Plasma Proteomic High-Performance Biomarkers for Early Diagnosis of Colorectal Cancer

Colorectal cancer (CRC) is a major global health challenge due to its high incidence, mortality, and low rate of early detection. Early diagnosis, targeting precancerous lesions (advanced adenomas) and early stage CRC (Tis and T1), is critical for improving patient survival. Given the limitations of current detection methods for advanced adenomas, developing high-performance early diagnostic strategies is essential for effective prevention. In this study, we employed the proximity extension assay using the Olink Explore 384 Cardiometabolic panel to identify 15 protein biomarkers, of which 8 proteins (MMP7, GDF15, REG1B, RNASE3, REG1A, TFF3, MFAP5, and TGM2) were incorporated into multiple machine learning models to diagnose colorectal advanced neoplasia (AN) in the discovery cohort (n = 80), achieving AUC values above 0.90. These models also demonstrated significant diagnostic performance, with AUCs greater than 0.88, for patients with AN or advanced adenomas in the validation cohort (n = 69). Furthermore, hub biomarkers (MMP7 and GDF15) were identified and subsequently validated along with an analysis of their clinical significance. Thus, our study identifies multiprotein signatures validated in two cohorts with high diagnostic performance for colorectal AN, contributing to the development of the clinical detection kit for noninvasive early diagnosis of CRC.