Molecular targets of metformin against ovarian cancer based on network pharmacology

The objective of this study was to analyze potential targets of metformin against ovarian cancer (OC) through network pharmacology. Pharmacodynamic targets of metformin were predicted using the Bioinformatics Analysis Tool for the molecular mechanism of traditional Chinese medicine (BATMAN), Drugbank, PharmMapper, SwissTargetPrediction, and TargetNet databases. R was utilized to analyze the gene expression of OC tissues, normal/adjacent noncancerous tissues, and screen differentially expressed genes (DEGs) in the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) + Genotype-Tissue Expression (GTEx) datasets. STRING 11.0 was utilized to explore the protein-protein interaction (PPI) of metformin target genes differentially expressed in OC. Cytoscape 3.8.0 was used to construct the network and screen the core targets. Additionally, gene ontology (GO) annotation and enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed for the common targets of metformin and OC through the DAVID 6.8 database. A total of 95 potential common targets of metformin and OC were identified from the intersection of 255 potential pharmacodynamic targets of metformin and 10,463 genes associated with OC. Furthermore, 10 core targets were screened from the PPI network [e.g., interleukin (IL) 1B, KCNC1, ESR1, HTR2C, MAOB, GRIN2A, F2, GRIA2, APOE, PTPRC]. In addition, it was shown in GO enrichment analysis that the common targets were mainly associated with biological processes (i.e., response to stimuli or chemical, cellular processes, and transmembrane transport), cellular components (i.e., plasma membrane, cell junction, and cell projection), and molecular functions (i.e., binding, channel activities, transmembrane transporter activity, and signaling receptor activities). Furthermore, it was indicated by KEGG pathway analysis that the common targets were enriched in metabolic pathways. The critical molecular targets and molecular pathways of metformin against OC were preliminarily determined by bioinformatics-based network pharmacology analysis, providing a basis, and reference for further experimental studies.

Automated summary

This study used network pharmacology to analyze potential targets of metformin against ovarian cancer. Pharmacodynamic targets were predicted and gene expression analysis was performed to identify differentially expressed genes. Protein-protein interaction analysis and enrichment analysis were used to determine the core targets of metformin, and pathway analysis was performed. The study provides preliminary insights into the critical targets and pathways of metformin against ovarian cancer.