WT1 Mutation and 11P15 Loss of Heterozygosity Predict Relapse in Very Low-Risk Wilms Tumors Treated With Surgery Alone: A Children's Oncology Group Study
Bibliographic record
Abstract
PURPOSE: Children's Oncology Group defines very low-risk Wilms tumors (VLRWT) as stage I favorable histology Wilms tumors weighing less than 550 g in children younger than 24 months of age. VLRWTs may be treated with nephrectomy alone. However, 10% to 15% of VLRWTs relapse without chemotherapy. Previous studies suggest that VLRWTs with low WT1 expression and/or 11p15 loss of heterozygosity (LOH) may have increased risk of relapse. The current study validates these findings within prospectively identified children with VLRWT who did not receive adjuvant chemotherapy. PATIENTS AND METHODS: Fifty-six VLRWTs (10 relapses) were analyzed for mutation of WT1, CTNNB1, and WTX; for 11p15 LOH using microsatellite analysis; and for H19DMR and KvDMR1 methylation. RESULTS: 11p15 LOH was identified in 19 (41%) of 46 evaluable VLRWTs and was significantly associated with relapse (P < .001); 16 of 19 were isodisomic for 11p15. WT1 mutation was identified in nine (20%) of 45 evaluable VLRWTs and was significantly associated with relapse (P = .004); all nine cases also had 11p15 LOH. All evaluable tumors showing LOH by microsatellite analysis also showed LOH by methylation analysis. Retention of the normal imprinting pattern was identified in 24 of 42 evaluable tumors, and none relapsed. Loss of imprinting at 11p15 was identified in one of 42 tumors. CONCLUSION: WT1 mutation and 11p15 LOH are associated with relapse in patients with VLRWTs who do not receive chemotherapy. These may provide meaningful biomarkers to stratify patients for reduced chemotherapy in the future. VLRWTs show a different incidence of WT1 mutation and 11p15 imprinting patterns than has been reported in Wilms tumors of all ages.
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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 | 0.002 |
| 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".