Expression of Hepatocyte Growth Factor and Its Receptor Met in Wilms' Tumors and Nephrogenic Rests Reflects Their Roles in Kidney Development
Bibliographic record
Abstract
PURPOSE: Hepatocyte growth factor (HGF) and its receptor Met are known to play diverse roles in both organogenesis and cancer. Wilms' tumor (WT) is a prototype for the link between abrogated development and neoplasia, with dysregulation of growth factor/receptor pathways playing key roles. Despite this, an understanding of the HGF/Met axis in the process is lacking. EXPERIMENTAL DESIGN: Observing copy number alterations at the loci for these genes in WTs and their precursor lesions nephrogenic rests, we examined protein expression by immunohistochemistry and investigated the effects of HGF on an in vitro model of kidney development. RESULTS: HGF was preferentially expressed in the blastemal cells of nephrogenic rests but not WTs. Met expression was infrequent and restricted to well-differentiated epithelial cells and stroma in both lesions. In an independent cohort of favorable histology WTs on a tissue microarray, HGF was expressed in 15 of 193 (8%) cases and correlated with a predominance of epithelial cells, whereas Met expression was observed in 25 of 179 (14%) cases and was associated with stromal subtypes. In a mouse mesonephric cell line model, we observed Met expression in culture conditions reflecting both mesenchymal and epithelial differentiation, whereas HGF was up-regulated in association with acquisition of a more epithelial-like phenotype. This could be mimicked by exogenous exposure of mesenchymal-like cells to recombinant HGF. CONCLUSIONS: These data show that the relatively infrequent expression of HGF and Met in WT tumorigenesis reflects their roles in nephrogenesis, particularly the mesenchymal-to-epithelial transition, rather than a dependence on oncogenic signaling pathways.
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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 | 0.001 | 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".