Prakrithi, P., Grice, L.F., Zhang, F. et al. (49 more authors) (2025) Integrating 12 Spatial and Single Cell Technologies to Characterise Tumour Neighbourhoods and Cellular Interactions in three Skin Cancer Types. [Preprint - bioRXiv]
Abstract
Cutaneous squamous cell carcinoma (cSCC), basal cell carcinoma (BCC), and melanoma, the three major types of skin cancer, account for over 70% of all cancer cases. Despite their prevalence, the skin cancer microenvironment remains poorly characterized, both in the outer skin layer where the cancer originates and at the deeper junctional and dermal layers into which it progresses. To address this, we integrated 12 complementary spatial single-cell technologies to construct orthogonally-validated cell signatures, spatial maps, and interactomes for cSCC, BCC, and melanoma. We comprehensively compared and integrated these spatial methods and provided practical guidelines on experimental design. Integrating four spatial transcriptomics platforms, we found keratinocyte cancer signatures, including six consistently validated gene markers. Spatial integration of transcriptomics, proteomics, and glycomics uncovered cancer communities enriched in melanocyte–fibroblast–T-cell colocalization with altered tyrosine and pyrimidine metabolism. Ligand-receptor analysis across >700 cell-type combinations and >1.5 million interactions highlighted key roles for CD44, integrins, and collagens, with CD44-FGF2 emerging as a potential therapeutic target. We consistently found differential interactions of melanocytes with fibroblasts and T-cells. We validated these interactions using Opal Polaris, RNAScope, and Proximal Ligation Assay. To integrate population-scale data, genetic association mapping in >500,000 individuals suggested SNPs enriched for spatial domains containing melanocytes, dysplastic keratinocytes, and fibroblasts, shedding light on functional mechanisms linking genetic heritability to cells within cancer tissue. This publicly available multiomics resource offers insights into the initiation and progression of the most lethal skin cancer (melanoma) and the most common forms (cSCC and BCC) and can be explored interactively at https://skincanceratlas.com.
Metadata
Item Type: | Preprint |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license. |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) |
Funding Information: | Funder Grant number Cancer Research UK Supplier No: 138573 c588/A19167 |
Depositing User: | Symplectic Publications |
Date Deposited: | 03 Sep 2025 13:37 |
Last Modified: | 03 Sep 2025 13:37 |
Published Version: | https://www.biorxiv.org/content/10.1101/2025.07.25... |
Identification Number: | 10.1101/2025.07.25.666708 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:231070 |
Download
Filename: integrating 12 Spatial and Single Cell Technologies to Characterise.pdf
Licence: CC-BY-ND 4.0