Genomic signatures of chromosomal instability and osteosarcoma progression detected by high resolution array CGH and interphase FISH
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Osteosarcoma (OS) is characterized by an unstable karyotype which typically has a heterogeneous pattern of complex chromosomal abnormalities. High-resolution array comparative genomic hybridization (CGH) in combination with interphase fluorescence in situ hybridization (FISH) analyses provides a complete description of genomic imbalances together with an evaluation of the contribution of cell-to-cell variation to copy number changes. There have been no analyses to date documenting genomic signatures consistent with chromosomal instability mechanisms in OS tumors using array CGH. In this study, we utilized high-resolution array CGH to identify and characterize recurrent signatures of genomic imbalances using ten OS tumors. Comparison between the genomic profiles identified tumor groups with low, intermediate and high levels of genomic imbalance. Bands 6p22-->p21, 8q24 and 17p12--> p11.2 were consistently involved in high copy gain or amplification events. Since these three locations have been consistently associated with OS oncogenesis, FISH probes from each cytoband were used to derive an index of cellular heterogeneity for copy number within each region. OS with the highest degree of genomic imbalance also exhibited the most extreme cell-to-cell copy number variation. Significantly, the three OS with the most imbalance and genomic copy number heterogeneity also had the poorest response to preoperative chemotherapy. This genome wide analysis is the first utilizing oligonucleotide array CGH in combination with FISH analysis to derive genomic signatures of chromosomal instability in OS tumors by studying genomic imbalance and intercellular heterogeneity. This comprehensive genomic screening approach provides important insights concerning the mechanisms responsible for generating complex genomes. The resulting phenotypic diversity can generate tumors with a propensity for an aggressive disease course. A better understanding of the underlying mechanisms leading to OS tumor development could result in the identification of prognostic markers and therapeutic targets.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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