Novel plasma protein signatures for early diagnosis and prognostic stratification in colorectal cancer.

Colorectal cancer (CRC) remains a major global health concern, underscoring the need for reliable biomarkers for diagnosis and prognosis. In this study, untargeted plasma proteomics was conducted across two cohorts comprising 321 participants in the discovery set and 353 in the validation set. Machine learning methods were employed to select biomarkers and develop diagnostic and prognostic models, with performance evaluated by the area under the receiver operating characteristic curve (AUC). An eight-protein panel for CRC and a six-protein panel for advanced adenoma discriminated from healthy controls with AUCs of 0.932 and 0.816 in the validation set, respectively. Additionally, a combined prognostic model incorporating eight proteins and clinical factors predicted 5-year disease-free survival in CRC with an AUC of 0.744 in the validation cohort. Overall, the identified protein biomarkers have the potential to foster the development of effective blood-based tests for early detection and prognostic prediction of CRC.