Interleukin-33-activated neuropeptide CGRP-producing memory Th2 cells cooperate with somatosensory neurons to induce conjunctival itch.

Allergic conjunctivitis is a chronic inflammatory disease that is characterized by severe itch in the conjunctiva, but how neuro-immune interactions shape the pathogenesis of severe itch remains unclear. We identified a subset of memory-type pathogenic Th2 cells that preferentially expressed Il1rl1-encoding ST2 and Calca-encoding calcitonin-gene-related peptide (CGRP) in the inflammatory conjunctiva using a single-cell analysis. The IL-33-ST2 axis in memory Th2 cells controlled the axonal elongation of the peripheral sensory C-fiber and the induction of severe itch. Pharmacological blockade and genetic deletion of CGRP signaling in vivo attenuated scratching behavior. The analysis of giant papillae from patients with severe allergic conjunctivitis revealed ectopic lymphoid structure formation with the accumulation of IL-33-producing epithelial cells and CGRP-producing pathogenic CD4+ T cells accompanied by peripheral nerve elongation. Thus, the IL-33-ST2-CGRP axis directs severe itch with neuro-reconstruction in the inflammatory conjunctiva and is a potential therapeutic target for severe itch in allergic conjunctivitis.

SELF-Former: multi-scale gene filtration transformer for single-cell spatial reconstruction.

The spatial reconstruction of single-cell RNA sequencing (scRNA-seq) data into spatial transcriptomics (ST) is a rapidly evolving field that addresses the significant challenge of aligning gene expression profiles to their spatial origins within tissues. This task is complicated by the inherent batch effects and the need for precise gene expression characterization to accurately reflect spatial information. To address these challenges, we developed SELF-Former, a transformer-based framework that utilizes multi-scale structures to learn gene representations, while designing spatial correlation constraints for the reconstruction of corresponding ST data. SELF-Former excels in recovering the spatial information of ST data and effectively mitigates batch effects between scRNA-seq and ST data. A novel aspect of SELF-Former is the introduction of a gene filtration module, which significantly enhances the spatial reconstruction task by selecting genes that are crucial for accurate spatial positioning and reconstruction. The superior performance and effectiveness of SELF-Former's modules have been validated across four benchmark datasets, establishing it as a robust and effective method for spatial reconstruction tasks. SELF-Former demonstrates its capability to extract meaningful gene expression information from scRNA-seq data and accurately map it to the spatial context of real ST data. Our method represents a significant advancement in the field, offering a reliable approach for spatial reconstruction.

Defining the activity of pro-reparative extracellular vesicles in wound healing based on miRNA payloads and cell type-specific lineage mapping.

Small extracellular vesicles (EVs) are released by cells and deliver biologically active payloads to coordinate the response of multiple cell types in cutaneous wound healing. Here we used a cutaneous injury model as a donor of pro-reparative EVs to treat recipient diabetic obese mice, a model of impaired wound healing. We established a functional screen for microRNAs (miRNAs) that increased the pro-reparative activity of EVs and identified a down-regulation of miR-425-5p in EVs in vivo and in vitro associated with the regulation of adiponectin. We tested a cell type-specific reporter of a tetraspanin CD9 fusion with GFP to lineage map the release of EVs from macrophages in the wound bed, based on the expression of miR-425-5p in macrophage-derived EVs and the abundance of macrophages in EV donor sites. Analysis of different promoters demonstrated that EV release under the control of a macrophage-specific promoter was most abundant and that these EVs were internalized by dermal fibroblasts. These findings suggested that pro-reparative EVs deliver miRNAs, such as miR-425-5p, that stimulate the expression of adiponectin that has insulin-sensitizing properties. We propose that EVs promote intercellular signaling between cell layers in the skin to resolve inflammation, induce proliferation of basal keratinocytes, and accelerate wound closure.

Single-cell RNA-seq with spatial transcriptomics to create an atlas of human diabetic kidney disease.

Diabetic kidney disease (DKD) develops in ~40% of patients with diabetes and is the leading cause of chronic kidney disease worldwide. We used single-cell RNA-sequencing and spatial transcriptomic analyses of kidney specimens from patients with DKD. Unsupervised clustering revealed distinct cell clusters, including epithelial cells and fibroblasts. We also identified differentially expressed genes (DEGs) and assessed enrichment, and cell-cell interactions. Specific enrichment of DKD was evident in venous endothelial cells (VECs) and fibroblasts with elevated CCL19 expression. The DEGs in most kidney parenchymal cells in DKD were primarily enriched in inflammatory signaling pathways. Intercellular crosstalk revealed that most cell interactions in DKD are associated with chemokines. Spatial transcriptomics revealed that VECs co-localized with fibroblasts, with most immune cells being enriched in areas of renal fibrosis. These results provided insight into the cell populations, intercellular interactions, and signaling pathways underlying the pathogenesis and potential targets for treating DKD.

The relationship between Sjögren's syndrome and recurrent pregnancy loss: a bioinformatics analysis.

RESEARCH QUESTION: As Sjögren's syndrome is an autoimmune disease and an essential factor in recurrent pregnancy loss (RPL), are there gene-related relationships between the pathogenesis of Sjögren's syndrome and RPL? DESIGN: The gene datasets for Sjögren's syndrome and RPL were obtained from the Gene Expression Omnibus database, and the co-expression modules and shared differentially expressed genes were identified through weighted gene co-expression network analysis (WGCNA) and limma analysis based on sample size. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes analyses were applied to reveal the hidden biological pathways. Additionally, shared hub gene identification, gene set enrichment analysis, association of the hub gene with ferroptosis and immunity, drug sensitivity analysis, single-cell RNA sequencing analysis, and construction of the competing endogenous RNA (ceRNA) network were conducted. RESULTS: By intersecting the genes from WGCNA and limma analysis, one shared hub gene (KCNN3) was derived, exhibiting up-regulation in Sjögren's syndrome and RPL. There was a positive relationship between KCNN3 and the immune-related gene TLR2. The ceRNA network revealed that XIST was the most shared long non-coding RNA, which may bind competitively with eight microRNA to regulate the expression of KCNN3. Forty-eight drugs were found to be strongly associated with KCNN3 expression, including estramustine and cyclosporine. Moreover, KCNN3 exhibited high expression in RPL endothelial cells of villous tissue. CONCLUSIONS: This is one of the first studies to reveal that Sjögren's syndrome shares common biological pathways with RPL. KCNN3 was identified as the hub gene associated with Sjögren's syndrome and RPL, and may be a new target for mechanistic studies on Sjögren's syndrome and RPL.

Cell Heterogeneity and Variability in Peripheral Nerve after Injury.

With the development of single-cell sequencing technology, the cellular composition of more and more tissues is being elucidated. As the whole nervous system has been extensively studied, the cellular composition of the peripheral nerve has gradually been revealed. By summarizing the current sequencing data, we compile the heterogeneities of cells that have been reported in the peripheral nerves, mainly the sciatic nerve. The cellular variability of Schwann cells, fibroblasts, immune cells, and endothelial cells during development and disease has been discussed in this review. The discovery of the architecture of peripheral nerves after injury benefits the understanding of cellular complexity in the nervous system, as well as the construction of tissue engineering nerves for nerve repair and axon regeneration.

Classification and characterisation of extracellular vesicles-related tuberculosis subgroups and immune cell profiles.

Around the world, tuberculosis (TB) remains one of the most common causes of morbidity and mortality. The molecular mechanism of Mycobacterium tuberculosis (Mtb) infection is still unclear. Extracellular vesicles (EVs) play a key role in the onset and progression of many disease states and can serve as effective biomarkers or therapeutic targets for the identification and treatment of TB patients. We analysed the expression profile to better clarify the EVs characteristics of TB and explored potential diagnostic markers to distinguish TB from healthy control (HC). Twenty EVs-related differentially expressed genes (DEGs) were identified, and 17 EVs-related DEGs were up-regulated and three DEGs were down-regulated in TB samples, which were related to immune cells. Using machine learning, a nine EVs-related gene signature was identified and two EVs-related subclusters were defined. The single-cell RNA sequence (scRNA-seq) analysis further confirmed that these hub genes might play important roles in TB pathogenesis. The nine EVs-related hub genes had excellent diagnostic values and accurately estimated TB progression. TB's high-risk group had significantly enriched immune-related pathways, and there were substantial variations in immunity across different groups. Furthermore, five potential drugs were predicted for TB using CMap database. Based on the EVs-related gene signature, the TB risk model was established through a comprehensive analysis of different EV patterns, which can accurately predict TB. These genes could be used as novel biomarkers to distinguish TB from HC. These findings lay the foundation for further research and design of new therapeutic interventions aimed at treating this deadly infectious disease.

Single-cell transcriptome analysis reveals endometrial immune microenvironment in minimal/mild endometriosis.

Endometriosis is a common inflammatory disorder in women of reproductive age due to an abnormal endometrial immune environment and is associated with infertility. This study aimed to systematically understand the endometrial leukocyte types, inflammatory environment, and impaired receptivity at single-cell resolution. We profiled single-cell RNA transcriptomes of 138 057 endometrial cells from endometriosis patients (n = 6) and control (n = 7), respectively, using 10x Genomics platform. We found that one cluster of epithelial cells that expressed PAEP and CXCL14 was mostly from the control during the window of implantation (WOI). This epithelial cell type is absent in the eutopic endometrium during the secretory phase. The proportion of endometrial immune cells decreased in the secretory phase in the control group, whereas the cycle variation of total immune cells, NK cells, and T cells was absent in endometriosis. Endometrial immune cells secreted more IL-10 in the secretory phase than in the proliferative phase in the control group; the opposite trend was observed in endometriosis. Proinflammatory cytokines levels in the endometrial immune cells were higher in endometriosis than in the control group. Trajectory analysis revealed that the secretory phase epithelial cells decreased in endometriosis. Ligand-receptor analysis revealed that 11 ligand-receptor pairs were upregulated between endometrial immune and epithelial cells during WOI. These results provide new insights into the endometrial immune microenvironment and impaired endometrial receptivity in infertile women with minimal/mild endometriosis.

A Consensus Gene Regulatory Network for Neurodegenerative Diseases Using Single-Cell RNA-Seq Data.

Gene regulatory network (GRN) inference from gene expression data is a highly complex and challenging task in systems biology. Despite the challenges, GRNs have emerged, and for complex diseases such as neurodegenerative diseases, they have the potential to provide vital information and identify key regulators. However, every GRN method produced predicts results based on its assumptions, providing limited biological insights. For that reason, the current work focused on the development of an ensemble method from individual GRN methods to address this issue. Four state-of-the-art GRN algorithms were selected to form a consensus GRN from their common gene interactions. Each algorithm uses a different construction method, and for a more robust behavior, both static and dynamic methods were selected as well. The algorithms were applied to a scRNA-seq dataset from the CK-p25 mus musculus model during neurodegeneration. The top subnetworks were constructed from the consensus network, and potential key regulators were identified. The results also demonstrated the overlap between the algorithms for the current dataset and the necessity for an ensemble approach. This work aims to demonstrate the creation of an ensemble network and provide insights into whether a combination of different GRN methods can produce valuable results.

Physiological and Pathophysiological Roles of IgM Fc Receptor (FcµR) Isoforms.

IgM is the first antibody to emerge during phylogeny, ontogeny, and immune responses and serves as a first line of defense. Effector proteins interacting with the Fc portion of IgM, such as complement and its receptors, have been extensively studied for their functions. IgM Fc receptor (FcµR), identified in 2009, is the newest member of the FcR family and is intriguingly expressed by lymphocytes only, suggesting the existence of distinct functions as compared to the FcRs for switched Ig isotypes, which are expressed by various immune and non-hematopoietic cells as central mediators of antibody-triggered responses by coupling the adaptive and innate immune responses. Results from FcµR-deficient mice suggest a regulatory function of FcµR in B cell tolerance, as evidenced by their propensity to produce autoantibodies of both IgM and IgG isotypes. In this article, we discuss conflicting views about the cellular distribution and potential functions of FcµR. The signaling function of the Ig-tail tyrosine-like motif in the FcµR cytoplasmic domain is now formally shown by substitutional experiments with the IgG2 B cell receptor. The potential adaptor protein associating with FcµR and the potential cleavage of its C-terminal cytoplasmic tail after IgM binding are still enigmatic. Critical amino acid residues in the Ig-like domain of FcµR for interacting with the IgM Cµ4 domain and the mode of interaction are now defined by crystallographic and cryo-electron microscopic analyses. Some discrepancies on these interactions are discussed. Finally, elevated levels of a soluble FcµR isoform in serum samples are described as the consequence of persistent B cell receptor stimulation, as seen in chronic lymphocytic leukemia and probably in antibody-mediated autoimmune disorders.

Characterisation of Ppy-lineage cells clarifies the functional heterogeneity of pancreatic beta cells in mice.

AIMS/HYPOTHESIS: Pancreatic polypeptide (PP) cells, which secrete PP (encoded by the Ppy gene), are a minor population of pancreatic endocrine cells. Although it has been reported that the loss of beta cell identity might be associated with beta-to-PP cell-fate conversion, at present, little is known regarding the characteristics of Ppy-lineage cells. METHODS: We used Ppy-Cre driver mice and a PP-specific monoclonal antibody to investigate the association between Ppy-lineage cells and beta cells. The molecular profiles of endocrine cells were investigated by single-cell transcriptome analysis and the glucose responsiveness of beta cells was assessed by Ca2+ imaging. Diabetic conditions were experimentally induced in mice by either streptozotocin or diphtheria toxin. RESULTS: Ppy-lineage cells were found to contribute to the four major types of endocrine cells, including beta cells. Ppy-lineage beta cells are a minor subpopulation, accounting for 12-15% of total beta cells, and are mostly (81.2%) localised at the islet periphery. Unbiased single-cell analysis with a Ppy-lineage tracer demonstrated that beta cells are composed of seven clusters, which are categorised into two groups (i.e. Ppy-lineage and non-Ppy-lineage beta cells). These subpopulations of beta cells demonstrated distinct characteristics regarding their functionality and gene expression profiles. Ppy-lineage beta cells had a reduced glucose-stimulated Ca2+ signalling response and were increased in number in experimental diabetes models. CONCLUSIONS/INTERPRETATION: Our results indicate that an unexpected degree of beta cell heterogeneity is defined by Ppy gene activation, providing valuable insight into the homeostatic regulation of pancreatic islets and future therapeutic strategies against diabetes. DATA AVAILABILITY: The single-cell RNA sequence (scRNA-seq) analysis datasets generated in this study have been deposited in the Gene Expression Omnibus (GEO) under the accession number GSE166164 ( www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE166164 ).

Gene expression profiling of α-gustducin-expressing taste cells in mouse fungiform and circumvallate papillae.

Taste buds are complex sensory organs embedded in the epithelium of fungiform papillae (FP) and circumvallate papillae (CV). The sweet, bitter, and umami tastes are sensed by type II taste cells that express taste receptors (Tas1rs and Tas2rs) coupled with the taste G-protein α-gustducin. Recent studies revealed that the taste response profiles of α-gustducin-expressing cells are different between FP and CV, but which genes could generate such distinctive cell characteristics are still largely unknown. We performed a comprehensive transcriptome analysis on α-gustducin-expressing cells in mouse FP and CV by single-cell RNA sequencing combined with fluorescence-activated cell sorting. Transcriptome profiles of the α-gustducin-expressing cells showed various expression patterns of taste receptors. Our clustering analysis defined the specific cell populations derived from FP or CV based on their distinct gene expression. Immunohistochemistry confirmed the specific expression of galectin-3, encoded by Lgals3, which was recognized as a differentially expressed gene in the transcriptome analysis. Our work provides fundamental knowledge toward understanding the genetic heterogeneity of type II cells, potentially revealing differential characterization of FP and CV taste bud cells.

Integrated multi-omics characterization of SMAD4 mutant colorectal cancer.

Colorectal cancer is one of the most common cancers around the world, which is a severe threat to people's health. SMAD4 belongs to the dwarfin/SMAD family, which plays a crucial role in TGF-ß and BMP signal pathways. As the molecular characterization of colon cancer patients following SMAD4 mutations remains unclear, we integrated multi-omics data of SMAD4 mutant patients to reveal the profile of molecular characterization of SMAD4 mutation. A missense mutation is the most common mutant type of SMAD4. Patients with SMAD4 mutation had worse survival. Tumor tissues from patients carrying the SMAD4 mutation showed a reduction in various immune cells, such as CD4 + memory T cells and memory B cells. Many differential genes were identified compared to the SMAD4 mutation-free group and could be significantly enriched for tumor- and immune-related signaling pathways. In addition, the mutant group had different drug sensitivities than the non-mutant group.

Multi-omic profiling of breast tumor microenvironment uncovers a role of mitochondrial calcium gatekeepers.

In this study, we aimed to elucidate the role of mitochondrial calcium uptake 1/2 (MiCU1/2) in breast cancer (BRCA) by employing a comprehensive multi-omics approach. Unlike previous research, we utilized a novel web application tailored for whole tumor tissue, single-cell, and spatial transcriptomics analysis to investigate the association between MiCU1/2 and the tumor immune microenvironment (TIME). Our gene set enrichment analysis (GSEA) provided insights into the primary biological effects of MiCU1/2, while our CRISPR-based drug screening repository identified potential effective drugs. Our study revealed that high MiCU1/2 expression serves as an independent diagnostic biomarker, correlating with advanced clinical status and indicating poorer recurrence-free survival (RFS) rates in BRCA patients. Additionally, spatial transcriptome analysis highlighted the heightened expression of MiCU1/2 in tumors and its relevance in surrounding immune cells. Furthermore, using the CIBERSORT algorithm, we discovered a positive correlation between MiCU1/2 levels and macrophage infiltration, underscoring their potential impact on immune infiltration. We also identified expression patterns of immune-related genes associated with responses against various immune cell types, including CXCL, MIF, GDF, SPP1, and IL16. Finally, our pharmacogenomic screening identified potential small molecule drugs capable of effectively targeting breast cancer cells with elevated MiCU1/2 expression. Overall, our study establishes MiCU1/2 as a promising novel biomarker for BRCA diagnosis and prognostic prediction, as well as a potential therapeutic target, highlighting the importance of exploring these pathways to advance patient care and outcomes in BRCA treatment.

Mechanism differences in the start time of sublingual immunotherapy in a mouse allergic airway inflammation model.

Sublingual immunotherapy (SLIT) has received considerable attention as a method for allergen immunotherapy (AIT). However, the mechanism of SLIT, especially its timing, has not been thoroughly investigated. We evaluated therapeutic and prophylactic SLIT in an allergic airway inflammation model and evaluated their efficacies. Mice were intranasally exposed to Dermatophagoides farinae (Der f) extract and received SLIT before (prophylactic model) and after (therapeutic model) intranasal exposure of Der f. We investigated airway responsiveness, airway inflammation, allergen-specific antibodies, lung histology and single-cell RNA sequencing (scRNA-seq) and T-cell receptor sequencing were also investigated. SLIT in the therapeutic model was effective; however, the effects of SLIT in the prophylactic model were stronger and immune tolerance was maintained for three months. ScRNA-seq of lung CD4+CD25+ T cells revealed that the expansion of induced T regulatory (iTreg) cells was greater in the prophylactic model than that in the therapeutic model. Additionally, the TCR repertoire of iTregs from the prophylactic model was abundant, sharing many clones with the TCR repertoire of effector T cells. These data suggest that the prophylactic model of AIT is extremely effective and persistent, and may respond to allergen diversity, and provide evidence for the clinical recommendation of preventive AIT.

Integrated-omics profiling unveils the disparities of host defense to ECM scaffolds during wound healing in aged individuals.

Extracellular matrix (ECM) scaffold membranes have exhibited promising potential to better the outcomes of wound healing by creating a regenerative microenvironment around. However, when compared to the application in younger individuals, the performance of the same scaffold membrane in promoting re-epithelialization and collagen deposition was observed dissatisfying in aged mice. To comprehensively explore the mechanisms underlying this age-related disparity, we conducted the integrated analysis, combing single-cell RNA sequencing (scRNA-Seq) with spatial transcriptomics, and elucidated six functionally and spatially distinctive macrophage groups and lymphocytes surrounding the ECM scaffolds. Through intergroup comparative analysis and cell-cell communication, we characterized the dysfunction of Spp1+ macrophages in aged mice impeded the activation of the type Ⅱ immune response, thus inhibiting the repair ability of epidermal cells and fibroblasts around the ECM scaffolds. These findings contribute to a deeper understanding of biomaterial applications in varied physiological contexts, thereby paving the way for the development of precision-based biomaterials tailored specifically for aged individuals in future therapeutic strategies.

Microgel-based carriers enhance skeletal stem cell reprogramming towards immunomodulatory phenotype in osteoarthritic therapy.

Skeletal stem cells (SSC) have gained attentions as candidates for the treatment of osteoarthritis due to their osteochondrogenic capacity. However, the immunomodulatory properties of SSC, especially under delivery operations, have been largely ignored. In the study, we found that Pdpn+ and Grem1+ SSC subpopulations owned immunoregulatory potential, and the single-cell RNA sequencing (scRNA-seq) data suggested that the mechanical activation of microgel carriers on SSC induced the generation of Pdpn+Grem1+Ptgs2+ SSC subpopulation, which was potent at suppressing macrophage inflammation. The microgel carriers promoted the YAP nuclear translocation, and the activated YAP protein was necessary for the increased expression of Ptgs2 and PGE2 in microgels-delivered SSC, which further suppressed the expression of TNF-ɑ, IL-1ß and promoted the expression of IL-10 in macrophages. SSC delivered with microgels yielded better preventive effects on articular lesions and macrophage activation in osteoarthritic rats than SSC without microgels. Chemically blocking the YAP and Ptgs2 in microgels-delivered SSC partially abolished the enhanced protection on articular tissues and suppression on osteoarthritic macrophages. Moreover, microgel carriers significantly prolonged SSC retention time in vivo without increasing SSC implanting into osteoarthritic joints. Together, our study demonstrated that microgel carriers enhanced SSC reprogramming towards immunomodulatory phenotype to regulate macrophage phenotype transformation for effectively osteoarthritic therapy by promoting YAP protein translocation into nucleus. The study not only complement and perfect the immunological mechanisms of SSC-based therapy at the single-cell level, but also provide new insight for microgel carriers in stem cell-based therapy.

New generative methods for single-cell transcriptome data in bulk RNA sequence deconvolution.

Numerous methods for bulk RNA sequence deconvolution have been developed to identify cellular targets of diseases by understanding the composition of cell types in disease-related tissues. However, issues of heterogeneity in gene expression between subjects and the shortage of reference single-cell RNA sequence data remain to achieve accurate bulk deconvolution. In our study, we investigated whether a new data generative method named sc-CMGAN and benchmarking generative methods (Copula, CTGAN and TVAE) could solve these issues and improve the bulk deconvolutions. We also evaluated the robustness of sc-CMGAN using three deconvolution methods and four public datasets. In almost all conditions, the generative methods contributed to improved deconvolution. Notably, sc-CMGAN outperformed the benchmarking methods and demonstrated higher robustness. This study is the first to examine the impact of data augmentation on bulk deconvolution. The new generative method, sc-CMGAN, is expected to become one of the powerful tools for the preprocessing of bulk deconvolution.

Single-cell RNA sequencing of submandibular gland reveals collagen type XV-positive fibroblasts as a disease-characterizing cell population of IgG4-related disease.

OBJECTIVES: IgG4-related disease (IgG4-RD) is a systemic autoimmune disease with an unknown etiology, affecting single/multiple organ(s). Pathological findings include the infiltration of IgG4-producing plasma cells, obliterative phlebitis, and storiform fibrosis. Although immunological studies have shed light on the dysregulation of lymphocytes in IgG4-RD pathogenesis, the role of non-immune cells remains unclear. This study aimed to investigate the demographics and characteristics of non-immune cells in IgG4-RD and explore potential biomarkers derived from non-immune cells in the sera. METHODS: We conducted single-cell RNA sequence (scRNA-seq) on non-immune cells isolated from submandibular glands of IgG4-RD patients. We focused on fibroblasts expressing collagen type XV and confirmed the presence of those fibroblasts using immunohistochemistry. Additionally, we measured the levels of collagen type XV in the sera of IgG4-RD patients. RESULTS: The scRNA-seq analysis revealed several distinct clusters consisting of fibroblasts, endothelial cells, ductal cells, and muscle cells. Differential gene expression analysis showed upregulation of COL15A1 in IgG4-RD fibroblasts compared to control subjects. Notably, COL15A1-positive fibroblasts exhibited a distinct transcriptome compared to COL15A1-negative counterparts. Immunohistochemical analysis confirmed a significant presence of collagen type XV-positive fibroblasts in IgG4-RD patients. Furthermore, immune-suppressive therapy in active IgG4-RD patients resulted in decreased serum levels of collagen type XV. CONCLUSIONS: Our findings suggest that collagen type XV-producing fibroblasts may represent a disease-characterizing non-immune cell population in IgG4-RD and hold potential as a disease-monitoring marker.

Coupled scRNA-seq and Bulk-seq reveal the role of HMMR in hepatocellular carcinoma.

Background: Hyaluronan-mediated motility receptor (HMMR) is overexpressed in multiple carcinomas and influences the development and treatment of several cancers. However, its role in hepatocellular carcinoma (HCC) remains unclear. Methods: The "limma" and "GSVA" packages in R were used to perform differential expression analysis and to assess the activity of signalling pathways, respectively. InferCNV was used to infer copy number variation (CNV) for each hepatocyte and "CellChat" was used to analyse intercellular communication networks. Recursive partitioning analysis (RPA) was used to re-stage HCC patients. The IC50 values of various drugs were evaluated using the "pRRophetic" package. In addition, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to confirm HMMR expression in an HCC tissue microarray. Flow cytometry (FCM) and cloning, Edu and wound healing assays were used to explore the capacity of HMMR to regulate HCC tumour. Results: Multiple cohort studies and qRT-PCR demonstrated that HMMR was overexpressed in HCC tissue compared with normal tissue. In addition, HMMR had excellent diagnostic performance. HMMR knockdown inhibited the proliferation and migration of HCC cells in vitro. Moreover, high HMMR expression was associated with "G2M checkpoint" and "E2F targets" in bulk RNA and scRNA-seq, and FCM confirmed that HMMR could regulate the cell cycle. In addition, HMMR was involved in the regulation of the tumour immune microenvironment via immune cell infiltration and intercellular interactions. Furthermore, HMMR was positively associated with genomic heterogeneity with patients with high HMMR expression potentially benefitting more from immunotherapy. Moreover, HMMR was associated with poor prognosis in patients with HCC and the re-staging by recursive partitioning analysis (RPA) gave a good prognosis prediction value and could guide chemotherapy and targeted therapy. Conclusion: The results of the present study show that HMMR could play a role in the diagnosis, prognosis, and treatments of patients with HCC based on bulk RNA-seq and scRAN-seq analyses and is a promising molecular marker for HCC.