Preclinical analysis of novel prognostic transcription factors and immune‑related gene signatures for bladder cancer via TCGA‑based bioinformatic analysis

Abstract

Bladder cancer (BLCA) is a common malignancy of human urinary tract, whose prognosis is influenced by complex gene interactions. Immune response activity can act as a potential prognostic factor in BLCA. The present study estab‑ lished a prognostic model, based on the identification of tumor transcription factors (TFs) and immune‑related genes (IRGs), and further explored their therapeutic potential in BLCA. The enrichment scores of 29 IRG sets, identified in The Cancer Genome Atlas BLCA tumor samples, were quantified by single‑sample Gene Set Enrichment Analysis. The abundance of infiltrated immune cells in tumor tissues was determined using the Estimating Relative algorithm. Tumor‑related TFs and IRGs signatures were retrieved using Least Absolute Shrinkage and Selection Operator Cox regression analysis. A prognostic gene network was built using Pearson's correlation analysis as a means of predicting the regulatory relationship between prognostic TFs and IRGs. A nomogram was devised to also