Metabolite Analysis and Histology on the Exact Same Tissue: Comprehensive Metabolomic Profiling and Metabolic Classification of Prostate Cancer.
Metabolite Analysis and Histology on the Exact Same Tissue: Comprehensive Metabolomic Profiling and Metabolic Classification of Prostate Cancer.
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完全相同组织的代谢分析和组织学：前列腺癌的综合代谢组学分析和代谢分类。
DOI：
10.1038/srep32272
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发表时间：
2016-08-31
影响因子：
4.6
通讯作者：
Li L
中科院分区：
文献类型：
--
作者：
Huan T;Troyer DA;Li L
We report a method of metabolomic profiling of intact tissue based on molecular preservation by extraction and fixation (mPREF) and high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS). mPREF extracts metabolites by aqueous methanol from tissue biopsies without altering tissue architecture and thus conventional histology can be performed on the same tissue. In a proof-of-principle study, we applied dansylation LC-MS to profile the amine/phenol submetabolome of prostate needle biopsies from 25 patient samples derived from 16 subjects. 2900 metabolites were consistently detected in more than 50% of the samples. This unprecedented coverage allowed us to identify significant metabolites for differentiating tumor and normal tissues. The panel of significant metabolites was refined using 36 additional samples from 18 subjects. Receiver Operating Characteristic (ROC) analysis showed area-under-the-curve (AUC) of 0.896 with sensitivity of 84.6% and specificity of 83.3% using 7 metabolites. A blind study of 24 additional validation samples gave a specificity of 90.9% at the same sensitivity of 84.6%. The mPREF extraction can be readily implemented into the existing clinical workflow. Our method of combining mPREF with CIL LC-MS offers a powerful and convenient means of performing histopathology and discovering or detecting metabolite biomarkers in the same tissue biopsy.
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DOI：
10.1158/1940-6207.capr-14-0058
发表时间：
2014-09
期刊：
Cancer prevention research (Philadelphia, Pa.)
影响因子：
--
作者：
Albanes D;Till C;Klein EA;Goodman PJ;Mondul AM;Weinstein SJ;Taylor PR;Parnes HL;Gaziano JM;Song X;Fleshner NE;Brown PH;Meyskens FL Jr;Thompson IM
通讯作者：
Thompson IM
影响因子：
1.8
作者：
Chokkathukalam A;Kim DH;Barrett MP;Breitling R;Creek DJ
通讯作者：
Creek DJ
影响因子：
12.3
作者：
Brown MV;McDunn JE;Gunst PR;Smith EM;Milburn MV;Troyer DA;Lawton KA
通讯作者：
Lawton KA
影响因子：
2.8
作者：
Huang, Wei;Eickhoff, Jens C.;Mehraein-Ghomi, Farideh;Church, Dawn R.;Wilding, George;Basu, Hirak S.
通讯作者：
Basu, Hirak S.
影响因子：
7.4
作者：
Li, Liang;Li, Ronghong;Lin, Guohui
通讯作者：
Lin, Guohui