Plasma proteomic and polygenic profiling improve risk stratification and personalized screening for colorectal cancer.

ABSTRACT: This study aims to identify colorectal cancer (CRC)-related proteomic profiles and develop a prediction model for CRC onset by integrating proteomic profiles with genetic and non-genetic factors (QCancer-15) to improve the risk stratification and estimate of personalized initial screening age. Here, using a two-stage strategy, we prioritize 15 protein biomarkers as predictors to construct a protein risk score (ProS). The risk prediction model integrating proteomic profiles with polygenic risk score (PRS) and QCancer-15 risk score (QCancer-S) shows improved performance (C-statistic: 0.79 vs. 0.71, P = 4.94E-03 in training cohort; 0.75 vs 0.69, P = 5.49E-04 in validation cohort) and net benefit than QCancer-S alone. The combined model markedly stratifies the risk of CRC onset. Participants w

SUBMITTER: Sun J 

PROVIDER: S-EPMC11473805 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature