Whole Genome and Reverse Protein Phase Array Landscapes of Patient Derived Osteosarcoma Xenograft Models

Authors

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

Publication Date

8-27-2024

Journal

Scientific Reports

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.

Keywords

Osteosarcoma, Humans, Animals, Bone Neoplasms, Mice, Xenograft Model Antitumor Assays, Whole Genome Sequencing, Protein Array Analysis, Transcriptome, Disease Models, Animal, Cancer, Bone cancer, Cancer genomics, Cancer models, Sarcoma

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Supplementary Materials

PMID: 39191826