title: Breast cancer prognostic biomarker using attractor metagenes and the FGD3-SUSD3 metagene.
abstract: BACKGROUND
  The winning model of the Sage Bionetworks/DREAM Breast Cancer Prognosis Challenge made use of several molecular features, called attractor metagenes, as well as another metagene defined by the average expression level of the two genes FGD3 and SUSD3. This is a follow-up study toward developing a breast cancer prognostic test derived from and improving upon that model.
  
  
  METHODS
  We designed a feature selector facility calculating the prognostic scores of combinations of features, including those that we had used earlier, as well as those used in existing breast cancer biomarker assays, identifying the optimal selection of features for the test.
  
  
  RESULTS
  The resulting test, called BCAM (Breast Cancer Attractor Metagenes), is universally applicable to all clinical subtypes and stages of breast cancer and does not make any use of breast cancer molecular subtype or hormonal status information, none of which provided additional prognostic value. BCAM is composed of several molecular features: the breast cancer-specific FGD3-SUSD3 metagene, four attractor metagenes present in multiple cancer types (CIN, MES, LYM, and END), three additional individual genes (CD68, DNAJB9, and CXCL12), tumor size, and the number of positive lymph nodes.
  
  
  CONCLUSIONS
  Our analysis leads to the unexpected and remarkable suggestion that ER, PR, and HER2 status, or molecular subtype classification, do not provide additional prognostic value when the values of the FGD3-SUSD3 and attractor metagenes are taken into consideration.
  
  
  CONCLUSIONS
  Our results suggest that BCAM's prognostic predictions show potential to outperform those resulting from existing breast cancer biomarker assays.
authors.affiliation: Department of Systems Biology, Columbia University, New York, New York. Department of Electrical Engineering, Columbia University, New York, New York.
authors.forename: Tai-Hsien
authors.initials: TH
authors.lastname: Ou Yang
authors.affiliation: Department of Systems Biology, Columbia University, New York, New York. Department of Electrical Engineering, Columbia University, New York, New York.
authors.forename: Wei-Yi
authors.initials: WY
authors.lastname: Cheng
authors.affiliation: Department of Statistics, Columbia University, New York, New York.
authors.forename: Tian
authors.initials: T
authors.lastname: Zheng
authors.affiliation: Division of Hematology/Oncology of the Department of Medicine, Columbia University, New York, New York. mm2058@columbia.edu da8@columbia.edu.
authors.forename: Matthew A
authors.initials: MA
authors.lastname: Maurer
authors.affiliation: Department of Systems Biology, Columbia University, New York, New York. Department of Electrical Engineering, Columbia University, New York, New York. mm2058@columbia.edu da8@columbia.edu.
authors.forename: Dimitris
authors.initials: D
authors.lastname: Anastassiou
mesh_terms: D014408:Biomarkers, Tumor; D001943:Breast Neoplasms / Q000235:genetics* / Q000401:mortality; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D056186:Metagenomics; D011379:Prognosis; D015996:Survival Rate
chemical_list: D014408:Biomarkers, Tumor