Genomic imbalances pinpoint potential oncogenes and tumor suppressors in Wilms tumors
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Wilms tumor (WT) has a not completely elucidated pathogenesis. DNA copy number alterations (CNAs) are common in cancer, and often define key pathogenic events. The aim of this work was to investigate CNAs in order to disclose new candidate genes for Wilms tumorigenesis. RESULTS: Array-CGH of 50 primary WTs without pre-chemotherapy revealed a few recurrent CNAs not previously reported, such as 7q and 20q gains, and 7p loss. Genomic amplifications were exclusively detected in 3 cases of WTs that later relapsed, which also exhibited an increased frequency of gains affecting a 16.2 Mb 1q21.1-q23.2 region, losses at 11p, 11q distal, and 16q, and WT1 deletions. Conversely, aneuploidies of chromosomes 13 and 19 were found only in WTs without further relapse. The 1q21.1-q23.2 gain associated with WT relapse harbours genes such as CHD1L, CRABP2, GJA8, MEX3A and MLLT11 that were found to be over-expressed in WTs. In addition, down-regulation of genes encompassed by focal deletions highlighted new potential tumor suppressors such as CNKSR1, MAN1C1, PAQR7 (1p36), TWIST1, SOSTDC1 (7p14.1-p12.2), BBOX and FIBIN (11p13), and PLCG2 (16q). CONCLUSION: This study confirmed the presence of CNAs previously related to WT and characterized new CNAs found only in few cases. The later were found in higher frequency in relapsed cases, suggesting that they could be associated with WT progression.
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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 | 0.000 | 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) | 0.000 | 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