title: Concordance among gene-expression-based predictors for breast cancer.
abstract: BACKGROUND
  Gene-expression-profiling studies of primary breast tumors performed by different laboratories have resulted in the identification of a number of distinct prognostic profiles, or gene sets, with little overlap in terms of gene identity.
  
  
  METHODS
  To compare the predictions derived from these gene sets for individual samples, we obtained a single data set of 295 samples and applied five gene-expression-based models: intrinsic subtypes, 70-gene profile, wound response, recurrence score, and the two-gene ratio (for patients who had been treated with tamoxifen).
  
  
  RESULTS
  We found that most models had high rates of concordance in their outcome predictions for the individual samples. In particular, almost all tumors identified as having an intrinsic subtype of basal-like, HER2-positive and estrogen-receptor-negative, or luminal B (associated with a poor prognosis) were also classified as having a poor 70-gene profile, activated wound response, and high recurrence score. The 70-gene and recurrence-score models, which are beginning to be used in the clinical setting, showed 77 to 81 percent agreement in outcome classification.
  
  
  CONCLUSIONS
  Even though different gene sets were used for prognostication in patients with breast cancer, four of the five tested showed significant agreement in the outcome predictions for individual patients and are probably tracking a common set of biologic phenotypes.
authors.affiliation: Department of Genetics, University of North Carolina at Chapel Hill and Lineberger Comprehensive Cancer Center, Chapel Hill 27599, USA.
authors.forename: Cheng
authors.initials: C
authors.lastname: Fan
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Oh
authors.forename: Lodewyk
authors.initials: L
authors.lastname: Wessels
authors.forename: Britta
authors.initials: B
authors.lastname: Weigelt
authors.forename: Dimitry S A
authors.initials: DS
authors.lastname: Nuyten
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Nobel
authors.forename: Laura J
authors.initials: LJ
authors.lastname: van't Veer
authors.forename: Charles M
authors.initials: CM
authors.lastname: Perou
mesh_terms: D000704:Analysis of Variance; D001943:Breast Neoplasms / Q000235:genetics* / Q000401:mortality; D005260:Female; D015870:Gene Expression; D020869:Gene Expression Profiling; D006801:Humans; D008957:Models, Genetic; D010641:Phenotype; D011379:Prognosis; D016016:Proportional Hazards Models; D018719:Erb-b2 Receptor Tyrosine Kinases; D011960:Receptors, Estrogen; D016019:Survival Analysis
chemical_list: D018719:Erb-b2 Receptor Tyrosine Kinases; D011960:Receptors, Estrogen