The aims of this study were to identify the common gene signatures of clear cell renal cell carcinoma (CCRCC), and to expand the respective protein-protein interaction networks associated with CCRCC regulation. For the latter, we utilized multiple gene expression data sets from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO), with which we could analyze the aberrant gene expression patterns at the transcriptome level that distinguish cancer from normal samples.
Recent progress in computational methods for investigating physical and functional gene interactions has provided new insights into the complexity of biological processes. An essential part of these methods is presented visually in the form of gene interaction networks that can be valuable in exploring the mechanisms of disease. Here, a combined network based on gene pairs with an extra layer of reliability was constructed after converting and combining the gene pair scores using a novel algorithm across multiple approaches.
Osteoarthritis is the most common form of arthritis among elderly adults. Herein, we performed protein-protein interaction (PPI) and miRNA network analysis to evaluate the global correlation between miRNA regulation and the PPI network in human osteoarthritis. Our results showed that desmoplakin (DSP), cystatin A (CSTA), calmodulin 1, tyrosine kinase endothelial, insulin-like growth factor 1 (IGF-1), IGF-binding protein 7 (IGFBP7), syndecan 1 (SDC1), ephrin type-A receptor 4, and PDZ and LIM domain protein 1 were associated with osteoarthritis.