A novel multi-scale bioinformatics strategy for identifying the molecular mechanism by insighting into ceRNA network integrating WGCNA and meta-analysis: compound kushen injection for treating gastric carcinoma as a proof

Abstract BackgroundGastric carcinoma (GC) is a severe digestive system tumor with high morbidity and mortality and poor prognosis, of which the novel treatments are urgently needed. Compound kushen injection (CKI), a classic Chinese medicine injection, has been widely used to treat a variety of tumors in clinical for decades. In recent years, a growing number of studies have confirmed that CKI has a favorable therapeutic effect on GC, but there are few reports on the potential molecular mechanism of action.MethodsHere, using network pharmacology as the core concept, we identified the ceRNA network and key targets of CKI in the treatment of GC. In order to further explore the impact of key targets, we conducted a meta-analysis of them and compared the expression differences between GC tissues and normal tissues. Functional analysis was utilized to understand the biological regulation pathways involved in key genes. Moreover, we further detected the significance of key genes for the prognosis of GC through survival analysis and immune infiltration analysis. Finally, molecular docking simulation was adopted so as to verify the combination of CKI components and key targets.ResultsAnalysis of the ceRNA network of CKI on GC illustrated that the potential molecular mechanism of CKI was possible to regulate PI3K-AKT and Toll-like receptor signaling pathways by intervening hub genes including AKR1B1, MMP2 and PTGERR3.ConclusionsIn conclusion, this study not only partially highlighted the molecular mechanism of CKI in GC therapy but also provided a novel strategy for exploring the effective mechanisms of traditional Chinese medicine formulations.