Bioinformatics Identification of Green Tea Anticancer Properties: a Network-Based Approach

Abstract

Background and objectives: Promising anticancer properties are associated with the consumption of green tea. On the other hand, lung cancer has been showing to possess the highest number of death compared to other types of cancer. The aim of this study was to understand the mechanisms by which green tea shows this effect; bioinformatics study of proteome profile could be essential. For this reason, the proteomics analysis of human lung adenocarcinoma A-549 cells treated with green tea extract was chosen for protein-protein interaction (PPI) network analysis. Methods: Cytoscape v.3.8.2 and its applications analyzed a number of 14 differentially expressed proteins (DEPs) from green tea treatment experiment as two networks. The biological annotations and action type exploration of the hub-bottlenecks of the PPI network were then carried out. Results. The investigation indicated that among 14 queries DEPs, HNRNPA2B1, PCBP1, and HNRNPC may show substantial role. Moreover, HSPA8 was the top hub-bottleneck and half of the central protein groups were enriched with heterogeneous nuclear ribonucleoproteins complex family (HNRNPs). Conclusion. The anticancer bioinformatics study of green tea suggests a complex nature for green tea. This finding urges complementary evaluations to validate whether green tea is applicable as an anticancer agent in medicine.