Breast cancer tumors have long been classified according to their expression of three surface proteins: estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (HER2).
These classifications are used to determine best treatments and prognoses, but are not adequate to describe tumor characteristics or compare them to normal breast tissue.
In this issue of the Journal of Clinical Investigation, Tan Ince and colleagues of the University of Miami devised a method to categorize normal breast tissue cells as a reference point to classify tumor cells. By analyzing sections of normal breast tissue from 36 donors, the group delineated 13 previously undescribed cell types within the lobular structures of the tissue.
These cell types fit four patterns of hormone receptor expression, which could then be used to classify breast tumor samples, and correlated with distinct survival outcomes.
In an accompanying commentary, Robert Cardiff and Alexander Borowsky of University of California, Davis indicate that this new classification scheme be used to refine patient treatment plans and expand our understanding of breast cancer development.