Integrative proteomic profiling of tumor and plasma extracellular vesicles identifies a diagnostic biomarker panel for colorectal cancer

作者：Jun Wang, Chenzheng Gu, Pengxiang Wang, Jingrong Xian, H. Wang, Anquan Shang, Yu-Chen Zhong, Wen-Jing Zheng, Jianwen Cheng, Wenjing Yang, Jian Zhou, Jia Fan, Wei Guo, Xin-Rong Yang, Haojie Lu · 发表于：Cell Reports Medicine · 年份：2025 · DOI：10.1016/j.xcrm.2025.102090 · 被引用次数：15 · 研究领域：Extracellular vesicles in disease、Advanced Proteomics Techniques and Applications、Nanoplatforms for cancer theranostics

The lack of reliable non-invasive biomarkers for early colorectal cancer (CRC) diagnosis underscores the need for improved diagnostic tools. Extracellular vesicles (EVs) have emerged as promising candidates for liquid-biopsy-based cancer monitoring. Here, we propose a comprehensive workflow that integrates staged mass spectrometry (MS)-based discovery and verification with ELISA-based validation to identify EV protein biomarkers for CRC. Our approach, applied to 1,272 individuals, yields a machine learning model, ColonTrack, incorporating EV proteins HNRNPK, CTTN, and PSMC6. ColonTrack effectively distinguishes CRC from non-CRC cases and identifies early-stage CRC with high accuracy (combined area under the curve [AUC] >0.97, sensitivity ∼0.94, specificity ∼0.93). Our analysis of EV protein profiles from tissue and plasma demonstrates ColonTrack's potential as a robust non-invasive biomarker panel for CRC diagnosis and early detection.