Identification of FADS1 Through Common Gene Expression Profiles for Predicting Survival in Patients with Bladder Cancer

Abstract

Purpose: Aim of this study was to identify biomarkers between different grades of bladder cancer (BLCA) and its prognostic value.

Methods: mRNA expression data from GSE32549 and GSE71576 were extracted for further analysis. Differentially expressed genes (DEGs) were identified using GEO2R web tool. Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction (PPI) network were conducted to explore the function and relationship of DEGs. The Cancer Genome Atlas (TCGA) database was used for external validation and Gene set enrichment analysis (GSEA) analysis was used to further identify FADS1 pathways. Bladder cancer cells and patient specimens were used to further demonstrate the function of FADS1.

Results: Datasets from GEO identified a panel of DEGs. Functional enrichment analysis highlighted that DEGs were associated with nuclear division, spindle, cell cycle and p53 signaling pathway. External validation from TCGA demonstrated that FADS1 was an independent prognostic marker in BLCA patients. In cell lines and tumor specimen analysis, FADS1 was overexpressed in the tumor specimen, compared with adjacent tissues, and positively correlated with tumor grade of BLCA. Moreover, FADS1 could enhance the proliferation ability and influence cell cycle of bladder cancer cells.

Conclusion: FADS1 was an independent prognostic biomarker for BLCA and could confer the bladder cancer cells increased proliferation ability.

Keywords: FADS1; TCGA; bioinformatics; bladder cancer; proliferation.