通过脂质组学和生物信息学鉴定前列腺癌的血浆脂质生物标志物。
Identification of plasma lipid biomarkers for prostate cancer by lipidomics and bioinformatics.
机构信息
Department of Pathology, University of Mississippi Medical Center, Jackson, Mississippi, United States of America.
出版信息
PLoS One. 2012;7(11):e48889. doi: 10.1371/journal.pone.0048889. Epub 2012 Nov 12.
BACKGROUND
Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer.
METHODOLOGY/PRINCIPAL FINDINGS: Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer.
CONCLUSIONS/SIGNIFICANCE: Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy.
背景
脂质在细胞能量储存、结构和信号传递中具有关键功能。许多单个脂质分子与前列腺癌的进化有关；然而，没有一种被批准作为生物标志物使用。本研究旨在从数百种血浆表观脂质种类中鉴定出脂质分子作为前列腺癌诊断的生物标志物。
方法/主要发现：使用脂质组学，对 105 名前列腺癌患者和 36 名男性对照的 141 份血浆样本进行了 390 种个体表观脂质种类的脂质谱分析。来自脂质组学的高通量数据使用生物信息学和统计方法进行分析。在 390 种表观脂质种类中，有 35 种被证明具有区分前列腺癌的潜力。在这 35 种物种中，有 12 种被鉴定为个体血浆脂质生物标志物，用于诊断前列腺癌，其敏感性高于 80%，特异性高于 50%，准确性高于 80%。使用前 15 种 35 种潜在生物标志物一起显著提高了前列腺癌诊断的预测能力，其敏感性为 93.6%，特异性为 90.1%，准确性为 97.3%。主成分分析（PCA）和层次聚类分析（HCA）表明，通过鉴定的脂质生物标志物，患者和对照人群在视觉上是分开的。随机森林和 10 倍交叉验证分析表明，鉴定的脂质生物标志物能够准确预测未知人群，且不受患者年龄和种族的影响。在 13 种脂质类别中有 3 种，磷脂酰乙醇胺（PE）、醚连接磷脂酰乙醇胺（ePE）和醚连接磷脂酰胆碱（ePC）可被视为前列腺癌诊断的生物标志物。
结论/意义：使用脂质组学以及生物信息学和统计方法，我们已经从数百种血浆表观脂质分子中鉴定出几种作为前列腺癌诊断的生物标志物，具有较高的敏感性、特异性和准确性。
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