TY - JOUR
T1 - Taxonomy of breast cancer based on normal cell phenotype predicts outcome
AU - Santagata, Sandro
AU - Thakkar, Ankita
AU - Ergonul, Ayse
AU - Wang, Bin
AU - Woo, Terri
AU - Hu, Rong
AU - Harrell, J. Chuck
AU - McNamara, George
AU - Schwede, Matthew
AU - Culhane, Aedin C.
AU - Kindelberger, David
AU - Rodig, Scott
AU - Richardson, Andrea
AU - Schnitt, Stuart J.
AU - Tamimi, Rulla M.
AU - Ince, Tan A.
PY - 2014/2/3
Y1 - 2014/2/3
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84893831447&partnerID=8YFLogxK
U2 - 10.1172/JCI70941
DO - 10.1172/JCI70941
M3 - Article
C2 - 24463450
AN - SCOPUS:84893831447
SN - 0021-9738
VL - 124
SP - 859
EP - 870
JO - Journal of Clinical Investigation
JF - Journal of Clinical Investigation
IS - 2
ER -