University of Utah Research Foundation

Washington University

The University of North Carolina at Chapel Hill

British Columbia Cancer Agency Branch

Maggie Cheang

Charles M Perou

Philip Seth Bernard

Joel S Parker

Torsten O Nielsen

Andrew Nobel

Elaine R Mardis

James Stephen Marron

Philip S Bernard

James Marron

Torsten Nielsen

Methods for classifying and for evaluating the prognosis of a subject having breast cancer are provided. The methods include prediction of breast cancer subtype using a supervised algorithm trained to stratify subjects on the basis of breast cancer intrinsic subtype. The prediction model is based on the gene expression profile of the intrinsic genes listed in Table 1. This prediction model can be used to accurately predict the intrinsic subtype of a subject diagnosed with or suspected of having breast cancer. Further provided are compositions and methods for predicting outcome or response to therapy of a subject diagnosed with or suspected of having breast cancer. These methods are useful for guiding or determining treatment options for a subject afflicted with breast cancer. Methods of the invention further include means for evaluating gene expression profiles, including microarrays and quantitative polymerase chain reaction assays, as well as kits comprising reagents for practicing the methods of the invention.

Method of classifying a breast cancer instrinsic subtype

Growing community of inventors

Vancouver, Canada

Maggie Cheang