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      Metabolic Profiling of Plasma from Benign and Malignant Pulmonary Nodules Patients Using Mass Spectrometry-Based Metabolomics

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          Abstract

          Solitary pulmonary nodule (SPN or coin lesion) is a mass in the lung and can be commonly found in chest X-rays or computerized tomography (CT) scans. However, despite the advancement of imaging technologies, it is still difficult to distinguish malignant cancer from benign SPNs. Here we investigated the metabolic profiling of patients with benign and malignant pulmonary nodules. A combination of gas chromatography/mass spectrometry (GC/MS) and liquid chromatography/mass spectrometry (LC/MS) was used to profile the plasma metabolites in 17 patients with malignant SPNs, 15 patients with benign SPNs and 20 healthy controls. The metabolic profiles were assayed using OPLS-DA, and further analyzed to identify marker metabolites related to diseases. Both GC/MS- and LC/MS-derived models showed clear discriminations in metabolic profiles among three groups. It was found that 63 metabolites (12 from GC/MS, 51 from LC/MS) contributed to the differences. Of these, 48 metabolites showed same change trend in both malignant and benign SPNs as compared with healthy controls, indicating some common pathways including inflammation and oxidative injury shared by two diseases. In contrast, 14 metabolites constituted distinct profiles that differentiated malignant from benign SPNs, which might be a unique biochemical feature associated with lung cancer. Overall, our data suggested that integration of two highly sensitive and complementary metabolomics platforms could enable a comprehensive metabolic profiling and assist in discrimination malignant from benign SPNs.

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          Most cited references33

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          Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner Society.

          Lung nodules are detected very commonly on computed tomographic (CT) scans of the chest, and the ability to detect very small nodules improves with each new generation of CT scanner. In reported studies, up to 51% of smokers aged 50 years or older have pulmonary nodules on CT scans. However, the existing guidelines for follow-up and management of noncalcified nodules detected on nonscreening CT scans were developed before widespread use of multi-detector row CT and still indicate that every indeterminate nodule should be followed with serial CT for a minimum of 2 years. This policy, which requires large numbers of studies to be performed at considerable expense and with substantial radiation exposure for the affected population, has not proved to be beneficial or cost-effective. During the past 5 years, new information regarding prevalence, biologic characteristics, and growth rates of small lung cancers has become available; thus, the authors believe that the time-honored requirement to follow every small indeterminate nodule with serial CT should be revised. In this statement, which has been approved by the Fleischner Society, the pertinent data are reviewed, the authors' conclusions are summarized, and new guidelines are proposed for follow-up and management of small pulmonary nodules detected on CT scans.
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            Global cancer statistics

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              Mass spectrometry-based metabolic profiling reveals different metabolite patterns in invasive ovarian carcinomas and ovarian borderline tumors.

              Metabolites are the end products of cellular regulatory processes, and their levels can be regarded as the ultimate response of biological systems to genetic or environmental changes. We have used a metabolite profiling approach to test the hypothesis that quantitative signatures of primary metabolites can be used to characterize molecular changes in ovarian tumor tissues. Sixty-six invasive ovarian carcinomas and nine borderline tumors of the ovary were analyzed by gas chromatography/time-of-flight mass spectrometry (GC-TOF MS) using a novel contamination-free injector system. After automated mass spectral deconvolution, 291 metabolites were detected, of which 114 (39.1%) were annotated as known compounds. By t test statistics with P < 0.01, 51 metabolites were significantly different between borderline tumors and carcinomas, with a false discovery rate of 7.8%, estimated with repeated permutation analysis. Principal component analysis (PCA) revealed four principal components that were significantly different between both groups, with the highest significance found for the second component (P = 0.00000009). PCA as well as additional supervised predictive models allowed a separation of 88% of the borderline tumors from the carcinomas. Our study shows for the first time that large-scale metabolic profiling using GC-TOF MS is suitable for analysis of fresh frozen human tumor samples, and that there is a consistent and significant change in primary metabolism of ovarian tumors, which can be detected using multivariate statistical approaches. We conclude that metabolomics is a promising high-throughput, automated approach in addition to functional genomics and proteomics for analyses of molecular changes in malignant tumors.
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                Author and article information

                Journal
                Metabolites
                Metabolites
                metabolites
                Metabolites
                MDPI
                2218-1989
                04 July 2013
                September 2013
                : 3
                : 3
                : 539-551
                Affiliations
                [1 ]NUS Environmental Research Institute, National University of Singapore, 5A Engineering Drive 1, Singapore 117411, Singapore; E-Mail: erigl@ 123456nus.edu.sg
                [2 ]Department of Anesthesiology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200433, China; E-Mails: wzm1103@ 123456126.com (Z.W.); wuchunyan581@ 123456sina.com (C.W.)
                [3 ]Saw Swee Hock School of Public Health, National University of Singapore, 16 Medical Drive, Singapore 117597, Singapore; E-Mails: wentao5281@ 123456163.com (T.W.); ephocn@ 123456nus.edu.sg (C.N.O.)
                Author notes
                [†]

                These authors contributed equally to this work.

                [* ] Author to whom correspondence should be addressed; E-Mail: ephocn@ 123456nus.edu.sg ; Tel.: +65-65164982; Fax: +65- 67791489.
                Article
                metabolites-03-00539
                10.3390/metabo3030539
                3901282
                24958138
                b532ee03-1bbc-4f72-b3eb-73fb00e99af8
                © 2013 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/3.0/).

                History
                : 03 May 2013
                : 07 June 2013
                : 24 June 2013
                Categories
                Article

                metabolomics,solitary pulmonary nodules,plasma,biomarkers,mass spectrometry

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