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

Journal: Cell reports. Medicine
Published Date: Apr 30, 2025

Abstract

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.

Authors

  • Jun Wang
    Department of Speech, Language, and Hearing Sciences and the Department of Neurology, The University of Texas at Austin, Austin, TX 78712, USA.
  • Chen-Zheng Gu
    Department of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, P.R. China.
  • Peng-Xiang Wang
    Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China.
  • Jing-Rong Xian
    Department of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, P.R. China.
  • Hao Wang
    Department of Cardiology, Second Medical Center, Chinese PLA General Hospital, Beijing, China.
  • An-Quan Shang
    Department of Laboratory Medicine, Lianyungang Clinical College of Jiangsu University, Lianyungang, 222006, P.R. China.
  • Yu-Chen Zhong
    Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China.
  • Wen-Jing Zheng
    Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China.
  • Jian-Wen Cheng
    Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China.
  • Wen-Jing Yang
    Department of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, P.R. China.
  • Jian Zhou
    CTIQ, Canon Medical Research USA, Inc., Vernon Hills, 60061, USA.
  • Jia Fan
    Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Wei Guo
    Emergency Department, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
  • Xin-Rong Yang
    Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China. Electronic address: yang.xinrong@zs-hospital.sh.cn.
  • Hao-Jie Lu
    Department of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China; Department of Chemistry, Institutes of Biomedical Sciences and Laboratory of Glycoconjugates Research, Fudan University, Shanghai 200032, P.R. China. Electronic address: luhaojie@fudan.edu.cn.

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