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      A novel methodology for in vivo endoscopic phenotyping of colorectal cancer based on real-time analysis of the mucosal lipidome: a prospective observational study of the iKnife

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          Abstract

          Background

          This pilot study assessed the diagnostic accuracy of rapid evaporative ionization mass spectrometry (REIMS) in colorectal cancer (CRC) and colonic adenomas.

          Methods

          Patients undergoing elective surgical resection for CRC were recruited at St. Mary’s Hospital London and The Royal Marsden Hospital, UK. Ex vivo analysis was performed using a standard electrosurgery handpiece with aspiration of the electrosurgical aerosol to a Xevo G2-S iKnife QTof mass spectrometer (Waters Corporation). Histological examination was performed for validation purposes. Multivariate analysis was performed using principal component analysis and linear discriminant analysis in Matlab 2015a (Mathworks, Natick, MA). A modified REIMS endoscopic snare was developed (Medwork) and used prospectively in five patients to assess its feasibility during hot snare polypectomy.

          Results

          Twenty-eight patients were recruited (12 males, median age 71, range 35–89). REIMS was able to reliably distinguish between cancer and normal adjacent mucosa (NAM) (AUC 0.96) and between NAM and adenoma (AUC 0.99). It had an overall accuracy of 94.4 % for the detection of cancer versus adenoma and an adenoma sensitivity of 78.6 % and specificity of 97.3 % (AUC 0.99) versus cancer. Long-chain phosphatidylserines (e.g., PS 22:0) and bacterial phosphatidylglycerols were over-expressed on cancer samples, while NAM was defined by raised plasmalogens and triacylglycerols expression and adenomas demonstrated an over-expression of ceramides. REIMS was able to classify samples according to tumor differentiation, tumor budding, lymphovascular invasion, extramural vascular invasion and lymph node micrometastases (AUC’s 0.88, 0.87, 0.83, 0.81 and 0.81, respectively). During endoscopic deployment, colonoscopic REIMS was able to detect target lipid species such as ceramides during hot snare polypectomy.

          Conclusion

          REIMS demonstrates high diagnostic accuracy for tumor type and for established histological features of poor prognostic outcome in CRC based on a multivariate analysis of the mucosal lipidome. REIMS could augment endoscopic and imaging technologies for precision phenotyping of colorectal cancer.

          Electronic supplementary material

          The online version of this article (doi:10.1007/s00464-016-5121-5) contains supplementary material, which is available to authorized users.

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          Most cited references12

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          Preparing for precision medicine.

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            Metabolic phenotyping in clinical and surgical environments.

            Metabolic phenotyping involves the comprehensive analysis of biological fluids or tissue samples. This analysis allows biochemical classification of a person's physiological or pathological states that relate to disease diagnosis or prognosis at the individual level and to disease risk factors at the population level. These approaches are currently being implemented in hospital environments and in regional phenotyping centres worldwide. The ultimate aim of such work is to generate information on patient biology using techniques such as patient stratification to better inform clinicians on factors that will enhance diagnosis or the choice of therapy. There have been many reports of direct applications of metabolic phenotyping in a clinical setting.
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              Chemo-informatic strategy for imaging mass spectrometry-based hyperspectral profiling of lipid signatures in colorectal cancer.

              Mass spectrometry imaging (MSI) provides the opportunity to investigate tumor biology from an entirely novel biochemical perspective and could lead to the identification of a new pool of cancer biomarkers. Effective clinical translation of histology-driven MSI in systems oncology requires precise colocalization of morphological and biochemical features as well as advanced methods for data treatment and interrogation. Currently proposed MSI workflows are subject to several limitations, including nonoptimized raw data preprocessing, imprecise image coregistration, and limited pattern recognition capabilities. Here we outline a comprehensive strategy for histology-driven MSI, using desorption electrospray ionization that covers (i) optimized data preprocessing for improved information recovery; (ii) precise image coregistration; and (iii) efficient extraction of tissue-specific molecular ion signatures for enhanced biochemical distinction of different tissue types. The proposed workflow has been used to investigate region-specific lipid signatures in colorectal cancer tissue. Unique lipid patterns were observed using this approach according to tissue type, and a tissue recognition system using multivariate molecular ion patterns allowed highly accurate (>98%) identification of pixels according to morphology (cancer, healthy mucosa, smooth muscle, and microvasculature). This strategy offers unique insights into tumor microenvironmental biochemistry and should facilitate compilation of a large-scale tissue morphology-specific MSI spectral database with which to pursue next-generation, fully automated histological approaches.
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                Author and article information

                Contributors
                0044(0) 7989344238 , j.kinross@imperial.ac.uk
                Journal
                Surg Endosc
                Surg Endosc
                Surgical Endoscopy
                Springer US (New York )
                0930-2794
                1432-2218
                8 August 2016
                8 August 2016
                2017
                : 31
                : 3
                : 1361-1370
                Affiliations
                [1 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, Department of Surgery and Cancer, , Imperial College London, St. Mary’s Hospital, ; Praed Street, London, NW1 1SQ UK
                [2 ]Waters Corporation, Wilmslow, UK
                [3 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, Department of Histopathology, , Imperial College London, ; London, UK
                [4 ]ISNI 0000 0004 0581 2008, GRID grid.451052.7, Department of Gastroenterology, , Imperial Healthcare NHS Trust, ; London, UK
                [5 ]ISNI 0000 0001 0304 893X, GRID grid.5072.0, Department of Colorectal Surgery, , Royal Marsden Hospital NHS Trust, ; London, UK
                Article
                5121
                10.1007/s00464-016-5121-5
                5315709
                27501728
                9e0c1ec6-1a7d-498e-943f-6abc05c02f44
                © The Author(s) 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 24 March 2016
                : 12 July 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000781, European Research Council;
                Award ID: 617896
                Award Recipient :
                Categories
                Article
                Custom metadata
                © Springer Science+Business Media New York 2017

                Surgery
                rapid evaporative ionization mass spectrometry,colorectal cancer,metabolic
                Surgery
                rapid evaporative ionization mass spectrometry, colorectal cancer, metabolic

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