterone receptor, thyroid receptor (TR), estrogen receptor (ER), and peroxisome proliferator-activated receptor (PPAR). The NR ligands, vitamin D(3), trans/cis RA, glucocorticoids, and thiazolidines, induce dramatic changes in the physiology of cells harboring high Wnt/beta-catenin/Tcf activity. Wnt signaling regulates, directly or indirectly, developmental processes such as ductal branching and adipogenesis, two processes dependent on NR function. Beta-catenin has been intensively studied in colorectal cancer; however, it is now evident that beta-catenin may be important in cancers of the breast, prostate, and thyroid. This review will focus on the cross-regulation of AR and Wnt/beta-catenin/Tcf but will also consider the dynamic manner in which RAR/RXR, GR, TR, VDR, ER, and PPAR modulate canonical Wnt signaling. Although many commonalities exist by which NRs interact with the Wnt/beta-catenin signaling pathway, striking cell line and tissue-specific differences require deciphering and application to endocrine pathology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".