Peer-reviewed veterinary case report
Biomarkers linked to outcome in dog bone cancer osteosarcoma
By O'Donoghue, Liza E et al.·Published in BMC cancer·2010·Department of Clinical Sciences, United States·View original on PubMed →
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Original publication title: Expression profiling in canine osteosarcoma: identification of biomarkers and pathways associated with outcome.
- Species:
- dog
Plain-English summary
A large breed dog with osteosarcoma (a type of bone cancer) underwent limb amputation followed by chemotherapy to treat the disease. Researchers analyzed tissue samples from dogs with different recovery times to identify genes that could help predict how well dogs would respond to treatment. They found several genes that could serve as potential markers for prognosis and discovered pathways that might be targeted for new therapies. This research could lead to better treatment options and outcomes for dogs with this aggressive cancer.
People also search for: dog osteosarcoma treatment · large breed dog cancer prognosis · chemotherapy for dog bone cancer
Abstract
BACKGROUND: Osteosarcoma (OSA) spontaneously arises in the appendicular skeleton of large breed dogs and shares many physiological and molecular biological characteristics with human OSA. The standard treatment for OSA in both species is amputation or limb-sparing surgery, followed by chemotherapy. Unfortunately, OSA is an aggressive cancer with a high metastatic rate. Characterization of OSA with regard to its metastatic potential and chemotherapeutic resistance will improve both prognostic capabilities and treatment modalities. METHODS: We analyzed archived primary OSA tissue from dogs treated with limb amputation followed by doxorubicin or platinum-based drug chemotherapy. Samples were selected from two groups: dogs with disease free intervals (DFI) of less than 100 days (n = 8) and greater than 300 days (n = 7). Gene expression was assessed with Affymetrix Canine 2.0 microarrays and analyzed with a two-tailed t-test. A subset of genes was confirmed using qRT-PCR and used in classification analysis to predict prognosis. Systems-based gene ontology analysis was conducted on genes selected using a standard J5 metric. The genes identified using this approach were converted to their human homologues and assigned to functional pathways using the GeneGo MetaCore platform. RESULTS: Potential biomarkers were identified using gene expression microarray analysis and 11 differentially expressed (p < 0.05) genes were validated with qRT-PCR (n = 10/group). Statistical classification models using the qRT-PCR profiles predicted patient outcomes with 100% accuracy in the training set and up to 90% accuracy upon stratified cross validation. Pathway analysis revealed alterations in pathways associated with oxidative phosphorylation, hedgehog and parathyroid hormone signaling, cAMP/Protein Kinase A (PKA) signaling, immune responses, cytoskeletal remodeling and focal adhesion. CONCLUSIONS: This profiling study has identified potential new biomarkers to predict patient outcome in OSA and new pathways that may be targeted for therapeutic intervention.
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Search related cases →Original publication on PubMed: https://pubmed.ncbi.nlm.nih.gov/20860831/