Multimodal single-cell profiling of T cell specificity and reactivity in lung cancer

Abstract

SUMMARYAdoptive transfer of autologous tumor-infiltrating lymphocyte T cells (TILs) offers one of the most promising approaches for cancer immunotherapy. However, high variability in patient responses highlight the need for an enhanced understanding of the transcriptional phenotypes of TILs and reactivity of their T cell receptors (TCR). Here, we employ single-cell multiomics approaches and TCR functional screening to investigate TILs from treatment-naive non-small cell lung cancer patients. This comprehensive analysis integrates scRNA-seq, scTCR-seq, and scATAC-seq, enabling a high-resolution examination of TILs within lung cancer tissue, as well as the adjacent non-tumor tissue. We apply a cellular functional screening platform to identify reactive TCRs that represent >1,000 TILs and have specificity towards a multitude of targets, including primary tumor cells, neoantigens, tumor-associated antigens, and viral antigens. Tumor-reactive TILs were primarily associated with dysfunctional phenotypes, whereas viral antigen-reactive TCRs were found in effector phenotype clusters. Key marker genes were identified and used to construct a tumor or viral reactivity score. Comparing clones shared in tumor and non-tumor tissue, a higher fraction of exhausted cells was observed in the tumor tissue, whereas non-tumor adjacent tissue possessed more effector cells, thus providing insight into potential sources for therapeutic T cells. Elucidating the specific T cell populations within TILs and their associated TCRs may support strategies to enhance the efficacy of TIL-based therapies.Graphical AbstractMultimodal single cell profiling and reactivity testing of TILs(A) CD8+T cells of treatment naive non-small cell lung cancer patients and adjacent lung tissue were isolated by fluorescence-activated cell sorting (FACS) and were then subjected to scRNA-seq + scTCR-seq or scATAC-seq. (B) TCRs were functionally screened using a cellular platform (TnT cells) and target cells (tumor cells, antigen-pulsed antigen-presenting cells, PBMCs) by flow cytometry and deep sequencing. (C) scRNA-seq + scATAC-seq allowed trajectory inference of transcription factors and genes along pseudotime. (D) Gene scores for tumor- and virus-reactivity were developed by combining functional reactivity and transcriptomic profiling for each CD8+T cell. (E) TIL scRNA-seq pre and post IL-2 treatment in tumor suspension displayed as alluvial plot shows change of clonal cell state composition.