Abstract 398: Genome-wide comparison of matched canine osteosarcoma primary tumours and metastases by array comparative genomic hybridization.
Bibliographic record
Abstract
Abstract Canine osteosarcoma is a common and highly aggressive cancer that shares many characteristics with human osteosarcoma and can serve as a model of this disease. We collected snap frozen normal muscle, primary appendicular skeleton tumour, and matched terminal lung metastases from 8 canine osteosarcoma patients. DNA was isolated from these samples and gene copy number aberrations were assessed using high-resolution oligonucleotide array comparative genomic hybridization (Agilent G3 Canine 180k array). Data analysis was performed using Agilent Genomic Workbench 5.0 analysis software and the Aberration Detection Method 2 and Circular Binary Segmentation algorithms were applied to identify aberrant chromosomal intervals with the log2 ratio threshold set to 0.5. As expected, many cases had copy number aberrations that contain genes commonly altered in canine and human osteosarcoma, including MYC, CDKN2A/CDKN2B, PTEN, p53, and RB. To assess the degree of genomic similarity of the 8 primary tumours to their corresponding metastasis, we used these same samples to generate 8 random pairings of unmatched primaries and metastases, as well as 8 random pairs of primary tumours and 8 random pairs of metastases. A set of 11,000 random 10 base pair segments spanning the entire genome was generated and a correlation analysis was conducted between pairs of samples using the log2 ratios for each segment. Matched samples showed significant correlation with the square of the correlation coefficient (R2) being 0.44 (p<0.05), whereas unmatched primaries and metastases, random pairs of primaries, and random pairs of metastases did not show any significant correlation (R2= 0.08, 0.08, and 0.06 respectively, p>0.05 for each). Thus, as a group, primary tumours are genomically more similar to their corresponding metastasis than to unmatched metastases, and are also more similar than primary tumours or metastases are to each other. However, the range of similarity between matched primaries and metastases was relatively wide, with half the cases showing very high similarity and half showing moderate similarity that was close to the upper range of unmatched samples. These results have implications for therapies that rely on analysis of primary tumours to derive strategies that target metastases. Citation Format: Jonathan H W Liu, Yang Washington Shao, Sam D. Molyneux, Rama Khokha, Geoffrey A. Wood. Genome-wide comparison of matched canine osteosarcoma primary tumours and metastases by array comparative genomic hybridization. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 398. doi:10.1158/1538-7445.AM2013-398
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".