title: Microarray-based class discovery for molecular classification of breast cancer: analysis of interobserver agreement.
abstract: BACKGROUND
  Breast cancers can be classified by hierarchical clustering using an "intrinsic" gene list into one of at least five molecular subtypes: basal-like, HER2, luminal A, luminal B, and normal breast-like. Five different intrinsic gene lists composed of varying numbers of genes have been used for molecular subtype identification and classification of breast cancers. The aim of this study was to determine the objectivity and interobserver reproducibility of the assignment of molecular subtype classes by hierarchical cluster analysis.
  
  
  METHODS
  Three publicly available breast cancer datasets (n = 779) were subjected to two-way average-linkage hierarchical cluster analysis using five distinct intrinsic gene lists. We used free-marginal Kappa statistics to analyze interobserver agreement among five breast cancer researchers for the whole classification and for each molecular subtype separately according to each intrinsic gene list for each breast cancer dataset.
  
  
  RESULTS
  None of the classification systems tested produced almost perfect agreement (Kappa ≥ 0.81) among observers. However, substantial interobserver agreement (70.8% to 76.1% of the samples and free-marginal Kappa scores from 0.635 to 0.701) was consistently observed in all datasets for four molecular subtypes (luminal, basal-like, HER2, and normal breast-like). When luminal cancers were subdivided (luminal A, B, and C), none of the classification systems produced substantial agreement (Kappa ≥ 0.61) in all the datasets analyzed. Analysis of each subtype separately revealed that only two (basal-like and HER2) could be reproducibly identified by independent observers (Kappa ≥ 0.81).
  
  
  CONCLUSIONS
  Assignment of molecular subtype classes of breast cancer based on the analysis of dendrograms obtained with hierarchical cluster analysis is subjective and shows modest interobserver reproducibility. For the development of a molecular taxonomy, objective definitions for each molecular subtype and standardized methods for their identification are required.
authors.affiliation: The Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, 237 Fulham Rd, London SW3 6JB, UK.
authors.forename: Alan
authors.initials: A
authors.lastname: Mackay
authors.forename: Britta
authors.initials: B
authors.lastname: Weigelt
authors.forename: Anita
authors.initials: A
authors.lastname: Grigoriadis
authors.forename: Bas
authors.initials: B
authors.lastname: Kreike
authors.forename: Rachael
authors.initials: R
authors.lastname: Natrajan
authors.forename: Roger
authors.initials: R
authors.lastname: A'Hern
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: D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000032:analysis*; D001943:Breast Neoplasms / Q000737:chemistry* / Q000235:genetics / Q000473:pathology*; D016000:Cluster Analysis; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D046228:Microarray Analysis; D008875:Middle Aged; D015588:Observer Variation; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000032:analysis; D015203:Reproducibility of Results; D012189:Retrospective Studies
chemical_list: D014408:Biomarkers, Tumor; D018719:Erb-b2 Receptor Tyrosine Kinases; C508053:ERBB2 protein, human