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A simple method of detecting K-ras point mutations in stool samples for colorectal cancer screening using one-step polymerase chain reaction/restriction fragment length polymorphism analysis

  • Takashi Nishikawa
  • , Kentaro Maemura
  • , Ichiro Hirata
  • , Ryouichi Matsuse
  • , Hiroshi Morikawa
  • , Ken Toshina
  • , Mitsuyuki Murano
  • , Keiichi Hashimoto
  • , Yoshihito Nakagawa
  • , Osamu Saitoh
  • , Kazuo Uchida
  • , Kenichi Katsu

Research output: Contribution to journalArticlepeer-review

Abstract

Background: We examined a technique for detecting point mutations of K-ras codon 12 in stool samples using one-step polymerase chain reaction/restriction fragment length polymorphism (PCR/RFLP) analysis, in order to determine whether it could be used to screen for colorectal cancer. Methods: DNA was extracted from 200-mg stool specimens of 5 healthy controls and 31 colorectal cancer patients. A 107-base-pair fragment of exon 1 of K-ras was amplified by PCR using mismatched primers. PCR products were digested with Bst NI and analyzed by gel electrophoresis followed by silver staining. Specificity of one-step PCR/RFLP was examined by using synthetic oligonucleotides. The detection limit of K-ras codon 12 mutations was determined by using SW480 and HT29 cells. Results: The K-ras gene was successfully amplified from all healthy controls and colorectal cancer patients studied. Mutations of K-ras codon 12 were not detected in any of the healthy controls, but were identified in 13 (41.9%) of the 31 patients with colorectal cancer. Mutations were detectable in all six synthetic mutant DNAs, while none were detected among the wild type. The detection limit of this method was ≥0.1%. Conclusions: PCR/RFLP analysis could be used in mass screening for colorectal cancer, because it is highly specific, has a low detection limit, and is simpler than conventional methods for detecting genetic abnormalities.

Original languageEnglish
Pages (from-to)107-112
Number of pages6
JournalClinica Chimica Acta
Volume318
Issue number1-2
DOIs
Publication statusPublished - 2002
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Clinical Biochemistry
  • Biochemistry, medical

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