title: 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.
authors.affiliation: Division of Diagnostic Oncology, The Netherlands Cancer Institute, 121 Plesmanlaan, 1066 CX Amsterdam, The Netherlands.
authors.forename: Laura J
authors.initials: LJ
authors.lastname: van 't Veer
authors.forename: Hongyue
authors.initials: H
authors.lastname: Dai
authors.forename: Marc J
authors.initials: MJ
authors.lastname: van de Vijver
authors.forename: Yudong D
authors.initials: YD
authors.lastname: He
authors.forename: Augustinus A M
authors.initials: AA
authors.lastname: Hart
authors.forename: Mao
authors.initials: M
authors.lastname: Mao
authors.forename: Hans L
authors.initials: HL
authors.lastname: Peterse
authors.forename: Karin
authors.initials: K
authors.lastname: van der Kooy
authors.forename: Matthew J
authors.initials: MJ
authors.lastname: Marton
authors.forename: Anke T
authors.initials: AT
authors.lastname: Witteveen
authors.forename: George J
authors.initials: GJ
authors.lastname: Schreiber
authors.forename: Ron M
authors.initials: RM
authors.lastname: Kerkhoven
authors.forename: Chris
authors.initials: C
authors.lastname: Roberts
authors.forename: Peter S
authors.initials: PS
authors.lastname: Linsley
authors.forename: René
authors.initials: R
authors.lastname: Bernards
authors.forename: Stephen H
authors.initials: SH
authors.lastname: Friend
mesh_terms: D000328:Adult; D001943:Breast Neoplasms / Q000235:genetics* / Q000503:physiopathology / Q000628:therapy; D017024:Chemotherapy, Adjuvant; D016000:Cluster Analysis; D004273:DNA, Neoplasm; D005260:Female; D020869:Gene Expression Profiling; D019398:Genes, BRCA1; D024522:Genes, BRCA2; D006801:Humans; D008207:Lymphatic Metastasis; D020411:Oligonucleotide Array Sequence Analysis; D018579:Patient Selection; D011237:Predictive Value of Tests; D011379:Prognosis; D016896:Treatment Outcome
chemical_list: D004273:DNA, Neoplasm