Background: The anti-carcinogenic properties of aspirin have been observed in some solid tumors. However, the molecular mechanism of therapeutic effects of aspirin on bladder cancer is still indistinct. We introduced a bioinformatics analysis approach, to explore the targets of aspirin in bladder cancer (BC).
Methods: To find out the potential targets of aspirin in BC, we analyzed direct protein targets (DPTs) of aspirin in Drug Bank 5.0. The protein-protein interaction (PPI) network and signaling pathway of aspirin DPTs were then analyzed subsequently. A detailed analysis of the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway has shown that aspirin is linked to BC. We identified overexpressed genes in BC comparing with normal samples by Oncomine and genes that interlinked with aspirin target genes in BC by STRING.
Results: Firstly, we explored 16 direct protein targets (DPT) of aspirin. We analyzed the protein-protein interaction (PPI) network and signaling pathways of aspirin DPT. We found that aspirin is closely associated with a variety of cancers, including BC. Then, we classified mutations in 3 aspirin DPTs (CCND1, MYC and TP53) in BC using the cBio Portal database. In addition, we extracted the top 50 overexpressed genes in bladder cancer by Oncomine and predicted the genes associated with the 3 aspirin DPTs (CCND1, MYC and TP53) in BC by STRING. Finally, 5 exact genes were identified as potential therapeutic targets of aspirin in bladder cancer.
Conclusion: The analysis of relevant databases will improve our mechanistic understanding of the role of aspirin in bladder cancer. This will guide the direction of our next drug-disease interaction studies.
Keywords: Aspirin; Bladder cancer; Comprehensive bioinformatics analysis; Target gene.
© 2022. The Author(s).