Nature Communications (Jul 2021)

Patient-derived models recapitulate heterogeneity of molecular signatures and drug response in pediatric high-grade glioma

  • Chen He,
  • Ke Xu,
  • Xiaoyan Zhu,
  • Paige S. Dunphy,
  • Brian Gudenas,
  • Wenwei Lin,
  • Nathaniel Twarog,
  • Laura D. Hover,
  • Chang-Hyuk Kwon,
  • Lawryn H. Kasper,
  • Junyuan Zhang,
  • Xiaoyu Li,
  • James Dalton,
  • Barbara Jonchere,
  • Kimberly S. Mercer,
  • Duane G. Currier,
  • William Caufield,
  • Yingzhe Wang,
  • Jia Xie,
  • Alberto Broniscer,
  • Cynthia Wetmore,
  • Santhosh A. Upadhyaya,
  • Ibrahim Qaddoumi,
  • Paul Klimo,
  • Frederick Boop,
  • Amar Gajjar,
  • Jinghui Zhang,
  • Brent A. Orr,
  • Giles W. Robinson,
  • Michelle Monje,
  • Burgess B. Freeman III,
  • Martine F. Roussel,
  • Paul A. Northcott,
  • Taosheng Chen,
  • Zoran Rankovic,
  • Gang Wu,
  • Jason Chiang,
  • Christopher L. Tinkle,
  • Anang A. Shelat,
  • Suzanne J. Baker

DOI
https://doi.org/10.1038/s41467-021-24168-8
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 17

Abstract

Read online

Patient-derived xenografts provide a resource for basic and translational cancer research. Here, the authors generate multiple pediatric high-grade glioma xenografts, use omics technologies to show that they are representative of primary tumours and use them to assess therapeutic response.