Identification of Signature Genes Associated With Invasiveness and the Construction of a Prognostic Model That Predicts the Overall Survival of Bladder Cancer

Abstract

Background: Bladder cancer has become the tenth most diagnosed cancer worldwide. The prognosis has been shown to differ between non-muscle invasive bladder cancer (NMIBC) and muscle invasive bladder cancer (MIBC). We aimed to identify signature genes that are associated with the invasiveness and survival of bladder cancer and to identify potential treatments.Methods: We downloaded gene expression profiles of bladder cancer from the Gene Expression Omnibus database to identify differentially expressed genes and perform weighted gene co-expression network analysis. Functional enrichment was analyzed by GO and KEGG analyses. Hub genes were identified from the significant module. Another dataset was also acquired to verify the expression of hub genes. Univariate and multivariate Cox regression analyses were applied to the dataset downloaded from The Cancer Genome Atlas database. Risk scores were calculated and the effect was evaluated by Kaplan-Meier survival analysis. A nomogram was constructed and validated using training and testing samples, respectively. Analysis of the tumor immune microenvironment was conducted with the CIBERSORT algorithm.Results: In total, 1,245 differentially expressed genes (DEGs) were identified. A distinct module was identified that was significantly correlated to invasiveness. The genes within this module were found to be significantly associated with extracellular exosomes, GTPase activity, metabolic pathways, etc. Three hub genes (VSIG2, PPFIBP2, and DENND2D) were identified as biomarkers of invasiveness; two of these (PPFIBP2 and DENND2D) were closely associated with prognosis. The risk score was regarded as an independent prognostic factor. The nomogram was associated with acceptable accuracy for predicting 1- and 5-year overall survival. The infiltrating levels of resting NK cells, activated natural killer (NK) cells, CD8+ T cells, activated memory CD4+ T cells, and T follicular helper cells, were significantly higher in the group with lower risk scores. The group with higher risk scores showed predominant infiltration by regulatory T cells (Tregs).Conclusion: We successfully identified three signature genes related to invasiveness and constructed a nomogram of bladder cancer with acceptable performance. Differences suggested by risk scores between groups of patients showing diverse patterns of immune cell infiltration may be beneficial for selecting therapeutic approaches and predicting prognosis.

Identification of Potential Biomarkers for Progression and Prognosis of Bladder Cancer by Comprehensive Bioinformatics Analysis

“…Due to BLCA having no obvious symptoms in the early stage, the difficulty of diagnosis is increased. In addition, high recurrence and metastasis rates contribute to the low 5-year overall survival of BLCA patients, which has become a major challenge for global health [ 20 ]. Up to now, the main treatment for BLCA is surgery, chemotherapy, and immunotherapy.…”

Prognostic nomogram based on the lymph node metastasis indicators for patients with bladder cancer: A SEER population‐based study and external validation

“…It has previously been reported that more recruitment of naïve M0 macrophages is associated with early LNM, which could prevent T cells from attacking tumor cells and secrete growth factors promoting tumor angiogenesis 48,49 . T follicular helper cells might contribute to the maintenance of a protective immune response, which was proved to be associated with better prognosis in BC 50,51 . Furthermore, we observed higher expression levels of CTLA4 and PDCD1 in low‐risk group, suggesting BC patients with low risk points based on OS classifier might benefit more from immunotherapy 52 .…”

“…48,49 T follicular helper cells might contribute to the maintenance of a protective immune response, which was proved to be associated with better prognosis in BC. 50,51 Furthermore, we observed higher expression levels of CTLA4 and PDCD1 in low-risk group, suggesting BC patients with low risk points based on OS classifier might benefit more from immunotherapy. 52 Collectively, these results explained the possible mechanisms from the perspective of tumor biological and immune function and further corroborated the validity of our risk classifiers for OS and CSS.…”

Multi-Omics Analysis of Novel Signature for Immunotherapy Response and Tumor Microenvironment Regulation Patterns in Urothelial Cancer

“…Besides, we used multiple omics data such as genomics, transcriptomics to make the analysis more in-depth and complete. Compared with many previous reported signatures ( Sun et al, 2021a ; Sun et al, 2021b ; He et al, 2021 ; Yan et al, 2021 ), the predictive power of TMsig is more outstanding. Besides, the TMSig scoring system we constructed can effectively assess the immune profile of patients with urothelial cancer and predict patient prognosis, which we have validated with a sample of 1025 cases.…”