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National Institute of Environmental Health Sciences

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Publication Detail

Title: Development and translational imaging of a TP53 porcine tumorigenesis model.

Authors: Sieren, Jessica C; Meyerholz, David K; Wang, Xiao-Jun; Davis, Bryan T; Newell Jr, John D; Hammond, Emily; Rohret, Judy A; Rohret, Frank A; Struzynski, Jason T; Goeken, J Adam; Naumann, Paul W; Leidinger, Mariah R; Taghiyev, Agshin; Van Rheeden, Richard; Hagen, Jussara; Darbro, Benjamin W; Quelle, Dawn E; Rogers, Christopher S

Published In J Clin Invest, (2014 Sep)

Abstract: Cancer is the second deadliest disease in the United States, necessitating improvements in tumor diagnosis and treatment. Current model systems of cancer are informative, but translating promising imaging approaches and therapies to clinical practice has been challenging. In particular, the lack of a large-animal model that accurately mimics human cancer has been a major barrier to the development of effective diagnostic tools along with surgical and therapeutic interventions. Here, we developed a genetically modified porcine model of cancer in which animals express a mutation in TP53 (which encodes p53) that is orthologous to one commonly found in humans (R175H in people, R167H in pigs). TP53(R167H/R167H) mutant pigs primarily developed lymphomas and osteogenic tumors, recapitulating the tumor types observed in mice and humans expressing orthologous TP53 mutant alleles. CT and MRI imaging data effectively detected developing tumors, which were validated by histopathological evaluation after necropsy. Molecular genetic analyses confirmed that these animals expressed the R167H mutant p53, and evaluation of tumors revealed characteristic chromosomal instability. Together, these results demonstrated that TP53(R167H/R167H) pigs represent a large-animal tumor model that replicates the human condition. Our data further suggest that this model will be uniquely suited for developing clinically relevant, noninvasive imaging approaches to facilitate earlier detection, diagnosis, and treatment of human cancers.

PubMed ID: 25105366 Exiting the NIEHS site

MeSH Terms: No MeSH terms associated with this publication

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