RATIONALE: Colorectal cancer (CRC) has attracted increasing attention due to its common occurrence and worldwide distribution. METHODS: Direct-infusion positive and negative ion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (DI-ESI(±)-FTICR MS) was applied to analyze the serum metabolites from 52 CRC patients and 52 healthy controls. Metabolites whose inter-group intensities were determined to be statistically significant by univariate and multivariate statistical analyses were further identified by a combination of the Human Metabolome Database, accurate mass measurement, isotopic abundance distribution simulation, and tandem mass spectrometry. Orthogonal partial least square discriminant analysis (OPLS-DA), based on the data from DI-ESI(±)-FTICR MS, revealed a remarkable discrimination among early stage patients, late stage patients, and healthy controls. RESULTS: A total of 15 differentially expressed metabolites were identified and categorized into four lipid classes. Each lipid class demonstrated specific changing trends in CRC progression. Biomarker panel 1 containing palmitic amide, oleamide, hexadecanedioic acid, octadecanoic acid, eicosatrienoic acid, LPC(18:2), LPC(20:4), LPC(22:6), myristic acid and LPC(16:0) achieved excellent diagnostic accuracy with area under the ROC curve (AUC) of 0.991, a sensitivity of 0.981 and a specificity of 1.000 for differentiating early stage patients from healthy controls, which was better than the carcinoembryonic antigen biomarker. CONCLUSIONS: Our study revealed that the consideration of CRC stages would be necessary in diagnostic biomarker discovery, as well as that attention should be paid to the facile loss of methyl chloride from the [M + Cl](-) form of LPC(16:0) in its tandem mass spectrum.
RATIONALE: Colorectal cancer (CRC) has attracted increasing attention due to its common occurrence and worldwide distribution. METHODS: Direct-infusion positive and negative ion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (DI-ESI(±)-FTICR MS) was applied to analyze the serum metabolites from 52 CRC patients and 52 healthy controls. Metabolites whose inter-group intensities were determined to be statistically significant by univariate and multivariate statistical analyses were further identified by a combination of the Human Metabolome Database, accurate mass measurement, isotopic abundance distribution simulation, and tandem mass spectrometry. Orthogonal partial least square discriminant analysis (OPLS-DA), based on the data from DI-ESI(±)-FTICR MS, revealed a remarkable discrimination among early stage patients, late stage patients, and healthy controls. RESULTS: A total of 15 differentially expressed metabolites were identified and categorized into four lipid classes. Each lipid class demonstrated specific changing trends in CRC progression. Biomarker panel 1 containing palmitic amide, oleamide, hexadecanedioic acid, octadecanoic acid, eicosatrienoic acid, LPC(18:2), LPC(20:4), LPC(22:6), myristic acid and LPC(16:0) achieved excellent diagnostic accuracy with area under the ROC curve (AUC) of 0.991, a sensitivity of 0.981 and a specificity of 1.000 for differentiating early stage patients from healthy controls, which was better than the carcinoembryonic antigen biomarker. CONCLUSIONS: Our study revealed that the consideration of CRC stages would be necessary in diagnostic biomarker discovery, as well as that attention should be paid to the facile loss of methyl chloride from the [M + Cl](-) form of LPC(16:0) in its tandem mass spectrum.
Authors: Reinaldo Almeida; Josch Konstantin Pauling; Elena Sokol; Hans Kristian Hannibal-Bach; Christer S Ejsing Journal: J Am Soc Mass Spectrom Date: 2014-11-13 Impact factor: 3.109
Authors: Chen Chen; Lingli Deng; Siwei Wei; G A Nagana Gowda; Haiwei Gu; Elena G Chiorean; Mohammad Abu Zaid; Marietta L Harrison; Joseph F Pekny; Patrick J Loehrer; Dabao Zhang; Min Zhang; Daniel Raftery Journal: J Proteome Res Date: 2015-05-13 Impact factor: 4.466