Gene expression profiling predicts clinical outcome of breast cancer.

Abstract:

:Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour. Chemotherapy or hormonal therapy reduces the risk of distant metastases by approximately one-third; however, 70-80% of patients receiving this treatment would have survived without it. None of the signatures of breast cancer gene expression reported to date allow for 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 ('poor prognosis' signature) in patients without tumour cells in local lymph nodes at diagnosis (lymph node negative). In addition, we established a signature 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 disease outcome. Our findings provide a strategy to select patients who would benefit from adjuvant therapy.

journal_name

Nature

journal_title

Nature

authors

van 't Veer LJ,Dai H,van de Vijver MJ,He YD,Hart AA,Mao M,Peterse HL,van der Kooy K,Marton MJ,Witteveen AT,Schreiber GJ,Kerkhoven RM,Roberts C,Linsley PS,Bernards R,Friend SH

doi

10.1038/415530a

keywords:

subject

Has Abstract

pub_date

2002-01-31 00:00:00

pages

530-6

issue

6871

eissn

0028-0836

issn

1476-4687

pii

415530a

journal_volume

415

pub_type

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