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Updated: Feb 8, 2026

LINE-1 Methylation Analysis in Mesenchymal Stem Cells Treated with Osteosarcoma-Derived Extracellular Vesicles
Published on: February 1, 2020
Extracellular Vesicle RNA Sequencing Reveals Dramatic Transcriptomic Alterations Between Metastatic and Primary
Qiyuan Bao1, Liangzhi Gong1, Jizhuang Wang1
1Department of Orthopaedics, Shanghai Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Background:
Osteosarcoma (OS) is a highly metastasizing bone malignancy despite wide surgical resection of the primary lesion. A liquid biopsy approach to detect residual disease and identify therapeutic targets is still lacking. In this report, we aimed to track the metastasis of OS via extracellular vesicle (EV) RNA profiling in a non-invasive manner.
Methods:
We applied RNA sequencing for 10 matched metastatic and primary OS EV samples, including two pairs of cell lines and three pairs of plasma, and compared the expressed mutation, gene expression, fusion transcript, and alternative splicing (AS) between metastatic and primary OS at the transcriptome-wide level. Additional paired tissue/EVs were sequenced and public datasets were used to validate the EV-based metastatic biopsy.
Results:
EVs were characterized through size-profiling, immunolabeling, and morphological examination. A drastic increase of mutation burden was observed in metastatic OS versus the non-metastatic counterpart. Hierarchical clustering of the expression profiles differentiated the metastatic EVs from the non-metastatic, with a signature enriched in cell-adhesion signaling and tyrosine kinase pathways. Moreover, 30 cancer-related gene fusions were identified in EV RNA as AS events tend to be more frequently observed in metastatic EVs. Further investigation suggested that over 70% of expressed point mutations from EVs could be validated in paired cell line/EV and tissue/EV analyses, and the expression signature significantly predicted 5-year survivorship of 42 patients from a public dataset.
Conclusion:
We have demonstrated a liquid biopsy-based approach for tracking cancer transcriptomic alterations, which is a promising source of prognostic and therapeutic biomarkers for metastatic OS.
Clinical Trial Registration:
NCT03108677.
Insights
Extracellular vesicle RNA profiling offers a non-invasive liquid biopsy for tracking osteosarcoma metastasis. This approach identifies prognostic and therapeutic biomarkers for metastatic bone cancer.
Area of Science:
- Oncology
- Molecular Biology
- Genomics
Background:
- Osteosarcoma (OS) is a bone cancer known for frequent metastasis, even after surgery.
- Current methods lack effective non-invasive tools for detecting residual disease or guiding therapy in metastatic OS.
- Extracellular vesicles (EVs) present a potential avenue for liquid biopsy in OS.
Purpose of the Study:
- To investigate extracellular vesicle (EV) RNA profiling for tracking osteosarcoma (OS) metastasis non-invasively.
- To compare transcriptome-wide RNA profiles of EVs from primary and metastatic OS.
- To identify potential prognostic and therapeutic biomarkers for metastatic OS.
Main Methods:
- RNA sequencing of 10 matched primary and metastatic OS EV samples (cell lines and plasma).
- Comparative analysis of mutations, gene expression, fusion transcripts, and alternative splicing (AS) in EVs.
- Validation using paired tissue/EVs and public datasets.
Main Results:
- Metastatic OS EVs showed a significantly increased mutation burden compared to non-metastatic.
- EV expression profiles differentiated metastatic from non-metastatic OS, highlighting cell-adhesion and tyrosine kinase pathways.
- 30 cancer-related gene fusions and increased AS events were identified in metastatic OS EVs.
- EV-based mutations were highly validated, and the expression signature predicted patient survivorship.
Conclusions:
- A liquid biopsy approach using EV RNA profiling can track transcriptomic changes in metastatic osteosarcoma.
- This non-invasive method provides a promising source for prognostic and therapeutic biomarkers in metastatic OS.
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