Understanding psoriatic disease at single-cell resolution: an update.

Mammalian reproduction requires the fusion of two specialized cells: an oocyte and a sperm. In addition to producing gametes, the reproductive system also provides the environment for the appropriate development of the embryo. Deciphering the reproductive system requires understanding the functions of each cell type and cell-cell interactions. Recent single-cell omics technologies have provided insights into the gene regulatory network in discrete cellular populations of both the male and female reproductive systems. However, these approaches cannot examine how the cellular states of the gametes or embryos are regulated through their interactions with neighboring somatic cells in the native tissue environment owing to tissue disassociations. Emerging spatial omics technologies address this challenge by preserving the spatial context of the cells to be profiled. These technologies hold the potential to revolutionize our understanding of mammalian reproduction. We aim to review the state-of-the-art spatial transcriptomics (ST) technologies with a focus on highlighting the novel biological insights that they have helped to reveal about the mammalian reproductive systems in the context of gametogenesis, embryogenesis, and reproductive pathologies. We also aim to discuss the current challenges of applying ST technologies in reproductive research and provide a sneak peek at what the field of spatial omics can offer for the reproduction community in the years to come. The PubMed database was used in the search for peer-reviewed research articles and reviews using combinations of the following terms: 'spatial omics', 'fertility', 'reproduction', 'gametogenesis', 'embryogenesis', 'reproductive cancer', 'spatial transcriptomics', 'spermatogenesis', 'ovary', 'uterus', 'cervix', 'testis', and other keywords related to the subject area. All relevant publications until April 2023 were critically evaluated and discussed. First, an overview of the ST technologies that have been applied to studying the reproductive systems was provided. The basic design principles and the advantages and limitations of these technologies were discussed and tabulated to serve as a guide for researchers to choose the best-suited technologies for their own research. Second, novel biological insights into mammalian reproduction, especially human reproduction revealed by ST analyses, were comprehensively reviewed. Three major themes were discussed. The first theme focuses on genes with non-random spatial expression patterns with specialized functions in multiple reproductive systems; The second theme centers around functionally interacting cell types which are often found to be spatially clustered in the reproductive tissues; and the thrid theme discusses pathological states in reproductive systems which are often associated with unique cellular microenvironments. Finally, current experimental and computational challenges of applying ST technologies to studying mammalian reproduction were highlighted, and potential solutions to tackle these challenges were provided. Future directions in the development of spatial omics technologies and how they will benefit the field of human reproduction were discussed, including the capture of cellular and tissue dynamics, multi-modal molecular profiling, and spatial characterization of gene perturbations. Like single-cell technologies, spatial omics technologies hold tremendous potential for providing significant and novel insights into mammalian reproduction. Our review summarizes these novel biological insights that ST technologies have provided while shedding light on what is yet to come. Our review provides reproductive biologists and clinicians with a much-needed update on the state of art of ST technologies. It may also facilitate the adoption of cutting-edge spatial technologies in both basic and clinical reproductive research.

Who am I? (re-)Defining fibroblast identity and immunological function in the age of bioinformatics.

Single-cell omics technologies - Fundamentals on how to create single-cell looking glasses for reproductive health.

Single-cell technologies: From research to application

As one of the most advanced technologies, single-cell omics technology develops rapidly in recent years. Based on different technical strategies, it enables unbiased and high-throughput access to multiple omics information at single-cell resolution. So far, single-cell omics technology, by virtue of its great powder in resolving tissue heterogeneity, has become a revolutionary tool to deeply understand the functional structure of tissues, reveal complex disease processes, and elucidate drug mechanisms of action. In view of the technical challenges in deconstructing the complexity of Chinese medicine and clarifying the modern scientific connotation of traditional Chinese medicine(TCM) theory, single-cell omics technology has huge application potential in the discovery of pharmacodynamic substances, construction of action networks, and elucidation of integrated regulatory mechanisms, which brings new opportunities for modern research in TCM. The present study briefly introduced three representative single-cell omics technologies, i.e., single-cell transcriptome sequencing, spatial transcriptomics, and single-cell multimodal omics, and their main application patterns. On this basis, an outlook was proposed on the strategies and applications for modern research in TCM using single-cell omics technology.

Inflammation is intimately involved at all stages of atherosclerosis and remains a substantial residual cardiovascular risk factor in optimally treated patients. The proof of concept that targeting inflammation reduces cardiovascular events in patients with a history of myocardial infarction has highlighted the urgent need to identify new immunotherapies to treat patients with atherosclerotic cardiovascular disease. Importantly, emerging data from new clinical trials show that successful immunotherapies for atherosclerosis need to be tailored to the specific immune alterations in distinct groups of patients. In this Review, we discuss how single-cell technologies — such as single-cell mass cytometry, single-cell RNA sequencing and cellular indexing of transcriptomes and epitopes by sequencing — are ideal for mapping the cellular and molecular composition of human atherosclerotic plaques and how these data can aid in the discovery of new precise immunotherapies. We also argue that single-cell data from studies in humans need to be rigorously validated in relevant experimental models, including rapidly emerging single-cell CRISPR screening technologies and mouse models of atherosclerosis. Finally, we discuss the importance of implementing single-cell immune monitoring tools in early phases of drug development to aid in the precise selection of the target patient population for data-driven translation into randomized clinical trials and the successful translation of new immunotherapies into the clinic.

Photosensitivity is a hallmark of cutaneous lupus erythematosus (CLE) and dermatomyositis (DM), yet the mechanisms linking ultraviolet B (UVB) exposure to tissue-specific autoimmunity remain incompletely defined. Here, we use an integrative human-based approach, including single-cell RNA sequencing, spatial transcriptomics (seqFISH+), in vivo UVB provocation, and in vitro modeling, to uncover a spatially coordinated inflammatory circuit that underlies interferon-I (IFN-I)-amplified skin pathology.We identify MMP9+ CD14+ myeloid cells as central effectors of photosensitivity in both CLE and DM. These cells are markedly expanded in lesional skin, serve as the dominant source of IFN-β, and colocalize with cytotoxic CD4+ T cells at the dermal–epidermal junction. Spatial transcriptomics further reveals a keratinocyte-fibroblast-myeloid axis, wherein keratinocytes activate discrete subsets of pro-inflammatory fibroblasts in the superficial dermis to produce monocyte-attracting chemokines, including CCL2, CCL19, CCL7, CCL8, and CXCL12, directing MMP9+ CD14+ cell recruitment toward the interface.In our in-vitro model, IFN-I-primed basal keratinocytes undergo heightened UVB-induced cell death and release membrane-associated cytokines such as TNF-α, IL-1α, which activate monocyte-derived dendritic cells (moDCs) and induce transcriptional programs mirroring those of MMP9+ CD14+ cells in vivo. In vivo, UVB irradiation of non-lesional DM skin, but not healthy controls, elicits rapid infiltration of these myeloid cells, confirming their disease-specific responsiveness to UVB.Finally, in a proof-of-concept clinical study, treatment with anifrolumab (anti-IFN-I receptor) blocked UVB-induced MMP9+ CD14+ infiltration and attenuated photosensitivity in CLE.Together, these findings define a multicellular inflammatory cascade linking keratinocyte injury, fibroblast chemotactic programming, and myeloid effector function in IFN-I-driven skin autoimmunity and nominate MMP9+ CD14+ cells as actionable targets in photosensitive dermatoses.Photosensitivity is central to cutaneous lupus erythematosus (CLE) and dermatomyositis (DM), but the mechanisms linking UVB exposure to tissue-specific autoimmunity are poorly defined. Using single-cell RNA sequencing, spatial transcriptomics, UVB provocation, and in vitro modeling, we identify MMP9+ CD14+ myeloid cells as critical mediators of photosensitivity. These cells expand significantly in lesional skin, produce IFN-β, and colocalize with cytotoxic CD4+ T cells at the dermal-epidermal junction. Keratinocytes activate fibroblasts in the superficial dermis, prompting them to release chemokines (CCL2, CCL19, CCL7, CCL8, CXCL12) that recruit MMP9+ CD14+ cells. IFN-I-primed keratinocytes exposed to UVB release cytokines activating dendritic cells, mirroring in vivo responses. UVB irradiation of non-lesional DM skin rapidly recruits these myeloid cells. In a clinical proof-of-concept study, anti-IFN-I treatment with anifrolumab prevented UVB-induced myeloid infiltration and reduced photosensitivity. Thus, targeting MMP9+ CD14+ cells may offer therapeutic potential for managing photosensitive autoimmune skin conditions.

IFN-α Enhances Poly-IC Responses in Human Keratinocytes by Inducing Expression of Cytosolic Innate RNA Receptors: Relevance for Psoriasis

Recent advances of single-cell transcriptomics technologies and allied computational methodologies have revolutionized molecular cell biology. Meanwhile, pioneering explorations in spatial transcriptomics have opened up avenues to address fundamental biological questions in health and diseases. Here, we review the technical attributes of single-cell RNA sequencing and spatial transcriptomics, and the core concepts of computational data analysis. We further highlight the challenges in the application of data integration methodologies and the interpretation of the biological context of the findings.

In the last 15 years, single-cell technologies have become robust and indispensable tools to investigate cell heterogeneity. Beyond transcriptomic, genomic and epigenome analyses, technologies are constantly evolving, in particular toward multi-omics, where analyses of different source materials from a single cell are combined, and spatial transcriptomics, where resolution of cellular heterogeneity can be detected in situ. While some of these techniques are still being optimized, single-cell RNAseq has commonly been used because the examination of transcriptomes allows characterization of cell identity and, therefore, unravel previously uncharacterized diversity within cell populations. Most endocrine organs have now been investigated using this technique, and this has given new insights into organ embryonic development, characterization of rare cell types, and disease mechanisms. Here, we highlight recent studies, particularly on the hypothalamus and pituitary, and examine recent findings on the pancreas and reproductive organs where many single-cell experiments have been performed.

Despite recent advances in understanding disease biology, treatment of group 3/4 medulloblastoma remains a therapeutic challenge in paediatric neuro-oncology1. Bulk-omics approaches have identified considerable intertumoural heterogeneity in group 3/4 medulloblastoma, including the presence of clear single-gene oncogenic drivers in only a subset of cases, whereas in most cases, large-scale copy number aberrations prevail2,3. However, intratumoural heterogeneity, the role of oncogene aberrations, and broad copy number variation in tumour evolution and treatment resistance remain poorly understood. To dissect this interplay, we used single-cell technologies (single-nucleus RNA sequencing (snRNA-seq), single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing (snATAC-seq) and spatial transcriptomics) on a cohort of group 3/4 medulloblastoma with known alterations in the oncogenes MYC, MYCN and PRDM6. We show that large-scale chromosomal aberrations are early tumour-initiating events, whereas the single-gene oncogenic events arise late and are typically subclonal, but MYC can become clonal upon disease progression to drive further tumour development and therapy resistance. Spatial transcriptomics shows that the subclones are mostly interspersed across tumour tissue, but clear segregation is also present. Using a population genetics model, we estimate medulloblastoma initiation in the cerebellar unipolar brush cell lineage starting from the first gestational trimester. Our findings demonstrate how single-cell technologies can be applied for early detection and diagnosis of this fatal disease.

In recent years, advancements in single-cell and spatial transcriptomics, which are highly regarded developments in the current era, particularly the emerging integration of single-cell and spatiotemporal transcriptomics, have enabled a detailed molecular comprehension of the complex regulation of cell fate. The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine. Currently, single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors. Starting from the perspective of RNA sequencing technology, this review outlined the significance of single-cell RNA sequencing (scRNA-seq) in prostate cancer research, encompassing preclinical medicine and clinical applications. We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies, as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis, treatment, and drug resistance characteristics of prostate cancer. These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer. Furthermore, we explore the potential clinical applications stemming from other single-cell technologies in this review, paving the way for future research in precision medicine.

Globally, endometrial cancer continues to impact a significant number of women. Immunotherapy provides those suffering from advanced or relapsed disease hope, but an important barrier is still the absence of trustworthy predictive biomarkers. To tackle this challenge, single-cell sequencing and spatial transcriptomics (ST) are increasingly applied. In cervical cancers of the no specific molecular profile (NSMP) subtype accompanied by p53 mutations. In many cases, the tumor microenvironment (TME) in endometrial cancer exhibits strong immunosuppression or poor immune cell infiltration, often leading to worse clinical outcomes. Single-cell sequencing reveals cellular heterogeneity and helps identify potential therapeutic targets and predict treatment responses. Conversely, ST assists in determining biomarkers that influence the effectiveness of immunotherapy by capturing the spatial organization of tumors. When combined, these technologies allow for integrated multi-omics analysis that aids in the development of immunotherapies, prognostication, and diagnosis. But there are still moral and legal issues. Clinicians may be able to improve outcomes for patients who don't respond well to current immunotherapies by utilizing these combined approaches.

Integrating single-cell RNA sequencing and spatial transcriptomics is the current imperative to manually explore the landscape of cellular mixtures. Herein, we developed CellMap (https://github.com/liuhong-jia/CellMap), a computational tool that allows spatial transcriptomic spots to be resolved at single-cell resolution. CellMap combines strategies that incorporate the co-linearity of seed genes, the random forest model, and the linear assignment algorithm to achieve optimal assignment of single cells to spatial spots. Using comprehensive benchmarking across various platforms and tissue types, we demonstrated that CellMap outperforms existing methods.

Background: Effective cancer immunotherapy is significantly affected by intratumoral heterogeneity, not only in different cell types and functions but also in the spatial pattern of immune cells within the tumor tissue. While most single-cell RNA sequencing technologies could enable the exploration of gene expression heterogeneity at the single-cell level, they cannot reveal spatial information within the tumor for us to map the whole transcriptome with morphological context. Spatial transcriptomics is an in situ capturing technique, which profiles gene expression at the RNA level, whilst preserving the spatial information of histological tissue sections. Thus we try to develop our spatial transcriptomics assay through a serial of validation experiments and to explore the mechanism of immune therapy against tumors. Material and Method: Firstly, the tumor was frozen and sections were cryosectioned at 10 μm thickness. Sections processing including H&E staining, tissue optimization, permeabilization, reverse transcription, and cDNA library preparation was carried out following the user guide of Visium Spatial Gene Expression Reagent Kits (10X Genomics). And the final cDNA libraries were sequenced using the Illumina Novaseq instrument. Using gene expression matrix and aligned H&E image processed by Cell Ranger and Loupe Browser with default parameters, we performed data QC, normalization, dimensionality reduction, and clustering by Seurat and cell components identification in tumor microenvironment based on a multistep approach. Differential gene expression and spatial heterogeneity were analyzed in each cluster. Results: Here we established a reliable system for spatial transcriptomics assay to elucidate the mechanism of anti-PD1 treatment in MC38 syngeneic colorectal tumor. Using this system, we constructed the gene expression spatial patterns of tumor cells and immune cells, including periphery and center of tumor cell, immune-cell enrichment area, and tumor cell surrounding the immune cell. Furthermore, we explored the cell-cell interactions in which the tumor cells directly interact with adjacent non-tumor cells, for example, macrophages. Using this system, we tried to investigate the mechanism of anti-PD-1 therapy against the tumors by comparing the spatial transcriptome profiles after the treatment with anti-PD-1 or isotype control in colorectal cancer models. Interestingly, changes in both gene-level and spatial levels were observed, and it will help reveal how the immune therapy may shake up the complex ecosystem. Summary: We established a reliable system for spatial transcriptomics analysis and explored the mechanism of anti-PD-1 treatment against the colorectal cancer by using this system. Citation Format: Panpan Wang, Huacheng He, Qiyao Zhang, Jingjing Wang, Dan Lu, Fei Duan, Qiangqiang Fan, Qingyang Gu, Qunsheng Ji. Establishment of spatial transcriptomics assay to study the mechanism of immune therapy against tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6128.