using a massively parallel sequencing technique to compare non-small-cell lung cancer (NSCLC) tissue and normal lung tissue. Lung cancer tissue and normal ...
MOLECULAR MEDICINE REPORTS 11: 2034-2040, 2015
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Differential expression of microRNAs and their target genes in non-small-cell lung cancer HUI-YOUNG LEE1, SEON-SOOK HAN1, HWANSEOK RHEE2, JUNG HOON PARK2, JAE SEUNG LEE3,4, YEON-MOK OH3,4, SUN SHIM CHOI5, SEUNG-HO SHIN5 and WOO JIN KIM1 1
Department of Internal Medicine, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon-si, Gangwon-do 200-722; 2Macrogen Bioinformatics Center, Macrogen, Seoul 153-023; 3 Department of Pulmonary and Critical Care Medicine and 4Clinical Research Center for Chronic Obstructive Airway Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul 138-736; 5 Department of Medical Biotechnology, College of Biomedical Science and Institute of Bioscience and Biotechnology, Kangwon National University, Chuncheon-si, Gangwon-do 200-701, Republic of Korea Received March 21, 2014; Accepted September 9, 2014 DOI: 10.3892/mmr.2014.2890 Abstract. MicroRNAs (miRNAs) are single‑stranded RNA species that constitute a class of non‑coding RNAs, and are emerging as key regulators of gene expression. Since each miRNA is capable of regulating multiple genes, miRNAs are attractive markers for studies of coordinated gene expression. In this study, we investigated miRNA expression profiling using a massively parallel sequencing technique to compare non‑small‑cell lung cancer (NSCLC) tissue and normal lung tissue. Lung cancer tissue and normal lung tissue were obtained from nine NSCLC patients. RNA isolated from these samples was processed using RNA sequencing (RNA Seq) and the HiSeq 2000 system. Differentially expressed miRNAs and mRNAs were analyzed using a t‑test. We selected target pairs that showed a negative correlation among significantly differentially expressed miRNAs and their putative target mRNAs using miRBase Targets. The differences in the expression levels of 222 miRNAs and 1,597 genes were statistically significant, as indicated by an absolute fold change ≥1.5 and P90% of the samples and samples with zero values across >80% of the miRNAs. We added 1 to the RPM value to facilitate log10 transformation. The remaining data processing was as for mRNA analysis. Integrative (mRNA‑miRNA) analysis. We performed mRNA‑miRNA data integration for matched samples in each data set. First, genes and miRNAs whose expression differed significantly (absolute fold change ≥1.5 and P
