RT Journal Article
SR Electronic
T1 A murine preclinical syngeneic transplantation model for breast cancer precision medicine
JF Science Advances
JO Sci Adv
FD American Association for the Advancement of Science
SP e1600957
DO 10.1126/sciadv.1600957
VO 3
IS 4
A1 Federico, Lorenzo
A1 Chong, Zechen
A1 Zhang, Dong
A1 McGrail, Daniel J.
A1 Zhao, Wei
A1 Jeong, Kang Jin
A1 Vellano, Christopher P.
A1 Ju, Zhenlin
A1 Gagea, Mihai
A1 Liu, Shuying
A1 Mitra, Shreya
A1 Dennison, Jennifer B.
A1 Lorenzi, Philip L.
A1 Cardnell, Robert
A1 Diao, Lixia
A1 Wang, Jing
A1 Lu, Yiling
A1 Byers, Lauren A.
A1 Perou, Charles M.
A1 Lin, Shiaw-Yih
A1 Mills, Gordon B.
YR 2017
UL http://advances.sciencemag.org/content/3/4/e1600957.abstract
AB We previously demonstrated that altered activity of lysophosphatidic acid in murine mammary glands promotes tumorigenesis. We have now established and characterized a heterogeneous collection of mouse-derived syngeneic transplants (MDSTs) as preclinical platforms for the assessment of personalized pharmacological therapies. Detailed molecular and phenotypic analyses revealed that MDSTs are the most heterogeneous group of genetically engineered mouse models (GEMMs) of breast cancer yet observed. Response of MDSTs to trametinib, a mitogen-activated protein kinase (MAPK) kinase inhibitor, correlated with RAS/MAPK signaling activity, as expected from studies in xenografts and clinical trials providing validation of the utility of the model. Sensitivity of MDSTs to talazoparib, a poly(adenosine 5′-diphosphate–ribose) polymerase (PARP) inhibitor, was predicted by PARP1 protein levels and by a new PARP sensitivity predictor (PSP) score developed from integrated analysis of drug sensitivity data of human cell lines. PSP score–based classification of The Cancer Genome Atlas breast cancer suggested that a subset of patients with limited therapeutic options would be expected to benefit from PARP-targeted drugs. These results indicate that MDSTs are useful models for studies of targeted therapies, and propose novel potential biomarkers for identification of breast cancer patients likely to benefit from personalized pharmacological treatments.