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The potential interaction of environmental pollutants and circadian rhythm regulations that may cause leukemia

Critical Reviews in Environmental Science and Technology 2021 16 citations

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This review examined how environmental pollutants including plasticizers and endocrine disruptors can disrupt circadian clock gene expression, potentially contributing to leukemia development by impairing the tumor-suppressive functions of genes such as BMAL1, CLOCK, and PER1/2.

Body Systems
Models

Tumor suppressor genes are highly affected during the development of leukemia, including circadian clock genes. Circadian rhythms constitute an evolutionary molecular machinery involving many genes, such as BMAL1, CLOCK, CRY1, CRY2, PER1, PER2, REV-ERBa, and RORA, for tracking time and optimizing daily life during day-night cycles and seasonal changes. For circulating blood cells many of these genes coordinate their proliferation, output, and function, and therein lies their importance for the development of leukemia. Recent findings suggest that environmental pollutants may affect circadian rhythms and thus affect cancer development and treatment. Such environmental pollutants are often found in mixtures and include benzene, tobacco smoke, pesticides and microplastics. Our understanding of the molecular basis for the interaction mechanisms within complex mixtures is also growing, confirming the plausible occurrence of synergistic (superadditive effect) and antagonistic (cancellation effect) actions of pollutant cocktails. In this work, we discuss the relationship of environmental pollutants and the alteration of circadian rhythms that potentially may cause leukemia. We highlight the need of additional dimensions and perhaps a paradigm shift for future studies in relation to continuously growing magnitude of environmental pollution using multitude of disciplines such as development of high throughput reporter cell lines, other cell screening methods, contaminant measurements in leukemia patients, advanced pharmacology and toxicological measurement of mixtures and highly efficient computer analysis including artificial intelligence, among others.

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