Concordance among gene-expression-based predictors for breast cancer

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  • Fan, Cheng
    • Affiliation: School of Medicine, Department of Genetics
  • Oh, Daniel S.
    • Affiliation: School of Medicine, Department of Genetics
  • Wessels, Lodewyk
    • Other Affiliation: Division of Diagnostic Oncology, the Netherlands Cancer Institute, Amsterdam
  • Weigelt, Britta
    • Other Affiliation: Division of Diagnostic Oncology, the Netherlands Cancer Institute, Amsterdam
  • Nuyten, Dimitry S.A.
    • Other Affiliation: Division of Radiotherapy, the Netherlands Cancer Institute, Amsterdam
  • Nobel, Andrew
    • Affiliation: College of Arts and Sciences, Department of Statistics and Operations Research
  • van't Veer, Laura J.
    • Other Affiliation: Division of Diagnostic Oncology, the Netherlands Cancer Institute, Amsterdam
  • Perou, Charles
    • ORCID: https://orcid.org/0000-0001-9827-2247
    • Affiliation: School of Medicine, Department of Pathology and Laboratory Medicine, N.C. Cancer Hospital, UNC Lineberger Comprehensive Cancer Center
Abstract
  • BACKGROUND Gene-expression–profiling studies of primary breast tumors performed by different laboratories have resulted in the identification of a number of distinct prognostic profiles, or gene sets, with little overlap in terms of gene identity. METHODS To compare the predictions derived from these gene sets for individual samples, we obtained a single data set of 295 samples and applied five gene-expression–based models: intrinsic subtypes, 70-gene profile, wound response, recurrence score, and the two-gene ratio (for patients who had been treated with tamoxifen). RESULTS We found that most models had high rates of concordance in their outcome predictions for the individual samples. In particular, almost all tumors identified as having an intrinsic subtype of basal-like, HER2-positive and estrogen-receptor–negative, or luminal B (associated with a poor prognosis) were also classified as having a poor 70-gene profile, activated wound response, and high recurrence score. The 70-gene and recurrence-score models, which are beginning to be used in the clinical setting, showed 77 to 81 percent agreement in outcome classification.
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  • In Copyright
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  • New England Journal of Medicine
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  • 355
Journal issue
  • 6
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  • English
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