Osteosarcoma gene prioritization through combined bioinformatics analysis

Osteosarcoma (OS) is a rare genetic disease that represents 20% of all types of malignant and benign neoplasms of the bone, and 2% of pediatric cancers. Therefore, our aim in this study is to generate a consensus gene list associated with the pathogenicity of OS by using several theoretical approaches that let to propose new drivers associated to this sarcoma, and also possible biomarkers. Firstly, we evaluated the consensus between 9 prioritization strategies to early determine pathogenic genes related to OS. From these genes, we performed a communality analysis in the protein-protein interaction network further enrichment analysis. The consensus prioritized gene list consisted of 1295 genes. Our results revealed that consensus strategy proposes genes related to control in the cell cycle that describe the etiology of cancer in general, and prioritizes not only suppressors already described for OS such as RB1 and TP53, but also postulates new candidates that would help to describe its pathogenesis.