Development and Validation of Prognostic Model in Transitional Bladder Cancer Based on Inflammatory Response-Associated Genes

Abstract

BackgroundBladder cancer is a common malignant type in the world, and over 90% are transitional cell carcinoma. While the impact of inflammatory response on cancer progression has been reported, the role of inflammatory response-associated genes (IRAGs) in transitional bladder cancer still needs to be understood.MethodsIn this study, IRAGs were download from Molecular Signature Database (MSigDB). The transcriptional expression and matched clinicopathological data were separately obtained from public databases. The TCGA-BLCA cohort was used to identify the differentially expressed IRAGs, and prognostic IRAGs were filtrated by univariate survival analysis. The intersection between them was displayed by Venn diagram. Based on least absolute shrinkage and selection operator (LASSO) regression analysis method, the TCGA-BLCA cohort was used to construct a risk signature. Survival analysis was conducted to calculate the overall survival (OS) in TCGA and GSE13507 cohort between two groups. We then conducted univariate and multivariate survival analyses to identify independently significant indicators for prognosis. Relationships between the risk scores and age, grade, stage, immune cell infiltration, immune function, and drug sensitivity were demonstrated by correlation analysis. The expression level of prognostic genes in vivo and in vitro were determined by qRT-PCR assay.ResultsComparing with normal tissues, there were 49 differentially expressed IRAGs in cancer tissues, and 12 of them were markedly related to the prognosis in TCGA cohort for transitional bladder cancer patients. Based on LASSO regression analysis, a risk model consists of 10 IRAGs was established. Comparing with high-risk groups, survival analysis showed that patients in low-risk groups were more likely to have a better survival time in TCGA and GSE13507 cohorts. Besides, the accuracy of the model in predicting prognosis is acceptable, which is demonstrated by receiver operating characteristic curve (ROC) analysis. Age, stage, and risk scores variables were identified as the independently significant indicators for survival in transitional bladder cancer. Correlation analysis represented that the risk score was identified to be significantly related to the above variables except gender variable. Moreover, the expression level of prognostic genes in vivo and in vitro was markedly upregulated for transitional bladder cancer.ConclusionsA novel model based on the 10 IRAGs that can be used to predict survival time for transitional bladder cancer. In addition, this study may provide treatment strategies according to the drug sensitivity in the future.

An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer

“…In the same context, L. Yang et al proposed a nine-gene prognostic model to enhance the prognosis prediction of BCa, achieving an AUC value of 0.76 at five years on the training set and a value of 0.63 for the same time on the test set [ 127 ]. In another study, Z. Xie et al suggested a 10-inflammatory response-associated gene prognostic model which reached AUC values of 0.71 and 0.67 at year one in the TCGA-BCa and GSE13507 cohorts, respectively [ 128 ]. Furthermore, J. Lin et al constructed an 11-gene prognostic model for predicting overall survival in BCa patients, reaching 1/3/5-year AUC values of 0.686/0.665/0.666, 0.800/0.742/0.697, 0.826/0.792/0.763, and 0.781/0.831/0.839 for the TCGA-BCa, GSE13507, GSE32548, and GSE32894 cohorts, respectively [ 129 ].…”

A novel molecular subtypes and risk model based on inflammatory response-related lncrnas for bladder cancer

“…For exploring more potential inflammatory response-related targets and mechanisms in development of tumor, similar risk models were successfully constructed in many cancers, such as nephroblastoma and bladder cancer [ 29 , 30 ]. Inflammatory diseases are linked to lncRNAs, which might be used as biomarkers to diagnose inflammatory diseases such as rheumatoid arthritis [ 31 ].…”

“…Previous studies have mainly focused on urinary biomarkers in diagnosis and monitoring, such as urine DNA methylation assay, while inflammatory biomarkers in the blood have also recently been demonstrated to be potential biomarkers in prognosis of BC patients, such as plasma fibrinogen and D-dimer [32][33][34]. Currently, a prognostic risk model based on the inflammatory response associated with mRNA may effectively distinguish BC patients with a good or worse prognosis [30]. IRRlncRNAs, on the other hand, have yet to be identified as predictive markers for BC.…”

Distinct immune and inflammatory response patterns contribute to the identification of poor prognosis and advanced clinical characters in bladder cancer patients

“…The immune and inflammatory process is dynamic and changing over time, reflecting the degree of the normal or abnormal responses of the body. Although increasing research has focused on the molecular characteristics of BLCA based on gene expression patterns of immune or inflammation (15)(16)(17)(18)(19), there has been no report of prognosis-related classification that combined immune with inflammatory response patterns. Therefore, it is meaningful to identify the distinct IIR patterns and develop a novel prognosis, immunotherapy, and chemotherapy-related signature based on IIR patterns.…”