Bioinformatics analysis of mRNA and miRNA microarray to identify the key miRNA‑gene pairs in small‑cell lung cancer

利用生物信息学方法分析mRNA和miRNA微阵列,以鉴定小细胞肺癌中的关键miRNA-基因对。

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作者:Yun Mao ,Peng Xue ,Linlu Li ,Pengpeng Xu ,Yafang Cai ,Xuelei Chu ,Pengyuan Jiang ,Shijie Zhu

Abstract

Small‑cell lung cancer (SCLC) is a type of lung cancer with early metastasis, and high recurrence and mortality rates. The molecular mechanism is still unclear and further research is required. The aim of the present study was to examine the pathogenesis and potential molecular markers of SCLC by comparing the differential expression of mRNA and microRNA (miRNA) between SCLC tissue and normal lung tissue. A transcriptome sequencing dataset (GSE6044) and a non‑coding RNA sequence dataset (GSE19945) were downloaded from the Gene Expression Omnibus (GEO) database. In total, 451 differentially expressed genes (DEGs) and 134 differentially expressed miRNAs (DEMs) were identified using the R limma software package and the GEO2R tool of the GEO, respectively. The Gene Ontology function was significantly enriched for 28 terms, and the Kyoto Encyclopedia of Genes and Genomes database had 19 enrichment pathways, mainly related to 'cell cycle', 'DNA replication' and 'oocyte meiosis mismatch repair'. The protein‑protein interaction network was constructed using Cytoscape software to identify the molecular mechanisms of key signaling pathways and cellular activities in SCLC. The 1,402 miRNA‑gene pairs encompassed 602 target genes of the DEMs using miRNAWalk, which is a bioinformatics platform that predicts DEM target genes and miRNA‑gene pairs. There were 19 overlapping genes regulated by 32 miRNAs between target genes of the DEMs and DEGs. Bioinformatics analysis may help to better understand the role of DEGs, DEMs and miRNA‑gene pairs in cell proliferation and signal transduction. The related hub genes may be used as biomarkers for the diagnosis and prognosis of SCLC, and as potential drug targets.

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