title: Metabonomics identifies serum metabolite markers of colorectal cancer.
abstract: Recent studies suggest that biofluid-based metabonomics may identify metabolite markers promising for colorectal cancer (CRC) diagnosis. We report here a follow-up replication study, after a previous CRC metabonomics study, aiming to identify a distinct serum metabolic signature of CRC with diagnostic potential. Serum metabolites from newly diagnosed CRC patients (N = 101) and healthy subjects (N = 102) were profiled using gas chromatography time-of-flight mass spectrometry (GC-TOFMS) and ultraperformance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOFMS). Differential metabolites were identified with statistical tests of orthogonal partial least-squares-discriminant analysis (VIP > 1) and the Mann-Whitney U test (p < 0.05). With a total of 249 annotated serum metabolites, we were able to differentiate CRC patients from the healthy controls using an orthogonal partial least-squares-discriminant analysis (OPLS-DA) in a learning sample set of 62 CRC patients and 62 matched healthy controls. This established model was able to correctly assign the rest of the samples to the CRC or control groups in a validation set of 39 CRC patients and 40 healthy controls. Consistent with our findings from the previous study, we observed a distinct metabolic signature in CRC patients including tricarboxylic acid (TCA) cycle, urea cycle, glutamine, fatty acids, and gut flora metabolism. Our results demonstrated that a panel of serum metabolite markers is of great potential as a noninvasive diagnostic method for the detection of CRC.
authors.affiliation: Ministry of Education Key Laboratory of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, PR China.
authors.forename: Binbin
authors.initials: B
authors.lastname: Tan
authors.forename: Yunping
authors.initials: Y
authors.lastname: Qiu
authors.forename: Xia
authors.initials: X
authors.lastname: Zou
authors.forename: Tianlu
authors.initials: T
authors.lastname: Chen
authors.forename: Guoxiang
authors.initials: G
authors.lastname: Xie
authors.forename: Yu
authors.initials: Y
authors.lastname: Cheng
authors.forename: Taotao
authors.initials: T
authors.lastname: Dong
authors.forename: Linjing
authors.initials: L
authors.lastname: Zhao
authors.forename: Bo
authors.initials: B
authors.lastname: Feng
authors.forename: Xiaofang
authors.initials: X
authors.lastname: Hu
authors.forename: Lisa X
authors.initials: LX
authors.lastname: Xu
authors.forename: Aihua
authors.initials: A
authors.lastname: Zhao
authors.forename: Menghui
authors.initials: M
authors.lastname: Zhang
authors.forename: Guoxiang
authors.initials: G
authors.lastname: Cai
authors.forename: Sanjun
authors.initials: S
authors.lastname: Cai
authors.forename: Zhanxiang
authors.initials: Z
authors.lastname: Zhou
authors.forename: Minhua
authors.initials: M
authors.lastname: Zheng
authors.forename: Yan
authors.initials: Y
authors.lastname: Zhang
authors.forename: Wei
authors.initials: W
authors.lastname: Jia
mesh_terms: D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000097:blood*; D002272:Carcinoembryonic Antigen / Q000097:blood; D016022:Case-Control Studies; D002952:Citric Acid Cycle; D015179:Colorectal Neoplasms / Q000097:blood* / Q000175:diagnosis*; D016002:Discriminant Analysis; D005227:Fatty Acids / Q000097:blood; D005260:Female; D008401:Gas Chromatography-Mass Spectrometry; D005973:Glutamine / Q000097:blood; D006801:Humans; D016018:Least-Squares Analysis; D008297:Male; D055432:Metabolomics; D064307:Microbiota / Q000502:physiology; D008875:Middle Aged; D009367:Neoplasm Staging; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; D018709:Statistics, Nonparametric; D014508:Urea / Q000097:blood
chemical_list: D014408:Biomarkers, Tumor; D002272:Carcinoembryonic Antigen; D005227:Fatty Acids; D005973:Glutamine; D014508:Urea