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Title: Predicting drug responsiveness in humans cancers using genetically engineered mice      
dateReleased:
01-01-2014
description:
Anti-cancer drug testing is challenging, but genetically engineered mouse models (GEMMs) and orthotopic, syngeneic transplants (OSTs) may offer advantages for pre-clinical testing including an intact microenvironment. We examined the efficacy of six chemotherapeutic or targeted anti-cancer drugs, alone and in combination, using over 500 GEMMs/OSTs representing three distinct breast cancer subtypes: Basal-like (C3(1)-T-antigen GEMM), Luminal B (MMTV-Neu GEMM), and Claudin-low (T11/TP53-/- OST). While a few single agents offered exceptional efficacy like lapatinib in the Neu/ERBB2 driven model, combination therapies tended to be more active and life prolonging. Using expression profiling of chemotherapy treated murine tumors, we identified an expression signature that was able to predict pathological complete response to neoadjuvant anthracycline-taxane treated human breast cancer patients, even after accounting for the common clinical variables and other genomic signatures. These results show that credentialed murine models can predict the efficacy of would-be anti-cancer compounds in humans, and that GEMMs can be used to develop new biomarkers of therapeutic responsiveness in humans. control X treatment
privacy:
not applicable
aggregation:
instance of dataset
ID:
E-GEOD-37915
refinement:
raw
alternateIdentifiers:
37915
keywords:
functional genomics
dateModified:
06-02-2014
availability:
available
types:
gene expression
name:
Mus musculus
ID:
A-MEXP-724
name:
Agilent Whole Mouse Genome Microarray 4x44K 014868 G4122F (annotation from 02.2007)
accessURL: https://www.ebi.ac.uk/arrayexpress/files/E-GEOD-37915/E-GEOD-37915.raw.1.zip
storedIn:
ArrayExpress
qualifier:
gzip compressed
format:
TXT
accessType:
download
authentication:
none
authorization:
none
accessURL: https://www.ebi.ac.uk/arrayexpress/files/E-GEOD-37915/E-GEOD-37915.processed.1.zip
storedIn:
ArrayExpress
qualifier:
gzip compressed
format:
TXT
accessType:
download
authentication:
none
authorization:
none
accessURL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE37915
storedIn:
Gene Expression Omnibus
qualifier:
not compressed
format:
HTML
accessType:
landing page
primary:
true
authentication:
none
authorization:
none
abbreviation:
EBI
homePage: http://www.ebi.ac.uk/
ID:
SCR:004727
name:
European Bioinformatics Institute
homePage: https://www.ebi.ac.uk/arrayexpress/
ID:
SCR:002964
name:
ArrayExpress
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