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

Authors

Xinyi Liu, Weiwei Chen, Le Wang, Yue Zhou, Xianxiu Ge, Lijuan Dai, Chengqu Fu, Yuefan Shen, Lu He, Xueni Cheng, Xuesi Dong, Ni Li, Lin Miao, Hongxia Ma, Guangfu Jin, Xiaosheng He, Lingbin Du, Dong Hang

Published in

iScience. Volume 29. Issue 8. Pages 116738. Aug 21, 2026. Epub Jul 14, 2026.

Abstract

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.

PMID:
42519036
Bibliographic data and abstract were imported from PubMed on 29 Jul 2026.

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