%0 Journal Article
%T High-dimensional regression analysis links magnetic resonance imaging features and protein expression and signaling pathway alterations in breast invasive carcinoma
%A Anindya Bhadra
%A Arvind Rao
%A Basak Dogan
%A Elizabeth Morris
%A Elizabeth S. Burnside
%A Elizabeth Sutton
%A Emerlinda Bonaccio
%A Gary J. Whitman
%A Jose Net
%A Kathy Brandt
%A Margarita Zuley
%A Marie Ganott
%A Michael Lehrer
%A Sathvik Aithala
%A TCGA Breast Phenotype Research Group
%A Visweswaran Ravikumar
%A Youyun Zheng
%J Archive of "Oncoscience".
%D 2018
%R 10.18632/oncoscience.397
%X Imaging features derived from MRI scans can be used for not only breast cancer detection and measuring disease extent, but can also determine gene expression and patient outcomes. The relationships between imaging features, gene/protein expression, and response to therapy hold potential to guide personalized medicine. We aim to characterize the relationship between radiologist-annotated tumor phenotypic features (based on MRI) and the underlying biological processes (based on proteomic profiling) in the tumor
%K breast invasive carcinoma
%K MRI
%K protein expression
%K signaling pathway analysis
%K TCGA
%U https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5854291/