Integrating 12 Spatial and Single Cell Technologies to Characterise Tumour Neighbourhoods and Cellular Interactions in three Skin Cancer Types

Prakrithi, P.; Grice, L. F.; Zhang, F.; Hockey, L.; Tan, S. X.; Tan, X.; Xiong, Z.; Mulay, O.; Causer, A.; Newman, A.; Pham, D.; Ni, G.; Tuong, K.; Jin, X.; Kim, E.; Tran, M.; Vu, H.; Muller, N. M.; Killingbeck, E. E.; Gregory, M. T.; Teoh, S. M.; Vo, T.; Zhang, M.; Landi, M. T.; Brown, K. M.; Iles, M. M.; Reitz, Z.; Devitt, K.; Pan, L.; Kulasinghe, A.; Kao, Y.-C.; Leon, M.; Murphy, S. R.; Sato, H.; Cruz, J. G.; Kumari, S.; Luu, H. N.; Warren, S. E.; McMillan, C.; Henricson, J.; Anderson, C.; Muller, D.; Everest-Dass, A.; O'Brien, B.; Seviiri, M.; Law, M. H.; Soyer, H. P.; Frazer, I.; Kim, Y.

doi:10.1101/2025.07.25.666708

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bioRxiv · 10.1101/2025.07.25.666708

Integrating 12 Spatial and Single Cell Technologies to Characterise Tumour Neighbourhoods and Cellular Interactions in three Skin Cancer Types

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Abstract

Cutaneous squamous cell carcinoma (cSCC), basal cell carcinoma (BCC), and melanoma - the three major skin cancers - collectively comprise over 70% of all cancer cases. Despite their prevalence, much understanding of cellular interactions in the skin cancer microenvironment is needed, 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 gap, we integrated 12 complementary spatial and single-cell technologies to generate orthogonally-validated cell signatures, spatial maps, and interactomes for cSCC, BCC, and melanoma. Through comprehensive comparisons and integrating these spatial methods, we provided practical benchmarking guidelines for experimental design and analysis. By identifying keratinocyte cancer cells and melanomas, we found distinct signatures of these cells compared to non-cancer keratinocytes and melanocytes. Spatial integration of transcriptomics, proteomics and glycomics uncovered cancer niches enriched for cancer initiating cells (melanocytes or keratinocytes) and fibroblast and T-cell (MKFT) clusters, 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. Consistently, melanoma showed strong MFT interactions, validated by Opal Polaris, RNAScope, Proximal Ligation Assay and two additional single-cell spatial platforms (making a total of 14 technologies). For population-scale generalisation, genetic associations from >500,000 individuals were mapped onto spatial skin tissues, identifying SNPs enriched in domains containing melanocytes and T cells and their ligand-receptor pairs, shedding light on functional mechanisms linking genetic heritability to cells within cancer tissue. We built an interactive multiomics resource for exploring spatially-resolved molecular signatures and cellular crosstalk in skin cancer, available at https://skincanceratlas.com.

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Prakrithi, P., Grice, L. F., Zhang, F., Hockey, L., Tan, S. X., Tan, X., Xiong, Z., Mulay, O., Causer, A., Newman, A., Pham, D., Ni, G., Tuong, K., Jin, X., Kim, E., Tran, M., Vu, H., Muller, N. M., Killingbeck, E. E., Gregory, M. T., Teoh, S. M., Vo, T., Zhang, M., Landi, M. T., Brown, K. M., Iles, M. M., Reitz, Z., Devitt, K., Pan, L., Kulasinghe, A., Kao, Y.-C., Leon, M., Murphy, S. R., Sato, H., Cruz, J. G., Kumari, S., Luu, H. N., Warren, S. E., McMillan, C., Henricson, J., Anderson, C., Muller, D., Everest-Dass, A., O'Brien, B., Seviiri, M., Law, M. H., Soyer, H. P., Frazer, I., Kim, Y.. 2025-07-28. Integrating 12 Spatial and Single Cell Technologies to Characterise Tumour Neighbourhoods and Cellular Interactions in three Skin Cancer Types. https://doi.org/10.1101/2025.07.25.666708

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