Related Experiment Video For Colorectal adenoma
Updated: Jun 28, 2025
Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing
Published on: September 25, 2011
Multiple-matrix metabolomics analysis for the distinct detection of colorectal cancer and adenoma
Ye Zhang1,2,3, Mingxin Ni2,3, Yuquan Tao2,3
1Department of Oncology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Objectives:
Although colorectal cancer (CRC) is the leading cause of cancer-related morbidity and mortality, current diagnostic tests for early-stage CRC and colorectal adenoma (CRA) are suboptimal. Therefore, there is an urgent need to explore less invasive screening procedures for CRC and CRA diagnosis.
Methods:
Untargeted gas chromatography-mass spectrometry (GC-MS) metabolic profiling approach was applied to identify candidate metabolites. We performed metabolomics profiling on plasma samples from 412 subjects including 200 CRC patients, 160 CRA patients and 52 normal controls (NC). Among these patients, 45 CRC patients, 152 CRA patients and 50 normal controls had their fecal samples tested simultaneously.
Results:
Differential metabolites were screened in the adenoma-carcinoma sequence. Three diagnostic models were further developed to identify cancer group, cancer stage, and cancer microsatellite status using those significant metabolites. The three-metabolite-only classifiers used to distinguish the cancer group always keeps the area under the receiver operating characteristic curve (AUC) greater than 0.7. The AUC performance of the classifiers applied to discriminate CRC stage is generally greater than 0.8, and the classifiers used to distinguish microsatellite status of CRC is greater than 0.9.
Conclusion:
This finding highlights potential early-driver metabolites in CRA and early-stage CRC. We also find potential metabolic markers for discriminating the microsatellite state of CRC. Our study and diagnostic model have potential applications for non-invasive CRC and CRA detection.
