2013 Fiscal Year Final Research Report
Establishment of saliva metabolome analysis using mice experimental cancer model
Project/Area Number |
23592784
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Pathobiological dentistry/Dental radiology
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Research Institution | Tsurumi University |
Principal Investigator |
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Co-Investigator(Kenkyū-buntansha) |
SHIMADA Akemi 鶴見大学, 歯学部, 助教 (00339813)
NAKASHIMA Kazuhisa 鶴見大学, 歯学部, 非常勤講師 (90252692)
SUGIMOTO Masahiro 慶應義塾大学, 政策メディア研究科, 准教 (30458963)
NIFUJI Akira 鶴見大学, 歯学部, 教授 (00240747)
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Project Period (FY) |
2011 – 2013
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Keywords | メタボローム / 唾液 / 腫瘍 |
Research Abstract |
Saliva contains components originating from blood but it is only applicated to diagnosis in specific diseases. Metabolome analysis aims to comprehensively identify and quantify metabolites in bodily fluids. To diagnose diseases with the salivary metabolome analysis, it should be clear whether or not there is the metabolome profile difference between saliva and blood, and whether or not a disease affects the metabolome profile. In this study, we compared the metabolome profiles of saliva and blood in mice and many metabolites were consistently detected in both saliva and blood, indicating that metabolites in blood transfer to saliva. Based on this result, we are analyzing the salivary metabolome profile in experimental mice cancer model.
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Research Products
(18 results)
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[Journal Article] Dynamics of serum metabolites in patients with chronic hepatitis C receiving pegylated interferon plus ribavirin : A metabolomics analysis2013
Author(s)
Saito T., Sugimoto M., Igarashi K., Saito K., Shao L., Katsumi T., Tomita K., Sato C., Aso R., Okumoto K., Nishise Y., Watanabe H., Tomita M.
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Journal Title
Metabolism
Volume: 10
Pages: 1577-86
DOI
Peer Reviewed
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[Journal Article] High-Resolution-Imaging Mass Spectrometry Reveals Detailed Spatial Distribution of Phosphatidylinositols in Human Breast Cancer2013
Author(s)
Kawashima M., Iwamoto N., Kawaguchi-Sakita, N., Sugimoto M., Ueno T., Mikami Y. Terasawa K., Sato, T., Tanaka K., Shimizu K., Toi M.
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Journal Title
Cancer Science
Volume: 104
Pages: 1372-9
Peer Reviewed
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[Journal Article] Predictions of the pathological response to neoadjuvant chemotherapy in patients with primary breast cancer using a data mining technique2012
Author(s)
Takada M., Sugimoto M., Ohno S., Kuroi K., Sato N., Bando H., Masuda N., Iwata H., Kondo M., Sasano H., Chow L.W.C., Inamoto T., Naito Y., Tomita M., and Toi M.
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Journal Title
Breast Cancer Research and Treatment
Volume: 134
Pages: 661-70
DOI
Peer Reviewed
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