利用核磁共振代谢谱预测乳腺癌的临床终点

Prediction of Clinical Endpoints in Breast Cancer Using NMR Metabolic Profiles.

作者信息

Euceda Leslie R, Haukaas Tonje H, Bathen Tone F, Giskeødegård Guro F

机构信息

Department of Circulation and Medical Imaging - MR Center, Faculty of Medicine and Health Sciences, NTNU - Norwegian University of Science and Technology, Postboks 8905, MTFS, 7489, Trondheim, Norway.

St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.

出版信息

Methods Mol Biol. 2018;1711:167-189. doi: 10.1007/978-1-4939-7493-1_9.

DOI:10.1007/978-1-4939-7493-1_9

PMID:29344890

Abstract

Metabolic profiles reflect biological conditions as a result of biochemical changes within a living system. It is therefore possible to associate metabolic signatures with clinical endpoints of diseases, such as breast cancer. Nuclear magnetic resonance (NMR) spectroscopy is one of the most common techniques used for metabolic profiling, and produces high dimensional datasets from which meaningful biological information can be extracted. Here, we present an overview of data analysis techniques used to achieve this, describing key steps in the procedure. Moreover, examples of clinical endpoints of interest are provided. Although these are specific for breast cancer, the procedures for the analysis of NMR spectra as described here are applicable to any type of cancer and to other diseases.

摘要

代谢谱反映了生物系统内生化变化所导致的生物学状况。因此，有可能将代谢特征与疾病的临床终点联系起来，如乳腺癌。核磁共振（NMR）光谱法是用于代谢谱分析的最常用技术之一，它能产生高维数据集，从中可以提取有意义的生物学信息。在此，我们概述了用于实现这一目标的数据分析技术，描述了该过程中的关键步骤。此外，还提供了感兴趣的临床终点的实例。尽管这些实例特定于乳腺癌，但此处所述的NMR光谱分析程序适用于任何类型的癌症和其他疾病。