Analysis of Differentially Expressed Genes, Clinical Value and Biological Pathways in Prostate Cancer

Overview

Journal Am J Transl Res

Specialty General Medicine

Date 2018 Jun 12

PMID 29887958

Citations 29

Authors

Zhaohui He

Fucai Tang

Zechao Lu

Yucong Huang

Hanqi Lei

Zhibiao Li

Guohua Zeng

Affiliations

Soon will be listed here.

Abstract

The present study aimed to investigate the gene expression changes in prostate cancer (PC) and screen the hub genes and associated pathways of PC progression. The authors employed integrated analysis of GSE46602 downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas databases to identify 484 consensual differentially expressed genes (DEGs) in PC, when compared with adjacent normal tissue samples. Functional annotation and pathway analysis were performed. The protein-protein interaction (PPI) networks and module were constructed. RT-qPCR was used to validate the results in clinical PC samples. Survival analysis of hub genes was performed to explore their clinical value. GO analysis results revealed that DEGs were significantly enriched in negative regulation of nitrobenzene metabolic process, extracellular space and protein homodimerization activity. KEGG pathway analysis results revealed that DEGs were most significantly enriched in focal adhesion. The top 10 hub genes were identified to be hub genes from the PPI network, and the model revealed that these genes were enriched in various pathways, including neuroactive ligand-receptor interaction, p53 and glutathione metabolism signaling pathways. RT-qPCR results validated that expression levels of eight genes (PIK3R1, BIRC5, ITGB4, RRM2, TOP2A, ANXA1, LPAR1 and ITGB8) were consistent with the bioinformatics analysis. ITGB4 and RRM2 with genetic alterations exhibited association with a poorer survival rate, compared with those without alterations. These results revealed that PC-related genes and pathways have an important role in tumor expansion, metastasis and prognosis. In summary, these hub genes and related pathways may act as biomarkers or therapeutic targets for PC.

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