ABSTRACT
BACKGROUND: Breast cancer (BC) is the second most common cause of death from cancer in women in the United States. As the molecular mechanism of BC has not yet been completely discovered, identification of hub genes and pathways of this disease is of importance for revealing molecular mechanism of breast cancer initiation and progression. OBJECTIVE: This study aimed to identify potential biomarkers and survival analysis of hub genes for BC treatment. METHODS: The differentially expressed genes (DEGs) between breast cancer and normal cells were screened using microarray data obtained from the Gene Expression Omnibus (GEO) database. Gene ontology (GO) and KEGG pathway enrichment analyses were performed for DEGs using DAVID database, the protein-protein interaction (PPI) network was constructed using the Cytoscape software, and module analysis was performed using MCODE. Then, overall survival (OS) analysis of hub genes was performed by the Kaplan-Meier plotter online tool. Finally, the potential molecular agents were identified with Connectivity Map (cMap) database. RESULTS: A total of 585 DEGs were obtained, which were significantly enriched in the terms related to positive regulation of cell migration, regulation of cell proliferation and focal adhesion. KEGG pathway analysis showed that the significant pathways included Focal adhesion, Pathways in cancer, ECM-receptor interaction, Ribosome, Transcriptional misregulation in cancer and other signaling pathways about cancer. The PPI network was established with 576 nodes and 1943 edges. A significant module was found from the PPI network, the enriched functions and pathways included ECM-receptor interaction and Focal adhesion. CONCLUSIONS: Fifteen genes were selected as hub genes because of high degrees, among which, low expression of four genes was associated with worse OS of patients with BC, including RPS9, RPL11, RPS14 and RPL10A. Additionally, the small molecular agent emetine may be a potential drug for BC.
Subject(s)
Biomarkers, Tumor/genetics , Breast Neoplasms/genetics , Gene Expression Profiling/methods , Gene Expression Regulation, Neoplastic , Female , Gene Ontology , Humans , Kaplan-Meier Estimate , Prognosis , Protein Interaction Maps/genetics , Ribosomal Protein L10 , Ribosomal Protein S9 , Ribosomal Proteins/geneticsABSTRACT
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.
