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      Global lipidomics identified plasma lipids as novel biomarkers for early detection of lung cancer

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          Abstract

          Purpose

          Lipids play roles in membrane structure, energy storage, and signal transduction as well as in human cancers. Here we adopt lipidomics to identify plasma lipid markers for early screening and detection of lung cancer.

          Experimental Design

          Using mass spectrometry, we profiled 390 individual lipids using training and validation strategy in a total of 346 plasma samples from 199 early NSCLC patients, including 113 adenocacinoma and 86 squamous cell cancers (SqCC), and from 147 healthy controls.

          Results

          In the training stage, we found distinct lipid groups that were significantly distributed between NSCLC cases and healthy controls. We further defined a panel of four lipid markers (LPE(18:1), ePE(40:4), C(18:2)CE and SM(22:0)) for prediction of early cancer with a accuracy of 82.3% AUC (Area under ROC curve), sensitivity of 81.9% and specificity of 70.7% at the training stage and yielded the predictive power with accuracy (AUC,80.8%), sensitivity 78.7%, specificity 69.4% and in the validation stage.

          Conclusions

          Using lipidomics we identified several lipid markers capable of discerning early stage lung carcinoma from healthy individuals, which might be further developed as a quick, safe blood test for early diagnosis of this disease.

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          Most cited references31

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          Cancer statistics, 2017

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            Implication of ceramide, ceramide 1-phosphate and sphingosine 1-phosphate in tumorigenesis

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              Dyslipidemia and diabetes: reciprocal impact of impaired lipid metabolism and Beta-cell dysfunction on micro- and macrovascular complications

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                Author and article information

                Journal
                Oncotarget
                Oncotarget
                Oncotarget
                ImpactJ
                Oncotarget
                Impact Journals LLC
                1949-2553
                8 December 2017
                11 November 2017
                : 8
                : 64
                : 107899-107906
                Affiliations
                1 Department of Laboratory Medicine, Shiyan Taihe Hospital, College of Biomedical Engineering, Hubei University of Medicine, Shiyan 442000, Hubei, China
                2 Department of Internal Medicine, Rush University Medical Center, Chicago, IL 60612, USA
                3 National Center of Colorectal Disease, Nanjing Municipal Hospital of Chinese Medicine, The Third Affiliated Hospital, Nanjing University of Chinese Medicine, Guangdong, Nanjing 210001, China
                4 Department of Pathology, Rush University Medical Center, Chicago, IL 60612, USA
                5 Department of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu 210006, China
                6 Department of Respiration, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu 210006, China
                7 Department of Complementary & Integrative Medicine, University of Hawaii John A. Burns School of Medicine, Honolulu, HI 96813, USA
                Author notes
                Article
                22391
                10.18632/oncotarget.22391
                5746113
                29296211
                9d81da9e-e67e-4aac-9a79-514f65bf2285
                Copyright: © 2017 Yu et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 4 April 2017
                : 26 August 2017
                Categories
                Research Paper

                Oncology & Radiotherapy
                lipidomics,lung cancer,early biomarkers,esi-ms
                Oncology & Radiotherapy
                lipidomics, lung cancer, early biomarkers, esi-ms

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