Lipid-based biomarkers for cancer

被引:78
作者
Fernandis, Aaron Zefrin
Wenk, Markus Rene [1 ,2 ]
机构
[1] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Life Sci, Dept Biochem, Singapore 117456, Singapore
[2] Natl Univ Singapore, Dept Biol Sci, Singapore 117548, Singapore
来源
JOURNAL OF CHROMATOGRAPHY B-ANALYTICAL TECHNOLOGIES IN THE BIOMEDICAL AND LIFE SCIENCES | 2009年 / 877卷 / 26期
基金
英国医学研究理事会; 新加坡国家研究基金会;
关键词
Lipidomic; Cancer; Mass spectrometry; Multiple reaction monitoring; Biomarker; TANDEM MASS-SPECTROMETRY; LYSOPHOSPHATIDIC ACID; PROSTATE-CANCER; OVARIAN-CANCER; BREAST-CANCER; SPHINGOSINE KINASE; PLASMA LYSOPHOSPHOLIPIDS; QUANTITATIVE-ANALYSIS; POTENTIAL BIOMARKERS; CELLULAR LIPIDOMES;
D O I
10.1016/j.jchromb.2009.06.015
中图分类号
Q5 [生物化学];
学科分类号
070307 [化学生物学];
摘要
Lipids play important and diverse roles in cells. Most obvious functions are storage of chemical energy, provision of structural support of biological membranes and signaling. All these cellular processes are of critical relevance to cells which undergo transformation, cancer progression and metastasis. Thus, it is likely that certain classes of lipids are reflective for the cellular physiology in cancer cells and tissue. Here we discuss key roles of lipids involved in cancer as well as challenges for development of novel lipid-based biomarkers. Special emphasis will be given to mass spectrometry based analysis of lipids. Such technology has been successfully used for qualitative and quantitative analysis of lipids with very different chemistries. Comparative analysis, often in case-control regimes, and either in non-targeted (e.g. by liquid chrormatography-single stage mass spectrometry) or targeted (i.e. by tandem mass spectrometry) fashion yields vast at-rays of information. Uni-variate (such as Student's t-test or Mann-Whitney U-test) and multivariate statistics (principal components analysis, machine learning and regression analysis) are next used to identify variations in individual lipid species and/or to lower dimensions for visualization and grouping of cases and controls. As a result surrogate (single or multi-parameter) markers are identified which form the basis for functional validation as well as potential translation to alternative analytical readouts. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:2830 / 2835
页数:6
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