Tissues are comprised of multiple cell types that work in concert to direct cellular responses. This intercellular communication amongst the cell types within the tissue is critical to function, and dysregulation of these circuits underlies disease progression. However, a technology gap exists in identifying intercellular circuits, one we propose to fill through the combination of single cell sequencing with dynamic single cell imaging of transcriptional activity. Single cell sequencing enables the identification of large-scale gene expression profiles and identification of heterogeneous phenotypes within a tissue. However, these cell and molecular profiles do not effectively convey the communication that may be driving the response of specific cell types. We propose a strategy in which the secretome of the environment is combined with live cell transcriptional activity measurements (transcription factors (TFs), gene expression) and ultimately to single cell phenotypes and expression profiles to determine the key intercellular circuits driving cell and tissue phenotypes. We propose to employ a metastatic niche as a model, and to investigate the intercellular circuits guiding TC quiescence, as well as natural killer (NK) cell activity. Metastatic niches consist of multiple cell types, such as supportive immune cells and fibroblasts, that provide paracrine and juxtacrine signals that facilitate subsequent migration, invasion, proliferation, and angiogenesis at the metastatic site. The Shea and Jeruss laboratories have developed a synthetic metastatic niche (sMN) consisting of a biomaterial scaffold that recruits metastatic breast cancer cells in vivo, resulting in decreased tumor burden and enhancing survival. This sMN has many similarities to the natural metastatic niche (nMN), yet differences that lead to distinct phenotypes. We thus propose to develop an ex vivo model of the sMN and nMN and to investigate the intercellular circuits that govern TC and NK cell phenotype.
Specific Aim 1 will investigate TC phenotypic heterogeneity and the circuits governing quiescence at the metastatic niche. We propose single cell sequencing to characterize cell types and phenotypes at the sMN and nMN, along with ex vivo metastatic niche cultures to identify TC phenotypic heterogeneity (Aim 1.1). We will then apply live cell reporter assays to correlate secretome to TF, gene expression, and phenotype, focusing on the quiescent phenotype that is differentially observed in the sMN and nMN (Aim 1.2).
Specific Aim 2 will investigate mechanisms associated with TC immune-evasion and NK cell activation at the metastatic niche. The unique microenvironment of the MN also influences immunosurveillance by NK cells, with the sMN enriched for cytotoxic NK cells. We will investigate how the ex vivo sMN and nMN alters NK cell phenotyping heterogeneity (Aim 2.1) and the intercellular circuits that govern NK cell killing (Aim 2.2). The research team includes breast cancer biologist and clinician (Jeruss), tissue engineer with unique system for measuring TF activity (Shea), a NK immunologist (Lowenstein), and a computational biologist to connect RNAseq with TF activity data (Chandrasekaran).

Public Health Relevance

Communication amongst the cell types within the tissue (i.e., intercellular circuits) is critical to its function, and dysregulation of this communication underlies disease progression. However, a technology gap exists in identifying these intercellular circuits, one we propose to fill through the combination of single cell sequencing with dynamic single cell imaging of transcriptional activity. We employ a metastatic niche as a model system, and to investigate the intercellular circuits guiding tumor cell proliferation or quiescence, as well as natural killer (NK) cell activity.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA243916-02
Application #
10017189
Study Section
Cellular and Molecular Technologies Study Section (CMT)
Program Officer
Snyderwine, Elizabeth G
Project Start
2019-09-12
Project End
2024-08-31
Budget Start
2020-09-01
Budget End
2021-08-31
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Biomedical Engineering
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109