A Review of Stable Isotope Labeling and Mass Spectrometry Methods to Distinguish Exogenous from Endogenous DNA Adducts and Improve Dose-Response Assessments.
Kun LuYun-Chung HsiaoChih-Wei LiuRita SchoenyRobinan GentryThomas B StarrPublished in: Chemical research in toxicology (2021)
Cancer remains the second most frequent cause of death in human populations worldwide, which has been reflected in the emphasis placed on management of risk from environmental chemicals considered to be potential human carcinogens. The formation of DNA adducts has been considered as one of the key events of cancer, and persistence and/or failure of repair of these adducts may lead to mutation, thus initiating cancer. Some chemical carcinogens can produce DNA adducts, and DNA adducts have been used as biomarkers of exposure. However, DNA adducts of various types are also produced endogenously in the course of normal metabolism. Since both endogenous physiological processes and exogenous exposure to xenobiotics can cause DNA adducts, the differentiation of the sources of DNA adducts can be highly informative for cancer risk assessment. This review summarizes a highly applicable methodology, termed stable isotope labeling and mass spectrometry (SILMS), that is superior to previous methods, as it not only provides absolute quantitation of DNA adducts but also differentiates the exogenous and endogenous origins of DNA adducts. SILMS uses stable isotope-labeled substances for exposure, followed by DNA adduct measurement with highly sensitive mass spectrometry. Herein, the utilities and advantage of SILMS have been demonstrated by the rich data sets generated over the last two decades in improving the risk assessment of chemicals with DNA adducts being induced by both endogenous and exogenous sources, such as formaldehyde, vinyl acetate, vinyl chloride, and ethylene oxide.
Keyphrases
- circulating tumor
- cell free
- mass spectrometry
- single molecule
- risk assessment
- papillary thyroid
- liquid chromatography
- high resolution
- circulating tumor cells
- human health
- squamous cell carcinoma
- machine learning
- high performance liquid chromatography
- climate change
- gas chromatography
- artificial intelligence
- ionic liquid
- pet imaging
- tandem mass spectrometry