A pathway-based classification of human breast cancer.
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| Abstract |
The hallmark of human cancer is heterogeneity, reflecting the complexity and variability of the vast array of somatic mutations 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 on previous 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.
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| Authors | 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 |
| Journal | Proceedings of the National Academy of Sciences of the United States of America (Proc Natl Acad Sci U S A) Vol. 107 Issue 15 Pg. 6994-9 (Apr 13 2010) ISSN: 1091-6490 [Electronic] United States |
| PMID | 20335537 (Publication Type: Journal Article, Research Support, N.I.H., Extramural) |
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