Spectral karyotyping identifies recurrent complex rearrangements of chromosomes 8, 17, and 20 in osteosarcomas
Bibliographic record
Abstract
Conventional cytogenetic studies have shown that osteosarcomas (OSs) are often highly aneuploid, with a large number of both structural and numerical chromosomal alterations. To investigate the complexity of OS karyotypes in detail, we applied spectral karyotyping (SKY) to a series of 14 primary OS tumors and four established OS cell lines. A total of 531 rearrangements were identified by SKY, of which 300 breakpoints could be assigned to a specific chromosome band. There was an average of 38.5 breakpoints identified by SKY per primary tumor. Chromosome 20 was involved in a disproportionately high number of structural rearrangements, with 38 different aberrations being detected. Chromosomal rearrangements between chromosomes 20 and 8 were evident in four tumors. FISH analysis using a 20q13 subtelomeric probe identified frequent involvement of 20q in complex structural rearrangements of OS cell lines. Characterization of the structural aberrations of chromosomes 8 and 17 by use of SKY demonstrated frequent duplication or partial gains of chromosome bands 8q23-24 and 17p11-13. Other chromosomes frequently involved in structural alteration were chromosomes 1 (47 rearrangements) and 6 (38 rearrangements). Centromeric rearrangements often involving chromosomes 1, 6, 13, 14, 17, and 20 were present. Four of the 14 primary OS tumors were characterized by nonclonal changes that included both structural and numerical alterations. In summary, OS tumors have a very high frequency of structural and numerical alterations, compounded by gross changes in ploidy. This intrinsic karyotype instability leads to a diversity of rearrangements and the acquisition of composite chromosomal rearrangements, with the highest frequency of alteration leading to gain of 8q23-24 and 17p11-13 and rearrangement of 20q. These findings suggest that specific sequences mapping to these chromosomal regions will likely have a role in the development and progression of OS.
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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 | 0.000 |
| 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".