Identification of a candidate single-nucleotide polymorphism related to chemotherapeutic response through a combination of knowledge-based algorithm and hypothesis-free genomic data

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Author(s)

    • Takahashi Hiro Takahashi Hiro
    • Graduate School of Horticulture, Chiba University:Plant Biology Research Center, Chubu University:Division of Genetics, National Cancer Center Research Institute
    • Sai Kimie
    • Division of Medical Safety Science, National Institute of Health Sciences
    • Hamaguchi Tetsuya
    • Gastrointestinal Medical Oncology Division, National Cancer Center Hospital
    • Shirao Kuniaki
    • Gastrointestinal Medical Oncology Division, National Cancer Center Hospital
    • Shimada Yasuhiro
    • Gastrointestinal Medical Oncology Division, National Cancer Center Hospital
    • Matsumura Yasuhiro
    • Division of Developental Therapeutics, Research Center for Innovative Oncology, National Cancer Center Hospital East
    • Ohtsu Atsushi
    • Department of Gastrointestinal Oncology, National Cancer Center Hospital East
    • Yoshino Takayuki
    • Department of Gastrointestinal Oncology, National Cancer Center Hospital East
    • Odaka Yoko
    • Division of Genetics, National Cancer Center Research Institute
    • Okuyama Misuzu
    • Division of Genetics, National Cancer Center Research Institute
    • Sawada Jun-ichi
    • Division of Functional Biochemistry and Genomics, National Institute of Health Sciences:(Present office)Pharmaceutical and Medical Devices Agency

Abstract

Inter-individual variations in drug responses among patients are known to cause serious problems in medicine. Genome-wide association study (GWAS) is powerful for examining single-nucleotide polymorphisms (SNPs) and their relationships with drug response variations. However, no significant SNP has been identified using GWAS due to multiple testing problems. Therefore, we propose a combination method consisting of knowledge-based algorithm, two stages of screening, and permutation test for identifying SNPs in the present study. We applied this method to a genome-wide pharmacogenomics study for which 109,365 SNPs had been genotyped using Illumina Human-1 BeadChip for 119 gastric cancer patients treated with fluoropyrimidine. We identified rs2293347 in epidermal growth factor receptor (EGFR) is as a candidate SNP related to chemotherapeutic response. The p value for the rs2293347 was 2.19×10^<-5> for Fisher's exact test, and the p value was 0.00360 for the permutation test (multiple testing problems are corrected). Additionally, rs2293347 was clearly superior to clinical parameters and showed a sensitivity value of 55.0% and specificity value of 94.4% in the evaluation by using multiple regression models. Recent studies have shown that combination chemotherapy of fluoropyrimidine and EGFR-targeting agents is effective for gastric cancer patients highly expressing EGFR. These results suggest that rs2293347 is a potential predictive factor for selecting chemotherapies, such as fluoropyrimidine alone or combination chemotherapies.

Journal

  • Journal of bioscience and bioengineering

    Journal of bioscience and bioengineering 116(6), 768-773, 2013-12

    The Society for Biotechnology, Japan

Codes

  • NII Article ID (NAID)
    110009687843
  • NII NACSIS-CAT ID (NCID)
    AA11307678
  • Text Lang
    ENG
  • ISSN
    1389-1723
  • NDL Article ID
    025121362
  • NDL Call No.
    Z53-S65
  • Data Source
    NDL  NII-ELS  Crossref 
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