| Autor: |
Chia-Chin Wu, Licai Huang, Zhongting Zhang, Zhenlin Ju, Xingzhi Song, E. Anders Kolb, Wendong Zhang, Jonathan Gill, Min Ha, Malcolm A. Smith, Peter Houghton, Christopher L. Morton, Raushan Kurmasheva, John Maris, Yael Mosse, Yiling Lu, Richard Gorlick, P. Andrew Futreal, Hannah C. Beird |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2045-2322 |
| DOI: |
10.1038/s41598-024-69382-8 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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