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      Sphingomyelin(d35:1) as a novel predictor for lung adenocarcinoma recurrence after a radical surgery: a case-control study

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          Abstract

          Background

          To improve the postoperative prognosis of patients with lung cancer, predicting the recurrence high-risk patients is needed for the efficient application of adjuvant chemotherapy. However, predicting lung cancer recurrence after a radical surgery is difficult even with conventional histopathological prognostic factors, thereby a novel predictor should be identified. As lipid metabolism alterations are known to contribute to cancer progression, we hypothesized that lung adenocarcinomas with high recurrence risk contain candidate lipid predictors. This study aimed to identify candidate lipid predictors for the recurrence of lung adenocarcinoma after a radical surgery.

          Methods

          Frozen tissue samples of primary lung adenocarcinoma obtained from patients who underwent a radical surgery were retrospectively reviewed. Recurrent and non-recurrent cases were assigned to recurrent ( n = 10) and non-recurrent (n = 10) groups, respectively. Extracted lipids from frozen tissue samples were subjected to liquid chromatography-tandem mass spectrometry analysis. The average total lipid levels of the non-recurrent and recurrent groups were compared. Candidate predictors were screened by comparing the folding change and P-value of t-test in each lipid species between the recurrent and non-recurrent groups.

          Results

          The average total lipid level of the recurrent group was 1.65 times higher than that of the non-recurrent group ( P < 0.05). A total of 203 lipid species were increased (folding change, ≥2; P < 0.05) and 4 lipid species were decreased (folding change, ≤0.5; P < 0.05) in the recurrent group. Among these candidates, increased sphingomyelin (SM)(d35:1) in the recurrent group was the most prominent candidate predictor, showing high performance of recurrence prediction (AUC, 9.1; sensitivity, 1.0; specificity, 0.8; accuracy, 0.9).

          Conclusion

          We propose SM(d35:1) as a novel candidate predictor for lung adenocarcinoma recurrence. Our finding can contribute to precise recurrence prediction and qualified postoperative therapeutic strategy for lung adenocarcinomas.

          Trial registration

          This retrospective study was registered at the UMIN Clinical Trial Registry ( UMIN000039202) on 21st January 2020.

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          Most cited references19

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          A Japanese Lung Cancer Registry study: prognosis of 13,010 resected lung cancers.

          The validation of tumor, node, metastasis staging system in terms of prognosis is an indispensable part of establishing a better staging system in lung cancer. In 2005, 387 Japanese institutions submitted information regarding the prognosis and clinicopathologic profiles of patients who underwent pulmonary resections for primary lung neoplasms in 1999 to the Japanese Joint Committee of Lung Cancer Registry. The data of 13,010 patients with only lung carcinoma histology (97.6%) were analyzed in terms of prognosis and clinicopathologic characteristics. The 5-year survival rate of the entire group was 61.4%. For the small cell histology (n = 390), the 5-year survival rates according to clinical (c) and pathologic (p) stages were as follows: 58.8% (n = 161) and 58.3% (n = 127) for IA, 58.0% (n = 77) and 60.2% (n = 79) for IB, 47.1% (n = 17) and 40.6% (n = 29) for IIA, 25.3% (n = 38) and 41.1% (n = 29) for IIB, 29.0% (n = 61) and 28.3% (n = 60) for IIIA, 36.3% (n = 19) and 34.6% (n = 40) for IIIB, and 27.8% (n = 12) and 30.8% for IV (n = 13). For the non-small cell histology (n = 12,620), the 5-year survival rates according to c-stage and p-stage were as follows: 77.3% (n = 5642) and 83.9% (n = 4772) for IA, 59.8% (n = 3081) and 66.3% (n = 2629) for IB, 54.1% (n = 205) and 61.0% (n = 361) for IIA, 43.9% (n = 1227) and 47.4% (n = 1330) for IIB, 38.3% (n = 1628) and 32.8% (n = 1862) for IIIA, 32.6% (n = 526) and 29.6% (n = 1108) for IIIB, and 26.5% (n = 198) and 23.1% (n = 375) for IV. Adenocarcinoma, female gender, and age less than 50 years were significant favorable prognostic factors. This large registry study provides benchmark prognostic statistics for lung cancer. The prognostic difference between stages IB and IIA was small despite different stages. Otherwise, the present tumor, node, metastasis staging system well characterizes the stage-specific prognoses.
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            The role of sphingomyelin and sphingomyelin synthases in cell death, proliferation and migration-from cell and animal models to human disorders.

            Sphingomyelin constitutes membrane microdomains such as lipid raft, caveolae, and clathrin-coated pits and implicates in the regulation of trans-membrane signaling. On the other hand, sphingomyelin emerges as an important molecule to generate bioactive sphingolipids through ceramide. Sphingomyelin synthase is an enzyme that generates sphingomyelin and diacylglycerol from phosphatidylcholine and ceramide. Although ceramide has a well-known role as a lipid mediator to regulate cell death and survival, the only known biological role of sphingomyelin regulated by sphingomyelin synthases was limited to being a source of bioactive lipids. Here, we describe the basic characters of sphingomyelin synthases and discuss additional roles for sphingomyelin and sphingomyelin synthase in biological functions including cell migration, apoptosis, autophagy, and cell survival/proliferation as well as in human disorders such as cancer and cardiovascular disorders. It is expected that a better understanding of the role of sphingomyelin regulated by sphingomyelin synthase will shed light on new mechanisms in cell biology, physiology and pathology. In the future, novel therapeutic procedures for currently incurable diseases could be developed through modifying the function of not only sphingolipids, such as sphingomyelin and ceramide, but also of their regulatory enzymes. This article is part of a Special Issue entitled New Frontiers in Sphingolipid Biology.
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              Demographics, Safety and Quality, and Prognostic Information in Both the Seventh and Eighth Editions of the TNM Classification in 18,973 Surgical Cases of the Japanese Joint Committee of Lung Cancer Registry Database in 2010

              The Japanese Joint Committee of Lung Cancer Registry performed the fourth nationwide registry study of surgical cases. Demographics, safety and quality, prognostic information, and correlations between the seventh and the eighth editions of the TNM classification were investigated. The principal results were compared with those of previous Japanese Joint Committee of Lung Cancer Registry studies.
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                Author and article information

                Contributors
                kahyo@hama-med.ac.jp
                Journal
                BMC Cancer
                BMC Cancer
                BMC Cancer
                BioMed Central (London )
                1471-2407
                24 August 2020
                24 August 2020
                2020
                : 20
                : 800
                Affiliations
                [1 ]GRID grid.505613.4, Department of Cellular and Molecular Anatomy, , Hamamatsu University School of Medicine, ; 1-20-1 Handayama, Higashi Ward, Hamamatsu, Shizuoka, 431-3192 Japan
                [2 ]GRID grid.505613.4, First Department of Surgery, , Hamamatsu University School of Medicine, ; 1-20-1 Handayama, Higashi Ward, Hamamatsu, Shizuoka, 431-3192 Japan
                [3 ]GRID grid.505613.4, Department of Tumor Pathology, , Hamamatsu University School of Medicine, ; 1-20-1 Handayama, Higashi Ward, Hamamatsu, Shizuoka, 431-3192 Japan
                [4 ]Preppers Co. Ltd., 1-23-17 Kitashinagawa, Shinagawa Ward, Tokyo, 140-0001 Japan
                [5 ]GRID grid.505613.4, International Mass Imaging Center, , Hamamatsu University School of Medicine, ; 1-20-1 Handayama, Higashi Ward, Hamamatsu, Shizuoka, 431-3192 Japan
                [6 ]GRID grid.505613.4, Department of Systems Molecular Anatomy, , Institute for Medical Photonics Research, Hamamatsu University School of Medicine, ; 1-20-1 Handayama, Higashi Ward, Hamamatsu, Shizuoka, 431-3192 Japan
                Article
                7306
                10.1186/s12885-020-07306-1
                7446133
                32831036
                84fbe903-94b6-4c20-850e-37e1f4786f8d
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 11 May 2020
                : 17 August 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100009619, Japan Agency for Medical Research and Development;
                Award ID: 15664816
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001700, Ministry of Education, Culture, Sports, Science and Technology;
                Award ID: JPMXS0410300220
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Oncology & Radiotherapy
                lung adenocarcinoma,prognostic factor,recurrence prediction,lipid,mass spectrometry

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