Expression patterns of keratin family members during tooth development and the role of keratin 17 in cytodifferentiation of stratum intermedium and stellate reticulum.

Keratins are typical intermediate filament proteins of the epithelium that exhibit highly specific expression patterns related to the epithelial type and stage of cellular differentiation. They are important for cytoplasmic stability and epithelial integrity and are involved in various intracellular signaling pathways. Several keratins are associated with enamel formation. However, information on their expression patterns during tooth development remains lacking. In this study, we analyzed the spatiotemporal expression of keratin family members during tooth development using single-cell RNA-sequencing (scRNA-seq) and microarray analysis. scRNA-seq datasets from postnatal Day 1 mouse molars revealed that several keratins are highly expressed in the dental epithelium, indicating the involvement of keratin family members in cellular functions. Among various keratins, keratin 5 (Krt5), keratin 14 (Krt14), and keratin 17 (Krt17) are highly expressed in the tooth germ; KRT17 is specifically expressed in the stratum intermedium (SI) and stellate reticulum (SR). Depletion of Krt17 did not affect cell proliferation in the dental epithelial cell line SF2 but suppressed their differentiation ability. These results suggest that Krt17 is essential for SI cell differentiation. Furthermore, scRNA-seq results indicated that Krt5, Krt14, and Krt17 exhibited distinct expression patterns in ameloblast, SI, and SR cells. Our findings contribute to the elucidation of novel mechanisms underlying tooth development.

Glycosylphosphatidylinositol anchor biosynthesis pathway-based biomarker identification with machine learning for prognosis and T cell exhaustion status prediction in breast cancer.

As the primary component of anti-tumor immunity, T cells are prone to exhaustion and dysfunction in the tumor microenvironment (TME). A thorough understanding of T cell exhaustion (TEX) in the TME is crucial for effectively addressing TEX in clinical settings and promoting the efficacy of immune checkpoint blockade therapies. In eukaryotes, numerous cell surface proteins are tethered to the plasma membrane via Glycosylphosphatidylinositol (GPI) anchors, which play a crucial role in facilitating the proper translocation of membrane proteins. However, the available evidence is insufficient to support any additional functional involvement of GPI anchors. Here, we investigate the signature of GPI-anchor biosynthesis in the TME of breast cancer (BC)patients, particularly its correlation with TEX. GPI-anchor biosynthesis should be considered as a prognostic risk factor for BC. Patients with high GPI-anchor biosynthesis showed more severe TEX. And the levels of GPI-anchor biosynthesis in exhausted CD8 T cells was higher than normal CD8 T cells, which was not observed between malignant epithelial cells and normal mammary epithelial cells. In addition, we also found that GPI -anchor biosynthesis related genes can be used to diagnose TEX status and predict prognosis in BC patients, both the TEX diagnostic model and the prognostic model showed good AUC values. Finally, we confirmed our findings in cells and clinical samples. Knockdown of PIGU gene expression significantly reduced the proliferation rate of MDA-MB-231 and MCF-7 cell lines. Immunofluorescence results from clinical samples showed reduced aggregation of CD8 T cells in tissues with high expression of GPAA1 and PIGU.

Identification of novel immune-related signatures for keloid diagnosis and treatment: insights from integrated bulk RNA-seq and scRNA-seq analysis.

BACKGROUND: Keloid is a disease characterized by proliferation of fibrous tissue after the healing of skin tissue, which seriously affects the daily life of patients. However, the clinical treatment of keloids still has limitations, that is, it is not effective in controlling keloids, resulting in a high recurrence rate. Thus, it is urgent to identify new signatures to improve the diagnosis and treatment of keloids. METHOD: Bulk RNA seq and scRNA seq data were downloaded from the GEO database. First, we used WGCNA and MEGENA to co-identify keloid/immune-related DEGs. Subsequently, we used three machine learning algorithms (Randomforest, SVM-RFE, and LASSO) to identify hub immune-related genes of keloid (KHIGs) and investigated the heterogeneous expression of KHIGs during fibroblast subpopulation differentiation using scRNA-seq. Finally, we used HE and Masson staining, quantitative reverse transcription-PCR, western blotting, immunohistochemical, and Immunofluorescent assay to investigate the dysregulated expression and the mechanism of retinoic acid in keloids. RESULTS: In the present study, we identified PTGFR, RBP5, and LIF as KHIGs and validated their diagnostic performance. Subsequently, we constructed a novel artificial neural network molecular diagnostic model based on the transcriptome pattern of KHIGs, which is expected to break through the current dilemma faced by molecular diagnosis of keloids in the clinic. Meanwhile, the constructed IG score can also effectively predict keloid risk, which provides a new strategy for keloid prevention. Additionally, we observed that KHIGs were also heterogeneously expressed in the constructed differentiation trajectories of fibroblast subtypes, which may affect the differentiation of fibroblast subtypes and thus lead to dysregulation of the immune microenvironment in keloids. Finally, we found that retinoic acid may treat or alleviate keloids by inhibiting RBP5 to differentiate pro-inflammatory fibroblasts (PIF) to mesenchymal fibroblasts (MF), which further reduces collagen secretion. CONCLUSION: In summary, the present study provides novel immune signatures (PTGFR, RBP5, and LIF) for keloid diagnosis and treatment, and identifies retinoic acid as potential anti-keloid drugs. More importantly, we provide a new perspective for understanding the interactions between different fibroblast subtypes in keloids and the remodeling of their immune microenvironment.

T-distributed Stochastic Neighbor Network for unsupervised representation learning.

Unsupervised representation learning (URL) is still lack of a reasonable operator (e.g. convolution kernel) for exploring meaningful structural information from generic data including vector, image and tabular data. In this paper, we propose a simple end-to-end T-distributed Stochastic Neighbor Network (TsNet) for URL with clustering downstream task. Concretely, our TsNet model has three major components: (1) an adaptive connectivity distribution learning module is presented to construct a pairwise graph for preserving the local structure of generic data; (2) a T-distributed stochastic neighbor embedding based loss function is designed to learn a transformation between embeddings and original data, which improves the discrimination of representations; (3) a nonlinear parametric mapping is learned via our TsNet on an unsupervised generalized manner, which can address the "out-of-sample" issue. By combining these components, our method is able to considerably outperform previous related unsupervised learning approaches on visualization and clustering of generic data. A simple deep neural network equipped on our model respectively achieves 74.90%, 76.56% ACC and NMI, which is 8% relative improvement over previous state-of-the-art on real single-cell RNA-sequencing (scRNA-seq) datasets clustering.

Identification of a pro-protein synthesis osteosarcoma subtype for predicting prognosis and treatment.

Osteosarcoma (OS) is a heterogeneous malignant spindle cell tumor that is aggressive and has a poor prognosis. Although combining surgery and chemotherapy has significantly improved patient outcomes, the prognosis for OS patients with metastatic or recurrent OS has remained unsatisfactory. Therefore, it is imperative to gain a fresh perspective on OS development mechanisms and treatment strategies. After studying single-cell RNA sequencing (scRNA-seq) data in public databases, we identified seven OS subclonal types based on intra-tumor heterogeneity. Subsequently, we constructed a prognostic model based on pro-protein synthesis osteosarcoma (PPS-OS)-associated genes. Correlation analysis showed that the prognostic model performs extremely well in predicting OS patient prognosis. We also demonstrated that the independent risk factors for the prognosis of OS patients were tumor primary site, metastatic status, and risk score. Based on these factors, nomograms were constructed for predicting the 3- and 5-year survival rates. Afterward, the investigation of the tumor immune microenvironment (TIME) revealed the vital roles of γδ T-cell and B-cell activation. Drug sensitivity analysis and immune checkpoint analysis identified drugs that have potential application value in OS. Finally, the jumping translocation breakpoint (JTB) gene was selected for experimental validation. JTB silencing suppressed the proliferation, migration, and invasion of OS cells. Therefore, our research suggests that PPS-OS-related genes facilitate the malignant progression of OS and may be employed as prognostic indicators and therapeutic targets in OS.

The SWI/SNF chromatin remodelling complex regulates pancreatic endocrine cell expansion and differentiation in mice in vivo.

AIMS/HYPOTHESIS: Strategies to augment functional beta cell mass include directed differentiation of stem cells towards a beta cell fate, which requires extensive knowledge of transcriptional programs governing endocrine progenitor cell differentiation in vivo. We aimed to study the contributions of the Brahma-related gene-1 (BRG1) and Brahma (BRM) ATPase subunits of the SWI/SNF chromatin remodelling complex to endocrine cell development. METHODS: We generated mice with endocrine progenitor-specific Neurog3-Cre BRG1 removal in the presence of heterozygous (Brg1Δendo;Brm+/-) or homozygous (double knockout: DKOΔendo) BRM deficiency. Whole-body metabolic phenotyping, islet function characterisation, islet quantitative PCR and histological characterisation were performed on animals and tissues postnatally. To test the mechanistic actions of SWI/SNF in controlling gene expression during endocrine cell development, single-cell RNA-seq was performed on flow-sorted endocrine-committed cells from embryonic day 15.5 control and mutant embryos. RESULTS: Brg1Δendo;Brm+/- mice exhibit severe glucose intolerance, hyperglycaemia and hypoinsulinaemia, resulting, in part, from reduced islet number; diminished alpha, beta and delta cell mass; compromised islet insulin secretion; and altered islet gene expression programs, including reductions in MAFA and urocortin 3 (UCN3). DKOΔendo mice were not recovered at weaning; however, postnatal day 6 DKOΔendo mice were severely hyperglycaemic with reduced serum insulin levels and beta cell area. Single-cell RNA-seq of embryonic day 15.5 lineage-labelled cells revealed endocrine progenitor, alpha and beta cell populations from SWI/SNF mutants have reduced expression of Mafa, Gcg, Ins1 and Ins2, suggesting limited differentiation capacity. Reduced Neurog3 transcripts were discovered in DKOΔendo endocrine progenitor clusters, and the proliferative capacity of neurogenin 3 (NEUROG3)+ cells was reduced in Brg1Δendo;Brm+/- and DKOΔendo mutants. CONCLUSIONS/INTERPRETATION: Loss of BRG1 from developing endocrine progenitor cells has a severe postnatal impact on glucose homeostasis, and loss of both subunits impedes animal survival, with both groups exhibiting alterations in hormone transcripts embryonically. Taken together, these data highlight the critical role SWI/SNF plays in governing gene expression programs essential for endocrine cell development and expansion. DATA AVAILABILITY: Raw and processed data for scRNA-seq have been deposited into the NCBI Gene Expression Omnibus (GEO) database under the accession number GSE248369.

Enterovirus-A71 preferentially infects and replicates in human motor neurons, inducing neurodegeneration by ferroptosis.

Enterovirus A71 (EV-A71) causes Hand, Foot, and Mouth Disease and has been clinically associated with neurological complications. However, there is a lack of relevant models to elucidate the neuropathology of EV-A71 and its mechanism, as the current models mainly utilize animal models or immortalized cell lines. In this study, we established a human motor neuron model for EV-A71 infection. Single cell transcriptomics of a mixed neuronal population reveal higher viral RNA load in motor neurons, suggesting higher infectivity and replication of EV-A71 in motor neurons. The elevated RNA load in motor neurons correlates with the downregulation of ferritin-encoding genes. Subsequent analysis confirms that neurons infected with EV-A71 undergo ferroptosis, as evidenced by increased levels of labile Fe2+ and peroxidated lipids. Notably, the Fe2+ chelator Deferoxamine improves mitochondrial function and promotes survival of motor neurons by 40% after EV-A71 infection. These findings deepen understanding of the molecular pathogenesis of EV-A71 infection, providing insights which suggest that improving mitochondrial respiration and inhibition of ferroptosis can mitigate the impact of EV-A71 infection in the central nervous system.

Organoids for Cancer Research: Advances and Challenges.

As 3D culture technology advances, new avenues have opened for the development of physiological human cancer models. These preclinical models provide efficient ways to translate basic cancer research into clinical tumor therapies. Recently, cancer organoids have emerged as a model to dissect the more complex tumor microenvironment. Incorporating cancer organoids into preclinical programs have the potential to increase the success rate of oncology drug development and recapitulate the most efficacious treatment regimens for cancer patients. In this review, four main types of cancer organoids are introduced, their applications, advantages, limitations, and prospects are discussed, as well as the recent application of single-cell RNA-sequencing (scRNA-seq) in exploring cancer organoids to advance this field.

Interleukin-7-based identification of liver lymphatic endothelial cells reveals their unique structural features.

Background & Aims: The lymphatic system plays crucial roles in maintaining fluid balance and immune regulation. Studying the liver lymphatics has been considered challenging, as common lymphatic endothelial cell (LyEC) markers are expressed by other liver cells. Additionally, isolation of sufficient numbers of LyECs has been challenging because of their extremely low abundance (<0.01% of entire liver cell population) in a normal liver. Methods: Potential LyEC markers was identified using our published single-cell RNA sequencing (scRNA-seq) dataset (GSE147581) in mouse livers. Interleukin-7 (IL7) promoter-driven green fluorescent protein knock-in heterozygous mice were used for the validation of IL7 expression in LyECs in the liver, for the development of liver LyEC isolation protocol, and generating liver ischemia/reperfusion (I/R) injury. Scanning electron microscopy was used for the structural analysis of LyECs. Changes in LyEC phenotypes in livers of mice with I/R were determined by RNA-seq analysis. Results: Through scRNA-seq analysis, we have identified IL7 as an exclusive marker for liver LyECs, with no overlap with other liver cell types. Based on IL7 expression in liver LyECs, we have established an LyEC isolation method and observed distinct cell surface structures of LyECs with fenestrae and cellular pores (ranging from 100 to 400 nm in diameter). Furthermore, we identified LyEC genes that undergo alterations during I/R liver injuries. Conclusions: This study not only identified IL7 as an exclusively expressed gene in liver LyECs, but also enhanced our understanding of LyEC structures and demonstrated transcriptomic changes in injured livers. Impact and implications: Understanding the lymphatic system in the liver is challenging because of the absence of specific markers for liver LyEC. This study has identified IL7 as a reliable marker for LyECs, enabling the development of an effective method for their isolation, elucidating their unique cell surface structure, and identifying LyEC genes that undergo changes during liver damage. The development of IL7 antibodies for detecting it in human liver specimens will further advance our understanding of the liver lymphatic system in the future.

Exploring single-cell RNA sequencing as a decision-making tool in the clinical management of Fuchs' endothelial corneal dystrophy.

Single-cell RNA sequencing (scRNA-seq) has enabled the identification of novel gene signatures and cell heterogeneity in numerous tissues and diseases. Here we review the use of this technology for Fuchs' Endothelial Corneal Dystrophy (FECD). FECD is the most common indication for corneal endothelial transplantation worldwide. FECD is challenging to manage because it is genetically heterogenous, can be autosomal dominant or sporadic, and progress at different rates. Single-cell RNA sequencing has enabled the discovery of several FECD subtypes, each with associated gene signatures, and cell heterogeneity. Current FECD treatments are mainly surgical, with various Rho kinase (ROCK) inhibitors used to promote endothelial cell metabolism and proliferation following surgery. A range of emerging therapies for FECD including cell therapies, gene therapies, tissue engineered scaffolds, and pharmaceuticals are in preclinical and clinical trials. Unlike conventional disease management methods based on clinical presentations and family history, targeting FECD using scRNA-seq based precision-medicine has the potential to pinpoint the disease subtypes, mechanisms, stages, severities, and help clinicians in making the best decision for surgeries and the applications of therapeutics. In this review, we first discuss the feasibility and potential of using scRNA-seq in clinical diagnostics for FECD, highlight advances from the latest clinical treatments and emerging therapies for FECD, integrate scRNA-seq results and clinical notes from our FECD patients and discuss the potential of applying alternative therapies to manage these cases clinically.

Identification and experimental validation of cuproptosis regulatory program in a sepsis immune microenvironment through a combination of single-cell and bulk RNA sequencing.

Background: In spite of its high mortality rate and poor prognosis, the pathogenesis of sepsis is still incompletely understood. This study established a cuproptosis-based risk model to diagnose and predict the risk of sepsis. In addition, the cuproptosis-related genes were identified for targeted therapy. Methods: Single-cell sequencing analyses were used to characterize the cuproptosis activity score (CuAS) and intercellular communications in sepsis. Differential cuproptosis-related genes (CRGs) were identified in conjunction with single-cell and bulk RNA sequencing. LASSO and Cox regression analyses were employed to develop a risk model. Three external cohorts were conducted to assess the model's accuracy. Differences in immune infiltration, immune cell subtypes, pathway enrichment, and the expression of immunomodulators were further evaluated in distinct groups. Finally, various in-vitro experiments, such as flow cytometry, Western blot, and ELISA, were used to explore the role of LST1 in sepsis. Results: ScRNA-seq analysis demonstrated that CuAS was highly enriched in monocytes and was closely related to the poor prognosis of sepsis patients. Patients with higher CuAS exhibited prominent strength and numbers of cell-cell interactions. A total of five CRGs were identified based on the LASSO and Cox regression analyses, and a CRG-based risk model was established. The lower riskScore cohort exhibited enhanced immune cell infiltration, elevated immune scores, and increased expression of immune modulators, indicating the activation of an antibacterial response. Ultimately, in-vitro experiments demonstrated that LST1, a key gene in the risk model, was enhanced in the macrophage in response to LPS, which was closely related to the decrease of macrophage survival rate, the enhancement of apoptosis and oxidative stress injury, and the imbalance of the M1/M2 phenotype. Conclusions: This study constructed a cuproptosis-related risk model to accurately predict the prognosis of sepsis. We further characterized the cuproptosis-related gene LST1 to provide a theoretical framework for sepsis therapy.

Single-cell sequencing reveals the correlation of aggrephagy signaling and multiple myeloma immune microenvironment composition.

Aggrephagy, a type of autophagy, degrades the aggregation of misfolded protein in cells. However, the role of aggrephagy in multiple myeloma (MM) has not been fully demonstrated. In this study, we first investigated the correlation between aggrephagy signaling, MM immune microenvironment composition and disease prognosis. Single-cell RNA-seq data, including the expression profiles of 12,187 single cells from seven MM bone marrow (BM) and seven healthy BM samples, were analyzed by non-negative matrix factorization for 44 aggrephagy-related genes. Bulk RNA-seq cohorts from the Gene Expression Omnibus database were used to evaluate the prognostic value of aggrephagy-related immune cell subtypes and predict immune checkpoint blockade immunotherapeutic response in MM. Compared with healthy BM, MM BM exhibited different patterns of aggrephagy-related gene expression. In MM BM, macrophages, CD8+ T cells, B cells and natural killer cells could be grouped into four to nine aggrephagy-related subclusters. The signature of aggrephagy signaling molecule expression in the immune cells correlates with the patient's prognosis. Our investigation provides a novel view of aggrephagy signaling in MM tumor microenvironment cells, which might be a prognostic indicator and potential target for MM treatment.

LiverSCA: A comprehensive and user-friendly cell atlas in human hepatocellular carcinoma.

We developed a cell atlas named LiverSCA on human liver cancer single-cell RNA sequencing data. It has a user-friendly web interface and comprehensive functionalities aiming to help researchers to make easy access to cellular and molecular landscapes of the tumor microenvironment in liver cancer. LiverSCA includes a complete analytical pipeline that allow mechanistic exploration on a wide variety of functionalities, such as cell clustering, cell annotation, identification of differentially expressed genes, functional enrichment analysis, analysis of cellular crosstalk, and pseudo-time trajectory analysis. Notably, our intuitive web interface allows users, particularly wet-lab researchers, to easily explore and undertake data discovery, without the need to handle any of the raw data.

Single-cell RNA-sequencing analysis reveals α-syn induced astrocyte-neuron crosstalk-mediated neurotoxicity.

Accumulation of alpha-synuclein (α-syn) is a key pathological hallmark of synucleinopathies and has been shown to negatively impact neuronal function and activity. α-syn is an important factor contributing to astrocyte overactivation, though the effect of astrocyte overactivation on neurons remains unclear. Single-cell RNA sequencing data of mouse brain frontal cortex and midbrain from Hua-Syn (A53T) and wild type mice were utilized from the GEO database. Enrichment analysis, protein-protein interaction networks, and cell-cell interaction networks all indicated enhanced communication between astrocytes and neurons, along with the involvement of TNF and inflammation-related signaling pathways. In vitro experiments were performed to further explore the mechanism of neurotoxicity in astrocyte-neuron crosstalk. Astrocytes were treated by α-syn, neuronal TNFR1 receptors were antagonized by R-7050, and the cells were co-cultured after 24 h treatment. ELISA results revealed that cytokines such as TNF-α and IL-6 were significantly upregulated in astrocytes following the endocytosis of α-syn. Immunofluorescence (IF) showed neuronal dendritic reduction, axon elongation and increased co-localisation of TNFR1 receptor expression. Western blot showed up-regulation of PKR, P-eIF2α and ATF4 protein expression. Conversely, after antagonizing neuronal TNFR1 receptors with the R-7050 chemical inhibitor, neuronal synaptic structure was significantly restored and the expression of PKR, P-eIF2α and ATF4 was down-regulated. In summary, TNF-α acts as a signaling molecule mediating the up-regulated astrocyte-neuron crosstalk, providing new insights into the pathogenesis of α-syn-related neurological disorders.

Single-cell RNA sequencing reveals dynamics of gene expression for 2D elongation and 3D growth in Physcomitrium patens.

The transition from two-dimensional (2D) to 3D growth likely facilitated plants to colonize land, but its heterogeneity is not well understood. In this study, we utilized single-cell RNA sequencing to analyze the moss Physcomitrium patens, whose morphogenesis involves a transition from 2D to 3D growth. We profiled over 17,000 single cells covering all major vegetative tissues, including 2D filaments (chloronema and caulonema) and 3D structures (bud and gametophore). Pseudotime analyses revealed larger numbers of candidate genes that determine cell fates for 2D tip elongation or 3D bud differentiation. Using weighted gene co-expression network analysis, we identified a module that connects ß-type carbonic anhydrases (ßCAs) with auxin. We further validated the cellular expression patterns of ßCAs and demonstrated their roles in 3D gametophore development. Overall, our study provides insights into cellular heterogeneity in a moss and identifies molecular signatures that underpin the 2D-to-3D growth transition at single-cell resolution.

Cross-species single-cell RNA sequencing reveals divergent phenotypes and activation states of adaptive immunity in human carotid and experimental murine atherosclerosis.

BACKGROUND AND AIMS: The distinct functions of immune cells in atherosclerosis have been mostly defined by preclinical mouse studies. Contrastingly, the immune cell composition of human atherosclerotic plaques and their contribution to disease progression is only poorly understood. It remains uncertain whether genetic animal models allow for valuable translational approaches. METHODS AND RESULTS: Single cell RNA-sequencing (scRNA-seq) was performed to define the immune cell landscape in human carotid atherosclerotic plaques. The human immune cell repertoire demonstrated an unexpectedly high heterogeneity and was dominated by cells of the T-cell lineage, a finding confirmed by immunohistochemistry. Bioinformatical integration with 7 mouse scRNA-seq data sets from adventitial and atherosclerotic vascular tissue revealed a total of 51 identities of cell types and differentiation states, of which some were only poorly conserved between species and exclusively found in humans. Locations, frequencies, and transcriptional programs of immune cells in mouse models did not resemble the immune cell landscape in human carotid atherosclerosis. In contrast to standard mouse models of atherosclerosis, human plaque leukocytes were dominated by several T-cell phenotypes with transcriptional hallmarks of T-cell activation and memory formation, T-cell receptor-, and pro-inflammatory signaling. Only mice at the age of 22 months partially resembled the activated T-cell phenotype. In a validation cohort of 43 patients undergoing carotid endarterectomy, the abundance of activated immune cell subsets in the plaque defined by multi-color flow cytometry associated with the extend of clinical atherosclerosis. CONCLUSIONS: Integrative scRNA-seq reveals a substantial difference in the immune cell composition of murine and human carotid atherosclerosis - a finding that questions the translational value of standard mouse models for adaptive immune cell studies. Clinical associations suggest a specific role for T-cell driven (auto-) immunity in human plaque formation and -instability.

IL-13 decreases susceptibility to airway epithelial SARS-CoV-2 infection but increases disease severity in vivo.

Treatments available to prevent progression of virus-induced lung diseases, including coronavirus disease 2019 (COVID-19) are of limited benefit once respiratory failure occurs. The efficacy of approved and emerging cytokine signaling-modulating antibodies is variable and is affected by disease course and patient-specific inflammation patterns. Therefore, understanding the role of inflammation on the viral infectious cycle is critical for effective use of cytokine-modulating agents. We investigated the role of the type 2 cytokine IL-13 on SARS-CoV-2 binding/entry, replication, and host response in primary HAE cells in vitro and in a model of mouse-adapted SARS-CoV-2 infection in vivo. IL-13 protected airway epithelial cells from SARS-CoV-2 infection in vitro by decreasing the abundance of ACE2-expressing ciliated cells rather than by neutralization in the airway surface liquid or by interferon-mediated antiviral effects. In contrast, IL-13 worsened disease severity in mice; the effects were mediated by eicosanoid signaling and were abolished in mice deficient in the phospholipase A2 enzyme PLA2G2D. We conclude that IL-13-induced inflammation differentially affects multiple steps of COVID-19 pathogenesis. IL-13-induced inflammation may be protective against initial SARS-CoV-2 airway epithelial infection; however, it enhances disease progression in vivo. Blockade of IL-13 and/or eicosanoid signaling may be protective against progression to severe respiratory virus-induced lung disease.

Single cell regulatory architecture of human pancreatic islets suggests sex differences in ß cell function and the pathogenesis of type 2 diabetes.

Type 2 and type 1 diabetes (T2D, T1D) exhibit sex differences in insulin secretion, the mechanisms of which are unknown. We examined sex differences in human pancreatic islets from 52 donors with and without T2D combining single cell RNA-seq (scRNA-seq), single nucleus assay for transposase-accessible chromatin sequencing (snATAC-seq), hormone secretion, and bioenergetics. In nondiabetic (ND) donors, sex differences in islet cells gene accessibility and expression predominantly involved sex chromosomes. Islets from T2D donors exhibited similar sex differences in sex chromosomes differentially expressed genes (DEGs), but also exhibited sex differences in autosomal genes. Comparing ß cells from T2D vs. ND donors, gene enrichment of female ß cells showed suppression in mitochondrial respiration, while male ß cells exhibited suppressed insulin secretion. Thus, although sex differences in gene accessibility and expression of ND ß cells predominantly affect sex chromosomes, the transition to T2D reveals sex differences in autosomes highlighting mitochondrial failure in females.

Integrating single-cell RNA-seq to identify fibroblast-based molecular subtypes for predicting prognosis and therapeutic response in bladder cancer.

BACKGROUND: Bladder cancer (BLCA) is a highly aggressive and heterogeneous disease, posing challenges for diagnosis and treatment. Cancer immunotherapy has recently emerged as a promising option for patients with advanced and drug-resistant cancers. Fibroblasts, a significant component of the tumor microenvironment, play a crucial role in tumor progression, but their precise function in BLCA remains uncertain. METHODS: Single-cell RNA sequencing (scRNA-seq) data for BLCA were obtained from the Gene Expression Omnibus database. The R package "Seurat" was used for processing scRNA-seq data, with uniform manifold approximation and projection (UMAP) for downscaling and cluster identification. The FindAllMarkers function identified marker genes for each cluster. Differentially expressed genes influencing overall survival (OS) of BLCA patients were identified using the limma package. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and chemotherapeutic drug sensitivity between high- and low-risk groups were investigated. RT-qPCR and immunohistochemistry validated the expression of prognostic genes. RESULTS: Fibroblast marker genes identified three molecular subtypes in the testing set. A prognostic signature comprising ten genes stratified BLCA patients into high- and low-score groups. This signature was validated in one internal and two external validation sets. High-score patients exhibited increased immune cell infiltration, elevated chemokine expression, and enhanced immune checkpoint expression but had poorer OS and a reduced response to immunotherapy. Six sensitive anti-tumor drugs were identified for the high-score group. RT-qPCR and immunohistochemistry showed that CERCAM, TM4SF1, FN1, ANXA1, and LOX were highly expressed, while EMP1, HEYL, FBN1, and SLC2A3 were downregulated in BLCA. CONCLUSION: A novel fibroblast marker gene-based signature was established, providing robust predictions of survival and immunotherapeutic response in BLCA patients.