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.