Array CGH profiling of favourable histology Wilms tumours reveals novel gains and losses associated with relapse
Why this work is in the frame
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Bibliographic record
Abstract
Despite the excellent survival of Wilms tumour patients treated with multimodality therapy, approximately 15% will suffer from tumour relapse, where response rates are markedly reduced. We have carried out microarray-based comparative genomic hybridisation on a series of 76 Wilms tumour samples, enriched for cases which recurred, to identify changes in DNA copy number associated with clinical outcome. Using 1Mb-spaced genome-wide BAC arrays, the most significantly different genomic changes between favourable histology tumours that did (n = 37), and did not (n = 39), subsequently relapse were gains on 1q, and novel deletions at 12q24 and 18q21. Further relapse-associated loci included losses at 1q32.1, 2q36.3-2q37.1, and gain at 13q31. 1q gains correlated strongly with loss of 1p and/or 16q. In 3 of 11 cases with concurrent 1p(-)/1q(+), a breakpoint was identified at 1p13. Multiple low-level sub-megabase gains along the length of 1q were identified using chromosome 1 tiling-path arrays. One such recurrent region at 1q22-q23.1 included candidate genes RAB25, NES, CRABP2, HDGF and NTRK1, which were screened for mRNA expression using quantitative RT-PCR. These data provide a high-resolution catalogue of genomic copy number changes in relapsing favourable histology Wilms tumours.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it