Identification of potential diagnostic and prognostic biomarkers in non-small cell lung cancer based on microarray data

Abstract

Non-small cell lung cancer (NSCLC) is the most commonly diagnosed subtype of lung cancer, and the leading cause of cancer-associated mortalities worldwide. However, NSCLC is typically diagnosed at a late stage of disease due to a lack of effective diagnostic methods. In the present study, the GSE19804 dataset was obtained from the Gene Expression Omnibus, and a number of differentially expressed genes were identified between NSCLC and adjacent normal tissues. Based on functional and pathway enrichment analyses, five hub genes (cell-division cycle 20, centromere protein F, kinesin family member 2C, BUB1 mitotic checkpoint serine/threonine kinase and ZW10 interacting kinetochore protein) were selected. After verifying that the mRNA level of these hub genes was also upregulated in NSCLC tissues by using the GSE10072 dataset and in cell lines by reverse transcription-quantitative polymerase chain reaction. The diagnostic and prognostic potentials of these five gene candidates were evaluated using receiver operating characteristic curves and survival analyses. Taken together, the present study identified five candidates that are overexpressed in NSCLC tissues and could also serve as potential diagnostic and prognostic biomarkers for patients with NSCLC.