TY - JOUR
T1 - Colorectal cancer detection using targeted serum metabolic profiling
AU - Zhu, Jiangjiang
AU - Djukovic, Danijel
AU - Deng, Lingli
AU - Gu, Haiwei
AU - Himmati, Farhan
AU - Chiorean, E. Gabriela
AU - Raftery, Daniel
N1 - Publisher Copyright:
© 2014 American Chemical Society.
PY - 2014/9/5
Y1 - 2014/9/5
N2 - Colorectal cancer (CRC) is one of the most prevalent and deadly cancers in the world. Despite an expanding knowledge of its molecular pathogenesis during the past two decades, robust biomarkers to enable screening, surveillance, and therapy monitoring of CRC are still lacking. In this study, we present a targeted liquid chromatography-tandem mass spectrometry-based metabolic profiling approach for identifying biomarker candidates that could enable highly sensitive and specific CRC detection using human serum samples. In this targeted approach, 158 metabolites from 25 metabolic pathways of potential significance were monitored in 234 serum samples from three groups of patients (66 CRC patients, 76 polyp patients, and 92 healthy controls). Partial least-squares-discriminant analysis (PLS-DA) models were established, which proved to be powerful for distinguishing CRC patients from both healthy controls and polyp patients. Receiver operating characteristic curves generated based on these PLS-DA models showed high sensitivities (0.96 and 0.89, respectively, for differentiating CRC patients from healthy controls or polyp patients), good specificities (0.80 and 0.88), and excellent areas under the curve (0.93 and 0.95). Monte Carlo cross validation was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach.
AB - Colorectal cancer (CRC) is one of the most prevalent and deadly cancers in the world. Despite an expanding knowledge of its molecular pathogenesis during the past two decades, robust biomarkers to enable screening, surveillance, and therapy monitoring of CRC are still lacking. In this study, we present a targeted liquid chromatography-tandem mass spectrometry-based metabolic profiling approach for identifying biomarker candidates that could enable highly sensitive and specific CRC detection using human serum samples. In this targeted approach, 158 metabolites from 25 metabolic pathways of potential significance were monitored in 234 serum samples from three groups of patients (66 CRC patients, 76 polyp patients, and 92 healthy controls). Partial least-squares-discriminant analysis (PLS-DA) models were established, which proved to be powerful for distinguishing CRC patients from both healthy controls and polyp patients. Receiver operating characteristic curves generated based on these PLS-DA models showed high sensitivities (0.96 and 0.89, respectively, for differentiating CRC patients from healthy controls or polyp patients), good specificities (0.80 and 0.88), and excellent areas under the curve (0.93 and 0.95). Monte Carlo cross validation was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach.
KW - LC-MS/MS
KW - colorectal cancer
KW - diagnostic biomarkers
KW - metabolomics
KW - polyps
KW - serum metabolites
KW - targeted metabolic profiling
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U2 - 10.1021/pr500494u
DO - 10.1021/pr500494u
M3 - Article
C2 - 25126899
AN - SCOPUS:84914170537
SN - 1535-3893
VL - 13
SP - 4120
EP - 4130
JO - Journal of Proteome Research
JF - Journal of Proteome Research
IS - 9
ER -