High‐resolution mapping of amplifications and deletions in pediatric osteosarcoma by use of CGH analysis of cDNA microarrays
Bibliographic record
Abstract
Conventional cytogenetic and comparative genomic hybridization (CGH) studies have shown that osteosarcomas (OSs) are characterized by complex structural and numerical chromosomal alterations and gene amplification. In this study, we used high-resolution CGH to investigate recurrent patterns of genomic imbalance by use of DNA derived from nine OS tumors hybridized to a 19,200-clone cDNA microarray. In six OSs, there was copy number gain or amplification of 6p, with a minimal region of gain centering on segment 6p12.1. In seven OSs, the pattern of amplification affecting chromosome arm 8q showed high-level gains of 8q12-21.3 and 8q22-q23, with amplification of the MYC oncogene at 8q24.2. Seven OSs showed copy number gain or amplification of 17p between the loci bounded by GAS7 and PMI (17p11.2-17p12), and three of these tumors also showed small losses at 17p13, including the region containing TP53. An in silico analysis of the distribution of segmental duplications (duplicons) in this region identified a large number of tracts consisting of paralogous sequences mapping to the 17p region, encompassing the region of deletions and amplifications in OS. Interestingly, within this same region there were clusters of duplicons and several genes that are expressed during bone morphogenesis and in OS. In summary, microarray CGH analysis of the chromosomal imbalances of OS confirm the overall pattern observed by use of metaphase CGH and provides a more precise refinement of the boundaries of genomic gains and losses that characterize this tumor.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".