A robust experimental and computational analysis framework at multiple resolutions, modalities and coverages - Tran, M.; Yoon, S.; Teoh, M.; Andersen, S.; Lam, PY.; Purdue, B. W.; Raghubar, A.; Hanson, SJ.; Devitt, K.; Jones, K.; Walters, S.; Monkman, J.; et al. (Frontiers in Immunology, 2022)
The ability to study cancer-immune cell communication across the whole tumor section without tissue dissociation is needed, especially for cancer immunotherapy development, which requires an understanding of molecular mechanisms and the discovery of more druggable targets. In this work, we assembled and evaluated an integrated experimental framework and analytical process to enable genome-wide scale discovery of ligand-receptors potentially used for cellular crosstalks, followed by targeted validation. We assessed the complementarity of four different technologies single-cell RNA sequencing and Spatial transcriptomic (measuring over >20,000 genes), RNA In Situ Hybridization (RNAscope, measuring 4-12 genes) and Opal Polaris multiplex protein staining (4-9 proteins). To utilise the multimodal data, we implemented existing methods and also developed STRISH (Spatial TRanscriptomic In Situ Hybridization), a computational method that can automatically scan across the whole tissue section for local expression of gene (e.g. RNAscope data) and/or protein markers (e.g. Polaris data) to recapitulate an interaction landscape across the whole tissue. We evaludated the approach to discover and validate cell-cell interaction in situ through in-depth analysis of two types of cancer, basal cell carcinoma and squamous cell carcinoma, which account for over 70% of cancer cases. We showed that inference of cell-cell interactions using scRNA-seq data can misdetect or detect false positive interactions. Spatial transcriptomics still suffers from misdetecting lowly expressed ligand-receptor interactions, but reduced fasle discovery. Both RNAscope and Polaris are sensitive and our STRISH program can statistically detect the pairs ligand-receptor pairs and interaction locations. We expect that the approach described here will be widely applied to discover and validate ligand receptor interaction in different types of solid cancer tumors.