Genome-wide profiling using single-nucleotide polymorphism arrays identifies novel chromosomal imbalances in pediatric glioblastomas
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Bibliographic record
Abstract
Available data on genetic events in pediatric grade IV astrocytomas (glioblastoma [pGBM]) are scarce. This has traditionally been a major impediment in understanding the pathogenesis of this tumor and in developing ways for more effective management. Our aim is to chart DNA copy number aberrations (CNAs) and get insight into genetic pathways involved in pGBM. Using the Illumina Infinium Human-1 bead-chip-array (100K single-nucleotide polymorphisms [SNPs]), we genotyped 18 pediatric and 6 adult GBMs. Results were compared to BAC-array profiles harvested on 16 of the same pGBM, to an independent data set of 9 pediatric high-grade astrocytomas (HGAs) analyzed on Affymetrix 250K-SNP arrays, and to existing data sets on HGAs. CNAs were additionally validated by real-time qPCR in a set of genes in pGBM. Our results identify with nonrandom clustering of CNAs in several novel, previously not reported, genomic regions, suggesting that alterations in tumor suppressors and genes involved in the regulation of RNA processing and the cell cycle are major events in the pathogenesis of pGBM. Most regions were distinct from CNAs in aGBMs and show an unexpectedly low frequency of genetic amplification and homozygous deletions and a high frequency of loss of heterozygosity for a high-grade I rapidly dividing tumor. This first, complete, high-resolution profiling of the tumor cell genome fills an important gap in studies on pGBM. It ultimately guides the mapping of oncogenic networks unique to pGBM, identification of the related therapeutic predictors and targets, and development of more effective therapies. It further shows that, despite commonalities in a few CNAs, pGBM and aGBMs are two different diseases.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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