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

Author:

Park Jihye1ORCID,Na Sae Jung2,Yoon Jung Sook3,Kim Seoree4,Chun Sang Hoon4ORCID,Kim Jae Jun5,Kim Young-Du5,Ahn Young-Ho6ORCID,Kang Keunsoo1ORCID,Ko Yoon Ho47ORCID

Affiliation:

1. Department of Microbiology, College of Science & Technology, Dankook University, Cheonan 31116, Republic of Korea

2. Department of Radiology, Uijeongbu St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea

3. Uijeongbu St. Mary’s Hospital Clinical Research Laboratory, The Catholic University of Korea, Uijeongbu 11765, Republic of Korea

4. Division of Medical Oncology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea

5. Department of Thoracic and Cardiovascular Surgery, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea

6. Department of Molecular Medicine and Inflammation-Cancer Microenvironment Research Center, College of Medicine, Ewha Womans University, Seoul 07804, Republic of Korea

7. Cancer Research Institute, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea

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.

Funder

National Research Foundation of Korea

National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea

Publisher

MDPI AG

Subject

Information Systems and Management,Computer Science Applications,Information Systems

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