Identification of therapeutic targets for breast cancer using biological informatics methods.
作者： XUEJIAN LIU , YONGZHEN MA , WENCHUAN YANG , XIA WU , LIHUA JIANG
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摘要: The present study aimed to investigate the modular mechanisms underlying breast cancer and identify potential targets for treatment. differentially expressed genes (DEGs) between normal cells were assessed using microarray data obtained from Gene Expression Omnibus database. ontology (GO) pathway enrichment analyses performed in order functions of these DEGs. Subsequently, protein-protein interaction (PPI) network was constructed Cytoscape software. identified subnetworks further analyzed Molecular Complex Detection plugin. In total, 571 (241 upregulated 330 downregulated genes) found be cells. GO terms significantly enriched by DEGs included cell adhesion, immune response extracellular region, while most significant pathways focal adhesion complement coagulation cascade pathways. PPI established with 273 nodes 718 edges, fibronectin 1 (FN1, degrees score, 39), interleukin 6 (IL6; degree 96) c-Fos protein (degree 32) as hub proteins subnetwork 2. These dysregulated involved development cancer. FN1, IL6 FOS may therefore treatment
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