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Alternative carcinogenicity screening assay using colon cancer stem cells: A quantitative PCR (qPCR)-based prediction system for colon carcinogenesis

  • Yesol Bak
  • , Hui Joo Jang
  • , Jong Woon Shin
  • , Soo Jin Kim
  • , Hyun Woo Chun
  • , Ji Hye Seo
  • , Su Hyun No
  • , Jung Il Chae
  • , Dong Hee Son
  • , Seung Yeoun Lee
  • , Jintae Hong
  • , Do Young Yoon*
  • *Corresponding author for this work
  • Konkuk University
  • Jeonbuk National University
  • Sejong University
  • Chungbuk National University

Research output: Contribution to journalJournal articlepeer-review

Abstract

The carcinogenicity of chemicals in the environment is a major concern. Recently, numerous studies have attempted to develop methods for predicting carcinogenicity, including rodent and cell-based approaches. However, rodent carcinogenicity tests for evaluating the carcinogenic potential of a chemical to humans are time-consuming and costly. This study focused on the development of an alternative method for predicting carcinogenicity using quantitative PCR (qPCR) and colon cancer stem cells. A toxicogenomic method, mRNA profiling, is useful for predicting carcinogenicity. Using microarray analysis, we optimized 16 predictive gene sets from five carcinogens (azoxymethane, 3,2’-dimethyl-4-aminobiphenyl, N-ethyl-n-nitrosourea, metronidazole, 4-(n-methyl-n-nitrosamino)-1-(3-pyridyl)-1-butanone) used to treat colon cancer stem cell samples. The 16 genes were evaluated by qPCR using 23 positive and negative carcinogens in colon cancer stem cells. Among them, six genes could differentiate between positive and negative carcinogens with a p-value of ≤0.05. Our qPCR-based prediction system for colon carcinogenesis using colon cancer stem cells is cost- and time-efficient. Thus, this qPCR-based prediction system is an alternative to in vivo carcinogenicity screening assays.

Original languageEnglish
Pages (from-to)645-651
Number of pages7
JournalJournal of Microbiology and Biotechnology
Volume28
Issue number4
DOIs
StatePublished - 2018.04

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

Keywords

  • Cancer stem cell
  • Carcinogenicity
  • Colon cancer
  • Microarray
  • Quantitative PCR

Quacquarelli Symonds(QS) Subject Topics

  • Biological Sciences

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