Machine Learning-Assisted Plasma Metabolomics Identifies a Five-Metabolite Panel for Colorectal Cancer Detection

-methylcytisine, 2-piperidone, theophylline, dl-norleucine, and linolenic acid, were consistently reduced in CRC patient plasma across both cohorts. The integrated five-metabolite panel achieved an area under the ROC curve of 0.968 in the validation cohort with a 97.9% sensitivity, an 89.4% specificity, and a 93.7% accuracy. Stratified analyses demonstrated robustness across disease stages and age groups. In vitro assays showed modulation of CRC cell migration and invasion under noncytotoxic conditions. This five-metabolite plasma signature reflects CRC-associated systemic metabolic alterations and demonstrates a strong discriminatory performance. The panel may complement existing screening modalities by contributing to CRC risk stratification and early detection.