Gene expression profile comparison of primary and pulmonary metastatic lesions in a dog with appendicular osteosarcoma and hypertrophic osteopathy
Bibliographic record
Abstract
<title>Abstract</title> Hypertrophic osteopathy (HO) is a paraneoplastic syndrome, and the most notable cause in dogs is pulmonary metastatic osteosarcoma (OSA). Although many molecular factors in canine OSA have been shown in metastasis, little is known about the gene expression profile of HO secondary to metastatic OSA. Therefore, the purpose of this study was to compare the gene expression profiles between primary and metastatic OSA lesions from the same dog and to look for gene expression changes that can elucidate the molecular mechanism of metastases and HO. Tumoral samples were obtained from a 2-year-old, intact male, Labrador retriever. At the first visit, the patient presented with an appendicular OSA as the primary lesion. About 10 months later, the dog developed HO due to a single pulmonary metastasis. Using these primary and metastatic samples from the same dog, as well as normal canine osteoblasts, we investigated the gene expression profiling using the NanoString nCounter® Canine IO panel. A total of 180 differentially expressed genes were identified between malignant OSA cells and non-malignant canine osteoblasts. Furthermore, 5 genes (CCL17, VEGFC, C3, C4BPA, and FOS) were differentially expressed in comparison between primary and metastatic OSA samples. CCL17 and VEGFC were upregulated in the primary lesion compared to the metastatic lesion, while C3, C4BPA, and FOS were downregulated in the primary lesion relative to the metastatic lesion. Given that the metastatic lesion was relevant to the development of HO, the different gene expression profiles may be relevant to understanding the pathophysiology of HO.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 0.004 |
| 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 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".