Overview of HBCA
The goal of this project is to generate a comprehensive reference of cell types and cell states in the adult human breast tissues using single cell and spatial genomic methods. This is part of the greater Human Cell Atlas (HCA) effort and is generously funded by the Chan-Zuckerberg Initiative (CZI). This project has also established optimized tissue dissociation protocols and data analysis code that are freely available for download. In addition to our HBCA project, there are several other ongoing human breast atlas projects that focus on different areas.
Here, we profiled breast tissues from over 100 women with diverse biological states (parity, menopause, age, ethnicity), which has identified 12 major cell types and over 60 biological cell states. These cell types and cell states are spatially organized into four major areas of the breast: ductal, lobular, adipose and connective regions. Our analysis has revealed abundant pericyte, endothelial and immune cell populations in normal breast, as well as highly diverse luminal epithelial cell states. Our spatial mapping using multiple technologies revealed an unexpectedly rich ecosystem of tissue-resident immune cells in the ducts and lobules, as well as distinct epithelial cell state differences between ductal and lobular regions. Collectively, these data provide an unprecedented reference of adult normal breast tissue for studying mammary biology and disease states such as breast cancer.
UMAP Cells
All Cells
*note : these have been downsampled to 100k cells
UMAP projection of scRNA-seq data from 714,331 cells integrated across 167 tissues from 126 women, showing 10 clusters that correspond to the major cell types
Epithelial Cells
*note : these have been downsampled to 50K cells
UMAP of scRNA-seq data from 240,804 epithelial cells, showing three major epithelial types
Basal-Myoepithelial
UMAP of 102,228 basal epithelial cells
LumHR
UMAP of 75,247 Luminal Hormone Responsive (LumHR) epithelial cells, showing 3 cell states
LumSec
UMAP of 63,329 Luminal Secretory (LumSec) epithelial cells, showing 7 cell states
NK/T Cells
UMAP of 76,567 NK/T cells from scRNA-seq data showing 14 cell state
B Cells
UMAP of 12,510 B cells from scRNA-seq data showing 5 cell states
Myeloid Cells
UMAP of 30,789 myeloid cells from scRNA-seq data showing of 15 cell types and states
Fibroblasts
UMAP of 208,390 fibroblast cells, showing 4 cell states
Vascular Endothelial Cells
UMAP of 83,651 vascular endothelial cells, showing 3 major cell states
Lymphatic Endothelial Cells
UMAP of 8,982 lymphatic endothelial cells, showing 4 major cell states
Perivascular Cells
UMAP projection and clustering of 52,638 perivascular cells, showing 2 cell states
UMAP Nuclei
Adipocytes
UMAP of snRNA-seq data from 120,024 nuclei from integrated across 20 tissues from 20 women, showing 11 cell type clusters
Epithelial Nuclei
UMAP of snRNA-seq data from 56,280 epithelial nuclei, showing 3 major epithelial types and 2 clusters of proliferating cells
Adipocyte Nuclei
UMAP of 4,917 adipocytes from snRNA- seq data
HBCA Team Members
Ni
Lead PI
MD Anderson
Kai Kessenbrock
Co-PI
UC Irvine
Devon A. Lawson
Co-PI
UC Irvine
Bora Lim, MD
Co-PI
Baylor College of Medicine
Tapsi Kumar
Graduate Student
MD Anderson
Kevin Nee, PhD
MSTP Student
UC Irvine
Runmin
Postdoctoral Associate
MD Anderson
Siyuan He
Graduate Student
MD Anderson
Quy H. Nguyen, PhD
Graduate Student
UC Irvine
Shanshan Bai
Research Laboratory Scientist
MD Anderson
Kerri
Graduate Student
UC Irvine
Yanwen Gong, PhD
Graduate Student
UC Irvine
Maren
Postdoctoral Scholar
UC Irvine
Anna Casasent
Computational Scientist
MD Anderson
Aatish Th
Postdoctoral Associate
Ken Chen, PhD
Professor
UC Irvine
Sharmila Mallya
Research Associate/ manager
UC Irvine
Tatyana Lev
Graduate Student
UC Irvine
Other Helpful Links
*Acknowledgements : A big Shout Out to Ivan Yao-Yi Chang, Jenny Wu, and Jessica Gonzalez for their effort to make this website*
