| Background and objective:Among primary bone malignancies,OS is the most common type.The combined application of surgical treatment and chemotherapy has gradually improved the fiveyear survival rate of patients.However,in recent decades,the treatment effect of OS has been stagnant,and no significant breakthrough has been made in the comprehensive treatment in the past 30 years.For patients with metastases,the prognosis is very poor,and the five-year survival rate of patients with lung metastases is only 19%.Therefore,it is urgent to strengthen research on disease genes and mechanisms to help clinicians predict survival outcomes and provide personalized treatment.Reprogramming of energy metabolism is found to be involved in OS development,progression,metastasis,and drug resistance,according to an increasing number of studies.However,key molecular features in OS remain unclear.Here,we developed and experimentally validated an energy metabolism gene-based classification and prognostic signature for OS.Methods:We collected the expression matrix from the TARGET database and the genes involved in energy metabolism from the Reactome database.In order to identify prognostic genes,a single-factor COX regression analysis was carried out.Subsequently,we created a protein interaction network and conducted a degree-based search for the top 10 hub genes using the Cytoscape program and the STRING online database.Then,we further screened for prognosis-related genes using LASSO approach,built a prognostic model,and generated risk scores.Survival analysis was used to compare overall survival time between high and low risk subgroups.Besides,ROC curve was used to assess model predictive power.Then,a prognostic Nomogram was constructed by integrating risk score,age,sex,and metastatic status.After that,the hub gene of PDK1 involved in the construction of the prognostic model was screened for its efficient target inhibitor based on structural biology and molecular docking methods.Finally,we verified the effect of the inhibitor in vitro experiments on cell proliferation and apoptosis.Results:In this study,31 energy metabolism-related genes related to prognosis were screened out.Functional enrichment analysis was performed on these genes and 10 hub genes were finally identified.Subsequently,this study established a prognostic risk model based on the three genes of ACADVL,PDK1 and PFKFB2.Patients were then divided into high and low risk subgroups based on the risk score of the prognostic model.Survival analysis showed that there were significant differences in the survival of high and low risk subgroups,and the prognostic model had high predictive ability,and its AUC values at 1,3,and 5 years were 0.870,0.868,and 0.777.Multivariate analysis proved that the prognostic model was an independent prognostic predictor of OS.Structural biology and molecular docking revealed that DIC was a highly effective and targeted inhibitor of PDK1.Next,in vitro experiments verified the effects of PDK1 inhibitors on the proliferation and apoptosis of OS MG63 cells.CCK8 experiments confirmed that DIC had a concentration-dependent inhibition on the proliferation of OS cells.Flow cytometry confirmed that DIC could induce apoptosis of OS cells.Conclusions:1.In this study,we developed a prognostic model based on genes related to energy metabolism,which has a high prognostic value in OS patients.2.Based on structural biology and molecular docking,DIC was identified as a highly effective targeted inhibitor of PDK1.3.In vitro experiments confirmed that inhibiting PDK1 can effectively inhibit the proliferation of OS cells and induce the apoptosis of OS cells. |
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