Screening and Identification of Key Biomarkers for Bladder Cancer: A Study Based on TCGA and GEO Data

Abstract

Bladder cancer (BLCA) is a common malignant cancer, and it is the most common genitourinary cancer in the world. The recurrence rate is the highest of all cancers, and the treatment of BLCA has only slightly improved over the past 30 years. Genetic and environmental factors play an important role in the development and progression of BLCA. However, the mechanism of cancer development remains to be proven. Therefore, the identification of potential oncogenes is urgent for developing new therapeutic directions and designing novel biomarkers for the diagnosis and prognosis of BLCA. Based on this need, we screened overlapping differentially expressed genes (DEG) from the GSE7476, GSE13507, and TCGA BLCA datasets. To identify the central genes from these DEGs, we performed a protein-protein interaction network analysis. To investigate the role of DEGs and the underlying mechanisms in BLCA, we performed Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) analysis; we identified the hub genes via different evaluation methods in cytoHubba and then selected the target genes by performing survival analysis. Finally, the relationship between these target genes and tumour immunity was analysed to explore the roles of these genes. In summary, our current studies indicate that both cell division cycle 20 (CDC20) and abnormal spindle microtubule assembly (ASPM) genes are potential prognostic biomarkers for BLCA. It may also be a potential immunotherapeutic target with future clinical significance.

Identification of 9-Core Immune-Related Genes in Bladder Urothelial Carcinoma Prognosis

“…Consistent with our study, PDGFRA, AHNAK and RAC3 were risk factors, whereas OAS1 and SH3BP2 were protective factors. Another study revealed that DEG between bladder cancers and normal tissues were enriched in PDGF signaling and immune-related signalings ( 28 ). Moreover, PDGF signaling contributed to immune microenvironment and unfavorable prognosis in an analysis of multiple tumors ( 29 ).…”

Identification of a Prognostic Risk Signature of Kidney Renal Clear Cell Carcinoma Based on Regulating the Immune Response Pathway Exploration

“…Bioinformatics analysis methods have been increasingly used in the medical field [ 14 , 15 ]. In this study, we used various bioinformatics methods to deeply study the potential role of pathways regulating immune responses in KIRC.…”

Identification of Hub Genes Associated With Progression and Prognosis of Bladder Cancer by Integrated Bioinformatics Analysis.

“…With regarding to BLCA, many potential biomarkers were identi ed with bioinformatics, for example, CDC20, ASPM, TAGLN, ACTA2, MYH11, CALD1, MYLK, GEM, PRELP, TPM2, and OGN (15)(16)(17)(18)(19). In addition, several signaling pathways involved in BLCA, including vascular smooth muscle contraction, hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), focal adhesion, cGMP-PKG, cAMP, MAPK and PI3K-AKT, were screened out(15) , (16). However, most previous studies only used the cancer genome atlas (TCGA) database or Gene Expression Omnibus (GEO) database when WGCNA was applied (13,18).…”

“…However, most previous studies only used the cancer genome atlas (TCGA) database or Gene Expression Omnibus (GEO) database when WGCNA was applied (13,18). Moreover, although there were studies based on TCGA and GEO database, only differential gene expression analysis was performed (16,17). It was the rst time to combine WGCNA with differential gene expression analysis to identify biomarkers of BLCA based on TCGA database and GEO database.…”