Method of classifying a breast cancer instrinsic subtype

US9631239B2 · kind B2 · utility

Assignees

• University of Utah Research Foundation · US
• British Columbia Cancer Agency Branch · CA
• Washington University · US
• The University of North Carolina at Chapel Hill · US

Inventors

• Charles M. Perou · Chapel Hill, US
• Joel S. Parker · Chapel Hill, US
• James Stephen Marron · Durham, US
• Andrew Nobel · Chapel Hill, US
• Philip S. Bernard · Salt Lake City, US
• Matthew J. Ellis · Romsey, GB
• Elaine Mardis · Glen Carbon, US
• Torsten O. Nielsen · North Vancouver, CA
• Maggie Cheang · London, GB

Key dates

• Filing date: Jun 1, 2009
• Grant date: Apr 25, 2017
• Expiry date: Oct 23, 2031

Classification

• Technology area (CPC G): Physics
• CPC primary: G16B40/00
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

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.