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- W4220845013 abstract "Non-small cell lung cancer (NSCLC) is responsible for about 85% of lung cancer types. The molecular mechanism of NSCLC has not been completely elucidated. The current study aims to explore the potential biomarkers and targets for NSCLC. The gene and miRNA expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed miRNAs (DEMs) and genes (DEGs) were determined and used for further analysis. Functional enrichment analyses were applied using the DAVID program. Moreover, the miRNA targets were predicted based on the miRWalk. The STRING software was constructed protein-protein interaction (PPI) and miRNA-mRNA networks and Cytoscape software was used to visualize PPI and miRNA-mRNA networks and to identify hub genes. As a result of bioinformatic analysis, a total of 159 DEGs and 22 DEMs were identified and DEGs were mostly enriched in the terms like ECM receptor interaction, signal transduction and leukocyte transendothelial migration. The identified hub genes were IL6, COL1A1, CLDN5, CAV1, CDH5, SPP1, GNG11, PPBP, CXCL2 and CXCR2. A total of 239 target genes were identified as potential mRNAs. The most significantly identified genes and miRNAs could serve as potential biomarkers for NSCLC." @default.
- W4220845013 created "2022-04-03" @default.
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- W4220845013 date "2022-03-30" @default.
- W4220845013 modified "2023-10-14" @default.
- W4220845013 title "A Bioinformatics Approach to Identify Potential Biomarkers in Non-Small Cell Lung Cancer" @default.
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- W4220845013 doi "https://doi.org/10.17776/csj.976510" @default.
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