title: A simple method for assigning genomic grade to individual breast tumours.
abstract: BACKGROUND
  The prognostic value of grading in breast cancer can be increased with microarray technology, but proposed strategies are disadvantaged by the use of specific training data or parallel microscopic grading. Here, we investigate the performance of a method that uses no information outside the breast profile of interest.
  
  
  RESULTS
  In 251 profiled tumours we optimised a method that achieves grading by comparing rank means for genes predictive of high and low grade biology; a simpler method that allows for truly independent estimation of accuracy. Validation was carried out in 594 patients derived from several independent data sets. We found that accuracy was good: for low grade (G1) tumors 83-94%, for high grade (G3) tumors 74-100%. In keeping with aim of improved grading, two groups of intermediate grade (G2) cancers with significantly different outcome could be discriminated.
  
  
  CONCLUSIONS
  This validates the concept of microarray-based grading in breast cancer, and provides a more practical method to achieve it. A simple R script for grading is available in an additional file. Clinical implementation could achieve better estimation of recurrence risk for 40 to 50% of breast cancer patients.
authors.affiliation: Department of Oncology and Pathology, Karolinska Institutet and University Hospital, Cancer Centrum Karolinska, R8:3, 171 76 Stockholm, Sweden. kriwen@ki.se
authors.forename: Kristian
authors.initials: K
authors.lastname: Wennmalm
authors.forename: Jonas
authors.initials: J
authors.lastname: Bergh
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics* / Q000473:pathology*; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods; D015972:Gene Expression Regulation, Neoplastic; D023281:Genomics / Q000379:methods*; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D011379:Prognosis; D015203:Reproducibility of Results; D016019:Survival Analysis; D059467:Transcriptome