ArticleDisease models & mechanisms2014
Cross-species analysis of genetically engineered mouse models of MAPK-driven colorectal cancer identifies hallmarks of the human disease.
Article in Disease models & mechanisms, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Macrophage-Derived PDGF-BB and GDF-15 Promote Drug Resistance in KRAS-Mutant Colorectal Cancer.bioRxiv : the preprint server for biology · 2026Article
- Review
- MmCMS: mouse models' consensus molecular subtypes of colorectal cancer.British journal of cancer · 2023Article
- Identification of potential therapeutic targets in prostate cancer through a cross-species approach.EMBO molecular medicine · 2018Article
- Colorectal cancer models for novel drug discovery.Expert opinion on drug discovery · 2015Review
- A transcriptomic insight into the impacts of mast cells in lung, breast, and colon cancers.OncoimmunologyArticle
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Authors and funding
14 authors.
Funding
Abstract
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.
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