MicroRNA Profiling of Fresh Lung Adenocarcinoma and Adjacent Normal Tissues from Ten Korean Patients Using miRNA-Seq

Jihye Park, Sae Jung Na, Jung Sook Yoon, Seoree Kim, Sang Hoon Chun, Jae Jun Kim, Young-Du Kim, Young-Ho Ahn, Keunsoo Kang () and Yoon Ho Ko ()
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Jihye Park: Department of Microbiology, College of Science & Technology, Dankook University, Cheonan 31116, Republic of Korea
Sae Jung Na: Department of Radiology, Uijeongbu St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
Jung Sook Yoon: Uijeongbu St. Mary’s Hospital Clinical Research Laboratory, The Catholic University of Korea, Uijeongbu 11765, Republic of Korea
Seoree Kim: Division of Medical Oncology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
Sang Hoon Chun: Division of Medical Oncology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
Jae Jun Kim: Department of Thoracic and Cardiovascular Surgery, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
Young-Du Kim: Department of Thoracic and Cardiovascular Surgery, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
Young-Ho Ahn: Department of Molecular Medicine and Inflammation-Cancer Microenvironment Research Center, College of Medicine, Ewha Womans University, Seoul 07804, Republic of Korea
Keunsoo Kang: Department of Microbiology, College of Science & Technology, Dankook University, Cheonan 31116, Republic of Korea
Yoon Ho Ko: Division of Medical Oncology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea

Data, 2023, vol. 8, issue 6, 1-7

Abstract: MicroRNA transcriptomes from fresh tumors and the adjacent normal tissues were profiled in 10 Korean patients diagnosed with lung adenocarcinoma using a next-generation sequencing (NGS) technique called miRNA-seq. The sequencing quality was assessed using FastQC, and low-quality or adapter-contaminated portions of the reads were removed using Trim Galore. Quality-assured reads were analyzed using miRDeep2 and Bowtie. The abundance of known miRNAs was estimated using the reads per million (RPM) normalization method. Subsequently, using DESeq2 and Wx, we identified differentially expressed miRNAs and potential miRNA biomarkers for lung adenocarcinoma tissues compared to adjacent normal tissues, respectively. We defined reliable miRNA biomarkers for lung adenocarcinoma as those detected by both methods. The miRNA-seq data are available in the Gene Expression Omnibus (GEO) database under accession number GSE196633, and all processed data can be accessed via the Mendeley data website.

Keywords: microRNA; lung adenocarcinoma; Korean patients; next-generation sequencing; miRNA-seq; Wx; deep learning (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2023
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