Urinary metabolite profiling by nuclear magnetic resonance spectroscopy to distinguish control patients from Wilms tumor (WT) and WT tumor by stage.
Bibliographic record
Abstract
e21013 Background: Accurate risk stratification of pediatric renal tumors is essential in optimal management. Urine metabolic profiling may enhance accurate categorization. We determined if the urinary metabolite signature of favourable histology WT is distinct from normal controls, and if these signatures vary between stages, histology and relapse. Methods: Urine was collected from 10 healthy male controls (average age 65 (range 25 to 95) months). 91 frozen urine samples from the Children’s Oncology Group biobank were obtained from Stage 1 (n=20), Stage 2 (n=27), Stage 3 (n=28), and Stage 4 (n=16) patients with anaplastic histology (n=15) and favorable histology (n=76). Relapse occurred in 38. Samples were matched for age, gender, and race. Urine samples (200 μL) were mixed with an internal reference standard in heavy water. For each sample, 600 μL of the solution was drawn and 1D 1H-NMR spectral data were acquired. The spectra underwent standard analysis before being exported to MATLAB R2008b (MathWorks, Natick, MA) for advanced statistical processing. Results: Separation of the metabolite signatures of control and WT tumor urine samples was demonstrated by a validated partial least squares discriminant analysis (PLS-DA). Urine levels of creatine, creatinine, acetate and citrate were decreased in WT tumor compared to controls. The urine of WT tumor patients demonstrated elevated levels of amino acids, sugars, dimethylamine, 2-oxoglutarate, alanine, and branched chain amino acids versus controls. The branched chain amino acids that were noted to be altered included: leucine, isoleucine, iso-valerate, 2-hydroxybutyrate, and 2-oxoisovalerate. Urinary metabolomic profiles among different stages of WT tumor showed distinct profiles and separation by PLS-DA. Group clustering was noted among control, different stages, relapse, and non-relapse samples, with some overlap. Conclusions: Metabolomic profiling of urine by NMR demonstrates distinct, but not completely separable, patterns that distinguish between controls, WT stage and histology, and relapse. Determining how distinct these findings are from other cancers and the pathways responsible is needed.
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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".