Identifying the intercellular networks regulating estrogen receptor expression with a high definition single cell printer

Sponsor: NIH National Cancer Institute

Location(s): United States


The proposed study seeks to develop a technology for printing single primary human cells into arrays of small multicellular tissues with the ability to specify the precise cell printed at every position. This printing technology is broadly relevant to human health, which we will demonstrate by using it to study the mechanism that drives estrogen receptor positive breast cancer. Ultimately, in addition to studying and experimenting on individual cells, we believe our groundbreaking technology will be able to print whole, functional tissues for organ replacement.

The long-term objective of this proposal is to reinvent live-cell printing by combining advances in droplet microfluidics, robotic automation, and microscopy techniques. The immediate scientific goal of this proposal is to recreate the in situ microenvironment by building combinatorial cellular interaction arrays using primary or limited life-span human mammary epithelial cells. Specifically, we will apply the multicellular interaction arrays to disset the cellular network that contributes to heterogeneous patterns of estrogen receptor expression. Estrogen receptor (ER) is the key regulator of human mammary gland growth and is necessary for the most prevalent forms of human breast cancer. Remarkably, however, the estrogen receptor is only expressed in one cell type in the human mammary gland - luminal epithelial cells. More remarkably still, the receptor is expressed in a binary fashion, and only in 5-20% of luminal epithelial cells in a normal tissue. Little is known about the mechanisms through which ER expression is regulated within the luminal population, but available evidence suggests that multiple other cell types in the microenvironment are critical. We will use the proposed high definition single cell printer to explore a large combination of primary human cell types, soluble factors, and ECM components to identify the minimal intercellular circuit necessary to sustain ER expression in the mammary gland. We hypothesize that ER expression in the luminal population is regulated by a combination of cell-cell contact with myoepithelial cells and a paracrine circuit involving fibroblasts and at least one other stromal component responsible for stabilizing estrogen receptor expression. " Specific Aim 1: Build and test the prototype single cel phenotype analysis tool. In this aim, we will build a prototype platform capable of assembling and imaging tens of thousands of 3D multicellular agglomerates with precisely defined compositions. First, we will design and construct microfluidics capable of delivering picodroplets containing single cells, matrix components, or growth factors to a target surface. Next, we will build the optical detection hardware, write control software, and integrate the system. Finally, we will perform control experiments using cultured primary human mammary epithelial cells to establish the capability of the system to assemble and recapitulate multicellular interactions. (Adam) " Specific Aim 2: Assemble heterotypic 2D and 3D tissue microarrays from cultured primary human breast tissue to identify the multicellular circuit regulating estrogen receptor expression. We will use early passage primary fibroblasts, endothelial cells, luminal epithelial and myoepithelial cells from the human breast to identify the minimal cellular interactions necessary to sustain or augment ER expression in the luminal population. These cells will be combined into microtissues with Matrigel and a cocktail of growth factors and hormones involved in ER function. Each printed tissue will combine 10 printed droplets spanning a combination of cells, matrix components, and soluble factors. ER expression will be measured after 48 hours in culture following fixing, staining, and high-content imaging of the cellular arras to identify combinations of cells and factors extending or enhancing ER expression.