Liquid chromatography/mass spectrometry methods for measuring dipeptide abundance in non‐small‐cell lung cancer. (13th August 2013)

• Record Type: Journal Article
• Authors: Wu, Manhong; Xu, Yue; Fitch, William L.; Zheng, Ming; Merritt, Robert E.; Shrager, Joseph B.; Zhang, Weiruo; Dill, David L.; Peltz, Gary; Hoang, Chuong D.
• Is Part Of: Rapid communications in mass spectrometry. Volume 27:Number 18(2013)
• Page Start: 2091
• Page End: 2098
• Publication Date: 2013-08-13
• Subjects: Mass spectrometry -- Periodicals; 543.65
• DOI: 10.1002/rcm.6656
• Languages: English
• ISSNs: 0951-4198

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="rcm6656-sec-0001" sec-type="section"> <title>RATIONALE</title> <p>Metabolomic profiling is a promising methodology of identifying candidate biomarkers for disease detection and monitoring. Although lung cancer is among the leading causes of cancer‐related mortality worldwide, the lung tumor metabolome has not been fully characterized.</p> </sec> <sec id="rcm6656-sec-0002" sec-type="section"> <title>METHODS</title> <p>We utilized a targeted metabolomic approach to analyze discrete groups of related metabolites. We adopted a dansyl [5‐(dimethylamino)‐1‐naphthalene sulfonamide] derivatization with liquid chromatography/mass spectrometry (LC/MS) to analyze changes of metabolites from paired tumor and normal lung tissues. Identification of dansylated dipeptides was confirmed with synthetic standards. A systematic analysis of retention times was required to reliably identify isobaric dipeptides. We validated our findings in a separate sample cohort.</p> </sec> <sec id="rcm6656-sec-0003" sec-type="section"> <title>RESULTS</title> <p>We produced a database of the LC retention times and MS/MS spectra of 361 dansyl dipeptides. Interpretation of the spectra is presented. Using this standard data, we identified a total of 279 dipeptides in lung tumor tissue. The abundance of 90 dipeptides was selectively increased in lung tumor tissue compared to normal tissue. In a second set of validation tissues, 12 dipeptides were selectively increased.</p> </sec> <sec id="rcm6656-sec-0004" sec-type="section"> <title>CONCLUSIONS</title> <p>A systematic evaluation of certain metabolite classes in lung tumors may identify promising disease‐specific metabolites. Our database of all possible dipeptides will facilitate ongoing translational applications of metabolomic profiling as it relates to lung cancer. Copyright © 2013 John Wiley & Sons, Ltd.</p> </sec> </abstract>