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Cross-species analysis of genetically engineered mouse models of MAPK-driven colorectal cancer identifies hallmarks of the human disease
PJ. Belmont, E. Budinska, P. Jiang, MJ. Sinnamon, E. Coffee, J. Roper, T. Xie, PA. Rejto, S. Derkits, OJ. Sansom, M. Delorenzi, S. Tejpar, KE. Hung, ES. Martin,
Jazyk angličtina Země Anglie, Velká Británie
Typ dokumentu časopisecké články, práce podpořená grantem
NLK
Directory of Open Access Journals
od 2011
Free Medical Journals
od 2008 do Před 6 měsíci
Freely Accessible Science Journals
od 2008
PubMed Central
od 2008
Europe PubMed Central
od 2008
ProQuest Central
od 2008-01-01
Open Access Digital Library
od 2011-01-01
Health & Medicine (ProQuest)
od 2008-01-01
ROAD: Directory of Open Access Scholarly Resources
od 2008
PubMed
24742783
DOI
10.1242/dmm.013904
Knihovny.cz E-zdroje
- MeSH
- alely MeSH
- druhová specificita MeSH
- geny ras MeSH
- kolorektální nádory enzymologie genetika patologie MeSH
- lidé MeSH
- mitogenem aktivované proteinkinasy metabolismus MeSH
- modely nemocí na zvířatech MeSH
- myši MeSH
- protoonkogenní proteiny B-raf genetika MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- myši MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Effective treatment options for advanced colorectal cancer (CRC) are limited, survival rates are poor and this disease continues to be a leading cause of cancer-related deaths worldwide. Despite being a highly heterogeneous disease, a large subset of individuals with sporadic CRC typically harbor relatively few established 'driver' lesions. Here, we describe a collection of genetically engineered mouse models (GEMMs) of sporadic CRC that combine lesions frequently altered in human patients, including well-characterized tumor suppressors and activators of MAPK signaling. Primary tumors from these models were profiled, and individual GEMM tumors segregated into groups based on their genotypes. Unique allelic and genotypic expression signatures were generated from these GEMMs and applied to clinically annotated human CRC patient samples. We provide evidence that a Kras signature derived from these GEMMs is capable of distinguishing human tumors harboring KRAS mutation, and tracks with poor prognosis in two independent human patient cohorts. Furthermore, the analysis of a panel of human CRC cell lines suggests that high expression of the GEMM Kras signature correlates with sensitivity to targeted pathway inhibitors. Together, these findings implicate GEMMs as powerful preclinical tools with the capacity to recapitulate relevant human disease biology, and support the use of genetic signatures generated in these models to facilitate future drug discovery and validation efforts.
Bioinformatics Core Facility SIB Swiss Institute of Bioinformatics 1015 Lausanne Switzerland
Division of Gastroenterology Tufts Medical Center Boston MA 02111 USA
Oncology Research Unit Pfizer Global Research and Development San Diego CA 92121 USA
Pfizer Biotherapeutics Clinical Research Cambridge 02140 MA USA
The Beatson Institute for Cancer Research Garscube Estate Glasgow G61 1BD UK
University Hospital Gasthuisberg Katholieke Universiteit Leuven 3000 Leuven Belgium
Citace poskytuje Crossref.org
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