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      Early prediction of liver carcinogenicity due to occupational exposure to pesticides

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          Abstract

          Several studies linked between pesticides exposure and development of liver cancer, through several mechanisms inform of genotoxicity, cytotoxicity, tumor promotion, immunotoxicity and hormonal actions. This study aimed to estimate novel biomarkers for early prediction of liver malignancy due to occupational exposure to pesticides in two groups of workers with different socioeconomic standard (highly educated urban researchers and low educated rural pesticides sprayers). This study included 50 urban researchers and 50 rural pesticides sprayers occupationally exposed to pesticides. They were compared with 50 non-exposed urban researchers and 50 non-exposed rural subjects. Several tumor biomarkers were estimated; P53 protein, Alfa fetoprotein (AFP), and Alpha-L-fucosidase (AFU). Additionally, telomerase enzyme activity, Relative telomere length (RTL), and DNA damage using comet assay were measured. Furthermore, the glutathione-S-Transferase (GST) gene polymorphisms were identified for both exposed groups. Statistical analysis revealed elevated level of tumor biomarkers among exposed subjects relative to control groups in spite of being within the normal range. Increase in the DNA damage was detected, with shortening of telomere length and decrease in telomerase enzyme activity in pesticides-exposed subjects compared to their controls. Most of these changes were related to the levels of butyrylcholinesterase. Subjects with GSTT1 genotype were suggested to be more susceptible to hepatic carcinogenicity. Telomere relative length and comets assay together with GST genes polymorphisms could be used as early predictors for liver cancer susceptibility among pesticides exposed workers.

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          Author and article information

          Journal
          Mutation Research/Genetic Toxicology and Environmental Mutagenesis
          Mutation Research/Genetic Toxicology and Environmental Mutagenesis
          Elsevier BV
          13835718
          December 2018
          December 2018
          Article
          10.1016/j.mrgentox.2018.12.004
          30678827
          b11cd1c5-da04-47f5-baa5-a2c040a60e7e
          © 2018

          https://www.elsevier.com/tdm/userlicense/1.0/

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