title: Agreement in breast cancer classification between microarray and quantitative reverse transcription PCR from fresh-frozen and formalin-fixed, paraffin-embedded tissues.
abstract: BACKGROUND
  Microarray studies have identified different molecular subtypes of breast cancer with prognostic significance. To transition these classifications into the clinical laboratory, we have developed a real-time quantitative reverse transcription (qRT)-PCR assay to diagnose the biological subtypes of breast cancer from fresh-frozen (FF) and formalin-fixed, paraffin-embedded (FFPE) tissues.
  
  
  METHODS
  We used microarray data from 124 breast samples as a training set for classifying tumors into 4 previously defined molecular subtypes: Luminal, HER2(+)/ER(-), basal-like, and normal-like. We used the training set data in 2 different centroid-based algorithms to predict sample class on 35 breast tumors (test set) procured as FF and FFPE tissues (70 samples). We classified samples on the basis of large and minimized gene sets. We used the minimized gene set in a real-time qRT-PCR assay to predict sample subtype from the FF and FFPE tissues. We evaluated primer set performance between procurement methods by use of several measures of agreement.
  
  
  RESULTS
  The centroid-based algorithms were in complete agreement in classification from FFPE tissues by use of qRT-PCR and the minimized "intrinsic" gene set (40 classifiers). There was 94% (33 of 35) concordance between the diagnostic algorithms when comparing subtype classification from FF tissue by use of microarray (large and minimized gene set) and qRT-PCR data. We found that the ratio of the diagonal SD to the dynamic range was the best method for assessing agreement on a gene-by-gene basis.
  
  
  CONCLUSIONS
  Centroid-based algorithms are robust classifiers for breast cancer subtype assignment across platforms and procurement conditions.
authors.affiliation: Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Mullins
authors.forename: Laurent
authors.initials: L
authors.lastname: Perreard
authors.forename: John F
authors.initials: JF
authors.lastname: Quackenbush
authors.forename: Nicholas
authors.initials: N
authors.lastname: Gauthier
authors.forename: Steven
authors.initials: S
authors.lastname: Bayer
authors.forename: Matthew
authors.initials: M
authors.lastname: Ellis
authors.forename: Joel
authors.initials: J
authors.lastname: Parker
authors.forename: Charles M
authors.initials: CM
authors.lastname: Perou
authors.forename: Aniko
authors.initials: A
authors.lastname: Szabo
authors.forename: Philip S
authors.initials: PS
authors.lastname: Bernard
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000145:classification* / Q000175:diagnosis* / Q000473:pathology; D015925:Cryopreservation; D005260:Female; D005404:Fixatives; D005557:Formaldehyde; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D016612:Paraffin Embedding; D011237:Predictive Value of Tests; D020133:Reverse Transcriptase Polymerase Chain Reaction; D013048:Specimen Handling / Q000379:methods*
chemical_list: D005404:Fixatives; D005557:Formaldehyde