A pathway-based classification of human breast cancer

Michael L. Gatza, Joseph E. Lucas, William T. Barry, Jong Wook Kim, Quanli Wang, Matthew D. Crawford, Michael B. Datto, Michael Kelley, Bernard Mathey-Prevot, Anil Potti, Joseph R. Nevins

Research output: Contribution to journalArticlepeer-review

265 Scopus citations


The hallmark of human cancer is heterogeneity, reflecting the complexity and variability of the vast array of somaticmutations acquired during oncogenesis. An ability to dissect this heterogeneity, to identify subgroups that represent common mechanisms of disease, will be critical to understanding the complexities of genetic alterations and to provide a framework to develop rational therapeutic strategies. Here, we describe a classification scheme for human breast cancer making use of patterns of pathway activity to build onprevious subtype characterizations using intrinsic gene expression signatures, to provide a functional interpretation of the gene expression data that can be linked to therapeutic options. We show that the identified subgroups provide a robust mechanism for classifying independent samples, identifying tumors that share patterns of pathway activity and exhibit similar clinical and biological properties, including distinct patterns of chromosomal alterations that were not evident in the heterogeneous total population of tumors. We propose that this classification scheme provides a basis for understanding the complex mechanisms of oncogenesis that give rise to these tumors and to identify rational opportunities for combination therapies.

Original languageEnglish (US)
Pages (from-to)6994-6999
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number15
StatePublished - Apr 13 2010
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General


  • Cancer genomics
  • Tumor subgroup


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