DOI QR코드

DOI QR Code

Alternative Carcinogenicity Screening Assay Using Colon Cancer Stem Cells: A Quantitative PCR (qPCR)-Based Prediction System for Colon Carcinogenesis

  • Bak, Yesol (Department of Bioscience and Biotechnology, Konkuk University) ;
  • Jang, Hui-Joo (Department of Bioscience and Biotechnology, Konkuk University) ;
  • Shin, Jong-Woon (Department of Bioscience and Biotechnology, Konkuk University) ;
  • Kim, Soo-Jin (Department of Bioscience and Biotechnology, Konkuk University) ;
  • Chun, Hyun woo (Department of Bioscience and Biotechnology, Konkuk University) ;
  • Seo, Ji-Hye (Department of Dental Pharmacology, School of Dentistry and Institute of Oral Bioscience, BK21 Plus, Chonbuk National University) ;
  • No, Su-Hyun (Department of Dental Pharmacology, School of Dentistry and Institute of Oral Bioscience, BK21 Plus, Chonbuk National University) ;
  • Chae, Jung-il (Department of Dental Pharmacology, School of Dentistry and Institute of Oral Bioscience, BK21 Plus, Chonbuk National University) ;
  • Son, Dong Hee (Department of Applied Statistics, College of Natural Sciences, Sejong University) ;
  • Lee, Seung Yeoun (Department of Applied Statistics, College of Natural Sciences, Sejong University) ;
  • Hong, Jintae (College of Pharmacy and Medical Research Center, Chungbuk National University) ;
  • Yoon, Do-Young (Department of Bioscience and Biotechnology, Konkuk University)
  • 투고 : 2017.12.21
  • 심사 : 2018.02.18
  • 발행 : 2018.04.28

초록

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 ${\leq}0.05$. 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.

키워드

참고문헌

  1. Siegel RL, Miller KD, Jemal A. 2016. Cancer statistics, 2016. CA Cancer J. Clin. 66: 7-30. https://doi.org/10.3322/caac.21332
  2. Kakarala M, Wicha MS. 2008. Implications of the cancer stem-cell hypothesis for breast cancer prevention and therapy. J. Clin. Oncol. 26: 2813-2820. https://doi.org/10.1200/JCO.2008.16.3931
  3. Gusenleitner D, Auerbach SS, Melia T, Gomez HF, Sherr DH, Monti S. 2014. Genomic models of short-term exposure accurately predict long-term chemical carcinogenicity and identify putative mechanisms of action. PLoS One 9: e102579. https://doi.org/10.1371/journal.pone.0102579
  4. Hartung T. 2009. Toxicology for the twenty-first century. Nature 460: 208-212. https://doi.org/10.1038/460208a
  5. Knight A, Bailey J, Balcombe J. 2006. Animal carcinogenicity studies: implications for the REACH system. Altern. Lab. Anim. 34 Suppl 1: 139-147.
  6. Caiment F, Tsamou M, Jennen D, Kleinjans J. 2014. Assessing compound carcinogenicity in vitro using connectivity mapping. Carcinogenesis 35: 201-207. https://doi.org/10.1093/carcin/bgt278
  7. Fielden MR, Adai A, Dunn RT 2nd, Olaharski A, Searfoss G, Sina J, et al. 2011. Development and evaluation of a genomic signature for the prediction and mechanistic assessment of nongenotoxic hepatocarcinogens in the rat. Toxicol. Sci. 124: 54-74. https://doi.org/10.1093/toxsci/kfr202
  8. Matsumoto H, Yakabe Y, Saito K, Sumida K, Sekijima M, Nakayama K, et al. 2009. Discrimination of carcinogens by hepatic transcript profiling in rats following 28-day administration. Cancer Inform. 7: 253-269.
  9. Dontu G, Abdallah WM, Foley JM, Jackson KW, Clarke MF, Kawamura MJ, et al. 2003. In vitro propagation and transcriptional profiling of human mammary stem/progenitor cells. Genes Dev. 17: 1253-1270. https://doi.org/10.1101/gad.1061803
  10. Bak Y, Kwon T, Bak IS, Hong J, Yu DY, Yoon DY. 2016. IL-32theta inhibits stemness and epithelial-mesenchymal transition of cancer stem cells via the STAT3 pathway in colon cancer. Oncotarget 7: 7307-7317.
  11. Ham SY, Kwon T, Bak Y, Yu JH, Hong J, Lee SK, et al. 2016. Mucin 1-mediated chemo-resistance in lung cancer cells. Oncogenesis 5: e185. https://doi.org/10.1038/oncsis.2015.47
  12. Kwon T, Bak Y, Park YH, Jang GB, Nam JS, Yoo JE, et al. 2016. Peroxiredoxin II is essential for maintaining stemness by redox regulation in liver cancer cells. Stem Cells 34: 1188-1197. https://doi.org/10.1002/stem.2323
  13. Reddig PJ, Juliano RL. 2005. Clinging to life: cell to matrix adhesion and cell survival. Cancer Metastasis Rev. 24: 425-439. https://doi.org/10.1007/s10555-005-5134-3
  14. Rathore K, Wang HC. 2013. Mesenchymal and stem-like cell properties targeted in suppression of chronically-induced breast cell carcinogenesis. Cancer Lett. 333: 113-123. https://doi.org/10.1016/j.canlet.2013.01.030
  15. Waters MD, Jackson M, Lea I. 2010. Characterizing and predicting carcinogenicity and mode of action using conventional and toxicogenomics methods. Mutat. Res. 705: 184-200. https://doi.org/10.1016/j.mrrev.2010.04.005
  16. Khoury L, Zalko D, Audebert M. 2016. Evaluation of four human cell lines with distinct biotransformation properties for genotoxic screening. Mutagenesis 31: 83-96.
  17. Rieswijk L, Brauers KJ, Coonen ML, Jennen DG, van Breda SG, Kleinjans JC. 2016. Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity. Mutagenesis 31: 603-615. https://doi.org/10.1093/mutage/gew027
  18. Schaap MM, Wackers PF, Zwart EP, Huijskens I, Jonker MJ, Hendriks G, et al. 2015. A novel toxicogenomics-based approach to categorize (non-)genotoxic carcinogens. Arch. Toxicol. 89: 2413-2427. https://doi.org/10.1007/s00204-014-1368-6
  19. Liu CC, Tseng YT, Li W, Wu CY, Mayzus I, Rzhetsky A, et al. 2014. DiseaseConnect: a comprehensive web server for mechanism-based disease-disease connections. Nucleic Acids Res. 42: W137-W146. https://doi.org/10.1093/nar/gku412
  20. Persani L, Beck-Peccoz P, Quatrini M, Bassetti M, Travella B, Bianchi P, et al. 1991. Patterns of gastrin secretion in patients with nonfunctioning pituitary adenomas. J. Endocrinol. Invest. 14: 861-865. https://doi.org/10.1007/BF03347944
  21. Syed V, Zhang X, Lau KM, Cheng R, Mukherjee K, Ho SM. 2005. Profiling estrogen-regulated gene expression changes in normal and malignant human ovarian surface epithelial cells. Oncogene 24: 8128-8143. https://doi.org/10.1038/sj.onc.1208959
  22. Mithani SK, Smith IM, Califano JA. 2011. Use of integrative epigenetic and cytogenetic analyses to identify novel tumor-suppressor genes in malignant melanoma. Melanoma Res. 21: 298-307. https://doi.org/10.1097/CMR.0b013e328344a003