title: Breast cancer molecular profiling with single sample predictors: a retrospective analysis.
abstract: BACKGROUND
  Microarray expression profiling classifies breast cancer into five molecular subtypes: luminal A, luminal B, basal-like, HER2, and normal breast-like. Three microarray-based single sample predictors (SSPs) have been used to define molecular classification of individual samples. We aimed to establish agreement between these SSPs for identification of breast cancer molecular subtypes.
  
  
  METHODS
  Previously described microarray-based SSPs were applied to one in-house (n=53) and three publicly available (n=779) breast cancer datasets. Agreement was analysed between SSPs for the whole classification system and for the five molecular subtypes individually in each cohort.
  
  
  RESULTS
  Fair-to-substantial agreement between every pair of SSPs in each cohort was recorded (kappa=0.238-0.740). Of the five molecular subtypes, only basal-like cancers consistently showed almost-perfect agreement (kappa>0.812). The proportion of cases classified as basal-like in each cohort was consistent irrespective of the SSP used; however, the proportion of each remaining molecular subtype varied substantially. Assignment of individual cases to luminal A, luminal B, HER2, and normal breast-like subtypes was dependent on the SSP used. The significance of associations with outcome of each molecular subtype, other than basal-like and luminal A, varied depending on SSP used. However, different SSPs produced broadly similar survival curves.
  
  
  CONCLUSIONS
  Although every SSP identifies molecular subtypes with similar survival, they do not reliably assign the same patients to the same molecular subtypes. For molecular subtype classification to be incorporated into routine clinical practice and treatment decision making, stringent standardisation of methodologies and definitions for identification of breast cancer molecular subtypes is needed.
  
  
  BACKGROUND
  Breakthrough Breast Cancer, Cancer Research UK.
authors.affiliation: Cancer Research UK, London Research Institute, London, UK.
authors.forename: Britta
authors.initials: B
authors.lastname: Weigelt
authors.forename: Alan
authors.initials: A
authors.lastname: Mackay
authors.forename: Roger
authors.initials: R
authors.lastname: A'hern
authors.forename: Rachael
authors.initials: R
authors.lastname: Natrajan
authors.forename: David S P
authors.initials: DS
authors.lastname: Tan
authors.forename: Mitch
authors.initials: M
authors.lastname: Dowsett
authors.forename: Alan
authors.initials: A
authors.lastname: Ashworth
authors.forename: Jorge S
authors.initials: JS
authors.lastname: Reis-Filho
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics* / Q000401:mortality / Q000473:pathology; D018270:Carcinoma, Ductal, Breast / Q000235:genetics* / Q000401:mortality / Q000473:pathology; D004273:DNA, Neoplasm / Q000145:classification*; D018572:Disease-Free Survival; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods* / Q000592:standards; D006801:Humans; D015999:Multivariate Analysis; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000592:standards; D016016:Proportional Hazards Models; D012015:Reference Standards; D015203:Reproducibility of Results; D013030:Spain / Q000453:epidemiology; D015996:Survival Rate; D014407:Tumor Cells, Cultured
chemical_list: D004273:DNA, Neoplasm