A Novel Prognostic Model of Oxidative Stress-related lncRNA in Hepatocellular Carcinoma and Its Validation in Vitro
Objective:To use bioinformatics methods to screen and experimentally validate long non-coding RNA(lncRNA)associated with oxidative stress(OS)in hepatocellular carcinoma(HCC)in relation to prognosis.Methods:We first downloaded HCC-related expression profile data and clinical data from The Cancer Genome Atlas(TCGA)database,and analyzed differentially expressed genes(DEGs)and OS-related lncRNA using R language.We then verified the reliability of the risk model using receiver operating characteristic(ROC)curves and LASSO regression analysis.Kaplan-Meier survival analysis was used to evaluate patient survival.We used Nomogram to construct a model of pathologic variables and risk scores for predicting 1-year,3-year,and 5-year survival rates of patients.The bioinformatics results were validated in vitro by RT-qPCR,colony formation,cell scratch,Transwell and cell cycle.Results:Eight prognostic lncRNAs(TMEM220-AS1,AC012360.2,SNHG3,GASAL1,PCAT6,AC009005.1,AL031985.3,AC009403.1)were acquired through regression analysis and were utilized to establish the prognostic model.AC009005.1 was highly expressed in tumor cells,and interference with AC009005.1 significantly inhibited the invasion,migration and proliferation of tumor cells.
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