Somatic mouse models of gastric cancer reveal genotype-specific features of metastatic disease
UID: 11309
- Description
- Summary from GEO:
"Metastatic gastric carcinoma is a highly lethal cancer that responds poorly to conventional and molecularly targeted therapies. Despite its clinical relevance, the mechanisms underlying the behavior and therapeutic response of this disease are poorly understood owing, in part, to a paucity of tractable models that faithfully recapitulate different subtypes of the human disease. To close this gap, we developed methods to somatically introduce different oncogenic lesions directly into the stomach epithelium and show that genotypic configurations observed in patients produce metastatic gastric cancers that recapitulate the histological, molecular, and clinical features of all non-viral molecular subtypes of the human disease. Applying this platform to both wild-type and immune-deficient mice revealed previously unappreciated links between the genotype, organotropism and immune surveillance of metastatic cells that produced distinct patterns of metastasis that were mirrored in patients. Our results establish and credential a highly portable platform for producing autochthonous cancer models with flexible genotypes and host backgrounds, which can unravel mechanisms of gastric tumorigenesis or test new therapeutic concepts aimed at improving outcomes in gastric cancer patients."
Overall design from GEO:
"For RNA-seq analysis of the transcriptional profiles of MYC-p53, MYC-Apc and MYC-p53-Msh2 EPO-GEMM gastric tumors, as well as normal stomach of wild-type (WT) C57BL/6 mice, total RNA was extracted from bulk tissue using the RNeasy Mini Kit (Qiagen). Purified polyA mRNA was subsequently fragmented, and first and second strand cDNA synthesis performed using standard Illumina mRNA TruSeq library preparation protocols. Double stranded cDNA was subsequently processed for TruSeq dual-index Illumina library generation."
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Access via GEO
Accession #: GSE199261Access via BioProject
Accession #: PRJNA819078 - Access Restrictions
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Free to All
- Access Instructions
- The NCBI Gene Expression Omnibus and BioProject databases provide open access to these files.
- Associated Publications
- Equipment Used
- Dataset Format(s)
- CSV
- Dataset Size
- 1.1 MB
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