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Patient-Derived Xenograft Models Reveal Intratumor Heterogeneity and Temporal Stability in Neuroblastoma

Journal article
Authors N. Braekeveldt
K. von Stedingk
Susanne Fransson
Angela Martinez-Monleon
D. Lindgren
H. Axelson
F. Levander
J. Willforss
K. Hansson
I. Ora
T. Backman
A. Borjesson
S. Beckman
J. Esfandyari
A. P. Berbegall
R. Noguera
J. Karlsson
J. Koster
Tommy Martinsson
D. Gisselsson
S. Pahlman
D. Bexell
Published in Cancer Research
Volume 78
Issue 20
Pages 5958-5969
ISSN 0008-5472
Publication year 2018
Published at Institute of Biomedicine, Department of Medical and Clinical Genetics
Institute of Biomedicine, Department of Pathology
Pages 5958-5969
Language en
Keywords high-risk neuroblastoma, orthotopic xenografts, tumor evolution, dynamics, cancer, mycn, metastasis, expression, mutations, target, Oncology
Subject categories Molecular medicine (genetics and pathology)


Patient-derived xenografts (PDX) and the Avatar, a single PDX mirroring an individual patient, are emerging tools in preclinical cancer research. However, the consequences of intratumor heterogeneity for PDX modeling of biomarkers, target identification, and treatment decisions remain under-explored. In this study, we undertook serial passaging and comprehensive molecular analysis of neuroblastoma orthotopic PDXs, which revealed strong intrinsic genetic, transcriptional, and phenotypic stability for more than 2 years. The PDXs showed preserved neuroblastoma-associated gene signatures that correlated with poor clinical outcome in a large cohort of patients with neuroblastoma. Furthermore, we captured spatial intratumor heterogeneity using ten PDXs from a single high-risk patient tumor. We observed diverse growth rates, transcriptional, proteomic, and phosphoproteomic profiles. PDX-derived transcriptional profiles were associated with diverse clinical characteristics in patients with high-risk neuroblastoma. These data suggest that high-risk neuroblastoma contains elements of both temporal stability and spatial intratumor heterogeneity, the latter of which complicates clinical translation of personalized PDX-Avatar studies into preclinical cancer research. Significance: These findings underpin the complexity of PDX modeling as a means to advance translational applications against neuroblastoma. (C) 2018 AACR.

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