Construction of a combinatorial pipeline using two somatic variant  calling  methods  for whole exome sequence data of gastric cancer

• Kohmoto Tomohiro

  Department of Human Genetics, Graduate School of Biomedical Sciences, Tokushima University

• Masuda Kiyoshi

  Department of Human Genetics, Graduate School of Biomedical Sciences, Tokushima University

• Naruto Takuya

  Department of Human Genetics, Graduate School of Biomedical Sciences, Tokushima University

• Tange Shoichiro

  Department of Human Genetics, Graduate School of Biomedical Sciences, Tokushima University

• Shoda Katsutoshi

  Department of Human Genetics, Graduate School of Biomedical Sciences, Tokushima University Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine

• Hamada Junichi

  Department of Human Genetics, Graduate School of Biomedical Sciences, Tokushima University Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine

• Saito Masako

  Department of Human Genetics, Graduate School of Biomedical Sciences, Tokushima University

• Ichikawa Daisuke

  Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine

• Tajima Atsushi

  Department of Human Genetics, Graduate School of Biomedical Sciences, Tokushima University Department of Bioinformatics and Genomics, Graduate School of Advanced Preventive Medical Sciences, Kanazawa University

• Otsuji Eigo

  Division of Digestive Surgery, Department of Surgery, Kyoto Prefectural University of Medicine

• Imoto Issei

  Department of Human Genetics, Graduate School of Biomedical Sciences, Tokushima University

抄録

High-throughput next-generation sequencing is a powerful tool to identify the genotypic landscapes of somatic variants and therapeutic targets in various cancers including gastric cancer, forming the basis for personalized medicine in the clinical setting. Although the advent of many computational algorithms leads to higher accuracy in somatic variant calling, no standard method exists due to the limitations of each method. Here, we constructed a new pipeline. We combined two different somatic variant callers with different algorithms, Strelka and VarScan 2, and evaluated performance using whole exome sequencing data obtained from 19 Japanese cases with gastric cancer (GC); then, we characterized these tumors based on identified driver molecular alterations. More single nucleotide variants (SNVs) and small insertions/deletions were detected by Strelka and VarScan 2, respectively. SNVs detected by both tools showed higher accuracy for estimating somatic variants compared with those detected by only one of the two tools and accurately showed the mutation signature and mutations of driver genes reported for GC. Our combinatorial pipeline may have an advantage in detection of somatic mutations in GC and may be useful for further genomic characterization of Japanese patients with GC to improve the efficacy of GC treatments. J. Med. Invest. 64: 233-240, August, 2017

収録刊行物

• The Journal of Medical Investigation

  The Journal of Medical Investigation 64 (3.4), 233-240, 2017

  国立大学法人　徳島大学医学部

キーワード

• Gastric cancer
• exome
• somatic mutations
• variant calling algorithms

詳細情報

• CRID: 1390001204247529344
• NII論文ID: 130006105184
• NII書誌ID: AA11166929
• DOI: 10.2152/jmi.64.233
• ISSN: 13496867
• ISSN: 13431420
• PubMed: 28954988
• Web Site: http://repo.lib.tokushima-u.ac.jp/111123
• Web Site: https://www.jstage.jst.go.jp/article/jmi/64/3.4/64_233/_pdf
• Web Site: https://search.jamas.or.jp/link/ui/2018243161
• 本文言語コード: en
• データソース種別:
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  • IRDB
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