Establishment And Analysis Of Autophagy-Related LncRNA Prognostic Risk Model In Renal Clear Cell Carcinoma

Background: Kidney tumor is a common malignant tumor in the urinary system.Clear cell renal cell carcinoma(ccRCC)is the most common pathological type of renal cancer.Because early renal cancer is mostly asymptomatic,most patients are diagnosed at an advanced stage with a poor prognosis.This study aimed to explore the role of autophagyrelated lncRNAs in ccRCC and establish a prognostic risk model for ccRCC autophagy-related lncRNAs.Methods: The clinical data and transcriptome data of ccRCC come from the TCGA database.Download the autophagy-related gene list in the HADB database to obtain the expression matrix of ccRCC-related autophagy-related genes.Person correlation screening was used to obtain ccRCC autophagy-related lncRNAs,and univariate COX regression analysis was used to obtain prognostic lncRNAs,which were further included in multivariate COX regression analysis to obtain autophagyrelated lncRNAs with independent prognosis,and Kaplan-Meier survival was used.The analysis method draws the survival curve of lncRNA,constructs the co-expression network and mulberry plot,draws the survival curve and constructs the prognostic risk model,evaluates the specificity and sensitivity of the model by the area under the curve,and analyzes the risk assessment and correlation with the univariate and multivariate Cox regression analysis.Multivariate Cox regression analysis was performed to analyze the relationship between risk scores and clinically relevant parameter characteristics,to evaluate independent predictors of ccRCC prognosis,and to make forest plots.Finally,KEGG pathways that may be enriched in high and low risk groups were analyzed by GSEA.Results: 75 ccRCC autophagy-related lncRNAs were screened out(correlation coefficient |R|>0.5 and P<0.001),and 17 autophagy-related lncRNAs with independent prognosis were obtained by univariate and multivariate COX regression analysis,of which 10 were lncRNAs.The regression coefficient of 7 lncRNAs is less than zero,HR = exp(coef)> 1,which is negatively correlated with the overall survival of patients.Survival showed a positive correlation.Obtaining the best prognostic risk model for ccRCC based on AIC,and the Kaplan-Meier survival curve of autophagy-related lncRNAs was drawn,the risk value of each sample was calculated,and the samples were divided into high and low risk groups according to the median value of the risk value.Use the R language to draw heatmaps,ROC curves and K-M curves.The area under the ROC curve of the predictive model was 0.706,the risk score of the prognostic model was an independent predictor of ccRCC,and pathological stage,T stage,tumor grade,distant metastasis and risk score were significantly correlated(P<0.05).Conclusion: The prognostic risk model constructed based on 17autophagy-related lncRNAs can better predict the survival prognosis of patients,and has certain guiding significance for evaluating the prognosis of patients with clear cell renal cell carcinoma.The individualized treatment has guiding value.