Identification of miRNA Biomarkers for Non-small Cell Lung Cancer using Microarray Datasets and Bioinformatics Analysis
DOI:
https://doi.org/10.21276/apjhs.2022.9.4.28Keywords:
Biomarkers, Gene expression omnibus, miRNA, Non-small cell lung cancer, Protein-protein interaction networkAbstract
Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, which accounts for about 81% percent of all lung cancer cases. Despite advances in NSCLC diagnosis and treatment, the mortality rate is still high. Patients with NSCLC have a 5-year survival rate of only 21%. NSCLC is currently diagnosed at an advanced stage when cancer has already metastasized. Hence, it is essential to elucidate the molecular mechanisms associated with NSCLC pathogenesis and identify early diagnostic or predictive biomarkers. Circulating miRNAs might act as non-invasive blood-based biomarkers for NSCLC diagnosis and prognosis. In this study, we used previously published microarray datasets from Gene Expression Omnibus database and identified 12 down-regulated miRNAs in tissue and blood of NSCLC. Further analysis identified three miRNAs that could serve as biomarkers in the diagnosis of NSCLC: miR-140-3p, miR-29c, and miR-199a. The functional enrichment analysis of the candidate microRNA’s target genes disclosed various overrepresented pathways associated with malignancy progression. Seven target genes are identified as hub genes of the PPI network and hold strong predictive power. In addition, the three-gene combination (IL6, SNAI1, and CDK6) shows a hazard ratio of more than one (hr = 1.5) and P-value <0.002. Since the expression levels of these three miRNAs were significantly decreased in both tissue and blood, measuring miRNA expression in the blood also gives information on its expression in tissue. Therefore, these three microRNAs could be used as NSCLC diagnostic and prognostic biomarkers.
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Copyright (c) 2022 Imteyaz Ahmad Khan, Srikant Sharma
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