Background: It is generally acknowledged that miRNAs play pivotal roles in the initiation and development of cancer. The aim of the current study is to investigate the clinicopathological role of miR-136-5p in lung adenocarcinoma and its underlying molecular mechanism.
Materials and methods: Data of a cohort of 1242 samples were provided by the Gene Expression Omnibus and The Cancer Genome Atlas to evaluate miR-136-5p expression in lung adenocarcinoma. A comprehensive meta-analysis integrating the expression data from all sources was performed, followed by a summary receiver operating curve plotted to appraise the upregulated expression of miR-136-5p in lung adenocarcinoma. Candidate targets of miR-136-5p were launched by the intersection of differentially expressed genes in The Cancer Genome Atlas and genes predicted by 12 web-based platforms. Then, hub genes were illustrated by a protein-protein interaction network. Furthermore, Kyoto Encyclopedia of Genes and Genomes, Gene Ontology and Protein Analysis Through Evolutionary Relationships analyses of potential target genes were carried out via bioinformatics tools.
Results: MiR-136-5p expression was upregulated in lung adenocarcinoma versus normal tissues (standard mean difference = 0.43, 95% confidence interval: 0.27-0.58). The summary receiver operating characteristic curve further verified the upregulation of miR-136-5p in lung adenocarcinoma (area under curve = 0.7459). A total of 311 candidate target genes of miR-136-5p were gathered to create a protein-protein interaction network. Molecular mechanism analysis unveiled the potential miR-136-5p target genes participated in cell adhesion molecules, focal adhesion, complement and coagulation cascades and blood coagulation.
Conclusion: MiR-136-5p is overexpressed in lung adenocarcinoma and is involved in the molecular mechanism of lung adenocarcinoma via suppressing the expressions of downstream targets, especially claudin-18, sialophorin and syndecan 2 that participate in cell adhesion.
Keywords: Bioinformatics; Cell adhesion molecules; Lung adenocarcinoma; Meta-analysis; miR-136a-5p.
Copyright © 2018. Published by Elsevier GmbH.