Transcriptomic profiling of mouse mammary tumors enables prognostic and predictive biomarker discovery for human breast cancers
The development of a genomically and phenotypically diverse murine tumor dataset with linked treatment outcomes establishes a robust translational resource to develop, test, and benchmark clinically relevant prognostic and therapeutic response biomarkers.
Authors
- Patrick D Raedler
- Stephanie Dance-Barnes
- Kevin R. Mott
- Alexei Lobanov (ORCID: https://orcid.org/0000-0002-9883-4374)
- Tulay Yilmaz-Swenson
- Anna R. Michmerhuizen (ORCID: https://orcid.org/0000-0003-1105-287X)
- C.-L. Lin
- Daniel P. Hollern (ORCID: https://orcid.org/0000-0003-0332-5516)
- He Xiaping
- Matthew D. Sutcliffe
- Denis Okumu
- M. East
- A. D. Pfefferle
- B. M. Felsheim
- Charles M. Perou
Institutions
- University of North Carolina at Chapel Hill (US)
- DePaul University (US)
- Salk Institute for Biological Studies (US)
Publication Details
- Journal
- bioRxiv (Cold Spring Harbor Laboratory)
- Published
- 2026-03-03
- DOI
- https://doi.org/10.64898/2026.02.28.707759
- Primary Topic
- Breast Cancer Treatment Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00