Abstract

BackgroundThe aim of this study was to gain further investigation of non-small cell lung cancer (NSCLC) tumorigenesis and identify biomarkers for clinical management of patients through comprehensive bioinformatics analysis.MethodsmiRNA and mRNA microarray datasets were downloaded from GEO (Gene Expression Omnibus) database under the accession number GSE102286 and GSE101929, respectively. Genes and miRNAs with differential expression were identified in NSCLC samples compared with controls, respectively. The interaction between differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs) was predicted, followed by functional enrichment analysis, and construction of miRNA-gene regulatory network, protein-protein interaction (PPI) network, and competing endogenous RNA (ceRNA) network. Through comprehensive bioinformatics analysis, we anticipate to find novel therapeutic targets and biomarkers for NSCLC.ResultsA total of 123 DEmiRs (5 up- and 118 down-regulated miRNAs) and 924 DEGs (309 up- and 615 down-regulated genes) were identified. These genes and miRNAs were significantly involved in different pathways including adherens junction, relaxin signaling pathway, and axon guidance. Furthermore, hsa-miR-9-5p, has-miR-196a-5p and hsa-miR-31-5p, as well as hsa-miR-1, hsa-miR-218-5p and hsa-miR-135a-5p were shown to have higher degree in the miRNA-gene regulatory network and ceRNA network, respectively. Furthermore, BIRC5 and FGF2, as well as RTKN2 and SLIT3 were hubs in the PPI network and ceRNA network, respectively.ConclusionSeveral pathways (adherens junction, relaxin signaling pathway, and axon guidance) miRNAs (hsa-miR-9-5p, has-miR-196a-5p, hsa-miR-31-5p, hsa-miR-1, hsa-miR-218-5p and hsa-miR-135a-5p) and genes (BIRC5, FGF2, RTKN2 and SLIT3) may play important roles in the pathogenesis of NSCLC.

Highlights

  • The aim of this study was to gain further investigation of non-small cell lung cancer (NSCLC) tumorigenesis and identify biomarkers for clinical management of patients through comprehensive bioinformatics analysis

  • MiRNA and mRNA microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database under the accession number GSE102286 and GSE101929, Fig. 1 Principal component analysis (PCA) and volcano plots of differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiR). a, PCA of DEGs. b, volcano plot of DEGs. c, PCA of DEmiR. d, volcano plot of DEmiR

  • We found that the DEGs and DEmiR were associated with relaxin signaling pathway

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Summary

Introduction

The aim of this study was to gain further investigation of non-small cell lung cancer (NSCLC) tumorigenesis and identify biomarkers for clinical management of patients through comprehensive bioinformatics analysis. Morris et al reported that FPR1 mRNA levels in whole blood predicts both NSCLC and small cell lung cancer [7]. MicroRNAs (miRNAs) are a large group of small non-coding RNAs of 20–24 nucleotides that are involved in the fine-tuning of various biological processes. They bind to multiple target mRNAs typically in the 3′-untranslated region (3′-UTR) and govern gene expression at the post-transcriptional level [8]. A possible tumor suppressor role for hsa-miR-30d in progression of NSCLC was shown in a recent study [9]. The roles of genes and miRNAs in NSCLCs are still not well understood [11]

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