(Note: Current Rosetta Inpharmatics employees are shown in boldface type.)

Laura J. van ‘t Veer¹‡, Hongyue Dai² ‡, Marc J. van de Vijver1‡, Yudong D. He², Augustinus A.M. Hart¹, Mao Mao², Hans L. Peterse¹, Karin van der Kooy¹, Matthew J. Marton², Anke T. Witteveen¹, George J. Schreiber², Ron M. Kerkhoven¹, Chris Roberts², Peter S. Linsley², René Bernards¹ and Stephen H. Friend²#

Abstract

Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases, e.g., lymph node status and histological grade, fail to accurately classify breast tumours according to their clinical behaviour. Chemo- or hormonal therapy reduces the risk of distant metastases by approximately 1/3rd, although 70-80% of the patients would have survived without this treatment. None of the breast cancer gene expression signatures reported so far allows patient-tailored therapy strategies. Here we used DNA microarray analysis on primary breast tumours of 117 young patients and applied supervised classification to identify a gene expression signature strongly predictive of a short interval to distant metastases in lymph node negative patients. In addition, a signature was established that identifies tumours of BRCA1 carriers. The “poor prognosis signature” consists of genes regulating cell cycle, invasion, metastasis and angiogenesis. This gene expression profile will outperform all currently used clinical parameters in predicting outcome of disease. Our findings provide a novel strategy to select patients who would benefit from adjuvant therapy.

Download Data

The data and additional information supporting this paper are currently available for download in Winzip or Excel format. Please click only once on each download link. It may take a few seconds for the link to connect. Also, depending on the speed of your connection, it may take a few minutes to download the data.

• Array Data - less than 5 years to metastases
  Zip |  Excel (WinZip file size - 15mb; Excel file size - 39,923kb)
  
  
• Oligo probe sequences
  Excel (Excel file size - 3,000kb)
  
  
• Array Data samples - at least five years disease-free
  Zip | Excel (WinZip file size - 20mb; Excel file size - 51,006kb)
  
  
• Array Data - 19 samples
  Zip | Excel (WinZip file size - 9mb; Excel file size - 23,585kb)
  
  
• Array Data - BRCA1
  Zip | Excel (Winzip file size - 10mb; Excel file size - 24,677kb)
  
  
• Representative Genbank accession numbers for EST contig assemblies, last updated 10/23/2000
  Excel (Excel file size - 1,474kb)
  
  Mapping EST-contigs to GenBank Accession Numbers (Word file size - 20kb)
  
  
• README file (Word, 24kb)

¹ Divisions of Diagnostic Oncology, Radiotherapy and Molecular Carcinogenesis
and Center for Biomedical Genetics
The Netherlands Cancer Institute
121 Plesmanlaan
1066 CX Amsterdam
The Netherlands

² Rosetta Inpharmatics LLC*
12040 115th Avenue NE
Kirkland, Washington 98034
USA
‡ These authors contributed equally
* A wholly-owned subsidiary of Merck & Co., Inc.
# To whom correspondence should be addressed (stephen_friend@merck.com)