The Immune Cell Infiltration Patterns and Characterization Score in Bladder Cancer to Identify Prognosis.

Abstract

Background: Bladder cancer (BLCA) is among the most frequent types of cancer. Patients with BLCA have a significant recurrence rate and a poor post-surgery survival rate. Recent research has found a link between tumor immune cell infiltration (ICI) and the prognosis of BLCA patients. However, the ICI’s picture of BLCA remains unclear. Methods: Common gene expression data were obtained by combining the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) expression databases. Two computational algorithms were proposed to unravel the ICI landscape of BLCA patients. The R package “limma” was applied to find differentially expressed genes (DEGs). ICI patterns were defined by the unsupervised clustering method. Principal-component analysis (PCA) was used to calculate the ICI score. In addition, the combined ICI score and tumor burden mutation (TMB) were utilized to assess BLCA patients’ prognosis. The predictive value of ICI scores was verified by different clinical characteristics. Results: A total of 569 common gene expression data were retrieved from TCGA and GEO cohorts. CD8+ T cells were found to have a substantial positive connection with activated memory CD4+ T cells and immune score. On the contrary, CD8+ T cells were found to have a substantial negative connection with macrophages M0. Thirty-eight DEGs were selected. Two ICI patterns were defined by the unsupervised clustering method. Patients of BLCA were separated into two groups. The high ICI score group exhibited a better outcome than the low ICI score one (p < 0.001). Finally, the group with a high tumor mutation burden (TMB) as well as a high ICI score had the best outcome. (p < 0.001). Conclusions: Combining TMB and ICI scores resulted in a more accurate survival prediction, suggesting that ICI scores could be used as a prognostic marker for BLCA patients.