T cell receptor-centric perspective to multimodal single-cell data analysis.

Abstract

The T-cell receptor (TCR) carries critical information regarding T-cell functionality. The TCR, despite its importance, is underutilized in single cell transcriptomics, with gene expression (GEx) features solely driving current analysis strategies. Here, we argue for a switch to a TCR-first approach, which would uncover unprecedented insights into T cell and TCR repertoire mechanics. To this end, we curated a large T-cell atlas from 12 prominent human studies, containing in total 500,000 T cells spanning multiple diseases, including melanoma, head-and-neck cancer, T-cell cancer, and lung transplantation. Herein, we identified severe limitations in cell-type annotation using unsupervised approaches and propose a more robust standard using a semi-supervised method or the TCR arrangement. We then showcase the utility of a TCR-first approach through application of the novel STEGO.R tool for the successful identification of hyperexpanded clones to reveal treatment-specific changes. Additionally, a meta-analysis based on neighbor enrichment revealed previously unknown public T-cell clusters with potential antigen-specific properties as well as highlighting additional common TCR arrangements. Therefore, this paradigm shift to a TCR-first with STEGO.R highlights T-cell features often overlooked by conventional GEx-focused methods, and enabled identification of T cell features that have the potential for improvements in immunotherapy and diagnostics. One Sentence SummaryRevamping the interrogation strategies for single-cell data to be centered on T cell receptor (TCR) rather than the generic gene expression improved the capacity to find relevant disease specific TCR. Key PointsO_LIThe TCR-first approach captures dynamic T cell features, even within a clonal population. C_LIO_LIA novel [~]500,000 T-cell atlas to enhance single cell analysis, especially for restricted populations. C_LIO_LINovel STEGO.R program and pipeline allows for consistent and reproducible interrogating of scTCR-seq with GEx. C_LI