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Updated: Aug 12, 2026
Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors
Published on: February 27, 2015
Urinary Proteomics Enables Non-Invasive and Longitudinal Monitoring of Tumor Burden Dynamics and Early Recurrence in
Xiaohua Xing1, En Hu2, Lei Song3
1The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China; Department of Pathology, Institute of Oncology, School of Basic Medical Science, Fujian Medical University, Fuzhou 350025, China.
Purpose:
To develop a non-invasive, urine-based approach for dynamic monitoring of tumor burden and early detection of recurrence in hepatocellular carcinoma (HCC), addressing the limited sensitivity of conventional serum biomarkers such as AFP and DCP, particularly for minimal residual disease (MRD) assessment.
Methods:
We established a prospective, multi-cohort urinary proteomics framework encompassing four longitudinal clinical cohorts (378 patients, 972 urine samples). In the discovery cohort, 26 patients contributing 130 longitudinal urine samples from patients undergoing primary and secondary resections were analyzed by mass spectrometry across five standardized follow-up time points to identify proteins associated with tumor burden dynamics. The validation cohort (n=46) used parallel reaction monitoring (PRM) to confirm candidate biomarkers and construct a composite urine-based tumor burden monitoring model integrating HPGD, AFP, DCP, and GGT. The model was then applied to an early recurrence cohort (306 patients, 612 urine samples) to detect MRD and predict recurrence prior to radiological confirmation.
Results:
Among 8,563 quantified urinary proteins, 217 significantly correlated with tumor burden, with HPGD closely mirroring dynamic changes. The integrated model achieved pre-recurrence AUC 0.86, sensitivity 73%, specificity 87%, outperforming AFP (0.73, 39%, 96%) and DCP (0.64, 59%, 88%). It predicted recurrence a median 4.1 months earlier than imaging and served as an independent prognostic factor for recurrence-free and overall survival (p<0.001).
Conclusion:
This urine-based model enables dynamic assessment of tumor burden and early recurrence detection, surpassing conventional serum biomarkers and providing a clinically actionable tool for personalized surveillance and therapeutic decision-making in HCC.
