Taxonomy of breast cancer based on normal cell phenotype predicts outcome

Sandro Santagata, Ankita Thakkar, Ayse Ergonul, Bin Wang, Terri Woo, Rong Hu, J. Chuck Harrell, George McNamara, Matthew Schwede, Aedin C. Culhane, David Kindelberger, Scott Rodig, Andrea Richardson, Stuart J. Schnitt, Rulla M. Tamimi, Tan A. Ince

Research output: Contribution to journalArticle

122 Scopus citations

Abstract

Accurate classification is essential for understanding the pathophysiology of a disease and can inform therapeutic choices. For hematopoietic malignancies, a classification scheme based on the phenotypic similarity between tumor cells and normal cells has been successfully used to define tumor subtypes; however, use of normal cell types as a reference by which to classify solid tumors has not been widely emulated, in part due to more limited understanding of epithelial cell differentiation compared with hematopoiesis. To provide a better definition of the subtypes of epithelial cells comprising the breast epithelium, we performed a systematic analysis of a large set of breast epithelial markers in more than 15,000 normal breast cells, which identified 11 differentiation states for normal luminal cells. We then applied information from this analysis to classify human breast tumors based on normal cell types into 4 major subtypes, HR0-HR3, which were differentiated by vitamin D, androgen, and estrogen hormone receptor (HR) expression. Examination of 3,157 human breast tumors revealed that these HR subtypes were distinct from the current classification scheme, which is based on estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. Patient outcomes were best when tumors expressed all 3 hormone receptors (subtype HR3) and worst when they expressed none of the receptors (subtype HR0). Together, these data provide an ontological classification scheme associated with patient survival differences and provides actionable insights for treating breast tumors.

Original languageEnglish (US)
Pages (from-to)859-870
Number of pages12
JournalJournal of Clinical Investigation
Volume124
Issue number2
DOIs
StatePublished - Feb 3 2014

ASJC Scopus subject areas

  • Medicine(all)

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    Santagata, S., Thakkar, A., Ergonul, A., Wang, B., Woo, T., Hu, R., Harrell, J. C., McNamara, G., Schwede, M., Culhane, A. C., Kindelberger, D., Rodig, S., Richardson, A., Schnitt, S. J., Tamimi, R. M., & Ince, T. A. (2014). Taxonomy of breast cancer based on normal cell phenotype predicts outcome. Journal of Clinical Investigation, 124(2), 859-870. https://doi.org/10.1172/JCI70941