Colorectal Cancer Detection Using Targeted Serum Metabolic Profiling

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.