Prediction Of Prognosis And Immunotherapy Response Of Bladder Cancer Based On DNA Damage Repair Genes

Objective: Bladder cancer has high morbidity,high mortality,and poor prognosis.Immunotherapy is one of the important clinical treatments,but it has high heterogeneity,and the prognosis and response to immunotherapy of different populations are quite different.In this study,a clinically independent prognostic model was constructed by screening DNA damage repair genes,and the risk of DNA damage repair can be used to distinguish the population,so as to more accurately predict the prognosis of bladder cancer patients and the response to immunotherapy,and guide clinicians to make more correct clinical decisions.Methods: 1.Download the gene expression profile data and clinical characteristic data of bladder cancer patients from the TCGA-BLCA cohort,and divide all patients into a training set and a test set in a “6:4”ratio.Obtain DNA damage repair-related genes from the Hallmark-DNA-REPAIR gene set of the molecular signature database Msig DB database;2.In the training set,LASSO regression,COX regression,etc.were used to screen out the final DNA damage repair genes to build a risk prognosis model.By quantifying the risk of DNA damage repair genes into risk scores,the samples were divided into two groups of high and low risk.ROC curve analysis,KM Survival analysis,risk factor association plots,single-gene analysis were used for model evaluation,and the test set was used for validation;3.Extending the clinical significance of models with feature heatmaps,forest plots,nomograms,and calibration curves;4.Enrichment analysis is used to explore the potential molecular mechanism of DNA damage repair in bladder cancer;5.Immune microenvironment analysis is used to explore The impact of models on immunotherapy.Results: 1.We obtained gene expression profiles and clinical data of patients from the TCGA-BLCA cohort and the Msig DB database;2.Through quadruple screening such as LASSO regression and COX regression,we finally obtained a prognostic model composed of 9 genes,and divided the samples into high and low risk groups by risk score.In the training set(N1=245)and the test set(N2=162),the KM survival curve showed a significant difference in prognosis between the high and low risk groups(p < 0.0001),and the risk factor association map showed that the high risk group had higher mortality rate and lower survival time.The 1-,3-,and 5-year AUCs for ROC in the training set were 0.736,0.735,and 0.76,respectively.The 1-,3-,and 5-year AUCs of ROC in the test set are 0.710,0.700,and 0.739,respectively,and the model has high prediction accuracy.Single-gene analysis demonstrated that 9 genes entered into the model were differentially expressed between high and low risk groups,and all 9 genes were independent prognostic factors for bladder cancer.Among them,the group with high expression of AK3,RAD52,TAF1 C,XPC and ZNRD1 has a better prognosis,while the group with high expression of DAD1,DDB1,ERCC4 and SSRP1 has a poor prognosis;3.Univariate and multivariate COX regression analysis identified DNA damage repair risk score as a clinically independent prognostic factor(p < 0.05).We constructed a nomogram combining common clinical characteristic factors,and the calibration curve showed that it has strong predictive power;4.Enrichment analysis suggests that DNA damage repair in bladder cancer is closely related to the development of extracellular matrix,cytoskeleton,epidermis and cell differentiation,and is involved in tumor signal transduction and chemical metabolism;5.Model genes are characteristically correlated with immune cells in the immune microenvironment.TAF1 C and RAD52 are negatively correlated with most immune cells,while DAD1 is highly expressed It suggests that the entire immune microenvironment is almost activated.There were significant differences in the expression of immune cells between high and low risk groups.DC cells,fibroblasts,macrophages,neutrophils,activated NK cells,and activated memory CD4+ T cells in the high-risk group were higher than those in the low-risk group,while memory B cells,quiescent mast cells,monocytes and Quiescent memory CD4+ T cells were more expressed in the low-risk group.Conclusion: The bladder cancer prognostic model constructed by 9DNA damage repair-related genes in this study can independently and more accurately predict the overall survival rate of bladder cancer patients,and has a certain predictive effect on the response to immunotherapy.