Stice Szabina, Liu Guangliang, Matulis Shannon, Boise Lawrence H, Cai Yong
Department of Chemistry & Biochemistry, FL International University, 11200 SW 8th St., Miami, FL 33199, United States.
Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University, Atlanta, GA 30322, United States.
J Chromatogr B Analyt Technol Biomed Life Sci. 2016 Jan 15;1009-1010:55-65. doi: 10.1016/j.jchromb.2015.12.008. Epub 2015 Dec 8.
During the metabolism of different arsenic-containing compounds in human, a variety of metabolites are produced with significantly varying toxicities. Currently available analytical methods can only detect a limited number of human metabolites in biological samples during one run due to their diverse characteristics. In addition, co-elution of species is often unnoticeable with most detection techniques leading to inaccurate metabolic profiles and assessment of toxicity. A high performance liquid chromatography inductively coupled mass spectrometry (HPLC-ICP-MS) method was developed that can identify thirteen common arsenic metabolites possibly present in human with special attention dedicated to thiolated or thiol conjugated arsenicals. The thirteen species included in this study are arsenite (As(III)), arsino-glutathione (As(GS)3), arsenate (As(V)), monomethylarsonous acid (MMA(III)), monomethylarsino-glutathione (MMA(III)(GS) 2), monomethylarsonic acid (MMA(V)), dimethylarsinous acid (DMA(III) (from DMA(III)I)), S-(dimethylarsinic)cysteine (DMA(III) (Cys)), dimethylarsino-glutathione (DMA(III)(GS)), dimethylarsinic acid (DMA(V)), dimethylmonothioarsinic acid (DMMTA(V)), dimethyldithioarsinic acid (DMDTA(V)), dimethylarsinothioyl glutathione (DMMTA(V)(GS)). The developed method was applied for the analysis of cancer cells that were incubated with darinaparsin (DMA(III)(GS)), a novel chemotherapeutic agent for refractory malignancies, and the arsenic metabolic profile obtained was compared to results using a previously developed method. This method provides a useful analytical tool which is much needed in unequivocally identifying the arsenicals formed during the metabolism of environmental arsenic exposure or therapeutic arsenic administration.
在人体对不同含砷化合物的代谢过程中,会产生多种毒性差异显著的代谢产物。由于其特性各异,目前可用的分析方法在一次检测中只能检测生物样品中有限数量的人体代谢产物。此外,大多数检测技术往往无法察觉物种的共洗脱情况,从而导致代谢谱不准确以及毒性评估有误。开发了一种高效液相色谱 - 电感耦合质谱联用(HPLC - ICP - MS)方法,该方法能够识别可能存在于人体中的13种常见砷代谢产物,特别关注硫醇化或硫醇共轭的砷化合物。本研究涵盖的13种物质包括亚砷酸盐(As(III))、砷 - 谷胱甘肽(As(GS)3)、砷酸盐(As(V))、一甲基亚砷酸(MMA(III))、一甲基砷 - 谷胱甘肽(MMA(III)(GS) 2)、一甲基砷酸(MMA(V))、二甲基亚砷酸(DMA(III) (来自DMA(III)I))、S - (二甲基砷酰基)半胱氨酸(DMA(III) (Cys))、二甲基砷 - 谷胱甘肽(DMA(III)(GS))、二甲基砷酸(DMA(V))、二甲基单硫代砷酸(DMMTA(V))、二甲基二硫代砷酸(DMDTA(V))、二甲基砷硫基谷胱甘肽(DMMTA(V)(GS))。所开发的方法应用于分析与新型难治性恶性肿瘤化疗药物达瑞纳帕辛(DMA(III)(GS))一起孵育的癌细胞,并将获得的砷代谢谱与使用先前开发的方法得到的结果进行比较。该方法提供了一种有用的分析工具,这在明确识别环境砷暴露或治疗性砷给药代谢过程中形成的砷化合物方面是非常必要的。