Integrated analyses of murine breast cancer models reveal critical parallels with human disease

Jonathan P. Rennhack, Briana To, Matthew Swiatnicki, Caleb Dulak, Martin P. Ogrodzinski, Yueqi Zhang, Caralynn Li, Evan Bylett, Christina Ross, Karol Szczepanek, William Hanrahan, Muthu Jayatissa, Sophia Y. Lunt, Kent Hunter and Eran R. Andrechek ()
Additional contact information
Jonathan P. Rennhack: Michigan State University
Briana To: Michigan State University
Matthew Swiatnicki: Michigan State University
Caleb Dulak: Michigan State University
Martin P. Ogrodzinski: Michigan State University
Yueqi Zhang: Michigan State University
Caralynn Li: Michigan State University
Evan Bylett: Michigan State University
Christina Ross: Michigan State University
Karol Szczepanek: Michigan State University
William Hanrahan: Michigan State University
Muthu Jayatissa: Michigan State University
Sophia Y. Lunt: Michigan State University
Kent Hunter: National Cancer Institute, National Institutes of Health
Eran R. Andrechek: Michigan State University

Nature Communications, 2019, vol. 10, issue 1, 1-12

Abstract: Abstract Mouse models have an essential role in cancer research, yet little is known about how various models resemble human cancer at a genomic level. Here, we complete whole genome sequencing and transcriptome profiling of two widely used mouse models of breast cancer, MMTV-Neu and MMTV-PyMT. Through integrative in vitro and in vivo studies, we identify copy number alterations in key extracellular matrix proteins including collagen 1 type 1 alpha 1 (COL1A1) and chondroadherin (CHAD) that drive metastasis in these mouse models. In addition to copy number alterations, we observe a propensity of the tumors to modulate tyrosine kinase-mediated signaling through mutation of phosphatases such as PTPRH in the MMTV-PyMT mouse model. Mutation in PTPRH leads to increased phospho-EGFR levels and decreased latency. These findings underscore the importance of understanding the complete genomic landscape of a mouse model and illustrate the utility this has in understanding human cancers.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-019-11236-3 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11236-3

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-019-11236-3

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().