Role of epithelial cell fibroblast growth factor receptor substrate 2α in prostate development, regeneration and tumorigenesis
Bibliographic record
Abstract
The fibroblast growth factor (FGF) regulates a broad spectrum of biological activities by activation of transmembrane FGF receptor (FGFR) tyrosine kinases and their coupled intracellular signaling pathways. FGF receptor substrate 2alpha (FRS2alpha) is an FGFR interactive adaptor protein that links multiple signaling pathways to the activated FGFR kinase. We previously showed that FGFR2 in the prostate epithelium is important for branching morphogenesis and for the acquisition of the androgen responsiveness. Here we show in mice that FRS2alpha is uniformly expressed in the epithelial cells of developing prostates, whereas it is expressed only in basal cells of the mature prostate epithelium. However, expression of FRS2alpha was apparent in luminal epithelial cells of regenerating prostates and prostate tumors. To investigate FRS2alpha function in the prostate, the Frs2alpha alleles were ablated specifically in the prostatic epithelial precursor cells during prostate development. Similar to the ablation of Fgfr2, ablation of Frs2alpha disrupted MAP kinase activation, impaired prostatic ductal branching morphogenesis and compromised cell proliferation. Unlike the Fgfr2 ablation, disrupting Frs2alpha had no effect on the response of the prostate to androgens. More importantly, ablation of Frs2alpha inhibited prostatic tumorigenesis induced by oncogenic viral proteins. The results suggest that FRS2alpha-mediated signals in prostate epithelial cells promote branching morphogenesis and proliferation, and that aberrant activation of FRS2-linked pathways might promote tumorigenesis. Thus, the prostate-specific Frs2alpha(cn) mice provide a useful animal model for scrutinizing the molecular mechanisms underlying prostatic development and tumorigenesis.
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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".