Into the multi-omics era: Progress of T cells profiling in the context of solid organ transplantation

Abstract

T cells are the common type of lymphocyte to mediate allograft rejection, remaining long-term allograft survival impeditive. However, the heterogeneity of T cells, in terms of differentiation and activation status, the effector function, and highly diverse T cell receptors (TCRs) have thus precluded us from tracking these T cells and thereby comprehending their fate in recipients due to the limitations of traditional detection approaches. Recently, with the widespread development of single-cell techniques, the identification and characterization of T cells have been performed at single-cell resolution, which has contributed to a deeper comprehension of T cell heterogeneity by relevant detections in a single cell – such as gene expression, DNA methylation, chromatin accessibility, surface proteins, and TCR. Although these approaches can provide valuable insights into an individual cell independently, a comprehensive understanding can be obtained when applied joint analysis. Multi-omics techniques have been implemented in characterizing T cells in health and disease, including transplantation. This review focuses on the thesis, challenges, and advances in these technologies and highlights their application to the study of alloreactive T cells to improve the understanding of T cell heterogeneity in solid organ transplantation.

Applications of single‐cell omics for chimeric antigen receptor T cell therapy

“…Single‐cell omics analyses have a generally similar workflow: single‐cell isolation, extraction and amplification of the desired biological molecule or sequence, construction of sequencing libraries and sequencing, and finally bioinformatic data analysis. A joint analysis of two or more of cell biological molecules is called multi‐omics [27]. Single‐cell analysis can be geared towards CAR T cell products, TME or any other tissue involved in the treatment process, and the data can be used in different scenarios, such as finding a correlation with treatment outcome, designing atlases of tumour or CAR T cells or their molecular alterations, and so forth.…”