Drug repositioning, development of new uses for marketed drugs, is an effective way to discover new antitumor compounds. In this study, we used a new method, filtering compounds
The data of gene expression in cancer and normal tissues of colorectal, breast, and liver cancer were obtained from The Cancer Genome Atlas Project (TCGA). The key targets combination was obtained from the protein-protein interaction network (PPI network) and the correlation analysis of the targets. Molecular docking was used to reposition the drugs which were obtained from DrugBank. MTT proliferation assay and animal experiments were used to verify the activity of candidate compounds. Flow cytometric analysis of proliferation, cell cycle and apoptosis, slice analysis, gene regulatory network, and Western blot were performed to elucidate the mechanism of drug action.
CDK1 and AURKB were identified as a pair of key targets by the analysis of different expression gene from TCGA. Three compounds, linagliptin, mupirocin, and tobramycin, from 12 computationally predicted compounds, were verified to inhibit cell viability in HCT116 (colorectal), MCF7 (breast), and HepG2 (liver) cancer cells. Linagliptin, a hypoglycemic drug, was proved to inhibit cell proliferation by cell cycle arrest and induce apoptosis in HCT116 cells, and suppress tumor growth in nude mice bearing HCT116 cells. Linagliptin reduced the tumor size and decreased the expression of Ki67, a nuclear protein expressed in all proliferative cells. Gene regulatory network and Western blot analysis suggested that linagliptin inhibited tumor cell proliferation and promoted cell apoptosis through suppressing the expression and phosphorylation of Rb, plus down-regulating the expression of Pro-caspase3 and Bcl-2, respectively.
The combination of key targets based on the protein-protein interaction network that were built by the different gene expression of TCGA data to reposition the marketed drugs turned out to be a new approach to discover new antitumor drugs. Hypoglycemic drug linagliptin could potentially lead to novel therapeutics for the treatment of tumors, especially for colorectal cancer. Gene regulatory network is a valuable method for predicting and explaining the mechanism of drugs action.