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Proteomic analysis demonstrates improved colorectal cancer screening efficiency using machine learning to identify patients for colonoscopy.
• Proteomic analysis of leftover FIT samples was explored. • High-throughput mass spectrometry and machine learning tools were used. • Proteomic signatures identify most of the false-FIT positive patients. • Proteomic signatures predicted patients with colorectal cancer (CRC). • This study provided the basis for further improving CRC screening. Proteomic analysis of leftover FIT samples was explored. High-throughput mass spectrometry and machine learning tools were used. Proteomic signatures identify most of the false-FIT positive patients. Proteomic signatures predicted patients with colorectal cancer (CRC). This study provided the basis for further improving CRC screening. The fecal immunochemical test (FIT) for detecting fecal occult blood, used alone or in combination with other stool biomarkers, has been demonstrated to be effective in the context of colorectal cancer (CRC) screening programs. However, FIT yields a significant proportion of false positives leading to unnecessary colonoscopies. In this study, we have investigated whether leftover FIT stool samples could be repurposed for proteomics analysis as a triage step for patients before recommending colonoscopy. High-throughput mass spectrometry analyses on a set of 141 FIT-positive samples (50 controls with no lesion, 45 with advanced adenomas (AA) and 46 with CRC) in combination with machine learning tools were used. Results showed that with a specificity ≥ 90%, a large proportion of the false FIT-positives could be identified thus providing an efficient strategy for reducing unnecessary colonoscopies. Furthermore, CRC cases were also precisely predicted to be true positives thus providing an approach for prioritizing patients for colonoscopy. In conclusion, this study demonstrates the feasibility of using proteomics for analysis of leftover FIT stool samples as an intermediate step to triage patients selected for colonoscopy in CRC screening programs.
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Gagné et al. (2026) studied this question.
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