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Eur Rev Med Pharmacol Sci ; 19(18): 3375-84, 2015 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-26439031

RESUMO

OBJECTIVE: The study was aimed to explore the underlying mechanisms and identify the potential target genes by bioinformatics analysis for non-small-cell lung carcinoma (NSCLC) treatment in non-smoking women. MATERIALS AND METHODS: The microarray data of GSE19804 was downloaded from Gene Expression Omnibus (GEO) database. Paired samples (from the same patient) of tumor and normal lung tissues from 60 non-smoking female NSCLC patients were used to identify differentially expressed genes (DEGs). The functional enrichment analysis was performed. Furthermore, the protein-protein interaction (PPI) network of the DEGs was constructed by Cytoscape software. The module analysis was performed. RESULTS: Totally, 817 DEGs including 273 up- and 544 down-regulated genes were identified. The up-regulated genes were mainly enriched in extracellular matrix (ECM)-receptor interaction, focal adhesion and cell cycle functions, while down-regulated genes were mainly enriched in the cytokine-cytokine receptor interaction pathway. DEGs including hyaluronan-mediated motility receptor (HMMR), collagen, type I alpha 2 (COL1A2), cyclin A2 (CCNA2), MAD2 mitotic arrest deficient-like 1 (MAD2L1), interleukin 6 (IL6) and interleukin 1, beta (IL1B) were identified in these functions. These genes were hub nodes in PPI networks. Besides, there were 3 up-regulated modules and 1 down-regulated module. The significant pathways were ECM-receptor interaction and focal adhesion in up-regulated modules, while in down-regulated module, the significant pathway was mitogen-activated protein kinase (MAPK) signaling pathway. CONCLUSIONS: The ECM-receptor interaction, focal adhesion, cell cycle and cytokine-cytokine receptor interaction functions may be associated with NSCLC development. Genes such as HMMR, COL1A2, CCNA2, MAD2L1, IL6 and IL1B may be potential therapeutic target genes for NSCLC.


Assuntos
Carcinoma Pulmonar de Células não Pequenas/genética , Biologia Computacional/métodos , Perfilação da Expressão Gênica/métodos , Regulação Neoplásica da Expressão Gênica/genética , Neoplasias Pulmonares/genética , Regulação para Baixo , Feminino , Humanos , Transdução de Sinais , Regulação para Cima
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