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Published on: July 22, 2020
Identification of prostate cancer hub genes and therapeutic agents using bioinformatics approach
Background:
Prostate cancer (PCa) is the most common and the second leading cause of cancer-related death among men in America. As the molecular mechanism of PCa has not yet been completely discovered, identification of hub genes and potential drug of this disease is an important area of research that could provide new insights into exploring the mechanisms underlying PCa.
Objective:
The aim of this study was to identify potential biomarkers and novel drug for prostate cancer treatment.
Methods:
The differentially expressed genes (DEGs) between prostate cancer and normal cells were screened using microarray data obtained from the Gene Expression Omnibus database. Gene ontology (GO) and pathway enrichment analyses were performed in order to investigate the functions of DEGs, and the protein-protein interaction (PPI) network of the DEGs was constructed using the Cytoscape software. DEGs were then mapped to the connectivity map database to identify molecular agents associated with the underlying mechanisms of PCa.
Results:
Totally, 359 genes (155 upregulated and 204 downregulated genes) were found to be differentially expressed between prostate cancer and normal cells. The GO terms significantly enriched by DEGs included cell adhesion, protein binding involved in cell-cell adhesion, response to BMP, extracellular region and extracellular region part. KEGG pathway analysis showed that the most significant pathways included cell adhesion molecules (CAMs) and TGF-beta signaling pathway. The PPI network of up-regulated DEGs and down-regulated DEGs were established, respectively. While CDH1, BMP2, NKX3-1, PPARG and PRKAR2B were identified as the hub genes in the PPI network.
Conclusions:
The BMP2, PPARG and PRKAR2B genes may therefore be potential biomarkers in the treatment of PCa. Additionally, the small molecular agent phenoxybenzamine may be a potential drug for PCa.
Insights
Researchers identified key genes like BMP2, PPARG, and PRKAR2B as potential biomarkers for prostate cancer (PCa). Phenoxybenzamine emerged as a potential drug candidate for PCa treatment.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Prostate cancer (PCa) is a leading cause of cancer-related death in men, with its molecular mechanisms still under investigation.
- Identifying key genes and therapeutic targets is crucial for advancing PCa research and treatment.
Purpose of the Study:
- To identify potential biomarkers for prostate cancer (PCa) treatment.
- To discover novel drug candidates for PCa therapy.
Main Methods:
- Screened differentially expressed genes (DEGs) between PCa and normal cells using Gene Expression Omnibus (GEO) microarray data.
- Utilized Gene Ontology (GO) and KEGG pathway analyses to understand DEG functions.
- Constructed protein-protein interaction (PPI) networks and mapped DEGs to the Connectivity Map database.
Main Results:
- Identified 359 DEGs (155 upregulated, 204 downregulated) between PCa and normal cells.
- Enriched GO terms included cell adhesion and extracellular region functions.
- Key pathways identified were cell adhesion molecules (CAMs) and TGF-beta signaling.
- Hub genes in PPI networks included CDH1, BMP2, NKX3-1, PPARG, and PRKAR2B.
Conclusions:
- BMP2, PPARG, and PRKAR2B are proposed as potential biomarkers for PCa treatment.
- Phenoxybenzamine is identified as a potential therapeutic drug for PCa.
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