Identification of immune-related genes as prognostic factors in bladder cancer

Abstract

Bladder cancer is one of the most common cancers worldwide. The immune response and immune cell infiltration play crucial roles in tumour progression. Immunotherapy has delivered breakthrough achievements in the past decade in bladder cancer. Differentially expressed genes and immune-related genes (DEIRGs) were identified by using the edgeR package. Gene ontology annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for functional enrichment analysis of DEIRGs. Survival-associated IRGs were identified by univariate Cox regression analysis. A prognostic model was established by univariate COX regression analysis, and verified by a validation prognostic model based on the GEO database. Patients were divided into high-risk and low-risk groups based on the median risk score value for immune cell infiltration and clinicopathological analyses. A regulatory network of survival-associated IRGs and potential transcription factors was constructed to investigate the potential regulatory mechanisms of survival-associated IRGs. Nomogram and ROC curve to verify the accuracy of the model. Quantitative real-time PCR was performed to validate the expression of relevant key genes in the prognostic model. A total of 259 differentially expressed IRGs were identified in the present study. KEGG pathway analysis of IRGs showed that the "cytokine-cytokine receptor interaction" pathway was the most significantly enriched pathway. Thirteen survival-associated IRGs were selected to establish a prognostic index for bladder cancer. In both TCGA prognostic model and GEO validation model, patients with high riskscore had worse prognosis compared to low riskscore group. A high infiltration level of macrophages was observed in high-risk patients. OGN, ELN, ANXA6, ILK and TGFB3 were identified as hub survival-associated IRGs in the network. EBF1, WWTR1, GATA6, MYH11, and MEF2C were involved in the transcriptional regulation of these survival-associated hub IRGs. The present study identified several survival-associated IRGs of clinical significance and established a prognostic index for bladder cancer outcome evaluation for the first time.

Figure 1

Differentially expressed genes (DEGs) and immune-related genes (DEIRGs): The heatmap (A) and volcano (B) of DEGs between bladder cancer tissues and no-cancer tissues. The heatmap (C) and volcano (D) of DEIRGs between bladder cancer tissues and no-cancer tissues.

Figure 2

Differentially expressed transcription factors (DETFs): the heatmap (A) and volcano (B) of DETFs between bladder cancer tissues and no-cancer tissue.

Figure 3

Prognostic values of survival-associated IRGs: the forest plot of survival-associated IRGs.

Figure 4

Development of the immune-related gene prognostic index (IRGPI) and validation model: (A) Heatmap of expression profiles of included genes in IRGPI. (B) Rank of prognostic index and distribution of groups in IRGPI. (C) Survival status of patients in different groups in IRGPI. (D) Heatmap of expression profiles of included genes in validation model. (E) Rank of prognostic index and distribution of groups in validation model. (F) Survival status of patients in different groups in validation model.

Figure 5

IRGPI and validation model for outcome prediction and relationship with clinical features: (A) patients in high-risk group suffered shorter overall survival in IRGPI. (B) The forest plot of univariate analyses of risk score with clinical features in IRGPI. (C) The forest plot of multivariate analyses of risk score with clinical features in IRGPI. (D) Patients in high-risk group suffered shorter overall survival in validation model. (E) The forest plot of univariate analyses of risk score with clinical features in validation model. (F) The forest plot of multivariate analyses of risk score with clinical features in validation model.

Figure 6

Verify the accuracy of IRGPI and validation model: (A) The ROC curve validation of prognostic value of IRGPI. (B) The ROC curve validation of prognostic value of validation model. (C) The nomogram of IRGPI. (D) The nomogram of validation model.

Figure 7

Relationships between the immune-related prognostic index and infiltration of six types of immune cells: (A) B cells; (B) CD4 T cells; (C) CD8 T cells; (D) dendritic cells; (E) macrophages; and (F) neutrophils.

Figure 8

Related expression levels of relevant key genes. (A) SLIT2; (B) MMP9; (C) STAT1; (D) AHNAK; (E) RAC3; (F) RBP7.