title: The 70-gene prognosis-signature predicts disease outcome in breast cancer patients with 1-3 positive lymph nodes in an independent validation study.
abstract: OBJECTIVE
  The 70-gene prognosis-signature has shown to be a valid prognostic tool in node-negative breast cancer. Although axillary lymph node status is considered to be one of the most important prognostic factors, still 25-30% of node-positive breast cancer patients will remain free of distant metastases, even without adjuvant systemic therapy. We therefore investigated whether the 70-gene prognosis-signature can accurately identify patients with 1-3 positive lymph nodes who have an excellent disease outcome.
  
  
  METHODS
  Frozen tumour samples from 241 patients with operable T1-3 breast cancer, and 1-3 positive axillary lymph nodes, with a median follow-up of 7.8 years, were selected from 2 institutes. Using a customized microarray, tumour samples were analysed for the 70-gene tumour expression signature. In addition, we reanalysed part of a previously described cohort (n = 106) with extended follow-up.
  
  
  RESULTS
  The 10-year distant metastasis-free (DMFS) and breast cancer specific survival (BCSS) probabilities were 91% (SE 4%) and 96% (SE 2%), respectively for the good prognosis-signature group (99 patients), and 76% (SE 4%) and 76% (SE 4%), respectively for the poor prognosis-signature group (142 patients). The 70-gene signature was significantly superior to the traditional prognostic factors in predicting BCSS with a multivariate hazard ratio (HR) of 7.17 (95% CI 1.81 to 28.43; P = 0.005).
  
  
  CONCLUSIONS
  The 70-gene prognosis-signature outperforms traditional prognostic factors in predicting disease outcome in patients with 1-3 positive nodes. Moreover, the signature can accurately identify patients with an excellent disease outcome in node-positive breast cancer, who may be safely spared adjuvant chemotherapy.
authors.affiliation: Department of Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
authors.forename: Stella
authors.initials: S
authors.lastname: Mook
authors.forename: Marjanka K
authors.initials: MK
authors.lastname: Schmidt
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Viale
authors.forename: Giancarlo
authors.initials: G
authors.lastname: Pruneri
authors.forename: Inge
authors.initials: I
authors.lastname: Eekhout
authors.forename: Arno
authors.initials: A
authors.lastname: Floore
authors.forename: Annuska M
authors.initials: AM
authors.lastname: Glas
authors.forename: Jan
authors.initials: J
authors.lastname: Bogaerts
authors.forename: Fatima
authors.initials: F
authors.lastname: Cardoso
authors.forename: Martine J
authors.initials: MJ
authors.lastname: Piccart-Gebhart
authors.forename: Emiel T
authors.initials: ET
authors.lastname: Rutgers
authors.forename: Laura J
authors.initials: LJ
authors.lastname: Van't Veer
mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000235:genetics* / Q000401:mortality / Q000473:pathology*; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D053208:Kaplan-Meier Estimate; D008207:Lymphatic Metastasis / Q000473:pathology; D008875:Middle Aged; D009364:Neoplasm Recurrence, Local / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis