GSE159709
Spatially resolved transcriptomics reveals the architecture of the tumor-microenvironment interface
Cancer cells interact with a wide variety of other cell types, but our understanding of microenvironmental heterogeneity and how it influences tumor phenotypes is limited. While single-cell RNA-seq (scRNA-seq) has helped define these TME cell types, it provides limited information on the mechanisms that define how individual tumor cells interact with TME. Here, we integrate spatial transcriptomics with scRNA-seq to define the architecture and nature of nascent tumor and surrounding microenvironment cells as they come into contact through the process of invasion. Using a well-defined transgenic zebrafish model of BRAFV600E-driven melanoma, we identify a transcriptionally unique “interface” cluster localized at the boundary between tumor cells and surrounding tissues. Using an unbiased, data-driven approach, we identify spatially-patterned gene modules specific to the interface and show that the interface is a distinct transcriptional entity that histologically resembles the microenvironment but transcriptionally resembles the tumor. By complementing ST with scRNA-seq, we demonstrate that the interface is composed of specialized tumor and microenvironment cells. Both cell types in the interface upregulate a common set of cilia genes, and we find enrichment of cilia proteins only where the tumor meets the TME. Cilia gene expression is regulated by ETS-family transcription factors, which normally act to suppress their expression outside of this region. This unique ETS-driven interface transcriptional state is conserved across ten different human patient samples, suggesting this is a conserved feature of human melanoma. Taken together, our results demonstrate the power of spatial and single-cell transcriptomics techniques in uncovering novel biological mechanisms that drive tumor invasion into new tissues.  Overall design: Spatial transcriptomics (Visium platform) of zebrafish bearing BRAF-V600E driven melanomas. Single-cell RNA-seq (10X Genomics v3) of two such zebrafish. Single-nucleus RNA-seq (10X Genomics v3) of three such zebrafish (pooled into one reaction).