ID 111123
著者
Kohmoto, Tomohiro Tokushima University
Shoda, Katsutoshi Tokushima University|Kyoto Prefectural University of Medicine
Hamada, Junichi Tokushima University|Kyoto Prefectural University of Medicine
Ichikawa, Daisuke Kyoto Prefectural University of Medicine
田嶋, 敦 Tokushima University|Kanazawa University KAKEN研究者をさがす
Otsuji, Eigo Kyoto Prefectural University of Medicine
キーワード
Gastric cancer
exome
somatic mutations
variant calling algorithms
資料タイプ
学術雑誌論文
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 standardmethod 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 somaticmutations in GC andmay be useful for further genomic characterization of Japanese patients with GC to improve the efficacy of GC treatments.
掲載誌名
The Journal of Medical Investigation
ISSN
13496867
13431420
cat書誌ID
AA11166929
AA12022913
出版者
Faculty of Medicine Tokushima University
64
3-4
開始ページ
233
終了ページ
240
並び順
233
発行日
2017-08
出版社版DOI
出版社版URL
フルテキストファイル
言語
eng
著者版フラグ
出版社版
部局
医学系