Phua Lee Cheng, Chue Xiu Ping, Koh Poh Koon, Cheah Peh Yean, Ho Han Kiat, Chan Eric Chun Yong
Department of Pharmacy; Faculty of Science; National University of Singapore; Singapore.
Department of Colorectal Surgery; Singapore General Hospital; Singapore.
Cancer Biol Ther. 2014 Apr;15(4):389-97. doi: 10.4161/cbt.27625. Epub 2014 Jan 14.
Colorectal cancer (CRC) is a major cause of mortality in many developed countries. Effective screening strategies were called for to facilitate timely detection and to promote a better clinical outcome. In this study, the role of fecal metabonomics in the non-invasive detection of CRC was investigated. Gas chromatography/time-of-flight mass spectrometry (GC/TOFMS) was utilized for the metabolic profiling of feces obtained from 11 CRC patients and 10 healthy subjects. Concurrently, matched tumor and normal mucosae surgically excised from CRC patients were profiled. CRC patients were differentiated clearly from healthy subjects based on their fecal metabonomic profiles (orthogonal partial least squares discriminant analysis [OPLS-DA], 1 predictive and 3 Y-orthogonal components, R (2)X = 0.373, R (2)Y = 0.995, Q (2) [cumulative] = 0.215). The robustness of the OPLS-DA model was demonstrated by an area of 1 under the receiver operator characteristic curve. OPLS-DA revealed fecal marker metabolites (e.g., fructose, linoleic acid, and nicotinic acid) that provided novel insights into the tumorigenesis of CRC. Interestingly, a disparate set of CRC-related metabolic aberrations occurred at the tissue level, implying the contribution of processes beyond the direct shedding of tumor cells to the fecal metabotype. In summary, this work established proof-of-principle for GC/TOFMS-based fecal metabonomic detection of CRC and offered new perspectives on the underlying mechanisms.
在许多发达国家,结直肠癌(CRC)是主要的死亡原因之一。因此需要有效的筛查策略以促进及时检测并改善临床结果。在本研究中,调查了粪便代谢组学在CRC非侵入性检测中的作用。利用气相色谱/飞行时间质谱(GC/TOFMS)对11例CRC患者和10名健康受试者的粪便进行代谢谱分析。同时,对CRC患者手术切除的匹配肿瘤组织和正常黏膜进行分析。基于粪便代谢组学谱(正交偏最小二乘判别分析[OPLS-DA],1个预测成分和3个Y正交成分,R(2)X = 0.373,R(2)Y = 0.995,Q(2)[累积] = 0.215),CRC患者与健康受试者能够被清晰区分。OPLS-DA模型的稳健性通过受试者工作特征曲线下面积为1得到证明。OPLS-DA揭示了粪便标记代谢物(如果糖、亚油酸和烟酸),为CRC的肿瘤发生提供了新的见解。有趣的是,在组织水平上出现了一组不同的与CRC相关的代谢异常,这意味着除了肿瘤细胞直接脱落之外的过程对粪便代谢型也有贡献。总之,这项工作为基于GC/TOFMS的粪便代谢组学检测CRC建立了原理验证,并为潜在机制提供了新的视角。