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2 "Genetic markers"
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Original Article
Quantitative Analysis of Cancer-associated Gene Methylation Connected to Risk Factors in Korean Colorectal Cancer Patients
Ho-Jin Kang, Eun-Jeong Kim, Byoung-Gwon Kim, Chang-Hun You, Sang-Yong Lee, Dong-Il Kim, Young-Seoub Hong
J Prev Med Public Health. 2012;45(4):251-258.   Published online July 31, 2012
DOI: https://doi.org/10.3961/jpmph.2012.45.4.251
Correction in: J Prev Med Public Health 2012;45(5):333
  • 9,445 View
  • 69 Download
  • 11 Crossref
AbstractAbstract PDF
Objectives

The purpose of this paper was to elucidate the potential methylation levels of adjacent normal and cancer tissues by comparing them with normal colorectal tissues, and to describe the correlations between the methylation and clinical parameters in Korean colorectal cancer (CRC) patients.

Methods

Hypermethylation profiles of nine genes (RASSF1, APC, p16INK4a, Twist1, E-cadherin, TIMP3, Smad4, COX2, and ABCB1) were examined with 100 sets of cancer tissues and 14 normal colorectal tissues. We determined the hypermethylation at a given level by a percent of methylation ratio value of 10 using quantitative methylation real-time polymerase chain reaction.

Results

Nine genes' hypermethylation levels in Korean CRC patient tissues were increased more higher than normal colorectal tissues. However, the amounts of p16INK4a and E-cadherin gene hypermethylation in normal and CRC tissues were not significantly different nor did TIMP3 gene hypermethylation in adjacent normal and cancer tissues differ significantly. The hypermethylation of TIMP3, E-cadherin, ABCB1, and COX2 genes among other genes were abundantly found in normal colorectal tissues. The hypermethylation of nine genes' methylation in cancer tissues was not significantly associated with any clinical parameters. In Cohen's kappa test, it was moderately observed that RASSF1 was related with E-cadherin, and Smad4 with ABCB1 and COX2.

Conclusions

This study provides evidence for different hypermethylation patterns of cancer-associated genes in normal and CRC tissues, which may serve as useful information on CRC cancer progression.

Summary

Citations

Citations to this article as recorded by  
  • Relevance of gene mutations and methylation to the growth of pancreatic intraductal papillary mucinous neoplasms based on pyrosequencing
    Go Asano, Katsuyuki Miyabe, Hiroyuki Kato, Michihiro Yoshida, Takeshi Sawada, Yasuyuki Okamoto, Hidenori Sahashi, Naoki Atsuta, Kenta Kachi, Akihisa Kato, Naruomi Jinno, Makoto Natsume, Yasuki Hori, Itaru Naitoh, Kazuki Hayashi, Yoichi Matsuo, Satoru Taka
    Scientific Reports.2022;[Epub]     CrossRef
  • Potential of RASSF1A promoter methylation as a biomarker for colorectal cancer: Meta-analysis and TCGA analysis
    Fei Hu, Li Chen, Ming-Yu Bi, Ling Zheng, Ji-Xiang He, Ying-Ze Huang, Yu Zhang, Xue-Lian Zhang, Qiang Guo, Ying Luo, Wen-Ru Tang, Miao-Miao Sheng
    Pathology - Research and Practice.2020; 216(8): 153009.     CrossRef
  • KLHL22 Regulates the EMT and Proliferation in Colorectal Cancer Cells in Part via the Wnt/β-Catenin Signaling Pathway


    Yi Song, Huiping Yuan, Jia Wang, Yuhe Wu, Yuhong Xiao, Shengxun Mao
    Cancer Management and Research.2020; Volume 12: 3981.     CrossRef
  • RHBDF1 regulates APC-mediated stimulation of the epithelial-to-mesenchymal transition and proliferation of colorectal cancer cells in part via the Wnt/β-catenin signalling pathway
    Huiping Yuan, Ran Wei, Yuhong Xiao, Yi Song, Jia Wang, Huihuan Yu, Ting Fang, Wei Xu, Shengxun Mao
    Experimental Cell Research.2018; 368(1): 24.     CrossRef
  • Smoking induces coordinated DNA methylation and gene expression changes in adipose tissue with consequences for metabolic health
    Pei-Chien Tsai, Craig A. Glastonbury, Melissa N. Eliot, Sailalitha Bollepalli, Idil Yet, Juan E. Castillo-Fernandez, Elena Carnero-Montoro, Thomas Hardiman, Tiphaine C. Martin, Alice Vickers, Massimo Mangino, Kirsten Ward, Kirsi H. Pietiläinen, Panos Delo
    Clinical Epigenetics.2018;[Epub]     CrossRef
  • A Novel Discriminating Colorectal Cancer Model for Differentiating Normal and Tumor Tissues
    Xiaohui Sun, Yiping Tian, Qianqian Zheng, Ruizhi Zheng, Aifen Lin, Tianhui Chen, Yimin Zhu, Maode Lai
    Epigenomics.2018; 10(11): 1463.     CrossRef
  • APC hypermethylation for early diagnosis of colorectal cancer: a meta-analysis and literature review
    Tie-Jun Liang, Hong-Xu Wang, Yan-Yan Zheng, Ying-Qing Cao, Xiaoyu Wu, Xin Zhou, Shu-Xiao Dong
    Oncotarget.2017; 8(28): 46468.     CrossRef
  • RETRACTED ARTICLE: Aberrant promoter methylation of RASSF1A gene may be correlated with colorectal carcinogenesis: a meta-analysis
    He-Ling Wang, Yu Zhang, Peng Liu, Ping-Yi Zhou
    Molecular Biology Reports.2014; 41(6): 3991.     CrossRef
  • Role of CDH1 Promoter Methylation in Colorectal Carcinogenesis: A Meta-Analysis
    Yu-Xi Li, Yao Lu, Chun-Yu Li, Peng Yuan, Shu-Sen Lin
    DNA and Cell Biology.2014; 33(7): 455.     CrossRef
  • Retracted: Promoter Methylation of theRASSF1AGene may Contribute to Colorectal Cancer Susceptibility: A Meta-Analysis of Cohort Studies
    He-Ling Wang, Peng Liu, Ping-Yi Zhou, Yu Zhang
    Annals of Human Genetics.2014; 78(3): 208.     CrossRef
  • Hypermethylation ofTWIST1andNID2in Tumor Tissues and Voided Urine in Urinary Bladder Cancer Patients
    Zeynep Yegin, Sezgin Gunes, Recep Buyukalpelli
    DNA and Cell Biology.2013; 32(7): 386.     CrossRef
Review
Risk Assessment and Pharmacogenetics in Molecular and Genomic Epidemiology.
Sue K Park, Ji Yeob Choi
J Prev Med Public Health. 2009;42(6):371-376.
DOI: https://doi.org/10.3961/jpmph.2009.42.6.371
  • 5,149 View
  • 60 Download
  • 3 Crossref
AbstractAbstract PDF
In this article, we reviewed the literature on risk assessment (RA) models with and without molecular genomic markers and the current utility of the markers in the pharmacogenetic field. Epidemiological risk assessment is applied using statistical models and equations established from current scientific knowledge of risk and disease. Several papers have reported that traditional RA tools have significant limitations in decision-making in management strategies for individuals as predictions of diseases and disease progression are inaccurate. Recently, the model added information on the genetic susceptibility factors that are expected to be most responsible for differences in individual risk. On the continuum of health care, from diagnosis to treatment, pharmacogenetics has been developed based on the accumulated knowledge of human genomic variation involving drug distribution and metabolism and the target of action, which has the potential to facilitate personalized medicine that can avoid therapeutic failure and serious side effects. There are many challenges for the applicability of genomic information in a clinical setting. Current uses of genetic markers for managing drug therapy and issues in the development of a valid biomarker in pharmacogenetics are discussed.
Summary

Citations

Citations to this article as recorded by  
  • Selected LDLR and APOE Polymorphisms Affect Cognitive and Functional Response to Lipophilic Statins in Alzheimer’s Disease
    Fabricio Ferreira de Oliveira, Elizabeth Suchi Chen, Marilia Cardoso Smith, Paulo Henrique Ferreira Bertolucci
    Journal of Molecular Neuroscience.2020; 70(10): 1574.     CrossRef
  • Towards a personalized risk assessment for exposure of humans to toxic substances
    Thaís de Almeida Pedrete, Caroline de Lima Mota, Eline Simões Gonçalves, Josino Costa Moreira
    Cadernos Saúde Coletiva.2016; 24(2): 262.     CrossRef
  • Effect of genetic and environmental influences on cardiometabolic risk factors: a twin study
    György Jermendy, Tamás Horváth, Levente Littvay, Rita Steinbach, Ádám L Jermendy, Ádám D Tárnoki, Dávid L Tárnoki, Júlia Métneki, János Osztovits
    Cardiovascular Diabetology.2011; 10(1): 96.     CrossRef

JPMPH : Journal of Preventive Medicine and Public Health