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代谢组学的新兴领域:在癌症生物标志物识别和药物发现方面前景广阔。

Emerging field of metabolomics: big promise for cancer biomarker identification and drug discovery.

作者信息

Patel Seema, Ahmed Shadab

机构信息

Bioinformatics and Medical Informatics Research Center, San Diego State University, San Diego 92182, USA.

Institute of Bioinformatics and Biotechnology, Savitribai Phule Pune University, Pune 411007, India.

出版信息

J Pharm Biomed Anal. 2015 Mar 25;107:63-74. doi: 10.1016/j.jpba.2014.12.020. Epub 2014 Dec 22.

Abstract

Most cancers are lethal and metabolic alterations are considered a hallmark of this deadly disease. Genomics and proteomics have contributed vastly to understand cancer biology. Still there are missing links as downstream to them molecular divergence occurs. Metabolomics, the omic science that furnishes a dynamic portrait of metabolic profile is expected to bridge these gaps and boost cancer research. Metabolites being the end products are more stable than mRNAs or proteins. Previous studies have shown the efficacy of metabolomics in identifying biomarkers associated with diagnosis, prognosis and treatment of cancer. Metabolites are highly informative about the functional status of the biological system, owing to their proximity to organismal phenotypes. Scores of publications have reported about high-throughput data generation by cutting-edge analytic platforms (mass spectrometry and nuclear magnetic resonance). Further sophisticated statistical softwares (chemometrics) have enabled meaningful information extraction from the metabolomic data. Metabolomics studies have demonstrated the perturbation in glycolysis, tricarboxylic acid cycle, choline and fatty acid metabolism as traits of cancer cells. This review discusses the latest progress in this field, the future trends and the deficiencies to be surmounted for optimally implementation in oncology. The authors scoured through the most recent, high-impact papers archived in Pubmed, ScienceDirect, Wiley and Springer databases to compile this review to pique the interest of researchers towards cancer metabolomics.

摘要

大多数癌症是致命的,代谢改变被认为是这种致命疾病的一个标志。基因组学和蛋白质组学在理解癌症生物学方面做出了巨大贡献。然而,由于在它们下游会发生分子差异,仍然存在一些缺失环节。代谢组学,即提供代谢谱动态图谱的组学科学,有望弥合这些差距并推动癌症研究。代谢物作为终产物比mRNA或蛋白质更稳定。先前的研究表明代谢组学在识别与癌症诊断、预后和治疗相关的生物标志物方面的功效。由于代谢物与生物体表型接近,它们能高度反映生物系统的功能状态。大量出版物报道了通过前沿分析平台(质谱和核磁共振)生成高通量数据的情况。进一步复杂的统计软件(化学计量学)能够从代谢组学数据中提取有意义的信息。代谢组学研究已经证明糖酵解、三羧酸循环、胆碱和脂肪酸代谢的紊乱是癌细胞的特征。本综述讨论了该领域的最新进展、未来趋势以及在肿瘤学中最佳应用有待克服的不足。作者在PubMed、ScienceDirect、Wiley和Springer数据库中搜索了最新的、高影响力的论文来撰写本综述,以激发研究人员对癌症代谢组学的兴趣。

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