Identification of key differentially expressed genes associated with non‑small cell lung cancer by bioinformatics analyses.

ABSTRACT: Increasing evidence has indicated that the abnormal expressions of certain genes serve important roles in tumorigenesis, progression and metastasis. The aim of the present study was to explore the key differentially expressed genes (DEGs) between non‑small cell lung cancer (NSCLC) and matched normal lung tissues by analyzing 4 different mRNA microarray datasets downloaded from the Gene Expression Omnibus (GEO) database. In improving the reliability of the bioinformatics analysis, the DEGs in each dataset that met the cut‑off criteria (adjust P‑value <0.05 and |log2fold‑change (FC)|>1) were intersected with each other, from which 195 were identified (consisting of 57 upregulated and 138 downregulated DEGs). The GO analysis results revealed that the upregulated DEGs were significantly enrich

SUBMITTER: Xiao Y 

PROVIDER: S-EPMC5928621 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature