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通过小分子代谢物和脂质的解吸电喷雾电离质谱成像诊断前列腺癌。

Diagnosis of prostate cancer by desorption electrospray ionization mass spectrometric imaging of small metabolites and lipids.

作者信息

Banerjee Shibdas, Zare Richard N, Tibshirani Robert J, Kunder Christian A, Nolley Rosalie, Fan Richard, Brooks James D, Sonn Geoffrey A

机构信息

Department of Chemistry, Stanford University, Stanford, CA 94305.

Department of Chemistry, Stanford University, Stanford, CA 94305;

出版信息

Proc Natl Acad Sci U S A. 2017 Mar 28;114(13):3334-3339. doi: 10.1073/pnas.1700677114. Epub 2017 Mar 14.

Abstract

Accurate identification of prostate cancer in frozen sections at the time of surgery can be challenging, limiting the surgeon's ability to best determine resection margins during prostatectomy. We performed desorption electrospray ionization mass spectrometry imaging (DESI-MSI) on 54 banked human cancerous and normal prostate tissue specimens to investigate the spatial distribution of a wide variety of small metabolites, carbohydrates, and lipids. In contrast to several previous studies, our method included Krebs cycle intermediates ( <200), which we found to be highly informative in distinguishing cancer from benign tissue. Malignant prostate cells showed marked metabolic derangements compared with their benign counterparts. Using the "Least absolute shrinkage and selection operator" (Lasso), we analyzed all metabolites from the DESI-MS data and identified parsimonious sets of metabolic profiles for distinguishing between cancer and normal tissue. In an independent set of samples, we could use these models to classify prostate cancer from benign specimens with nearly 90% accuracy per patient. Based on previous work in prostate cancer showing that glucose levels are high while citrate is low, we found that measurement of the glucose/citrate ion signal ratio accurately predicted cancer when this ratio exceeds 1.0 and normal prostate when the ratio is less than 0.5. After brief tissue preparation, the glucose/citrate ratio can be recorded on a tissue sample in 1 min or less, which is in sharp contrast to the 20 min or more required by histopathological examination of frozen tissue specimens.

摘要

手术时在冰冻切片中准确识别前列腺癌具有挑战性,这限制了外科医生在前列腺切除术中最佳确定切除边缘的能力。我们对54份保存的人类癌性和正常前列腺组织标本进行了解吸电喷雾电离质谱成像(DESI-MSI),以研究多种小分子代谢物、碳水化合物和脂质的空间分布。与之前的几项研究不同,我们的方法纳入了三羧酸循环中间产物(<200),我们发现这些中间产物在区分癌组织和良性组织方面具有很高的信息量。与良性前列腺细胞相比,恶性前列腺细胞表现出明显的代谢紊乱。我们使用“最小绝对收缩和选择算子”(Lasso)分析了DESI-MS数据中的所有代谢物,并确定了用于区分癌组织和正常组织的简约代谢谱集。在一组独立的样本中,我们可以使用这些模型以近90%的患者准确率将前列腺癌与良性标本区分开来。基于之前关于前列腺癌的研究表明葡萄糖水平高而柠檬酸盐水平低,我们发现当葡萄糖/柠檬酸盐离子信号比超过1.0时可准确预测癌症,当该比值小于0.5时可预测为正常前列腺。经过简短的组织制备后,可在1分钟或更短时间内记录组织样本上的葡萄糖/柠檬酸盐比值,这与冰冻组织标本的组织病理学检查所需的20分钟或更长时间形成鲜明对比。

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