Urine Metabolomics Analysis for Kidney Cancer Detection and Biomarker Discovery
Urine Metabolomics Analysis for Kidney Cancer Detection and Biomarker Discovery
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DOI：
10.1074/mcp.m800165-mcp200
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发表时间：
2009-03-01
影响因子：
7
通讯作者：
Weiss, Robert H.
中科院分区：
文献类型：
--
作者：
Kim, Kyoungmi;Aronov, Pavel;Weiss, Robert H.
肾细胞癌（RCC）在美国每年造成11，000人死亡。当早期发现时，通常是偶然通过其他原因进行的成像，长期生存通常是极好的。当发现有症状时，预后很差。在这些情况下，筛选生物标志物具有显著的公共卫生益处的潜力。本研究的目的是评估尿液代谢组学分析的代谢组学分析，生物标志物的鉴定，并最终设计一个尿液筛查试验RCC的效用。从两个机构的RCC和对照患者中获得50份尿样，在另一项研究中，从13名正常人中采集尿样。进行亲水相互作用色谱-质谱法，以鉴别每份样品中存在的小分子代谢物。数据分析方法包括聚类分析、主成分分析、线性判别分析、差异分析和方差成分分析。以前的工作扩展到使用更大和更多样化的患者队列来确认尿液代谢组学分析的有效性。现在表明，该技术的实用性取决于尿液收集的部位，并且存在尿代谢组学特征的大量变异来源，尽管组变异足以产生可行的生物标志物。令人惊讶的是，正常患者的尿代谢组学特征由于距最后一餐的时间而存在小程度的变化，并且肾切除术（部分或根治性）前后肾细胞癌患者的尿代谢组学特征几乎没有差异，这表明与RCC相关的代谢变化在原发性肿瘤切除后持续存在。在进一步研究了个体生物标志物的发现和识别以及残留变异源的衰减后，我们的工作表明，尿液代谢组学分析有可能导致RCC的诊断测定。Molecular & Cellular Proteomics 8：558-570，2009.
Renal cell carcinoma (RCC) accounts for 11,000 deaths per year in the United States. When detected early, generally serendipitously by imaging conducted for other reasons, long term survival is generally excellent. When detected with symptoms, prognosis is poor. Under these circumstances, a screening biomarker has the potential for substantial public health benefit. The purpose of this study was to evaluate the utility of urine metabolomics analysis for metabolomic profiling, identification of biomarkers, and ultimately for devising a urine screening test for RCC. Fifty urine samples were obtained from RCC and control patients from two institutions, and in a separate study, urine samples were taken from 13 normal individuals. Hydrophilic interaction chromatography-mass spectrometry was performed to identify small molecule metabolites present in each sample. Cluster analysis, principal components analysis, linear discriminant analysis, differential analysis, and variance component analysis were used to analyze the data. Previous work is extended to confirm the effectiveness of urine metabolomics analysis using a larger and more diverse patient cohort. It is now shown that the utility of this technique is dependent on the site of urine collection and that there exist substantial sources of variation of the urinary metabolomic profile, although group variation is sufficient to yield viable biomarkers. Surprisingly there is a small degree of variation in the urinary metabolomic profile in normal patients due to time since the last meal, and there is little difference in the urinary metabolomic profile in a cohort of pre- and postnephrectomy (partial or radical) renal cell carcinoma patients, suggesting that metabolic changes associated with RCC persist after removal of the primary tumor. After further investigations relating to the discovery and identity of individual biomarkers and attenuation of residual sources of variation, our work shows that urine metabolomics analysis has potential to lead to a diagnostic assay for RCC. Molecular & Cellular Proteomics 8:558-570, 2009.