Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma

Abstract

Summary To 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.

BayesSpace enables the robust characterization of spatial gene expression architecture in tissue sections at increased resolution

“…We also use BayesSpace to analyze a squamous cell carcinoma (SCC) Visium sample first described by Ji et al 25 . A pathologist annotated the original H&E stained tissue to identify the tumor borders and other major tissue structures ( Figure 4A).…”

“…A pathologist annotated the original H&E stained tissue to identify the tumor borders and other major tissue structures ( Figure 4A). We defined expression profiles for the major cell types present in the sample based on known marker genes from literature: keratinocytes (KRT1, KRT5, KRT10, KRT14), melanocytes (MLANA, DCT, PMEL), myeloid cells (LYZ), and T cells (CD2, CD3D, CD3E, CD3G, CD7) 24,25 . The keratinocytes were further separated into basal keratinocytes (KRT5, KRT14) and suprabasal keratinocytes (KRT1, KRT10) since KRT5 and KRT14 form heterodimers that localize to the basal layer of the epidermis while KRT1 and KRT10 form heterodimers that localize to the suprabasal layer 26 .…”

“…Biopsy 1 contains 293 spots covered by tissue. The final dataset included ten human skin SCCs profiled on either the ST or the Visium platform 25 . Among the two samples run on the Visium platform, we chose to analyze patient 4 (P4) since the data quality was higher as shown in the original paper.…”

Spatial analysis of ligand-receptor interaction in skin cancer at genome-wide and single-cell resolution

“…Only recently, Ji et al generated spatial transcriptomic data on human squamous cell carcinoma (SCC) combining scRNA-seq and multiplexed ion beam imaging analysis. In the study, integration of multi-modal data revealed ligand-receptor (L-R) networks specific to stromal and tumor cells (Ji et al 2020).…”

“…ST-seq has been applied to studies on the landscape of tissues and diseases, such as prostate cancer (Ji et al 2020;Berglund et al 2018), pancreatic cancer (Moncada et al), melanoma (Thrane et al 2018) and allows for mapping the transcripts in the tissue sections. However, STseq still lacks single-cell resolution, and the number of transcriptomes (cell numbers) as well as the read quality that can be captured in each spot depend on the tissue context.…”