Bladder cancer (BLCA) is a common type of urogenital malignancy worldwide. The recurrence and metastasis of bladder cancer are closely related to angiogenesis, but the underlying mechanisms are unclear. In this study, we developed a method to predict survival outcomes among BLCA patients, which could be used to guide immunotherapy and chemotherapy. We obtained patient data from The Cancer Genome Atlas (TCGA) and identified angiogenesis-related genes from the GeneCards database. First, we used differential expression analysis and univariate Cox analysis to identify angiogenesis-related genes and used correlation analysis to generate molecular subtypes based on M2 macrophages. Next, we constructed a prognostic signature consisting of four genes (ECM1, EFEMP1, SLIT2, and PDGFRΑ), which was found to be an independent prognostic factor. Higher risk scores were associated with worse overall survival and higher expression of immune checkpoints. We also evaluated immune cell infiltration using the CIBERSORT and ssGSEA algorithms. Additionally, we performed stratification analyses, constructed a nomogram, and predicted chemotherapeutic responses based on the risk signature. Finally, we validated our findings by using qRT-PCR as well as IHC data to detect the expression levels of the four genes at mRNA and protein levels in BLCA patients and obtained results that were consistent with our predictions. Our study demonstrates the utility of a four-gene prognostic signature for prognostication in bladder cancer patients and designing personalized treatments, which could provide new avenues for personalized management of these patients.
Keywords: Angiogenesis; Bladder cancer; Chemotherapy; Immune infiltration; Macrophage; Signature.
Copyright © 2023 Elsevier Inc. All rights reserved.