Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0

GEMM CRC collection analysis


ABSTRACT: A collection of genetically engineered mouse models (GEMM) of colorectal cancer (CRC) were created, and primary tumors from these GEMMs were analyzed. Primary CRC tumors from these GEMMs were genotyped to confirm that they contain the core genetic lesions of interest, including APC, P53, KRAS, and BRAF. Primary tumors from GEMMs with combinations of lesions of interest were analyzed by whole genome expression, and their expression profiles were compared to determine how they segregate. Signatures were then generated from GEMM tumors of interest and compared to human clinical datasets with expression and outcome data. Primary tumors from CRC GEMMs with different combinations of mutant alleles of interested were generated and analyzed. Alleles include mutant forms of APC (A), P53 (P), KRAS (K) and BRAF (B).

ORGANISM(S): Mus musculus

SUBMITTER: Peter Belmont 

PROVIDER: E-GEOD-50794 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

altmetric image

Publications

Cross-species analysis of genetically engineered mouse models of MAPK-driven colorectal cancer identifies hallmarks of the human disease.

Belmont Peter J PJ   Budinska Eva E   Jiang Ping P   Sinnamon Mark J MJ   Coffee Erin E   Roper Jatin J   Xie Tao T   Rejto Paul A PA   Derkits Sahra S   Sansom Owen J OJ   Delorenzi Mauro M   Tejpar Sabine S   Hung Kenneth E KE   Martin Eric S ES  

Disease models & mechanisms 20140417 6


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, incl  ...[more]

Similar Datasets

2014-07-01 | GSE50794 | GEO
2013-07-02 | E-GEOD-39557 | biostudies-arrayexpress
2015-05-08 | E-GEOD-57979 | biostudies-arrayexpress
2013-07-02 | GSE39557 | GEO
2015-05-08 | GSE57979 | GEO
2023-07-18 | MSV000092468 | MassIVE
2015-06-18 | E-GEOD-67186 | biostudies-arrayexpress
2014-04-01 | E-GEOD-56386 | biostudies-arrayexpress
| phs001111 | dbGaP
2019-10-16 | GSE119197 | GEO