A comprehensive single-cell breast tumor atlas defines epithelial and immune heterogeneity and interactions predicting anti-PD-1 therapy response
Lily Xu, Kaitlyn Saunders, Shao-Po Huang, Hildur Knútsdóttir, Kenneth Martinez-Algarin, Isabella Terrazas, Kenian Chen, Heather M. McArthur, Julia Maués, Christine Hodgdon, Sangeetha M. Reddy, Evanthia T. Roussos Torres, Lin Xu, Isaac S. Chan
Abstract
We present an integrated single-cell RNA sequencing atlas of the primary breast tumor microenvironment (TME) containing 236,363 cells from 119 biopsy samples across eight datasets. In this study, we leverage this resource for multiple analyses of immune and cancer epithelial cell heterogeneity. We define natural killer (NK) cell heterogeneity through six subsets in the breast TME. Because NK cell heterogeneity correlates with epithelial cell heterogeneity, we characterize epithelial cells at the level of single-gene expression, molecular subtype, and 10 categories reflecting intratumoral transcriptional heterogeneity. We develop InteractPrint, which considers how cancer epithelial cell heterogeneity influences cancer-immune interactions. We use T cell InteractPrint to predict response to immune checkpoint inhibition (ICI) in two breast cancer clinical trials testing neoadjuvant anti-PD-1 therapy. T cell InteractPrint was predictive of response in both trials versus PD-L1 (AUC = 0.82, 0.83 vs. 0.50, 0.72). This resource enables additional high-resolution investigations of the breast TME.