Abstract
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.
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Data availability
All data is publicly available as part of supplemental data.
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Funding
This research was funded by the key project of the Grants from the National Key R&D Program of China (No.2017YFC1700602, 2022YFC3500200, 2022YFC3500202), Priority Academic Program Development of Jiangsu Higher Education Institutions, Jiangsu Provincial Natural Science Foundation of Higher Education (No.22KJB310003), National Natural Science Foundation of China (Key Program, No.81930117), Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine (No. ZYYCXTD-C-202208), Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD), NATCM’s Project of High-level Construction of Key TCM Disciplines(Chinese Medicine Education Letter [2023] No. 85) .
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YZ: conceptualization, methodology, data curation, writing—original draft. MN, YT, WX, MS: sample and data collection. YZ, MN, YT, MF, JS: clinical data collection and diagnosis of patients. HC: supervision, funding acquisition, and diagnosis of patients. HC, MF: conceptualization, writing—review and editing, and funding acquisition.
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Zhang, Y., Ni, M., Tao, Y. et al. Multiple-matrix metabolomics analysis for the distinct detection of colorectal cancer and adenoma. Metabolomics 20, 47 (2024). https://doi.org/10.1007/s11306-024-02114-1
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DOI: https://doi.org/10.1007/s11306-024-02114-1