The underlying molecular mechanism and potential drugs for treatment in papillary renal cell carcinoma: A study based on TCGA and Cmap datasets

Papillary renal cell carcinoma (PRCC) accounts for 15–20% of all kidney neoplasms and continually attracts attention due to the increase in the incidents in which it occurs. The molecular mechanism of PRCC remains unclear and the efficacy of drugs that treat PRCC lacks sufficient evidence in clinical trials. Therefore, it is necessary to investigate the underlying mechanism in the development of PRCC and identify additional potential anti-PRCC drugs for its treatment. The differently expressed genes (DEGs) of PRCC were identified, followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses for functional annotation. Then, potential drugs for PRCC treatment were predicted by Connectivity Map (Cmap) based on DEGs. Furthermore, the latent function of query drugs in PRCC was explored by integrating drug-target, drug-pathway and drug-protein interactions. In total, 627 genes were screened as DEGs, and these DEGs were annotated using KEGG pathway analyses and were clearly associated with the complement and coagulation cascades, amongst others. Then, 60 candidate drugs, as predicted based on DEGs, were obtained from the Cmap database. Vorinostat was considered as the most promising drug for detailed discussion. Following protein-protein interaction (PPI) analysis and molecular docking, vorinostat was observed to interact with C3 and ANXN1 proteins, which are the upregulated hub genes and may serve as oncologic therapeutic targets in PRCC. Among the top 20 metabolic pathways, several significant pathways, such as complement and coagulation cascades and cell adhesion molecules, may greatly contribute to the development and progression of PRCC. Following the performance of the PPI network and molecular docking tests, vorinostat exhibited a considerable and promising application in PRCC treatment by targeting C3 and ANXN1.