Chakraborty Tanushree, Manna Soumen Kanti
Biophysics and Structural Genomics Division, Saha Institute of Nuclear Physics (HBNI), Kolkata, India.
Methods Mol Biol. 2019;1928:205-234. doi: 10.1007/978-1-4939-9027-6_12.
Cancer poses a daunting challenge to researchers and clinicians alike. Early diagnosis, accurate prognosis, and prediction of therapeutic response remain elusive in most types of cancer. In addition, lacunae in our understanding of cancer biology continue to hinder advancement of therapeutic strategies. Metabolic reprogramming has been identified as integral to pathogenesis and progression of the disease. Consequently, analysis of biofluid metabolome has emerged as a promising approach to further our understanding of disease biology as well as to identify cancer biomarkers. However, unbiased identification of robust and meaningful differences in metabolic signatures remains a non-trivial task. This chapter describes a generalized strategy for global metabolic profiling of human biofluids using ultra-performance liquid chromatography (UPLC) and mass spectrometry, which together offer a sensitive, high-throughput, and versatile platform. A step-by-step protocol for performing untargeted metabolic profiling of urine and serum (or plasma), using hydrophilic interaction liquid chromatography (HILIC) or reverse-phase (RP) chromatography coupled with electrospray ionization mass spectrometry (ESI-MS) to multivariate data analysis and identification of metabolites of interest has been detailed.
癌症对研究人员和临床医生来说都是一项艰巨的挑战。在大多数癌症类型中，早期诊断、准确的预后以及治疗反应的预测仍然难以实现。此外，我们对癌症生物学认识的空白继续阻碍着治疗策略的进步。代谢重编程已被确定为该疾病发病机制和进展所不可或缺的一部分。因此，生物流体代谢组分析已成为一种有前景的方法，有助于我们进一步了解疾病生物学以及识别癌症生物标志物。然而，无偏差地识别代谢特征中稳健且有意义的差异仍然是一项艰巨的任务。本章描述了一种使用超高效液相色谱（UPLC）和质谱对人类生物流体进行全局代谢谱分析的通用策略，二者共同提供了一个灵敏、高通量且多功能的平台。详细介绍了一个逐步的方案，用于使用亲水相互作用液相色谱（HILIC）或反相（RP）色谱结合电喷雾电离质谱（ESI-MS）对尿液和血清（或血浆）进行非靶向代谢谱分析，直至多变量数据分析以及识别感兴趣的代谢物。
