Amplification and Overexpression of <i>CACNA1E</i> Correlates with Relapse in Favorable Histology Wilms' Tumors
Bibliographic record
Abstract
PURPOSE: The most well established molecular markers of poor outcome in Wilms' tumor are loss of heterozygosity at chromosomes 1p and/or 16q, although to date no specific genes at these loci have been identified. We have previously shown a link between genomic gain of chromosome 1q and tumor relapse and sought to further elucidate the role of genes on 1q in treatment failure. EXPERIMENTAL DESIGN: Microarray-based comparative genomic hybridization identified a microamplification harboring a single gene (CACNA1E) at 1q25.3 in 6 of 76 (7.9%) Wilms' tumors, correlating with a shorter relapse-free survival (P = 0.0044, log-rank test). Further characterization of this gene was carried out by measuring mRNA and protein expression as well as stable transfection of HEK293 cells. RESULTS: Overexpression of the CACNA1E transcript was associated with DNA copy number (P = 0.0204, ANOVA) and tumor relapse (P = 0.0851, log-rank test). Immunohistochemistry against the protein product Ca(V)2.3 revealed expression localized to the apical membrane in the distal tubules of normal kidney but not to the metanephric blastemal cells of fetal kidney from which Wilms' tumors arise. Nuclear localization in 99 of 160 (61.9%) Wilms' tumor cases correlated with a reduced relapse-free survival, particularly in cases treated with preoperative chemotherapy (P = 0.009, log-rank test). Expression profiling of stably transfected HEK293 cells revealed specific up-regulation of the immediate early response genes EGR1/EGR2/EGR3 and FOS/FOSB, mediated by activation of the MEK/ERK5/Nur77 pathway. CONCLUSIONS: These data identify a unique genetic aberration with direct clinical relevance in Wilms' tumor relapse and provide evidence for a potential novel mechanism of treatment resistance in these tumors.
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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 | 0.000 |
| 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".