Identification of Prognostic Immune Genes in Bladder Urothelial Carcinoma

Abstract

Background. The aim of this study is to identify possible prognostic-related immune genes in bladder urothelial carcinoma and to try to predict the prognosis of bladder urothelial carcinoma based on these genes. Methods. The Cancer Genome Atlas (TCGA) expression profile data and corresponding clinical traits were obtained. Differential gene analysis was performed using R software. Reactome was used to analyze the pathway of immune gene participation. The differentially expressed transcription factors and differentially expressed immune-related genes were extracted from the obtained list of differentially expressed genes, and the transcription factor-immune gene network was constructed. To analyze the relationship between immune genes and clinical traits of bladder urothelial carcinoma, a multifactor Cox proportional hazards regression model based on the expression of immune genes was established and validated. Results. Fifty-eight immune genes were identified to be associated with the prognosis of bladder urothelial carcinoma. These genes were enriched in Cytokine Signaling in Immune System, Signaling by Receptor Tyrosine Kinases, Interferon alpha/beta signaling, and other immune related pathways. Transcription factor-immune gene regulatory network was established, and EBF1, IRF4, SOX17, MEF2C, NFATC1, STAT1, ANXA6, SLIT2, and IGF1 were screened as hub genes in the network. The model calculated by the expression of 16 immune genes showed a good survival prediction ability (p<0.05 and AUC = 0.778). Conclusion. A transcription factor-immune gene regulatory network related to the prognosis of bladder urothelial carcinoma was established. EBF1, IRF4, SOX17, MEF2C, NFATC1, STAT1, ANXA6, SLIT2, and IGF1 were identified as hub genes in the network. The proportional hazards regression model constructed by 16 immune genes shows a good predictive ability for the prognosis of bladder urothelial carcinoma.

Development of a prognostic index and screening of prognosis related genes based on an immunogenomic landscape analysis of bladder cancer

“…Studies found that IRGs play critical regulatory roles in immune responses, including the following: regulation of differentiation and development of bone marrow hematopoietic stem cells; regulation of the development, differentiation, and activation of immune cells; and participation in the activation of autophagy and inflammatory processes [ 27 ]. Studies showed that IRGs predict survival and outcomes for various tumors, and they are potential targets for tumor therapy [ 5 , 7 , 8 , 28 , 29 ].…”

STAT1 is a key gene in a gene regulatory network related to immune phenotypes in bladder cancer: An integrative analysis of multi‐omics data

“…In 2019, Cao et al 30 using TCGA‐BLCA data set found four survival‐related immune cells and 24 hub genes, four of which were related to overall survival. Recently, there were many papers published using only TCGA‐BLCA data set to analyse the tumour‐infiltrating immune cells and prognostic genes related to the microenvironment of bladder cancer 31‐37 . Additionally, Song et al 38 using TCGA‐BLCA data set analysed immune‐related long non‐coding RNA signature for muscle‐invasive bladder cancer; Li et al 39 using GES13507 data set analysed tumour microenvironment and found three immune‐related prognostic genes for bladder cancer; Luo et al 40 and Qiu et al 41 using TCGA‐BLCA as training cohort and http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507 as validation cohort constructed six and seven immune‐related genes prognostic signature, separately; Tian et al 42 using TCGA‐BLCA cohort and four GEO data sets (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48075, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31684 and http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32894) identified a prognostic signature based on six immune‐related genes.…”