Meijun Lv1, Lishan Wang. 1. 1Department of Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine , Shanghai , People's Republic of China.
Abstract
PURPOSE: The aim of this study was to investigate the molecular mechanism of lung cancer among nonsmoking Taiwan females. MATERIALS AND METHODS: By using the GSE19804 microarray data accessible from Gene Expression Omnibus (GEO) database, we identified differentially expressed genes (DEGs) between nonsmoking female lung cancer patients and healthy controls (!logFC! >1.5 and p-value < 0.05). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene ontology (GO) enrichment analysis was performed using Database for Annotation, Visualization and Integrated Discovery (DAVID). The Search Tool for the Retrieval of Interacting Genes (STRING) tool was utilized to build a protein-protein interaction (PPI) network, followed by the construction of a transcriptional regulatory network based on Transcription factor (TRANSFAC) database. RESULTS: As a result, 320 DEGs were identified between nonsmoking female patients with lung cancer and healthy controls. Pathway enrichment analysis showed significantly enriched pathways such as extracellular matrix (ECM)-receptor interaction and peroxisome proliferator-activated receptor (PPAR) signaling pathway, both of which were enriched with genes COL11A1 (encoding collagen XI alpha-1 chain protein), COL1A1, cluster of differentiation 36(CD36). GO enrichment analysis found that DEGs were significantly related to chemotaxis, vasculature development and cell adhesion GO terms. IL-6 was the node of the PPI network. Critical transcription factors (TFs) including CCAAT/enhancer-binding protein delta (CEBPD) and Rel/NF-κB were also identified. CONCLUSIONS: Our study revealed that ECM-receptor interaction, PPAR signaling pathways, and important biomolecules including COL11A1, COL1A1, CD36, IL-6, CEBPD, and Rel/NF-κB might be involved in lung cancer. This study might pave the way for the development and application of targeted therapeutics of lung cancer irrelevant to smoking.
PURPOSE: The aim of this study was to investigate the molecular mechanism of lung cancer among nonsmoking Taiwan females. MATERIALS AND METHODS: By using the GSE19804 microarray data accessible from Gene Expression Omnibus (GEO) database, we identified differentially expressed genes (DEGs) between nonsmoking female lung cancerpatients and healthy controls (!logFC! >1.5 and p-value < 0.05). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene ontology (GO) enrichment analysis was performed using Database for Annotation, Visualization and Integrated Discovery (DAVID). The Search Tool for the Retrieval of Interacting Genes (STRING) tool was utilized to build a protein-protein interaction (PPI) network, followed by the construction of a transcriptional regulatory network based on Transcription factor (TRANSFAC) database. RESULTS: As a result, 320 DEGs were identified between nonsmoking female patients with lung cancer and healthy controls. Pathway enrichment analysis showed significantly enriched pathways such as extracellular matrix (ECM)-receptor interaction and peroxisome proliferator-activated receptor (PPAR) signaling pathway, both of which were enriched with genes COL11A1 (encoding collagen XI alpha-1 chain protein), COL1A1, cluster of differentiation 36(CD36). GO enrichment analysis found that DEGs were significantly related to chemotaxis, vasculature development and cell adhesion GO terms. IL-6 was the node of the PPI network. Critical transcription factors (TFs) including CCAAT/enhancer-binding protein delta (CEBPD) and Rel/NF-κB were also identified. CONCLUSIONS: Our study revealed that ECM-receptor interaction, PPAR signaling pathways, and important biomolecules including COL11A1, COL1A1, CD36, IL-6, CEBPD, and Rel/NF-κB might be involved in lung cancer. This study might pave the way for the development and application of targeted therapeutics of lung cancer irrelevant to smoking.