Periodic Reporting for period 2 - DualRP (Exploring cell interactions in the tumor microenvironment with dual ribosome profiling)
Reporting period: 2019-12-01 to 2021-05-31
Tumors grow in very heterogeneous cellular environments. Tumors are composed not only of cancer cells, but also recruit a number of immune cells, fibroblasts, endothelial cells, and others. Cancer progression depends on the heterogeneity of the tumor microenvironment (TME) for sustained growth, metastasis, and therapy resistance. The TME plays also a very important role as a source of nutrients for cancer cells. Recent evidence shows that cancer cells can reprogram the non-malignant cells of the TME to acquire nutrients essential for growth. However, methods to study metabolic interactions in the TME are lacking.
We recently harnessed ribosome profiling for sensing restrictive amino acids, and developed diricore, a procedure for differential ribosome measurements of codon reading. In this project, we developed and validated Dual Ribosome Profiling (DualRP), a system to study cell interactions in the TME. DualRP is an approach that allows not only simultaneous analysis of gene expression in two interacting cell populations in vivo, but also is able to uncover metabolic limitations in multiple cellular types in tumors by reading selectively the stalling of ribosomes.
In this project, we propose to use dual ribosome profiling (DualRP) and diricore analysis to study cell interactions and metabolic limitations in the tumor microenvironment (TME). First, we propose to study systematically the interactions between breast cancer cells and non-transformed fibroblasts and how therapy affects the response of stromal cells to promote cancer cell survival. Next, we’ll explore how cellular interactions in the TME can help cancer cells to overcome amino acid and metabolic limitations. Finally, we’ll study the interactions between cancer cells and immune cells in a mouse genetic model tailored for DualRP.
We recently harnessed ribosome profiling for sensing restrictive amino acids, and developed diricore, a procedure for differential ribosome measurements of codon reading. In this project, we developed and validated Dual Ribosome Profiling (DualRP), a system to study cell interactions in the TME. DualRP is an approach that allows not only simultaneous analysis of gene expression in two interacting cell populations in vivo, but also is able to uncover metabolic limitations in multiple cellular types in tumors by reading selectively the stalling of ribosomes.
In this project, we propose to use dual ribosome profiling (DualRP) and diricore analysis to study cell interactions and metabolic limitations in the tumor microenvironment (TME). First, we propose to study systematically the interactions between breast cancer cells and non-transformed fibroblasts and how therapy affects the response of stromal cells to promote cancer cell survival. Next, we’ll explore how cellular interactions in the TME can help cancer cells to overcome amino acid and metabolic limitations. Finally, we’ll study the interactions between cancer cells and immune cells in a mouse genetic model tailored for DualRP.
My group has developed and refined the DualRP approach in cultured cells as well as in mouse models of breast cancer. First, we genetically engineered breast cancer cells and fibroblasts to endogenously express tagged ribosomes. The tagging is essential to select the ribosomes from distinct cellular populations in heterogeneous co-cultures or tissue. By using DualRP in co-cultured systems, we were able to extract gene expression programs from each interacting population. Importantly, we also could determine metabolic dependencies when the populations grow in limiting concentrations of nutrients. Our findings show that DualRP can be used to discover metabolic limitations in interacting cellular populations.
Next, in order to study multiple cellular populations in vivo, we adapted the DualRP method to mouse genetic models. We used transgenic mice that expressed tagged ribosomes in specific immune cells of the TME. We injected these animals with breast cancer cells expressing a different ribosomal tag. We were also able to extract gene expression information from different cellular compartments in the tumor. More importantly, our approach showed that distinct immune compartments exhibit different metabolic limitations compared to cancer cells.
Next, in order to study multiple cellular populations in vivo, we adapted the DualRP method to mouse genetic models. We used transgenic mice that expressed tagged ribosomes in specific immune cells of the TME. We injected these animals with breast cancer cells expressing a different ribosomal tag. We were also able to extract gene expression information from different cellular compartments in the tumor. More importantly, our approach showed that distinct immune compartments exhibit different metabolic limitations compared to cancer cells.
We developed an approach to uncover metabolic restrictions in the TME by tagging selectively the ribosomes of stromal and cancer cells. Our system has the potential to provide insight into how gene expression and metabolic programs define the interactions between cancer and stromal cells to promote tumor growth and metastasis, identify potential targets for therapeutic intervention, and provide maps of cell interactions in vivo.