Challenges and Opportunities for the Translation of Single-Cell RNA Sequencing Technologies to Dermatology

Skin in the game: a review of single-cell and spatial transcriptomics in dermatological research

Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) are two emerging research technologies that uniquely characterize gene expression microenvironments on a cellular or subcellular level. The skin, a clinically accessible tissue composed of diverse, essential cell populations, serves as an ideal target for these high-resolution investigative approaches. Using these tools, researchers are assembling a compendium of data and discoveries in healthy skin as well as a range of dermatologic pathophysiologies, including atopic dermatitis, psoriasis, and cutaneous malignancies. The ongoing advancement of single-cell approaches, coupled with anticipated decreases in cost with increased adoption, will reshape dermatologic research, profoundly influencing disease characterization, prognosis, and ultimately clinical practice.

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

Chimeric antigen receptor (CAR) T cell therapy is a promising cancer treatment modality. The breakthroughs in CAR T cell therapy were, in part, possible with the help of cell analysis methods, such as single-cell analysis. Bulk analyses have provided invaluable information regarding the complex molecular dynamics of CAR T cells, but their results are an average of thousands of signals in CAR T or tumour cells. Since cancer is a heterogeneous disease where each minute detail of a subclone could change the outcome of the treatment, single-cell analysis could prove to be a powerful instrument in deciphering the secrets of tumour microenvironment for cancer immunotherapy. With the recent studies in all aspects of adoptive cell therapy making use of single-cell analysis, a comprehensive review of the recent preclinical and clinical findings in CAR T cell therapy was needed. Here, we categorized and summarized the key points of the studies in which single-cell analysis provided insights into the genomics, epigenomics, transcriptomics and proteomics as well as their respective multi-omics of CAR T cell therapy.

Identification of diagnostic molecules and potential therapeutic agents for atopic dermatitis by single-cell RNA sequencing combined with a systematic computing framework that integrates network pharmacology

Atopic dermatitis (AD) is composed of highly flexible cellular participants. To better understand its pathobiology and molecular regulation mechanisms, it is necessary to combine single-cell RNA sequencing (scRNA-seq) with new computing frameworks or specific technologies, which may contribute to the development of better treatments for AD. The scRNA-seq data of GSE180885 and bulk RNA-seq data of GSE193309 were obtained from Gene Expression Omnibus (GEO) database, and the scRNA-seq data was analyzed by Seurat package to identify the cell types in AD. The genes related to the activity of AD topical drugs were obtained from the ChEMBL database, which provided a variety of bioactivity data such as multiple drugs and targets. AD-related genes were obtained from DisGeNET and CTD databases synthesizing human disease-related genes; the intersection of AD-related genes from these three sources with differentially expressed genes (DEGs) between non-diseased AD and normal human skin (NHS) samples and differential cell type marker genes was taken. The proximity analysis of drug gene network was performed based on the gene with the largest area of receiver operating characteristic (ROC) curve. Ten distinct cell types of AD and NHS were identified, except for phagocytes cells. Three hub genes, F10 and CALCRL and CTSB, were obtained. The area under the curve of ROC based on CTSB expression was the largest, which was 60.15%. By binding drug CTSB-related gene interaction network, we identified 145 potential drugs. Among them, the score of DB07045 and CTSB docking was the lowest, and molecular docking and molecular dynamics (MD) simulation confirmed the close and stable binding of DB07045 and cathepsin B. This work identified diagnostic molecules and potential therapeutic drugs of AD by scRNA-seq combined with a systematic computing framework of network pharmacology, which may provide valuable clues for drug design.

The imbalance between Type 17 T-cells and regulatory immune cell subsets in psoriasis vulgaris

Psoriasis vulgaris is a common inflammatory disease affecting 7.5 million adults just in the US. Previously, psoriasis immunopathogenesis has been viewed as the imbalance between CD4⁺ T-helper 17 (Th17) cells and regulatory T-cells (Tregs). However, current paradigms are rapidly evolving as new technologies to study immune cell subsets in the skin have been advanced. For example, recently minted single-cell RNA sequencing technology has provided the opportunity to compare highly differing transcriptomes of Type 17 T-cell (T17 cell) subsets depending on IL-17A vs. IL-17F expression. The expression of regulatory cytokines in T17 cell subsets provided evidence of T-cell plasticity between T17 cells and regulatory T-cells (Tregs) in humans. In addition to Tregs, other types of regulatory cells in the skin have been elucidated, including type 1 regulatory T-cells (Tr1 cells) and regulatory dendritic cells. More recently, investigators are attempting to apply single-cell technologies to clinical trials of biologics to test if monoclonal blockade of pathogenic T-cells will induce expansion of regulatory immune cell subsets involved in skin homeostasis.

Activation of the NFκB signaling pathway in IL6+CSF3+ vascular endothelial cells promotes the formation of keloids

Background: Keloid is a disease caused by abnormal proliferation of skin fibres, the causative mechanism of which remains unclear.

Method: In this study, endothelial cells of keloids were studied using scRNAseq combined with bulk-RNAseq data from keloids. The master regulators driving keloid development were identified by transcription factor enrichment analysis. The pattern of changes in vascular endothelial cells during keloid development was explored by inferring endothelial cell differentiation trajectories. Deconvolution of bulkRNAseq by CIBERSORTX verified the pattern of keloidogenesis. Immunohistochemistry for verification of the lesion process in keloid endothelial cells.

Results: The endothelial cells of keloids consist of four main cell populations (MMP1+ Endo0, FOS + JUN + Endo1, IL6+CSF3+Endo2, CXCL12 + Endo3). Endo3 is an endothelial progenitor cell, Endo1 is an endothelial cell in the resting state, Endo2 is an endothelial cell in the activated state and Endo0 is an endothelial cell in the terminally differentiated state. Activation of the NFΚB signaling pathway is a typical feature of Endo2 and represents the early skin state of keloids.

Conclusion: We have identified patterns of vascular endothelial cell lesions during keloidogenesis and development, and have found that activation of the NFΚB signaling pathway is an essential feature of keloid formation. These findings are expected to contribute to the understanding of the pathogenesis of keloids and to the development of new targeted therapeutic agents for the lesional characteristics of vascular endothelial cells.