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Updated: Nov 10, 2025

Three-Dimensional Bone Extracellular Matrix Model for Osteosarcoma
Published on: April 12, 2019
Plasma Exosome-Derived Sentrin SUMO-Specific Protease 1: A Prognostic Biomarker in Patients With Osteosarcoma
1Department of Orthopedics, The Third People's Hospital of Yancheng City, Yancheng, China.
Background:
The exosomes contain many important proteins that can be used for early tumor diagnosis or patient prognosis analysis. In this study, we investigated plasma exosome-derived sentrin SUMO-specific protease 1 (SENP1) levels as a prognostic biomarker in patients with osteosarcoma.
Methods:
The expression of SENP1 protein in osteosarcoma tissues and adjacent tissues was detected by immunohistochemistry (IHC). The exosomes were identified by transmission electron microscopy, nanoparticle tracking analysis, and western blotting. ELISA was used to detect plasma exosome-derived SENP1 levels to assess prognosis in patients with osteosarcoma.
Results:
IHC showed that the positive expression rate of SENP1 in osteosarcoma tissues was 88.33%, whereas that in adjacent tissues was 46.67% (P < 0.05). Plasma exosome-derived SENP1 levels were related to tumor size, tumor location, necrosis rate, pulmonary metastasis, and surgical stage. Both disease-free survival (DFS) and overall survival (OS) were worse in patients who had higher plasma exosome-derived SENP1 levels compared with those in patients with lower plasma exosome-derived SENP1 levels (P < 0.001). The area under the receiver operating characteristic curve (AUROC) of plasma exosome-derived SENP1, as 1-year DFS and 3-year DFS prognostic biomarkers, was 0.90 (95% CI: 0.83-0.98) and 0.96 (95% CI: 0.94-0.99), respectively. As to OS, the AUROC of plasma exosome-derived SENP1 for 1-year and 3-year prediction was 0.90 (95% CI: 0.82-0.99) and 0.96 (0.93-0.98), respectively. The plasma exosome-derived SENP1 was better than plasma SENP1 as a prognostic biomarker both in DFS and OS.
Conclusions:
Our findings show that the plasma exosome-derived SENP1 may serve as a novel and independent prognostic predictor in clinical applications.

