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Updated: Jul 8, 2026
Modeling Osteosarcoma Using Li-Fraumeni Syndrome Patient-derived Induced Pluripotent Stem Cells
Published on: June 13, 2018
Whole genome and reverse protein phase array landscapes of patient derived osteosarcoma xenograft models
Chia-Chin Wu1, Licai Huang2, Zhongting Zhang3
1Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Abstract:
Osteosarcoma is the most common primary bone malignancy in children and young adults, and it has few treatment options. As a result, there has been little improvement in survival outcomes in the past few decades. The need for models to test novel therapies is especially great in this disease since it is both rare and does not respond to most therapies. To address this, an NCI-funded consortium has characterized and utilized a panel of patient-derived xenograft models of osteosarcoma for drug testing. The exomes, transcriptomes, and copy number landscapes of these models have been presented previously. This study now adds whole genome sequencing and reverse-phase protein array profiling data, which can be correlated with drug testing results. In addition, four additional osteosarcoma models are described for use in the research community.
Insights
New osteosarcoma models offer better drug testing for this rare bone cancer. Researchers added whole genome sequencing and protein data to existing models, improving therapeutic development for children and young adults.
Area of Science:
- Oncology
- Genomics
- Translational Research
Background:
- Osteosarcoma is a rare bone cancer with limited treatment options and poor survival outcomes.
- Developing new therapies is challenging due to the rarity and poor response to existing treatments.
- Patient-derived xenograft (PDX) models are crucial for testing novel osteosarcoma therapies.
Purpose of the Study:
- To enhance a panel of osteosarcoma patient-derived xenograft models for drug testing.
- To provide comprehensive genomic and proteomic data for these models.
- To introduce four new osteosarcoma models for research.
Main Methods:
- Whole genome sequencing (WGS) was performed on existing models.
- Reverse-phase protein array (RPPA) profiling was conducted.
- Characterization data was correlated with drug testing results.
Main Results:
- New WGS and RPPA data were generated for the osteosarcoma PDX panel.
- This data provides a deeper understanding of the models' molecular landscapes.
- Four additional osteosarcoma models were characterized and made available.
Conclusions:
- The enhanced PDX models provide valuable resources for osteosarcoma drug discovery.
- Integrated multi-omics data facilitates the identification of potential therapeutic targets.
- These models will accelerate the development of effective treatments for osteosarcoma.
