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Delineating colorectal cancer distribution, interaction, and risk prediction by environmental risk factors and serum trace elements.


ABSTRACT: The burden of colorectal cancer (CRC) is increasing worldwide especially in developing countries. This phenomenon may be attributable to lifestyle, dietary and environmental risk factors. We aimed to determine the level of 25 trace elements, their interaction with environmental risk factors, and subsequently develop a risk prediction model for CRC (RPM CRC). For the discovery phase, we used a hospital-based case-control study (CRC and non-CRC patients) and in the validation phase we analysed pre-symptomatic samples of CRC patients from The Malaysian Cohort Biobank. Information on the environmental risk factors were obtained and level of 25 trace elements measured using the ICP-MS method. CRC patients had lower Zn and Se levels but higher Li, Be, Al, Co, Cu, As, Cd, Rb, Ba, Hg, Tl, and Pb levels compared to non-CRC patients. The positive interaction between red meat intake???50 g/day and Co???4.77 µg/L (AP 0.97; 95% CI 0.91, 1.03) doubled the risk of CRC. A panel of 24 trace elements can predict simultaneously and accurate of high, moderate, and low risk of CRC (accuracy 100%, AUC 1.00). This study provides a new input on possible roles for various trace elements in CRC as well as using a panel of trace elements as a screening approach to CRC.

SUBMITTER: Nawi AM 

PROVIDER: S-EPMC7596468 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Delineating colorectal cancer distribution, interaction, and risk prediction by environmental risk factors and serum trace elements.

Nawi Azmawati Mohammed AM   Chin Siok Fong SF   Mazlan Luqman L   Jamal Rahman R  

Scientific reports 20201029 1


The burden of colorectal cancer (CRC) is increasing worldwide especially in developing countries. This phenomenon may be attributable to lifestyle, dietary and environmental risk factors. We aimed to determine the level of 25 trace elements, their interaction with environmental risk factors, and subsequently develop a risk prediction model for CRC (RPM CRC). For the discovery phase, we used a hospital-based case-control study (CRC and non-CRC patients) and in the validation phase we analysed pre  ...[more]

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