Transcriptomic Analysis in Renal Cell Carcinoma and COVID-19 patients.

Abstract

COVID-19 pandemic poses a heavy risk upon global public health. The disease's severity and infection rate are high, especially among cancer patients. The current research was conducted to identify the most common biological pathways and how far they are associated with COVID-19 infection and clear cell renal cell carcinoma. In the current study, the authors analyzed the differentially expressed genes from the experimental and control groups with the help of the GEO2R tool. The study analyzed the protein-protein interactions that occur between the upregulated and downregulated genes from both groups based on the STRING database. In addition, the module analysis was conducted with the Cytoscape software using the MCODE plugin. The outcomes infer the upregulation of 67 genes and downregulation of 176 genes among COVID-19 patients. In the case of patients diagnosed with clear cell renal cell carcinoma, 106 genes got upregulated whereas 77 genes were downregulated. As per the outcomes achieved from the GO analysis, the differentially expressed genes play a role in C-X-C chemokine receptor activity and glycolytic process. Further, the results from the KEGG analysis establish the presence of a genetic association between HIF-1 signaling and lipid metabolism. The current study found the key genes that play a crucial role in the metabolic pathways of COVID-19 and clear cell renal cell carcinoma patients. These genes are found to be promising therapeutic targets in the prevention of complications of infection among cancer patients.