Credentialing a preclinical mouse model of alveolar rhabdomyosarcoma

Koichi Nishijo, Qing Rong Chen, Lei Zhang, Amanda T. McCleish, Andrea Rodriguez, Min Jung Cho, Suresh I. Prajapati, Jonathan A.L. Gelfond, Gary B. Chisholm, Joel E. Michalek, Bruce J. Aronow, Frederic G. Barr, R. Lor Randall, Marc Ladanyi, Stephen J. Qualman, Brian P. Rubin, Robin D. LeGaIIo, Chiayeng Wang, Javed Khan, Charles Keller

Producción científica: Articlerevisión exhaustiva

75 Citas (Scopus)

Resumen

The highly aggressive muscle cancer alveolar rhabdomyosar- coma (ABMS) is one of the most common soft tissue sarcoma of childhood, yet the outcome for the unresectable and metastatic disease is dismal and unchanged for nearly three decades. To better understand the pathogenesis of this disease and to facilitate novel preclinical approaches, we previously developed a conditional mouse model of ARMS by faithfully recapitulating the genetic mutations observed in the human disease, i.e., activation of Pax3:Fkhr fusion gene with either p53 or Cdkn2a inactivation. In this report, we show that this model recapitulates the immunohistochemical profile and the rapid progression of the human disease. We show that Pax3:Fkhr expression increases during late preneoplasia but tumor cells undergoing metastasis are under apparent selection for Pax3:Fkhr expression. At a whole-genome level, a cross-species gene set enrichment analysis and metagene projection study showed that our mouse model is most similar to human ARMS when compared with other pediatric cancers. We have defined an expression profile conserved between mouse and human ARMS, as well as a Pax&Fkhr signature, including the target gene, SKP2. We further identified 7 "draggable" kinases overexpressed across species. The data affirm the accuracy of this genetically engineered mouse model.

Idioma originalEnglish (US)
Páginas (desde-hasta)2902-2911
Número de páginas10
PublicaciónCancer Research
Volumen69
N.º7
DOI
EstadoPublished - abr 1 2009

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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