الفهرس 
Lung cancerOnly 14 pages are availabe for public view
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Abstract
Lung cancer is the leading cause of cancer-related death and is the most commonly diagnosed cancer. Cancer is a complex and highly heterogeneous disease as it is mediated by a multiple cellular pathways. Identifying a potential therapeutic target is a crucial step toward efficient drugs. A Systems biology is capable of providing a big-picture view for the key players in tumor pathogenesis which can act as efficient drug targets and biomarkers. In this study, systems biology approach was used for drug targets identification in lung cancer. This approach includes: first, identifying Differentially expressed genes (DE) between normal lung and cancerous lung, second, integration of these DE with protein-protein interactions databases to build a network model then identifying functional modules and further pathway analysis, and third, gene set enrichment analysis of DE lists using the ChIP-x Enrichment Analysis (ChEA) database, the Kinase Enrichment Analysis (KEA) gene-set library, Protein-Protein Interaction (PPI) hubs gene-set library, and KEGG (Kyoto Encyclopedia of Genes and Genomes) databases.In this study, it was found that MAPK signaling pathway, 5 Mitogen-activated protein kinases (MAPK14 (p38α), MAPK1 (ERK2), MAPK8 (JNK1), MAPK3 (ERK-1), and MAPK9 (JNK2)), 3 transcription factors (CREB-1, CUX1, and TRIM28), and a significant protein (Pin1) were found to play a significant role in lung tumor progression and provide attractive drug targets.
Keywords: Systems biology, Lung cancer, Network modeling and analysis, Enrichment analysis, drug targets.