A Risk Score Model Of Pyroptosis Co-Expressed Genes Based On Bioinformatics Analysis

Objectives: Bladder cancer(BLCA)is one of the most common causes of cancerrelated death in the world,with a poor prognosis.Immunotherapy has revolutionized the treatment of BLCA,but due to its heterogeneity,only a few patients have achieved lasting clinical benefit.More and more studies have shown that pyroptosis is related to the shaping of Tumor Microenvironment(TME)and the prediction of treatment response.However,the relationship between pyroptosis and BLCA immunotherapy response is still unclear.In this study,we performed bioinformatics analysis to construct a risk score model of pyroptosis co-expressed genes to predict prognosis,evaluate tumor immune infiltration,analyze the sensitivity of immunotherapy,understand the role of pyroptosis in BLCA,and provide reference for further research on clinical prognosis and therapeutic targets of BLCA.Methods: RNA sequencing(Rna-Seq)data and corresponding clinical data of BLCA patients were downloaded from the Cancer Genome Atlas(TCGA)database,GSE32894 data set was downloaded from the Gene Expression Omnibus(GEO)database,and pyroptosis-related genes were obtained from the Molecular Signature database(MSig DB)and relevant literature.Firstly,single-sample gene set enrichment analysis(ss GSEA)was used for analysis,and then BLCA patients were divided into high expression group and low expression group according to the median pyroptosis score.Kaplan-Meier curve was used to compare the survival of low expression group and high expression group.Then,weighted gene co-expression network analysis(WGCNA)was used to obtain the genes co-expressed with pyroptosis,and the risk score model of pyroptosis co-expressed genes that could predict the prognosis of bladder cancer patients was constructed by random forest.The BLCA cohort in TCGA was used as the training dataset,and the GSE32894 dataset downloaded from GEO database was used as an independent test dataset to test the performance of the risk score model in predicting the prognosis of BLCA patients.Gene ontology(GO)enrichment analysis was used to understand the biochemical metabolic pathways and biological processes involved in the screened genes,and gene set enrichment analysis(GSEA)was used to explore the potential molecular mechanism of enrichment in pyroptosis-related genes.The CIBERSORT algorithm was used to analyze the differences in the infiltration of immune cells in TME.Finally,the tumor immune dysfunction and exclusion(TIDE)algorithm was further used to evaluate the response to immunotherapy.Results: Patients with the high expression of pyroptosis-related genes have a better prognosis than those with the low expression,suggesting that pyroptosis-related genes are closely related to the survival of bladder cancer.In order to further explore the role of pyroptosis genes in bladder cancer,30 co-expression modules were identified by WGCNA.After visualization of the correlation between modules and clinical features,946 co-expressed pyroptosis genes in the black module and the blue module were selected for further analysis.Random forest further screened SPINK1,IKZF3,BLNK,LY75,ZNF432,MST1 R,TSPAN8,ACOXL,TNFAIP2,CYP4F12,OVGP1,PBX4,PLA2G2 F,PPFIBP2,ALOX5,ZNF83,B3GNT3,KCNN4,SP6,GATA3,DTX4,ACSL5,TMEM51,ATP1A4,TMC7 and BATF The 26 pyroptosis co-expressed genes,constructed a risk score model that could predict the prognosis of bladder cancer patients.Bladder cancer patients were divided into high-risk group and low-risk group according to the median of pyroptosis risk score.The KM curve of the two risk groups in TCGABLCA cohort and GEO cohort showed that the high-risk group was significantly related to the poor prognosis of bladder cancer.GO analysis showed that most of the genes were related to the development of connective tissue,the organization of external encapsulation structure,the organization of extracellular matrix,and the process of fatty acid metabolism.GSEA analysis showed that the genes were mainly enriched in 28 signaling pathways such as cell cycle signaling pathway,WNT signaling pathway and focal adhesion signaling pathway.The analysis of immune cell infiltration in TME showed that the degree of M0 macrophage infiltration was higher in the high-risk group,indicating that the infiltration of M0 macrophages in the tumor microenvironment was not conducive to the prognosis of patients.TIDE algorithm was used to analyze the sensitivity of immunotherapy between different risk score groups.It was found that the risk score of pyroptosis-related genes in non-responders to immune checkpoint blockade(ICB)treatment was significantly higher than that in responders,and the sensitivity of bladder cancer patients in low-risk group was higher than that in high-risk group.These results indicate that the risk score model based on the co-expressed genes of pyroptosis in this study has a good performance in predicting the response to immunotherapy.Conclusions: Bioinformatics based studies can provide additional insights into the occurrence and progression of BLCA.The risk score model based on the co-expressed genes of pyroptosis in this study not only helps doctors evaluate the prognosis of BLCA patients,but also estimates the tumor immunotherapy response of BLCA patients,which can provide an important reference for the tumor immunotherapy of BLCA patients.