Identification of key genes associated with bladder cancer using gene expression profiles
- Yuping Han
- Xuefei Jin
- Hui Zhou
- Bin Liu
Published online on: October 31, 2017
Copyright: © Han et al.
This is an open access article distributed under the terms of Creative Commons Attribution License.
The aim of the present study was to further investigate the molecular mechanisms of bladder cancer. The microarray data GSE52519 were downloaded from Gene Expression Omnibus, comprising 9 bladder cancer and 3 normal bladder tissue samples. Differentially expressed genes (DEGs) were identified using Limma package analysis. Subsequently, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes and Reactome pathway enrichment analyses were performed for down‑ and upregulated DEGs. Transcription factors and genes associated with cancer from DEGs were identified. Protein‑protein interaction (PPI) networks were constructed using STRING, and pathway enrichment analysis was also conducted for genes in the core sub‑network that was identified using BioNet. In total, 420 downregulated and 335 upregulated DEGs were identified. Functional and pathway enrichment analyses identified that a number of DEGs, including AURKA, CCNA2, CCNE1, CDC20 and CCNB2, were enriched in the cell cycle. Furthermore, a total of 12 upregulated proto‑oncogenes were identified, including AURKA and CCNA2. In the PPI sub‑network, a number of DEGs (e.g., CCNB2, CDC20, CCNA2 and MCM6) with higher degrees were enriched in the KEGG pathway of the cell cycle. In conclusion, the DEGs associated with the cell cycle (e.g., CDC20, CCNA2, CCNB2 and AURKA) may serve pivotal roles in the pathogenesis of bladder cancer.