Spatially resolved transcriptomics reveals the architecture of the tumor-microenvironment interface(Dataset ID: STDS0000086)

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Spots: 7,281
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Genes: 32,268
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PMID: 34725363
Summary
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Dataset information
Summary:
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).
Technology:
10x Visium
Platform:
GPL20828, GPL24995
Species:
Danio rerio(GRCz10.88)
Tissues:
Skin
Disease:
Cancer
Submission date: 2020-10-20Update date: 2021-09-23
DOI: To be continue
Contributors
Reuben Moncada,Miranda V Hunter
Contact: hunterm@mskcc.org
Accessions
GEO Series Accessions: GSE159709
How to cite
  • Cite database of STOmicsDB:
    [1] Xu, Zhicheng et al. "STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysis and visualization." Nucleic acids research vol. 52,D1 (2024): D1053-D1061. doi: 10.1093/nar/gkad933'
  • Cite visualization dataset:
    [2] Reuben Moncada,Miranda V Hunter. Spatially resolved transcriptomics reveals the architecture of the tumor-microenvironment interface[DS/OL]. STOmicsDB, 2020[2020-10-20]. https://db.cngb.org/stomics/datasets/STDS0000086/. doi: xxxxxx
    #Format: {contributors}. {title}[DS/OL]. STOmicsDB, {the year of submission data}[{submission data}]. {dataset link}. doi: {doi ID}
  • Cite original data article:
    Citation: Hunter, Miranda V et al. “Spatially resolved transcriptomics reveals the architecture of the tumor-microenvironment interface.” Nature communications vol. 12,1 6278. 1 Nov. 2021, doi:10.1038/s41467-021-26614-z