Validation of quercetin in the treatment of colon cancer with diabetes via network pharmacology and molecular dynamics simulation

Abstract

Abstract Objectives Patients suffering from colon cancer with diabetes (CRC-Diabetes) are more likely to metastasis and relapse when compare with colon cancer (CRC). However, there is a lack of a prognostic model and efficient treatment for CRC-Diabetes. Based on these clinical requirements, this study built a prognosis model for CRC-Diabetes and analyzed whether quercetin could be used for CRC-Diabetes treatment through network pharmacology, Molecular dynamics simulation and bioinformatics . Methods Firstly, the differentially expressed genes (DEG) in colon cancer and the related genes in diabetes were screened, and the intersection genes of the two gene clusters were used to construct the prognosis model. Then the potential prognostic markers were screened by univariate Cox proportional hazards regression and lasso regression. Furthermore, multivariate Cox proportional hazards regression was used to construct the prognosis model of CRC-Diabetes. Consequently, quercetin related target genes were screened. The intersection of quercetin target genes with CRC-Diabetes genes was used to find the potential target for quercetin in the treatment of CRC-Diabetes. Molecular docking and molecular dynamics simulation were used to screen reliable targets for quercetin in treatment of CRC-Diabetes. Results There are 1008 intersection genes between colon cancer and diabetes. The constructed multivariate Cox proportional hazards regression model based on the above genes shows that the ROC values of 1, 3 and 5 years are 0.787, 0.793 and 0.85 respectively. There are 101 intersection genes in quercetin and CRC-Diabetes. Through molecular docking, seven proteins (HMOX1, ACE, MYC, MMP9, PLAU, MMP3, MMP1) were selected as potential targets of quercetin. We conducted molecular dynamics simulation of quercetin and the above proteins respectively, and found that the binding structure of quercetin with MMP9 and PLAU was relatively stable, which can be considered as a reliable target for quercetin treatment of CRC-Diabetes. Conclusions Based on TCGA, TTD, Drugbank and other databases, a prediction model that can effectively predict the prognosis of colon cancer patients with diabetes was constructed. Quercetin can treat colon cancer patients with diabetes by influencing PLAU and its downstream pathways.