Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell CarcinomaTo define the cellular composition and architecture of cutaneous squamous cell carcinoma (cSCC), we combined single-cell RNA sequencing with spatial transcriptomics and multiplexed ion beam imaging from a series of human cSCCs and matched normal skin. cSCC exhibited four tumor subpopulations, three recapitulating normal epidermal states, and a tumor-specific keratinocyte (TSK) population unique to cancer, which localized to a fibrovascular niche. Integration of single-cell and spatial data mapped ligand-receptor networks to specific cell types, revealing TSK cells as a hub for intercellular communication. Multiple features of potential immunosuppression were observed, including T regulatory cell (Treg) co-localization with CD8 T cells in compartmentalized tumor stroma. Finally, single-cell characterization of human tumor xenografts and in vivo CRISPR screens identified essential roles for specific tumor subpopulation-enriched gene networks in tumorigenesis. These data define cSCC tumor and stromal cell subpopulations, the spatial niches where they interact, and the communicating gene networks that they engage in cancer.
Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma(Cell 182, 497–514.e1–e22; July 23, 2020) As a result of human error, the spatial feature plot labeled ITGB1 in Figure 6G was instead a duplicate of the ITGA3 data just below it. Additionally, in Figure S4C, the order of some of the bar labels on the plot were swapped, in particular, the order of Treg, CD4+ Naïve, NK, and CD8+ Naive. Both figures have been corrected online. We are confident that these inadvertent panel duplication and labeling errors did not have any effect on our analyses or on any conclusions drawn from the paper, and we apologize for the errors.Figure 6GCellular Crosstalk Landscape Associated with Leading Edge Niches (original)View Large Image Figure ViewerDownload Hi-res image Download (PPT)Figure S4CT Cell Subset Characterization and Spatial Positioning (corrected)View Large Image Figure ViewerDownload Hi-res image Download (PPT)Figure S4CT Cell Subset Characterization and Spatial Positioning (original)View Large Image Figure ViewerDownload Hi-res image Download (PPT) Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell CarcinomaJi et al.CellJune 23, 2020In BriefIntegration of high-dimensional multi-omics approaches to characterize human cutaneous squamous cell carcinoma identifies a tumor-specific keratinocyte population as well as the immune infiltrates and heterogeneity at tumor leading edges. Full-Text PDF Open Access
Combined protein and nucleic acid imaging reveals virus-dependent B cell and macrophage immunosuppression of tissue microenvironmentsUnderstanding the mechanisms of HIV tissue persistence necessitates the ability to visualize tissue microenvironments where infected cells reside; however, technological barriers limit our ability to dissect the cellular components of these HIV reservoirs. Here, we developed protein and nucleic acid in situ imaging (PANINI) to simultaneously quantify DNA, RNA, and protein levels within these tissue compartments. By coupling PANINI with multiplexed ion beam imaging (MIBI), we measured over 30 parameters simultaneously across archival lymphoid tissues from healthy or simian immunodeficiency virus (SIV)-infected nonhuman primates. PANINI enabled the spatial dissection of cellular phenotypes, functional markers, and viral events resulting from infection. SIV infection induced IL-10 expression in lymphoid B cells, which correlated with local macrophage M2 polarization. This highlights a potential viral mechanism for conditioning an immunosuppressive tissue environment for virion production. The spatial multimodal framework here can be extended to decipher tissue responses in other infectious diseases and tumor biology.
Subcellular localization of biomolecules and drug distribution by high-definition ion beam imagingXavier Rovira‐Clavé, Sizun Jiang, Yun Bai et al.|Nature Communications|2021 Simultaneous visualization of the relationship between multiple biomolecules and their ligands or small molecules at the nanometer scale in cells will enable greater understanding of how biological processes operate. We present here high-definition multiplex ion beam imaging (HD-MIBI), a secondary ion mass spectrometry approach capable of high-parameter imaging in 3D of targeted biological entities and exogenously added structurally-unmodified small molecules. With this technology, the atomic constituents of the biomolecules themselves can be used in our system as the "tag" and we demonstrate measurements down to ~30 nm lateral resolution. We correlated the subcellular localization of the chemotherapy drug cisplatin simultaneously with five subnuclear structures. Cisplatin was preferentially enriched in nuclear speckles and excluded from closed-chromatin regions, indicative of a role for cisplatin in active regions of chromatin. Unexpectedly, cells surviving multi-drug treatment with cisplatin and the BET inhibitor JQ1 demonstrated near total cisplatin exclusion from the nucleus, suggesting that selective subcellular drug relocalization may modulate resistance to this important chemotherapeutic treatment. Multiplexed high-resolution imaging techniques, such as HD-MIBI, will enable studies of biomolecules and drug distributions in biologically relevant subcellular microenvironments by visualizing the processes themselves in concert, rather than inferring mechanism through surrogate analyses.
Adjacent Cell Marker Lateral Spillover Compensation and Reinforcement for Multiplexed ImagesYunhao Bai, Bokai Zhu, Xavier Rovira‐Clavé et al.|Frontiers in Immunology|2021 Multiplex imaging technologies are now routinely capable of measuring more than 40 antibody-labeled parameters in single cells. However, lateral spillage of signals in densely packed tissues presents an obstacle to the assignment of high-dimensional spatial features to individual cells for accurate cell-type annotation. We devised a method to correct for lateral spillage of cell surface markers between adjacent cells termed REinforcement Dynamic Spillover EliminAtion (REDSEA). The use of REDSEA decreased contaminating signals from neighboring cells. It improved the recovery of marker signals across both isotopic (i.e., Multiplexed Ion Beam Imaging) and immunofluorescent (i.e., Cyclic Immunofluorescence) multiplexed images resulting in a marked improvement in cell-type classification.