Th47 - Single Cell and Spatially Resolved Analysis of Tissues by Integrated RNA and Protein Multi-omics Identifies Novel Tumour-infiltrating Lymphocyte Phenotypes

The development of single-cell methods to incorporate detection of cellular protein epitopes via barcoded antibodies has enabled advances in immunophenotyping but its application to investigating tissue immunology is limited. Here we present an optimised experimental and analytical framework for the phenotyping of human tissues by integrated transcriptome and barcoded antibody clustering analysis of single cell suspensions and tissue sections. Using a dataset of 6 breast cancer patients, we demonstrate how the integration of proteomic data with RNA enhances cellular stratification across cell types within the tumour microenvironment, leading to the identification of unique clinically relevant lymphocyte subsets. We characterise tumour-infiltrating lymphocyte subsets indistinguishable by transcriptomics alone. We reveal patterns of RNA and protein co-expression across lymphocytes, identifying new protein markers of resting and activated tissue resident lymphocytes including innate lymphoid cells, T cells and NK cells. We characterise a CD4 Tfh subset previously not described in breast tissues, one associated with markers of tissue residency and exhaustion, found to be strongly associated with prognosis and response to checkpoint immunotherapy across multiple cancers. We further investigate these phenotypes spatially, developing Spatial Indexing of Transcriptomes and Epitopes (SITE-Seq), a method for spatially resolved joint transcriptome and epitope analysis of snap frozen tissues using a modified 10X Visium protocol. We show that the integration of RNA and protein resolves immune subsets at higher resolution than either modality alone. This work highlights the importance of multi-omic methods for the phenotyping of cell states and the emergence of novel cellular states in the tumour microenvironment.