结直肠癌
仿形(计算机编程)
危险分层
计算生物学
精密医学
个性化医疗
结直肠癌筛查
多基因风险评分
生物信息学
医学
生物
癌症
计算机科学
遗传学
内科学
结肠镜检查
单核苷酸多态性
基因
基因型
操作系统
作者
Jing Sun,Yue Liu,Jianhui Zhao,Bin Lü,Siyun Zhou,Lu Wei,Jingsun Wei,Yeting Hu,Xiangxing Kong,Junshun Gao,Hong Guan,Junli Gao,Qian Xiao,Xue Li
标识
DOI:10.1038/s41467-024-52894-2
摘要
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 with high ProS, PRS, or combined risk score are proposed to start screening at age 46, 41, or before 40 years old. In this work, the integration of blood proteomics with PRS and QCancer-15 demonstrates improved performance for risk stratification and clinical implication for the derivation of risk-adapted starting ages of CRC screening, which may contribute to the decision-making process for CRC screening.
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