Bladder cancer is among the most prevalent tumors in the urinary system and is known for its high malignancy. Although traditional diagnostic and treatment methods are established, recent research has focused on understanding the molecular mechanisms underlying bladder cancer. The primary objective of this study is to identify novel diagnostic markers and discover more effective targeted therapies for bladder cancer. This study identified differentially expressed genes (DEGs) between bladder cancer tissues and adjacent normal tissues using data from The Cancer Genome Atlas (TCGA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore the functional roles of these genes. A protein-protein interaction (PPI) network was also constructed to identify and analyze hub genes within this network. Gene set variation analysis (GSVA) was conducted to investigate the involvement of these genes in various biological processes and pathways. Ten key genes were found to be significantly associated with bladder cancer: IL6, CCNA2, CCNB1, CDK1, PLK1, TOP2A, AURKA, AURKB, FOXM1, and CALML5. GSVA analyses revealed that these genes are involved in a variety of biological processes and signaling pathways, including coagulation, UV-response-down, apoptosis, Notch signaling, and Wnt/beta-catenin signaling. The diagnostic relevance of these genes was validated through ROC curve analysis. Additionally, potential therapeutic drug interactions with these key genes were identified. This study provides valuable insights into key genes and their roles in bladder cancer. The identified genes and their interactions with therapeutic drugs could serve as potential biomarkers, presenting new opportunities for enhancing the diagnosis and prognosis of bladder cancer.
Keywords: DEGs; biomarkers; bladder cancer; transcription factors.