“…4d-e ). This is in line with recent work showing that melanomas can reprogram microenvironmental cells such as liver cells even when not in physical contact 8 . However, similar to our scRNA-seq and SRT datasets, there were many genes that were specifically upregulated across the interface subclusters that were not upregulated in any other cell type in the snRNA-seq dataset, further suggesting that the “interface” cell state is a distinct transcriptional entity ( Fig.…”
Section: Resultssupporting
confidence: 91%
“…This uncertainty is compounded by the fact that tumor cells themselves are highly heterogeneous 7 , making it challenging to determine which subset of tumor cells are directly interacting with surrounding non-tumor cells. The macroenvironment may also influence tumor progression, since the tumor cells can interact with other cells in the body at a distance, as recently demonstrated for metabolic coupling between melanoma cells and distant cells in the liver 8 .…”
During tumor progression, cancer cells come into contact with new cell types in the microenvironment, but it is unclear how tumor cells adapt to new environments. Here, we integrate spatial transcriptomics and scRNA-seq to characterize tumor/microenvironment interactions during the initial steps of invasion. Using a zebrafish model of melanoma, we identify a unique "interface" cell state at the tumor/microenvironment boundary. This interface is composed of specialized tumor and microenvironment cells that upregulate a common set of cilia genes, and cilia proteins are enriched only where the tumor contacts the microenvironment. Cilia gene expression is regulated by ETS-family transcription factors, which normally act to suppress cilia genes outside of the interface. An ETS-driven interface is conserved across ten patient samples, suggesting it is a conserved feature of human melanoma. Our results demonstrate the power of spatial transcriptomic approaches in uncovering mechanisms that allow tumors to invade into the microenvironment.
“…4d-e ). This is in line with recent work showing that melanomas can reprogram microenvironmental cells such as liver cells even when not in physical contact 8 . However, similar to our scRNA-seq and SRT datasets, there were many genes that were specifically upregulated across the interface subclusters that were not upregulated in any other cell type in the snRNA-seq dataset, further suggesting that the “interface” cell state is a distinct transcriptional entity ( Fig.…”
Section: Resultssupporting
confidence: 91%
“…This uncertainty is compounded by the fact that tumor cells themselves are highly heterogeneous 7 , making it challenging to determine which subset of tumor cells are directly interacting with surrounding non-tumor cells. The macroenvironment may also influence tumor progression, since the tumor cells can interact with other cells in the body at a distance, as recently demonstrated for metabolic coupling between melanoma cells and distant cells in the liver 8 .…”
During tumor progression, cancer cells come into contact with new cell types in the microenvironment, but it is unclear how tumor cells adapt to new environments. Here, we integrate spatial transcriptomics and scRNA-seq to characterize tumor/microenvironment interactions during the initial steps of invasion. Using a zebrafish model of melanoma, we identify a unique "interface" cell state at the tumor/microenvironment boundary. This interface is composed of specialized tumor and microenvironment cells that upregulate a common set of cilia genes, and cilia proteins are enriched only where the tumor contacts the microenvironment. Cilia gene expression is regulated by ETS-family transcription factors, which normally act to suppress cilia genes outside of the interface. An ETS-driven interface is conserved across ten patient samples, suggesting it is a conserved feature of human melanoma. Our results demonstrate the power of spatial transcriptomic approaches in uncovering mechanisms that allow tumors to invade into the microenvironment.
“…14 ) suggest that the interface is not solely restricted to tumor and muscle, but that other cell types may also be reprogrammed to adopt this cell state, such as immune cells or liver cells. Recent work has suggested that in melanoma, tumor cells can reprogram microenvironment cells such as liver cells at a distance 8 . It is not clear yet whether direct physical contact between tumor/microenvironment cells is required to induce an interface-like cell state, or whether longer-range signaling mechanisms may also be at play, but determining the nature of these tumor–microenvironment interactions (whether metabolic or epigenetic) is an exciting area for future mechanistic study.…”
During tumor progression, cancer cells come into contact with various non-tumor cell types, but it is unclear how tumors adapt to these new environments. Here, we integrate spatially resolved transcriptomics, single-cell RNA-seq, and single-nucleus RNA-seq to characterize tumor-microenvironment interactions at the tumor boundary. Using a zebrafish model of melanoma, we identify a distinct “interface” cell state where the tumor contacts neighboring tissues. This interface is composed of specialized tumor and microenvironment cells that upregulate a common set of cilia genes, and cilia proteins are enriched only where the tumor contacts the microenvironment. Cilia gene expression is regulated by ETS-family transcription factors, which normally act to suppress cilia genes outside of the interface. A cilia-enriched interface is conserved in human patient samples, suggesting it is a conserved feature of human melanoma. Our results demonstrate the power of spatially resolved transcriptomics in uncovering mechanisms that allow tumors to adapt to new environments.
“… 27 It is believed that there are more glucose and amino acids in tumor tissue for its rapid proliferation, and gluconic acid and α-keto acid are their oxidation products, which are conducive to reducing pH value. 28 , 29 The catalytic mechanism is shown in Figure 2 . Figure 2 Mechanism diagram of promoting pH reduction by using of catalytic enzymes.…”
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