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Article: Plasma metabolite biomarkers for the detection of pancreatic cancer

TitlePlasma metabolite biomarkers for the detection of pancreatic cancer
Authors
KeywordsGC-MS
LC-MS
logistic regression
metabonomics
multivariate statistical analysis
OPLS-DA
Pancreatic cancer
plasma
ROC
Issue Date2015
Citation
Journal of Proteome Research, 2015, v. 14, n. 2, p. 1195-1202 How to Cite?
AbstractPatients with pancreatic cancer (PC) are usually diagnosed at late stages, when the disease is nearly incurable. Sensitive and specific markers are critical for supporting diagnostic and therapeutic strategies. The aim of this study was to use a metabonomics approach to identify potential plasma biomarkers that can be further developed for early detection of PC. In this study, plasma metabolites of newly diagnosed PC patients (n = 100) and age- and gender-matched controls (n = 100) from Connecticut (CT), USA, and the same number of cases and controls from Shanghai (SH), China, were profiled using combined gas and liquid chromatography mass spectrometry. The metabolites consistently expressed in both CT and SH samples were used to identify potential markers, and the diagnostic performance of the candidate markers was tested in two sample sets. A diagnostic model was constructed using a panel of five metabolites including glutamate, choline, 1,5-anhydro-d-glucitol, betaine, and methylguanidine, which robustly distinguished PC patients in CT from controls with high sensitivity (97.7%) and specificity (83.1%) (area under the receiver operating characteristic curve [AUC] = 0.943, 95% confidence interval [CI] = 0.908-0.977). This panel of metabolites was then tested with the SH data set, yielding satisfactory accuracy (AUC = 0.835; 95% CI = 0.777-0.893), with a sensitivity of 77.4% and specificity of 75.8%. This model achieved a sensitivity of 84.8% in the PC patients at stages 0, 1, and 2 in CT and 77.4% in the PC patients at stages 1 and 2 in SH. Plasma metabolic signatures show promise as biomarkers for early detection of PC.
Persistent Identifierhttp://hdl.handle.net/10722/342485
ISSN
2023 Impact Factor: 3.8
2023 SCImago Journal Rankings: 1.299
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXie, Guoxiang-
dc.contributor.authorLu, Lingeng-
dc.contributor.authorQiu, Yunping-
dc.contributor.authorNi, Quanxing-
dc.contributor.authorZhang, Wei-
dc.contributor.authorGao, Yu Tang-
dc.contributor.authorRisch, Harvey A.-
dc.contributor.authorYu, Herbert-
dc.contributor.authorJia, Wei-
dc.date.accessioned2024-04-17T07:04:09Z-
dc.date.available2024-04-17T07:04:09Z-
dc.date.issued2015-
dc.identifier.citationJournal of Proteome Research, 2015, v. 14, n. 2, p. 1195-1202-
dc.identifier.issn1535-3893-
dc.identifier.urihttp://hdl.handle.net/10722/342485-
dc.description.abstractPatients with pancreatic cancer (PC) are usually diagnosed at late stages, when the disease is nearly incurable. Sensitive and specific markers are critical for supporting diagnostic and therapeutic strategies. The aim of this study was to use a metabonomics approach to identify potential plasma biomarkers that can be further developed for early detection of PC. In this study, plasma metabolites of newly diagnosed PC patients (n = 100) and age- and gender-matched controls (n = 100) from Connecticut (CT), USA, and the same number of cases and controls from Shanghai (SH), China, were profiled using combined gas and liquid chromatography mass spectrometry. The metabolites consistently expressed in both CT and SH samples were used to identify potential markers, and the diagnostic performance of the candidate markers was tested in two sample sets. A diagnostic model was constructed using a panel of five metabolites including glutamate, choline, 1,5-anhydro-d-glucitol, betaine, and methylguanidine, which robustly distinguished PC patients in CT from controls with high sensitivity (97.7%) and specificity (83.1%) (area under the receiver operating characteristic curve [AUC] = 0.943, 95% confidence interval [CI] = 0.908-0.977). This panel of metabolites was then tested with the SH data set, yielding satisfactory accuracy (AUC = 0.835; 95% CI = 0.777-0.893), with a sensitivity of 77.4% and specificity of 75.8%. This model achieved a sensitivity of 84.8% in the PC patients at stages 0, 1, and 2 in CT and 77.4% in the PC patients at stages 1 and 2 in SH. Plasma metabolic signatures show promise as biomarkers for early detection of PC.-
dc.languageeng-
dc.relation.ispartofJournal of Proteome Research-
dc.subjectGC-MS-
dc.subjectLC-MS-
dc.subjectlogistic regression-
dc.subjectmetabonomics-
dc.subjectmultivariate statistical analysis-
dc.subjectOPLS-DA-
dc.subjectPancreatic cancer-
dc.subjectplasma-
dc.subjectROC-
dc.titlePlasma metabolite biomarkers for the detection of pancreatic cancer-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1021/pr501135f-
dc.identifier.pmid25429707-
dc.identifier.scopuseid_2-s2.0-84922627331-
dc.identifier.volume14-
dc.identifier.issue2-
dc.identifier.spage1195-
dc.identifier.epage1202-
dc.identifier.eissn1535-3907-
dc.identifier.isiWOS:000349276400054-

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