Omics Technologies and Data mining approaches in Canine Osteosarcoma: Insights from High-Throughput Genetics and Bioinformatic Analysis

Osteosarcoma is the most common primary bone malignancy which originates fromprimitive bone-forming mesenchymal cells. In canines, it constitutes ۸۵% of the tumors that occur inthe bone. By the emersion of omics technologies and molecular phenotyping analysis (e.g., genomics,transcriptomics, proteomics, and metabolomics), our recent achievements in high-throughput geneticshave attracted more attention than ever before. The resulting information from these methods can beutilized to enhance our understanding of diseases through the assessment of various correlations. Thedata can be fitted into a logical framework that shows the affected pathways and different factors thatcontribute to the development of a disease. Precision medicine, tumor classification and phenotypingsmall animals as models for enhancing the understanding of human biology and diseases are someexamples of these technologies. In this study, we used ۴ datasets and analyzed their microarray datawith different bioinformatic software, such as R, geWorkbench, GSEA and PennCNV. We assessed theobtained results from our analyzes, the up and down regulation of gene expressions and clustering anddifferent gene sets that were harvested from our analyzes. We also detected CNV’s in one of the datasets with ۵۷۰ cases. Our findings showed relations between osteosarcoma and gene sets related to lipidcycles, such as Adipogenesis, Acid metabolism, and Oxidative phosphorylation, which were acquiredfrom MSigDB. The change in lipid profile is undeniable, and it should be considered in future studiesof cancer treatment and other related research.

کلیدواژه ها:

Osteosarcoma ، Omics technologies ، Gene expression