Abstract
High throughput single cell multi-omics platforms, such as mass cytometry (cytometry by time-of-flight; CyTOF), high dimensional imaging (>6 marker; Hyperion, MIBIscope, CODEX, MACSima) and the recently evolved genomic cytometry (Citeseq or REAPseq) have enabled unprecedented insights into many biological and clinical questions, such as hematopoiesis, transplantation, cancer, and autoimmunity. In synergy with constantly adapting new single-cell analysis approaches and subsequent accumulating big data collections from these platforms, whole atlases of cell types and cellular and sub-cellular interaction networks are created. These atlases build an ideal scientific discovery environment for reference and data mining approaches, which often times reveals new cellular disease networks. In this review we will discuss how combinations and fusions of different -omic workflows on a single cell level can be used to examine cellular phenotypes, immune effector functions, and even dynamic changes, such as metabolomic state of different cells in a sample or even in a defined tissue location. We will touch on how pre-print platforms help in optimization and reproducibility of workflows, as well as community outreach. We will also shortly discuss how leveraging single cell multi-omic approaches can be used to accelerate cellular biomarker discovery during clinical trials to predict response to therapy, follow responsive cell types, and define novel druggable target pathways. Single cell proteome approaches already have changed how we explore cellular mechanism in disease and during therapy. Current challenges in the field are how we share these disruptive technologies to the scientific communities while still including new approaches, such as genomic cytometry and single cell metabolomics.
Highlights
Since the early days of cell biology scientists have been using optical instruments to identify cell types in homeostatic conditions and diseases
This study showed for the first time that the frequency of CD14+ CD16− HLA-DRhi monocytes may serve as a prognostic biomarker of progressionfree and overall survival before immunotherapy [20]
This study showed that both anti-CTLA-4 and anti-PD-1 antibodies expand exhausted-like CD8 T cells, and that anti-CTLA-4 antibody modulates an ICOS+ Th1-like CD4 effector subset for engaging exhausted-like CD8 T cells
Summary
Since the early days of cell biology scientists have been using optical instruments to identify cell types in homeostatic conditions and diseases. With the wide introduction of flow cytometry in the early 70-ies markers and subsequent cell types have evolved but it was only in the last decade that the introduction of single cell transcriptome sequencing, high dimensional cytometry and imaging cytometry started revolutionizing the way we interrogate biological samples. Isolation of multiple types of molecules (DNA, RNA, or protein) from a single cell simultaneously, stands at the beginning of each approach and having standardized and validated protocols for single cell solutions is surely the foundation of all the described approaches. In this review article we will recapitulate the highlights of each of these technologies, analysis pipelines and discuss their potential to revolutionize future sample analysis, clinical trial design and redefine clinical research
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