Identification of salivary metabolomic biomarkers for oral cancer screening
The objective of this study was to explore salivary metabolite biomarkers by profiling both saliva and tumor tissue samples for oral cancer screening. Paired tumor and control tissues were obtained from oral cancer patients and whole unstimulated saliva samples were collected from patients and healt...
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Published in | Scientific reports Vol. 6; no. 1; p. 31520 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
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London
Nature Publishing Group UK
19.08.2016
Nature Publishing Group |
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Abstract | The objective of this study was to explore salivary metabolite biomarkers by profiling both saliva and tumor tissue samples for oral cancer screening. Paired tumor and control tissues were obtained from oral cancer patients and whole unstimulated saliva samples were collected from patients and healthy controls. The comprehensive metabolomic analysis for profiling hydrophilic metabolites was conducted using capillary electrophoresis time-of-flight mass spectrometry. In total, 85 and 45 metabolites showed significant differences between tumor and matched control samples and between salivary samples from oral cancer and controls, respectively (
P
< 0.05 correlated by false discovery rate); 17 metabolites showed consistent differences in both saliva and tissue-based comparisons. Of these, a combination of only two biomarkers yielded a high area under receiver operating characteristic curves (0.827; 95% confidence interval, 0.726–0.928,
P
< 0.0001) for discriminating oral cancers from controls. Various validation tests confirmed its high generalization ability. The demonstrated approach, integrating both saliva and tumor tissue metabolomics, helps eliminate pseudo-molecules that are coincidentally different between oral cancers and controls. These combined salivary metabolites could be the basis of a clinically feasible method of non-invasive oral cancer screening. |
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AbstractList | The objective of this study was to explore salivary metabolite biomarkers by profiling both saliva and tumor tissue samples for oral cancer screening. Paired tumor and control tissues were obtained from oral cancer patients and whole unstimulated saliva samples were collected from patients and healthy controls. The comprehensive metabolomic analysis for profiling hydrophilic metabolites was conducted using capillary electrophoresis time-of-flight mass spectrometry. In total, 85 and 45 metabolites showed significant differences between tumor and matched control samples and between salivary samples from oral cancer and controls, respectively (
P
< 0.05 correlated by false discovery rate); 17 metabolites showed consistent differences in both saliva and tissue-based comparisons. Of these, a combination of only two biomarkers yielded a high area under receiver operating characteristic curves (0.827; 95% confidence interval, 0.726–0.928,
P
< 0.0001) for discriminating oral cancers from controls. Various validation tests confirmed its high generalization ability. The demonstrated approach, integrating both saliva and tumor tissue metabolomics, helps eliminate pseudo-molecules that are coincidentally different between oral cancers and controls. These combined salivary metabolites could be the basis of a clinically feasible method of non-invasive oral cancer screening. The objective of this study was to explore salivary metabolite biomarkers by profiling both saliva and tumor tissue samples for oral cancer screening. Paired tumor and control tissues were obtained from oral cancer patients and whole unstimulated saliva samples were collected from patients and healthy controls. The comprehensive metabolomic analysis for profiling hydrophilic metabolites was conducted using capillary electrophoresis time-of-flight mass spectrometry. In total, 85 and 45 metabolites showed significant differences between tumor and matched control samples, and between salivary samples from oral cancer and controls, respectively (P < 0.05 correlated by false discovery rate); 17 metabolites showed consistent differences in both saliva and tissue-based comparisons. Of these, a combination of only two biomarkers yielded a high area under receiver operating characteristic curves (0.827; 95% confidence interval, 0.726-0.928, P < 0.0001) for discriminating oral cancers from controls. Various validation tests confirmed its high generalization ability. The demonstrated approach, integrating both saliva and tumor tissue metabolomics, helps eliminate pseudo-molecules that are coincidentally different between oral cancers and controls. These combined salivary metabolites could be the basis of a clinically feasible method of non-invasive oral cancer screening. The objective of this study was to explore salivary metabolite biomarkers by profiling both saliva and tumor tissue samples for oral cancer screening. Paired tumor and control tissues were obtained from oral cancer patients and whole unstimulated saliva samples were collected from patients and healthy controls. The comprehensive metabolomic analysis for profiling hydrophilic metabolites was conducted using capillary electrophoresis time-of-flight mass spectrometry. In total, 85 and 45 metabolites showed significant differences between tumor and matched control samples, and between salivary samples from oral cancer and controls, respectively (P < 0.05 correlated by false discovery rate); 17 metabolites showed consistent differences in both saliva and tissue-based comparisons. Of these, a combination of only two biomarkers yielded a high area under receiver operating characteristic curves (0.827; 95% confidence interval, 0.726-0.928, P < 0.0001) for discriminating oral cancers from controls. Various validation tests confirmed its high generalization ability. The demonstrated approach, integrating both saliva and tumor tissue metabolomics, helps eliminate pseudo-molecules that are coincidentally different between oral cancers and controls. These combined salivary metabolites could be the basis of a clinically feasible method of non-invasive oral cancer screening.The objective of this study was to explore salivary metabolite biomarkers by profiling both saliva and tumor tissue samples for oral cancer screening. Paired tumor and control tissues were obtained from oral cancer patients and whole unstimulated saliva samples were collected from patients and healthy controls. The comprehensive metabolomic analysis for profiling hydrophilic metabolites was conducted using capillary electrophoresis time-of-flight mass spectrometry. In total, 85 and 45 metabolites showed significant differences between tumor and matched control samples, and between salivary samples from oral cancer and controls, respectively (P < 0.05 correlated by false discovery rate); 17 metabolites showed consistent differences in both saliva and tissue-based comparisons. Of these, a combination of only two biomarkers yielded a high area under receiver operating characteristic curves (0.827; 95% confidence interval, 0.726-0.928, P < 0.0001) for discriminating oral cancers from controls. Various validation tests confirmed its high generalization ability. The demonstrated approach, integrating both saliva and tumor tissue metabolomics, helps eliminate pseudo-molecules that are coincidentally different between oral cancers and controls. These combined salivary metabolites could be the basis of a clinically feasible method of non-invasive oral cancer screening. |
ArticleNumber | 31520 |
Author | Soga, Tomoyoshi Kitabatake, Kenichiro Ota, Sana Hiwatari, Kana Kaneko, Miku Tomita, Masaru Nakamura, Marina Iino, Mitsuyoshi Sugimoto, Masahiro Sugano, Ayako Enomoto, Ayame Ishikawa, Shigeo |
Author_xml | – sequence: 1 givenname: Shigeo surname: Ishikawa fullname: Ishikawa, Shigeo organization: Department of Dentistry, Oral and Maxillofacial Plastic and Reconstructive Surgery, Faculty of Medicine, Yamagata University – sequence: 2 givenname: Masahiro surname: Sugimoto fullname: Sugimoto, Masahiro organization: Institute for Advanced Biosciences, Keio University, Department of Oral Science, Division of Orthodontics, Graduate School of Dentistry, Kanagawa Dental University – sequence: 3 givenname: Kenichiro surname: Kitabatake fullname: Kitabatake, Kenichiro organization: Department of Dentistry, Oral and Maxillofacial Plastic and Reconstructive Surgery, Faculty of Medicine, Yamagata University – sequence: 4 givenname: Ayako surname: Sugano fullname: Sugano, Ayako organization: Department of Dentistry, Oral and Maxillofacial Plastic and Reconstructive Surgery, Faculty of Medicine, Yamagata University – sequence: 5 givenname: Marina surname: Nakamura fullname: Nakamura, Marina organization: Department of Dentistry, Oral and Maxillofacial Plastic and Reconstructive Surgery, Faculty of Medicine, Yamagata University – sequence: 6 givenname: Miku surname: Kaneko fullname: Kaneko, Miku organization: Institute for Advanced Biosciences, Keio University – sequence: 7 givenname: Sana surname: Ota fullname: Ota, Sana organization: Institute for Advanced Biosciences, Keio University – sequence: 8 givenname: Kana surname: Hiwatari fullname: Hiwatari, Kana organization: Institute for Advanced Biosciences, Keio University – sequence: 9 givenname: Ayame surname: Enomoto fullname: Enomoto, Ayame organization: Institute for Advanced Biosciences, Keio University – sequence: 10 givenname: Tomoyoshi surname: Soga fullname: Soga, Tomoyoshi organization: Institute for Advanced Biosciences, Keio University – sequence: 11 givenname: Masaru surname: Tomita fullname: Tomita, Masaru organization: Institute for Advanced Biosciences, Keio University – sequence: 12 givenname: Mitsuyoshi surname: Iino fullname: Iino, Mitsuyoshi organization: Department of Dentistry, Oral and Maxillofacial Plastic and Reconstructive Surgery, Faculty of Medicine, Yamagata University |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/27539254$$D View this record in MEDLINE/PubMed |
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SubjectTerms | 631/67/1665 692/4028/67/2327 Adult Aged Aged, 80 and over Biomarkers, Tumor - metabolism Female Humanities and Social Sciences Humans Male Metabolomics - methods Middle Aged Mouth Neoplasms - diagnosis Mouth Neoplasms - metabolism multidisciplinary Saliva - metabolism Science |
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Title | Identification of salivary metabolomic biomarkers for oral cancer screening |
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