Bladder cancer (BC) is one of the most often reported malignancies globally, with a high recurrence rate and associated morbidity and mortality, especially in advanced BC. There has been a surge in the number of molecular targets revealed for BC prognosis and treatment. However, there is still a great need to discover novel biomarkers. Consequently, the current study investigated biomarkers that might indicate the progression of bladder cancer. In this study, bioinformatics analysis was done on a single GEO dataset, and TCGA-BLCA information was connected with differentially expressed genes (DEGs). The levels of mRNA and protein expression were validated using qRT-PCR. According to our findings, CRYAB, ECM1, ALDOB, AOC, GPX3, IGFBP7, AQP2, LASS2, TMEM176A, GALNT1, and LASS2 were highly enriched in cell division, identical protein binding, and developmental process in bladder cancer patients. In addition, among the highly differentiated genes, ECM1, GALNT1, LASS2, and GPX3 showed significant molecular alterations in BC, which are crucial for marker identification. Moreover, the mRNA, CNVs, and protein levels of ECM1, GALNT1, LASS2, and GPX3 were significantly increased in BC patients. Our predictions and analysis studies stated that these four genes act as urine biomarkers and played a crucial role in disease prognosis and the therapeutic process of bladder cancer. Our outcomes showed that these four novel urine biomarkers have the potential to provide innovative diagnostics, early predictions, and disease targets, ultimately improving the BC patient's prognosis.
Keywords: Bladder cancer; DEGs; NGS data analysis; Prognosis; Urine biomarkers.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.