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ABSTRACT Airway inflammatory diseases include allergic rhinitis (AR), chronic rhinosinusitis (CRS), bronchial asthma (BA), chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF). Single‐cell sequencing (SCS), as a powerful tool for revealing cellular and molecular landscapes at single‐cell resolution, which has revealed many of the intrinsic biological features and dynamics of airway inflammation, viral infections and other pathologies, as well as constructing immune landscapes of health and disease states. We reviewed the literature focusing on the past several years have focused on using SCS technology increased our understanding of the airway immune cell landscape of airway diseases, including CRS, AR, BA, COPD, IPF, as well as the landscape of airway immune cells in healthy and pathological conditions. We also have elucidated the role of a subset of T cells, myeloid cell, basophils and mast cells in airway diseases revealed by SCS. Meanwhile we also highlighted the use of SCS to explore the potential mechanisms of immune cell interactions. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the molecular mechanisms of periodontitis and identify key immune‐related biomarkers using machine learning and Mendelian randomization (MR). Differentially expressed gene (DEG) analysis was performed on periodontitis datasets GSE16134 and GSE10334 from the Gene Expression Omnibus (GEO) database, followed by weighted gene co‐expression network analysis (WGCNA) to identify relevant gene modules. Various machine learning algorithms were utilized to construct predictive models, highlighting core genes, while MR assessed the causal relationships between these genes and periodontitis. Additionally, immune infiltration analysis and single‐cell sequencing were employed to explore the roles of key genes in immunity and their expression across different cell types. The integration of machine learning, MR, and single‐cell sequencing represents a novel approach that significantly enhances our understanding of the immune dynamics and gene interactions in periodontitis. The study identified 682 significant DEGs, with WGCNA revealing seven gene modules associated with periodontitis and 471 core candidate genes. Among the 113 machine learning algorithms tested, XGBoost was the most effective in identifying periodontitis samples, leading to the selection of 19 core genes. MR confirmed significant causal relationships between CD93, CD69, and CXCL6 and periodontitis. Further analysis showed that these genes were correlated with various immune cells and exhibited specific expression patterns in periodontitis tissues. The findings suggest that CD93, CD69, and CXCL6 are closely related to the progression of periodontitis, with MR confirming their causal links to the disease. These genes have potential applications in the diagnosis and treatment of periodontitis, offering new insights into the disease's molecular mechanisms and providing valuable resources for precision medicine approaches in periodontitis management. Limitations of this study include the demographic and sample size constraints of the datasets, which may impact the generalizability of the findings. Future research is needed to validate these biomarkers in larger, diverse cohorts and to investigate their functional roles in the pathogenesis of periodontitis. [ABSTRACT FROM AUTHOR]

To uncover the complex immune mechanisms driving inflammation in ankylosing spondylitis and lay the groundwork for identifying new therapeutic targets and innovative approaches, we conducted 10× single‐cell sequencing on bone marrow cell samples collected from the vertebrae of three AS patients and three non‐AS patients. Using single‐cell sequencing data, we analysed the expression of differentially expressed genes (DEGs) by comparing AS patients with non‐AS patients. Key genes among the related DEGs were identified through protein–protein interaction networks and hub gene screening and further validated using immunohistochemistry. We performed clustering and annotation of the single‐cell sequencing data and externally validated the findings using the GSE232131 single‐cell dataset. By integrating transcriptome data, we assessed the differential expression of immune cells in AS. Finally, we explored the interactions between immune cells in AS through cell communication analysis. The upregulated gene CD74 was identified as a hub gene in T cells in AS. Further research revealed the important relationship between T cells and NK cells in the fundamental processes of AS. Additionally, we found that the macrophage migration inhibitory factor signalling pathway is prominently expressed in the interactions among various cell types in AS. [ABSTRACT FROM AUTHOR]

Gefitinib resistance (GR) presents a significant challenge in treating lung adenocarcinoma (LUAD), highlighting the need for alternative therapies. This study explores the genetic basis of GR to improve prediction, prevention, and treatment strategies. We utilized public databases to obtain GR gene sets, single‐cell data, and transcriptome data, applying univariate and multivariate regression analyses alongside machine learning to identify key genes and develop a predictive signature. The signature's performance was evaluated using survival analysis and time‐dependent ROC curves on internal and external datasets. Enrichment and tumor immune microenvironment analyses were conducted to understand the mechanistic roles of the signature genes in GR. Our analysis identified a robust 22‐gene signature with strong predictive performance across validation datasets. This signature was significantly associated with chromosomal processes, DNA replication, immune cell infiltration, and various immune scores based on enrichment and tumor microenvironment analyses. Importantly, the signature also showed potential in predicting the efficacy of immunotherapy in LUAD patients. Moreover, we identified alternative agents to gefitinib that could offer improved therapeutic outcomes for high‐risk and low‐risk patient groups, thereby guiding treatment strategies for gefitinib‐resistant patients. In conclusion, the 22‐gene signature not only predicts prognosis and immunotherapy efficacy in gefitinib‐resistant LUAD patients but also provides novel insights into non‐immunotherapy treatment options. [ABSTRACT FROM AUTHOR]

IgA nephropathy (IgAN) is the most prevalent primary glomerulonephritis, resulting in end‐stage renal disease and increased mortality rates. Prognostic biomarkers reflecting molecular mechanisms for effective IgAN management are urgently needed. Analysis of kidney single‐cell transcriptomic sequencing data demonstrated that IgAN expressed high‐expression levels of inflammatory cytokines TNFSF10, TNFSF12, CCL2, CXCL1, and CXCL12 than healthy controls (HCs). We also measured the urine proteins in 120 IgAN (57 stable and 63 progressive) and 32 HCs using the proximity extension assay (PEA), and the multivariable and least absolute shrinkage and selection operator (LASSO) logistic regression analysis both revealed that CXCL12, MCP1 were the prognostic significant variables to predict IgAN progression severity. These two proteins exhibited negative correlation with the estimated glomerular filtration rate (eGFR) and patients with higher expression levels of these two proteins had a higher probability to have poorer renal outcome. We further developed a risk index model utilizing CXCL12, MCP1, and baseline clinical indicators, which achieved an impressive area under the curve (AUC) of 0.896 for prediction of IgAN progression severity. Our study highlights the significance of the inflammatory protein biomarkers for noninvasive prediction of IgAN severity and progression, offering valuable insights for clinical management. [ABSTRACT FROM AUTHOR]

Heart failure (HF) is a prevalent cardiovascular disease with significant morbidity and mortality rates worldwide. Due to the intricate structure of the heart, diverse cell types, and the complex pathogenesis of HF, further in‐depth investigation into the underlying mechanisms is required. The elucidation of the heterogeneity of cardiomyocytes and the intercellular communication network is particularly important. Traditional high‐throughput sequencing methods provide an average measure of gene expression, failing to capture the "heterogeneity" between cells and impacting the accuracy of gene function knowledge. In contrast, single‐cell sequencing techniques allow for the amplification of the entire genome or transcriptome at the individual cell level, facilitating the examination of gene structure and expression with unparalleled precision. This approach offers valuable insights into disease mechanisms, enabling the identification of changes in cellular components and gene expressions during hypertrophy associated with HF. Moreover, it reveals distinct cell populations and their unique roles in the HF microenvironment, providing a comprehensive understanding of the cellular landscape that underpins HF pathogenesis. This review focuses on the insights provided by single‐cell sequencing techniques into the mechanisms underlying HF and discusses the challenges encountered in current cardiovascular research. [ABSTRACT FROM AUTHOR]

Distal metastases result from metastatic microenvironment and tumour epithelial cell interactions, the cellular heterogeneity of primary colorectal cancer (CRC) and liver metastases (LM) was evaluated by integrating single‐cell sequencing data, and the collected gene expression data from metastatic epithelial cell subsets was used to construct a prognostic model and to identify intercellular receptor‐ligand interactions between epithelial and immune cells in CRC and LM. Multiplex immunofluorescence staining, and in vitro wound healing, cell migration and cell apoptosis assays were performed to further explore the biological relevance of identified potential regulatory molecules. In this study, approximately 17 epithelial cell subtypes were detected, with Epi‐11 cells being highly expressed in LM tissues compared with CRC samples. Furthermore, patients with high expression of the metastasis‐related genetic profile of Epi‐11 had a poorer prognosis. By predicting receptor–ligand interactions, Epi‐11 cells were found to interact more with myeloid and T/natural killer cells in LM tissues when compared to primary CRC samples, which was mediated by the PLXNB1/SEMA4D axis. In addition, high SEMA4D expression was correlated with decreased overall survival of patients with CRC, whereas PLXNB1 was not. SEMA4D knockdown prevented the migration and promoted the apoptosis of HCT116 cells in vitro. In summary, Epi‐11 cells, an important subset of epithelial cells, may drive the LM of CRC and act by crosstalk with immune cells through the PLXNB1/SEMA4D signalling axis. [ABSTRACT FROM AUTHOR]

The African turquoise killifish (Nothobranchius furzeri) combines a short lifespan with spontaneous age‐associated loss of neuro‐regenerative capacity, an intriguing trait atypical for a teleost. The impact of aging on the cellular composition of the adult stem cell niches, leading to this dramatic decline in the postnatal neuro‐ and gliogenesis, remains elusive. Single‐cell RNA sequencing of the telencephalon of young adult female killifish of the short‐lived GRZ‐AD strain unveiled progenitors of glial and non‐glial nature, different excitatory and inhibitory neuron subtypes, as well as non‐neural cell types. Sub‐clustering of the progenitors identified four radial glia (RG) cell types, two non‐glial progenitor (NGP) and four intermediate (intercell) cell states. Two astroglia‐like, one ependymal, and one neuroepithelial‐like (NE) RG subtype were found at different locations in the forebrain in line with their role, while proliferative, active NGPs were spread throughout. Lineage inference pointed to NE‐RG and NGPs as start and intercessor populations for glio‐ and neurogenesis. Upon aging, single‐cell RNA sequencing revealed major perturbations in the proportions of the astroglia and intercell states, and in the molecular signatures of specific subtypes, including altered MAPK, mTOR, Notch, and Wnt pathways. This cell catalog of the young regeneration‐competent killifish telencephalon, combined with the evidence for aging‐related transcriptomic changes, presents a useful resource to understand the molecular basis of age‐dependent neuroplasticity. This data is also available through an online database (killifishbrain_scseq). [ABSTRACT FROM AUTHOR]

Solid tumours exhibit a well‐defined architecture, comprising a differentiated core and a dynamic border that interfaces with the surrounding tissue. This border, characterised by distinct cellular morphology and molecular composition, serves as a critical determinant of the tumour's invasive behaviour. Notably, the invasive border of the primary tumour represents the principal site for intravasation of metastatic cells. These cells, known as circulating tumour cells (CTCs), function as 'seeds' for distant dissemination and display remarkable heterogeneity. Advancements in spatial sequencing technology are progressively unveiling the spatial biological features of tumours. However, systematic investigations specifically targeting the characteristics of the tumour border remain scarce. In this comprehensive review, we illuminate key biological insights along the tumour body‐border‐haematogenous metastasis axis over the past five years. We delineate the distinctive landscape of tumour invasion boundaries and delve into the intricate heterogeneity and phenotype of CTCs, which orchestrate haematogenous metastasis. These insights have the potential to explain the basis of tumour invasion and distant metastasis, offering new perspectives for the development of more complex and precise clinical interventions and treatments. [ABSTRACT FROM AUTHOR]

Lymph node metastasis contributed to the leading cause and treatment failure in nasopharyngeal carcinoma (NPC). The microenvironment and the cellular communications of lymph node metastasized tumours determine the tumour progression and therapeutic effect, but the ecosystems about the lymph node metastasis (LNM) for NPC patients remain poorly characterized. Here, we integrated the transcriptomes of 47,618 single cells from eight samples related to NPC LNM. The dynamic immune ecosystems and immunosuppressive microenvironment including T cells, myeloid cells and B cells were observed in the lymph node metastatic samples compared with primary tumours. Additionally, the heterogeneity of epithelial cells was also revealed, and several clusters with expression programs that were associated with the progression‐free survival of NPC patients were identified. Additionally, our data revealed the complex intercellular communications from primary to lymph node metastasis. The rewiring of CCL signalling which plays an important role in tumour metastasis was further identified. Altogether, we systematically characterized the ecosystem of NPC primary and lymph node metastasized tumours, which may shed light on the development of a therapeutic strategy to improve clinical outcomes of NPC patients with lymph node metastasis. [ABSTRACT FROM AUTHOR]

The mechanisms underlying protective immunity in mild Mycoplasma pneumoniae pneumonia (MPP) and the pathogenesis of severe MPP, characterized by dysregulated immune responses, remain unclear. Here, we performed single‐cell RNA sequencing (scRNA‐seq) to profile bronchoalveolar lavage fluid (BALF) samples from 13 healthy donors and 24 hospitalized pediatric patients with MPP, covering both mild and severe cases. Severe MPP patients exhibited high levels of exhausted T cells and M1‐like macrophages, with the exhaustion of T cells attributed to persistent type I interferon signaling and inadequate assistance from CD4+ T cells. Significant cell‐cell interactions between exhausted T cells and programmed death‐ligand 1+ (PD‐L1+) macrophages were detected in severe patients, potentially mediated through inhibitor molecules (e.g., PD1) and their receptors (e.g., PD‐L1), as well as human leukocyte antigen class I molecules and their receptors (e.g., KLRC1/D2), resulting in the dysfunction of anti‐MP immune responses. Mild MPP patients were featured by an increased abundance of neutrophils, coupled with enhanced activation, contributing to protective immunity. Together, our study provides a detailed characterization of the BALF immune landscape in MPP patients, revealing distinct immune characteristics between mild and severe cases, which offers a valuable resource for understanding MPP immunopathogenesis and formulating effective therapeutic strategies. [ABSTRACT FROM AUTHOR]

Radiation‐induced tissue injury (RITI) is the most common complication in clinical tumor radiotherapy. Due to the heterogeneity in the response of different tissues to radiation (IR), radiotherapy will cause different types and degrees of RITI, which greatly limits the clinical application of radiotherapy. Efforts are continuously ongoing to elucidate the molecular mechanism of RITI and develop corresponding prevention and treatment drugs for RITI. Single‐cell sequencing (Sc‐seq) has emerged as a powerful tool in uncovering the molecular mechanisms of RITI and for identifying potential prevention targets by enhancing our understanding of the complex intercellular relationships, facilitating the identification of novel cell phenotypes, and allowing for the assessment of cell heterogeneity and spatiotemporal developmental trajectories. Based on a comprehensive review of the molecular mechanisms of RITI, we analyzed the molecular mechanisms and regulatory networks of different types of RITI in combination with Sc‐seq and summarized the targeted intervention pathways and therapeutic drugs for RITI. Deciphering the diverse mechanisms underlying RITI can shed light on its pathogenesis and unveil new therapeutic avenues to potentially facilitate the repair or regeneration of currently irreversible RITI. Furthermore, we discuss how personalized therapeutic strategies based on Sc‐seq offer clinical promise in mitigating RITI. [ABSTRACT FROM AUTHOR]

Background: Various epigenetic regulations systematically govern gene expression in cells involving various biological processes. Dysregulation of the epigenome leads to aberrant transcriptional programs and subsequently results in diseases, such as cancer. Therefore, comprehensive profiling epigenomics is essential for exploring the mechanisms underlying gene expression regulation during development and disease. Methods: In this study, we developed single‐cell chromatin proteins and accessibility tagmentation (scCPA‐Tag), a multi‐modal single‐cell epigenetic profile capturing technique based on barcoded Tn5 transposases and a droplet microfluidics platform. scCPA‐Tag enables the simultaneous capture of DNA profiles of histone modification and chromatin accessibility in the same cell. Results: By applying scCPA‐Tag to K562 cells and a hepatocellular carcinoma (HCC) sample, we found that the silence of several chromatin‐accessible genes can be attributed to lysine‐27‐trimethylation of the histone H3 tail (H3K27me3) modification. We characterized the epigenetic features of the tumour cells and different immune cell types in the HCC tumour tissue by scCPA‐Tag. Besides, a tumour cell subtype (C2) with more aggressive features was identified and characterized by high chromatin accessibility and a lower abundance of H3K27me3 on tumour‐promoting genes. Conclusions: Our multi‐modal scCPA‐Tag provides a comprehensive approach for exploring the epigenetic landscapes of heterogeneous cell types and revealing the mechanisms of gene expression regulation during developmental and pathological processes at the single‐cell level. Highlights: scCPA‐Tag offers a highly efficient and high throughput technique to simultaneously profile histone modification and chromatin accessibility within a single cell.scCPA‐Tag enables to uncover multiple epigenetic modification features of cellular compositions within tumor tissues.scCPA‐Tag facilitates the exploration of the epigenetic landscapes of heterogeneous cell types and provides the mechanisms governing gene expression regulation. [ABSTRACT FROM AUTHOR]

Despite being one of the most prevalent RNA modifications, the role of N6‐methyladenosine (m6A) in amyotrophic lateral sclerosis (ALS) remains ambiguous. In this investigation, we explore the contribution of genetic defects of m6A‐related genes to ALS pathogenesis. We scrutinized the mutation landscape of m6A genes through a comprehensive analysis of whole‐exome sequencing cohorts, encompassing 508 ALS patients and 1660 population‐matched controls. Our findings reveal a noteworthy enrichment of RNA binding motif protein X‐linked (RBMX) variants among ALS patients, with a significant correlation between pathogenic m6A variants and adverse clinical outcomes. Furthermore, Rbmx knockdown in NSC‐34 cells overexpressing mutant TDP43Q331K results in cell death mediated by an augmented p53 response. Similarly, RBMX knockdown in ALS motor neurons derived from induced pluripotent stem cells (iPSCs) manifests morphological defects and activation of the p53 pathway. Transcriptional analysis using publicly available single‐cell sequencing data from the primary motor cortex indicates that RBMX‐regulated genes selectively influence excitatory neurons and exhibit enrichment in ALS‐implicated pathways. Through integrated analyses, our study underscores the emerging roles played by RBMX in ALS, suggesting a potential nexus between the disease and dysregulated m6A‐mediated mRNA metabolism. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is a typical highly heterogeneous solid tumor with high morbidity and mortality worldwide, especially in China; however, the immune microenvironment of HCC has not been clarified so far. Here, we employed single‐cell RNA sequencing (scRNA‐seq) on diethylnitrosamine (DEN)‐induced mouse HCC model to dissect the immune cell dynamics during tumorigenesis. Our findings reveal distinct immune profiles in both precancerous and cancerous lesions, indicating early tumor‐associated immunological alterations. Notably, specific T and B cell subpopulations are preferentially enriched in the HCC tumor microenvironment (TME). Furthermore, we identified a subpopulation of naïve B cells with high CD83 expression, correlating with improved prognosis in human HCC. These signature genes were validated in The Cancer Genome Atlas HCC RNA‐seq dataset. Moreover, cell interaction analysis revealed that subpopulations of B cells in both mouse and human samples are activated and may potentially contribute to oncogenic processes. In summary, our study provides insights into the dynamic immune microenvironment and cellular networks in HCC pathogenesis, with a specific emphasis on naïve B cells. These findings emphasize the significance of targeting TME in HCC patients to prevent HCC pathological progression, which may give a new perspective on the therapeutics for HCC. [ABSTRACT FROM AUTHOR]

A comprehensive immune landscape for Brucella infection is crucial for developing new treatments for brucellosis. Here, we utilized single‐cell RNA sequencing (scRNA‐seq) of 290,369 cells from 35 individuals, including 29 brucellosis patients from acute (n = 10), sub‐acute (n = 9), and chronic (n = 10) phases as well as six healthy donors. Enzyme‐linked immunosorbent assays were applied for validation within this cohort. Brucella infection caused a significant change in the composition of peripheral immune cells and inflammation was a key feature of brucellosis. Acute patients are characterized by potential cytokine storms resulting from systemic upregulation of S100A8/A9, primarily due to classical monocytes. Cytokine storm may be mediated by activating S100A8/A9‐TLR4‐MyD88 signaling pathway. Moreover, monocytic myeloid‐derived suppressor cells were the probable contributors to immune paralysis in acute patients. Chronic patients are characterized by a dysregulated Th1 response, marked by reduced expression of IFN‐γ and Th1 signatures as well as a high exhausted state. Additionally, Brucella infection can suppress apoptosis in myeloid cells (e.g., mDCs, classical monocytes), inhibit antigen presentation in professional antigen‐presenting cells (APCs; e.g., mDC) and nonprofessional APCs (e.g., monocytes), and induce exhaustion in CD8+ T/NK cells, potentially resulting in the establishment of chronic infection. Overall, our study systemically deciphered the coordinated immune responses of Brucella at different phases of the infection, which facilitated a full understanding of the immunopathogenesis of brucellosis and may aid the development of new effective therapeutic strategies, especially for those with chronic infection. Highlights: scRNA‐seq analysis reveals distinct immune responses across the acute, sub‐acute, and chronic phases of Brucella infection.Acute infection is characterized by a cytokine storm, potentially mediated by the activation of the S100A8/A9‐TLR4‐MyD88 pathway, along with immune suppression driven by Mono‐MDSCsChronic infection is marked by a dysregulated Th1 immune response and widespread exhaustion of T and NK cells. [ABSTRACT FROM AUTHOR]

Single‐cell whole‐genome sequencing (scWGS) detects cell heterogeneity at the aspect of genomic variations, which are inheritable and play an important role in life processes such as aging and cancer progression. The recent explosive development of high‐throughput single‐cell sequencing methods has enabled high‐performance heterogeneity detection through a vast number of novel strategies. Despite the limitation on total cost, technical advances in high‐throughput single‐cell whole‐genome sequencing methods are made for higher genome coverage, parallel throughput, and level of integration. This review highlights the technical advancements in high‐throughput scWGS in the aspects of strategies design, data efficiency, parallel handling platforms, and their applications on human genome. The experimental innovations, remaining challenges, and perspectives are summarized and discussed. [ABSTRACT FROM AUTHOR]

Endometriosis is defined as an oestrogen‐dependent and inflammatory gynaecological disease of which the pathogenesis remains unclear. This study aimed to investigate the cellular heterogeneity and reveal the effect of CD8+ T cells on the progress of endometriosis. Three ovarian endometriosis patients were collected, and single‐cell RNA sequencing (scRNA‐seq) progressed and delineated the cellular landscape of endometriosis containing five cell clusters. The endometrial cells (EMCs) were the major component, of which the mesenchymal cells were preponderant and characterized with increased inflammation and oestrogen synthesis in endometriosis. The proportion of T cells, mainly CD8+ T cells rather than CD4+, was reduced in endometriotic lesions, and the cytokines and cytotoxicity of ectopic T cells were depressed. CD8+ T cells depressed the proliferation of ESCs through inhibiting CDK1/CCNB1 pathway to arrest the cell cycle and triggered inflammation through activating STAT1 pathway. Correspondingly, the coculture with ESCs resulted in the dysfunction of CD8+ T cells through upregulating STAT1/PDCD1 pathway and glycolysis‐promoted metabolism reprogramming. The endometriotic lesions were larger in nude mouse models with T‐cell deficiency than the normal mouse models. The inhibition of T cells via CD90.2 or CD8A antibody increased the endometriotic lesions in mouse models, and the supplement of T cells to nude mouse models diminished the lesion sizes. In conclusion, this study revealed the global cellular variation of endometriosis among which the cellular count and physiology of EMCs and T cells were significantly changed. The depressed cytotoxicity and aberrant metabolism of CD8+ T cells were induced by ESCs with the activation of STAT1/PDCD1 pathway resulting in immune survival to promote endometriosis. [ABSTRACT FROM AUTHOR]

Objective: This narrative review illuminates on the application of single‐cell RNA sequencing (scRNA‐seq) and spatial transcriptomics (ST) in periodontitis and highlights the probability of relating cell population and gene signatures to the pathogenesis of the disease for a better diagnosis. Methods: An electronic search of the literature in the PubMed database for the keywords, "single cell sequencing" OR "spatial transcriptomics" and "periodontitis" OR "gingiva" OR "oral mucosa" yielded 486 research articles and reviews. After filtering duplicates and careful curation, 22 papers conducted in humans were retained. Results: The molecular mechanisms underlying periodontitis are complex and involve the interaction of multiple cells and various gene expressions. Most residing cells in periodontal tissues participate in maintaining homeostasis and health, while in addition to infiltrating immune cells contribute to the fight against the bacterial insult. Conclusion: scRNA‐seq and ST have provided new insights into the cellular and molecular changes associated with periodontitis for a better diagnosis and clinical outcome. New functions of cells and genes are revealed with these techniques; however, no cells or gene signatures are attributed to periodontitis so far. [ABSTRACT FROM AUTHOR]

Intracerebral hemorrhage (ICH) poses a formidable challenge in stroke management, with limited therapeutic options, particularly in the realm of immune‐targeted interventions. Clinical trials targeting immune responses post‐ICH have encountered setbacks, potentially attributable to the substantial cellular heterogeneity and intricate intercellular networks within the brain. Here, we present a pioneering investigation utilizing single‐cell RNA sequencing and spatial transcriptome profiling at hyperacute (1 h), acute (24 h), and subacute (7 days) intervals post‐ICH, aimed at unraveling the dynamic immunological landscape and spatial distributions within the cerebral tissue. Our comprehensive analysis revealed distinct cell differentiation patterns among myeloid and lymphocyte populations, along with delineated spatial distributions across various brain regions. Notably, we identified a subset of lymphocytes characterized by the expression of Spp1 and Lyz2, termed macrophage‐associated lymphocytes, which exhibited close interactions with myeloid cells. Specifically, we observed prominent interactions between Lgmn+Macro‐T cells and microglia through the spp1–cd44 pathway during the acute phase post‐ICH in the choroid plexus. These findings represent a significant advancement in our understanding of immune cell dynamics at single‐cell resolution across distinct post‐ICH time points, thereby laying the groundwork for exploring critical temporal windows and informing the development of targeted therapeutic strategies. [ABSTRACT FROM AUTHOR]

Background: The significance of regulatory T cells (Tregs) in colorectal cancer is unclear. Methods: The single‐cell sequencing data for colorectal cancer, specifically GSE132465 and GSE188711, were retrieved from the GEO database. Simultaneously, bulk transcriptome data were obtained from the UCSC Xena website. To delve into the heterogeneity of Treg cells and identify key genes at the single‐cell sequencing level, we employed dimensionality reduction techniques alongside clustering and conducted differential expression gene analysis. For the bulk transcriptome data, we utilized weighted co‐expression network analysis to investigate critical gene modules. Additionally, we employed COX regression and Lasso regression methodologies to construct prognostic models, thereby assessing patient outcomes. To facilitate outcome evaluation, nomograms were constructed. The integration of these diverse approaches aims to comprehensively study colorectal cancer, encompassing single‐cell heterogeneity, key gene identification, and prognosis modeling using both single‐cell and bulk transcriptome data. Polymerase chain reaction (PCR) experiments are used to verify mRNA expression levels of key genes. The analysis software was R software (version 4.3.2). Results: Through single‐cell sequencing analysis and bulk transcriptome analysis, we constructed a prognostic model composed with Treg‐associated signatures. The high‐risk group demonstrated significantly worse prognosis compared with the low‐risk group, highlighting the clinical relevance of our models. PCR confirmed that the key gene DEAH‐box helicase 15 (DHX15) was significantly overexpressed in colorectal cancer. Conclusions: The prognostic models developed in this study offer a potential tool for risk assessment, guiding treatment decisions for colorectal cancer patients. [ABSTRACT FROM AUTHOR]

Recent advances in genomic technology, including the rapid development of long‐read sequencing technology and single‐cell RNA‐sequencing methods, are poised to significantly expand the kinds of studies that are feasible in ecological genomics. In this perspective, we review these new technologies and discuss their potential impact on gene expression studies in non‐model organisms. Although traditional RNA‐sequencing methods have been an extraordinarily powerful tool to apply functional genomics in an ecological context, bulk RNA‐seq approaches often rely on de novo transcriptome assembly, and cannot capture expression changes in rare cell populations or distinguish shifts in cell type abundance. Advancements in genome assembly technology, particularly long‐read sequencing, and improvements in the scalability of single‐cell RNA‐sequencing (scRNA‐seq) offer unprecedented resolution in understanding cellular heterogeneity and gene regulation. We discuss the potential of these technologies to enable disentangling differential gene regulation from cell type composition differences and uncovering subtle expression patterns masked by bulk RNA‐seq. The integration of these approaches provides a more nuanced understanding of the ecological and evolutionary dynamics of gene expression, paving the way for refined models and deeper insights into the generation of biodiversity. [ABSTRACT FROM AUTHOR]

Recently, the pathomechanisms of keloids have been extensively researched using transcriptomic analysis, but most studies did not consider the activity of keloids. We aimed to profile the transcriptomics of keloids according to their clinical activity and location within the keloid lesion, compared with normal and mature scars. Tissue samples were collected (keloid based on its activity (active and inactive), mature scar from keloid patients and normal scar (NS) from non‐keloid patients). To reduce possible bias, all keloids assessed in this study had no treatment history and their location was limited to the upper chest or back. Multiomics assessment was performed by using single‐cell RNA sequencing and multiplex immunofluorescence. Increased mesenchymal fibroblasts (FBs) was the main feature in keloid patients. Noticeably, the proportion of pro‐inflammatory FBs was significantly increased in active keloids compared to inactive ones. To explore the nature of proinflammatory FBs, trajectory analysis was conducted and CCN family associated with mechanical stretch exhibited higher expression in active keloids. For vascular endothelial cells (VECs), the proportion of tip and immature cells increased in keloids compared to NS, especially at the periphery of active keloids. Also, keloid VECs highly expressed genes with characteristics of mesenchymal activation compared to NS, especially those from the active keloid center. Multiomics analysis demonstrated the distinct expression profile of active keloids. Clinically, these findings may provide the future appropriate directions for development of treatment modalities of keloids. Prevention of keloids could be possible by the suppression of mesenchymal activation between FBs and VECs and modulation of proinflammatory FBs may be the key to the control of active keloids. [ABSTRACT FROM AUTHOR]

Background: Lung cancer stands out as a highly perilous malignant tumor with severe implications for human health. There has been a growing interest in neutrophils as a result of their role in promoting cancer in recent years. Thus, the present study aimed to investigate the heterogeneity of neutrophils in non‐small cell lung cancer (NSCLC). Methods: Single‐cell RNA sequencing of tumor‐associated neutrophils (TANs) and polymorphonuclear neutrophils sourced from the Gene Expression Omnibus database was analyzed. Moreover, cell–cell communication, differentiation trajectories and transcription factor analyses were performed. Results: Neutrophils were found to be closely associated with macrophages. Four major types of TANs were identified: a transitional subcluster that migrated from blood to tumor microenvironment (TAN‐0), an inflammatory subcluster (TAN‐1), a subpopulation that displayed a distinctive transcriptional signature (TAN‐2) and a final differentiation state that promoted tumor formation (TAN‐3). Meanwhile, TAN‐3 displayed a marked increase in glycolytic activity. Finally, transcription factors were analyzed to uncover distinct TAN cluster‐specific regulons. Conclusions: The discovery of the dynamic characteristics of TANs in the present study is anticipated to contribute to yielding a better understanding of the tumor microenvironment and advancing the treatment of NSCLC. [ABSTRACT FROM AUTHOR]

Hormones promote the progression of prostate cancer (PRCA) through the activation of a complex regulatory network. Inhibition of hormones or modulation of specific network nodes alone is insufficient to suppress the entire oncogenic network. Therefore, it is imperative to elucidate the mechanisms underlying the occurrence and development of PRCA in order to identify reliable diagnostic markers and therapeutic targets. To this end, we used publicly available data to analyze the potential mechanisms of hormone‐stimulated genes in PRCA, construct a prognostic model, and assess immune infiltration and drug sensitivity. The single‐cell RNA‐sequencing data of PRCA were subjected to dimensionality reduction clustering and annotation, and the cells were categorized into two groups based on hormone stimulus‐related scores. The differentially expressed genes between the two groups were screened and incorporated into the least absolute shrinkage and selection operator machine learning algorithm, and a prognostic model comprising six genes (ZNF862, YIF1A, USP22, TAF7, SRSF3, and SPARC) was constructed. The robustness of the model was validation through multiple methods. Immune infiltration scores in the two risk groups were calculated using three different algorithms. In addition, the relationship between the model genes and immune cell infiltration, and that between risk score and immune cell infiltration were analyzed. Drug sensitivity analysis was performed for the model genes and risk score using public databases to identify potential candidate drugs. Our findings provide novel insights into the mechanisms of hormone‐stimulated genes in PRCA progression, prognosis, and drug screening. [ABSTRACT FROM AUTHOR]

We investigated subarachnoid haemorrhage (SAH) macrophage subpopulations and identified relevant key genes for improving diagnostic and therapeutic strategies. SAH rat models were established, and brain tissue samples underwent single‐cell transcriptome sequencing and bulk RNA‐seq. Using single‐cell data, distinct macrophage subpopulations, including a unique SAH subset, were identified. The hdWGCNA method revealed 160 key macrophage‐related genes. Univariate analysis and lasso regression selected 10 genes for constructing a diagnostic model. Machine learning algorithms facilitated model development. Cellular infiltration was assessed using the MCPcounter algorithm, and a heatmap integrated cell abundance and gene expression. A 3 × 3 convolutional neural network created an additional diagnostic model, while molecular docking identified potential drugs. The diagnostic model based on the 10 selected genes achieved excellent performance, with an AUC of 1 in both training and validation datasets. The heatmap, combining cell abundance and gene expression, provided insights into SAH cellular composition. The convolutional neural network model exhibited a sensitivity and specificity of 1 in both datasets. Additionally, CD14, GPNMB, SPP1 and PRDX5 were specifically expressed in SAH‐associated macrophages, highlighting its potential as a therapeutic target. Network pharmacology analysis identified some targeting drugs for SAH treatment. Our study characterised SAH macrophage subpopulations and identified key associated genes. We developed a robust diagnostic model and recognised CD14, GPNMB, SPP1 and PRDX5 as potential therapeutic targets. Further experiments and clinical investigations are needed to validate these findings and explore the clinical implications of targets in SAH treatment. [ABSTRACT FROM AUTHOR]

Liver metastasis (LM) is an important factor leading to colorectal cancer (CRC) mortality. However, the effect of T‐cell exhaustion on LM in CRC is unclear. Single‐cell sequencing data derived from the Gene Expression Omnibus database. Data were normalized using the Seurat package and subsequently clustered and annotated into different cell clusters. The differentiation trajectories of epithelial cells and T cells were characterized based on pseudo‐time analysis. Single‐sample gene set enrichment analysis (ssGSEA) was used to calculate enrichment scores for different cell clusters and to identify enriched biological pathways. Finally, cell communication analysis was performed. Nine cell subpopulations were identified from CRC samples with LM. The proportion of T cells increased in LM. T cells can be subdivided into NK/T cells, regulatory T cells (Treg) and exhausted T cells (Tex). In LM, cell adhesion and proliferation activity of Tex were promoted. Epithelial cells can be categorized into six subpopulations. The transformation of primary CRC into LM involved two evolutionary branches of Tex cells. Epithelial cells two were at the beginning of the trajectory in CRC but at the end of the trajectory in CRC with LM. The receptor ligands CEACAM5 and ADGRE5‐CD55 played critical roles in the interactions between Tex and Treg cell‐epithelial cell, which may promote the epithelial‐mesenchymal transition process in CRC. Tex cells are able to promote the process of LM in CRC, which in turn promotes tumour development. This provides a new perspective on the treatment and diagnosis of CRC. [ABSTRACT FROM AUTHOR]

Liver hepatocellular carcinoma (LIHC) is a highly lethal form of cancer that is among the deadliest cancer types globally. In terms of cancer‐related mortality rates, liver cancer ranks among the top three, underscoring the severity of this disease. Insufficient analysis has been conducted to fully understand the potential value of the extracellular matrix (ECM) in immune infiltration and the prognostic stratification of LIHC, despite its recognised importance in the development of this disease. The scRNA‐seq data of GSE149614 was used to conduct single‐cell analysis on 10 LIHC samples. CellChat scores were calculated for seven cell populations in the descending cohort to investigate cellular communication, while PROGENy scores were calculated to determine tumour‐associated pathway scores in different cell populations. The pathway analysis using GO and KEGG revealed the enrichment of ECM‐associated genes in the pathway, highlighting the potential role of the ECM in LIHC development. By utilizing the TCGA‐LIHC cohort, an ECM‐based prognostic model for LIHC was developed using Lasso regression. Immune infiltration scores were calculated using two methods, and the performance of the ECM‐related risk score was evaluated using an independent cohort from the CheckMate study. To determine the precise expression of ECM‐associated risk genes in LIHC, we evaluated hepatocellular carcinoma cell lines using a range of assays, including Western blotting, invasion assays and Transwell assays. Using single‐cell transcriptome analysis, we annotated the spatially‐specific distribution of major immune cell types in single‐cell samples of LIHC. The main cell types identified and annotated included hepatocytes, T cells, myeloid cells, epithelial cells, fibroblasts, endothelial cells and B cells. The utilisation of cellchat and PROGENy analyses enabled the investigation and unveiling of signalling interactions, protein functionalities and the prominent influential pathways facilitated by the primary immune cell types within the LIHC. Numerous tumour pathways, including PI2K, EGFR and TGFb, demonstrated a close correlation with the involvement of ECM in LIHC. Moreover, an evaluation was conducted to assess the primary ECM‐related functional changes and biological pathway enrichment in LIHC. Differential genes associated with ECM were identified and utilised to create prognostic models. The prognostic stratification value of these models for LIHC patients was confirmed through validation in multiple databases. Furthermore, through immune infiltration analysis, it was discovered that ECM might be linked to the irregular expression and regulation of numerous immune cells. Additionally, histone acetylation was mapped against gene mutation frequencies and differential expression profiles. The prognostic stratification efficacy of the ECM prediction model constructed in the context of PD‐1 inhibitor therapy was also examined, and it exhibited strong stratification performance. Cellular experiments, including Western blotting, invasion and Transwell assays, revealed that ECM‐associated risk genes have a promoting effect on the development of LIHC. The creation of biomarkers for LIHC using ECM‐related genes unveiled substantial correlations with immune microenvironmental infiltration and functional mutations in various tumour pathways. This enlightens us to the possibility that the influence of ECM on tumours may extend beyond simply promoting the fibrotic process and the stromal composition of tumours. [ABSTRACT FROM AUTHOR]

Aims: This study aimed to investigate the potential therapeutic applications of stigmasterol for treating neuropathic pain. Methods: Related mechanisms were investigated by DRG single‐cell sequencing analysis and the use of specific inhibitors in cellular experiments. In animal experiments, 32 male Sprague–Dawley rats were randomly divided into the sham operation group, CCI group, ibuprofen group, and stigmasterol group. We performed behavioral tests, ELISA, H&E staining and immunohistochemistry, and western blotting. Results: Cell communication analysis by single‐cell sequencing reveals that after peripheral nerve injury, Schwann cells secrete IL‐34 to act on CSF1R in macrophages. After peripheral nerve injury, the mRNA expression levels of CSF1R pathway and NLRP3 inflammasome in macrophages were increased in DRG. In vitro studies demonstrated that stigmasterol can reduce the secretion of IL‐34 in LPS‐induced RSC96 Schwann cells; stigmasterol treatment of LPS‐induced Schwann cell‐conditioned medium (L‐S‐CM) does not induce the proliferation and migration of RAW264.7 macrophages; L‐S‐CM reduces CSF1R signaling pathway (CSF1R, P38MAPK, and NFκB) activation, NLRP3 inflammasome activation, and ROS production. In vivo experiments have verified that stigmasterol can reduce thermal and cold hyperalgesia in rat chronic compressive nerve injury (CCI) model; stigmasterol can reduce IL‐1β, IL‐6, TNF‐α, CCL2, SP, and PGE2 in serum of CCI rats; immunohistochemistry and western blot confirmed that stigmasterol can reduce the levels of IL‐34/CSF1R signaling pathway and NLRP3 inflammasome in DRG of CCI rats. Conclusion: Stigmasterol alleviates neuropathic pain by reducing Schwann cell‐macrophage cascade in DRG by modulating IL‐34/CSF1R axis. [ABSTRACT FROM AUTHOR]

Cutaneous melanoma poses a formidable challenge within the field of oncology, marked by its aggressive nature and capacity for metastasis. Despite extensive research uncovering numerous genetic and molecular contributors to cutaneous melanoma development, there remains a critical knowledge gap concerning the role of lipids, notably low‐density lipoprotein (LDL), in this lethal skin cancer. This article endeavours to bridge this knowledge gap by delving into the intricate interplay between LDL metabolism and cutaneous melanoma, shedding light on how lipids influence tumour progression, immune responses and potential therapeutic avenues. Genes associated with LDL metabolism were extracted from the GSEA database. We acquired and analysed single‐cell sequencing data (GSE215120) and bulk‐RNA sequencing data, including the TCGA data set, GSE19234, GSE22153 and GSE65904. Our analysis unveiled the heterogeneity of LDL across various cell types at the single‐cell sequencing level. Additionally, we constructed an LDL‐related signature (LRS) using machine learning algorithms, incorporating differentially expressed genes and highly correlated genes. The LRS serves as a valuable tool for assessing the prognosis, immunity and mutation status of patients with cutaneous melanoma. Furthermore, we conducted experiments on A375 and WM‐115 cells to validate the function of PPP2R1A, a pivotal gene within the LRS. Our comprehensive approach, combining advanced bioinformatics analyses with an extensive review of current literature, presents compelling evidence regarding the significance of LDL within the cutaneous melanoma microenvironment. [ABSTRACT FROM AUTHOR]

Despite its importance, the functional heterogeneity surrounding the dynamics of interactions between mycobacterium tuberculosis and human immune cells in determining host immune strength and tuberculosis (TB) outcomes, remains far from understood. This work now describes the development of a new technological platform to elucidate the immune function differences in individuals with TB, integrating single‐cell RNA sequencing and cell surface antibody sequencing to provide both genomic and phenotypic information from the same samples. Single‐cell analysis of 23 990 peripheral blood mononuclear cells from a new cohort of primary TB patients and healthy controls enables to not only show four distinct immune phenotypes (TB, myeloid, and natural killer (NK) cells), but also determine the dynamic changes in cell population abundance, gene expression, developmental trajectory, transcriptomic regulation, and cell–cell signaling. In doing so, TB‐related changes in immune cell functions demonstrate that the immune response is mediated through host T cells, myeloid cells, and NK cells, with TB patients showing decreased naive, cytotoxicity, and memory functions of T cells, rather than their immunoregulatory function. The platform also has the potential to identify new targets for immunotherapeutic treatment strategies to restore T cells from dysfunctional or exhausted states. [ABSTRACT FROM AUTHOR]

Objective: Proliferative verrucous leukoplakia (PVL) is characterized by a spectrum of clinicopathological features and a high risk of malignant transformation. In this study, we aimed to delineate the dynamic changes in molecular signature during PVL progression and identify the potential cell subtypes that play a key role in the premalignant evolution of PVL. Methods: We performed single‐cell RNA sequencing on three biopsy samples from a large PVL lesion. These samples exhibited a histopathological continuum of PVL progression. Results: By analyzing the transcriptome profiles of 27,611 cells from these samples, we identified ten major cell lineages and revealed that cellular remodeling occurred during the progression of PVL lesions, including epithelial, stromal, and immune cells. Epithelial cells are shifted to tumorigenic states and secretory patterns at the premalignant stage. Immune cells showed growing immunosuppressive phenotypes during PVL progression. Remarkably, two novel cell subtypes INSR+ endothelial cells and ASPN+ fibroblasts, were discovered and may play vital roles in microenvironment remodeling, such as angiogenesis and stromal fibrosis, which are closely involved in malignant transformation. Conclusion: Our work is the first to depict the cellular landscape of PVL and speculate that disease progression may be driven by functional remodeling of multiple cell subtypes. [ABSTRACT FROM AUTHOR]

The global COVID‐19 pandemic has caused more than 1 billion infections, and numerous SARS‐CoV‐2 vaccines developed rapidly have been administered over 10 billion doses. The world is continuously concerned about the cytokine storms induced by the interaction between SARS‐CoV‐2 and host, long COVID, breakthrough infections postvaccination, and the impact of SARS‐CoV‐2 variants. BCR‐CDR3 repertoire serves as a molecular target for monitoring the antiviral response "trace" of B cells, evaluating the effects, mechanisms, and memory abilities of individual responses to B cells, and has been successfully applied in analyzing the infection mechanisms, vaccine improvement, and neutralizing antibodies preparation of influenza virus, HIV, MERS, and Ebola virus. Based on research on BCR‐CDR3 repertoire of COVID‐19 patients and volunteers who received different SARS‐CoV‐2 vaccines in multiple laboratories worldwide, we focus on analyzing the characteristics and changes of BCR‐CDR3 repertoire, such as diversity, clonality, V&J genes usage and pairing, SHM, CSR, shared CDR3 clones, as well as the summary on BCR sequences targeting virus‐specific epitopes in the preparation and application research of SARS‐CoV‐2 potential therapeutic monoclonal antibodies. This review provides comparative data and new research schemes for studying the possible mechanisms of differences in B cell response between SARS‐CoV‐2 infection or vaccination, and supplies a foundation for improving vaccines after SARS‐CoV‐2 mutations and potential antibody therapy for infected individuals. [ABSTRACT FROM AUTHOR]

Adenocarcinoma of the bladder is a rare urinary bladder carcinoma with limited therapy options due to lack of molecular characterization. Here, we aimed to reveal the mutational and transcriptomic landscapes of adenocarcinoma of the bladder and assess any relationship with prognosis. Between February 2015 and June 2021, a total of 23 patients with adenocarcinoma of the bladder were enrolled. These included 16 patients with primary bladder adenocarcinomas and seven patients with urachal adenocarcinoma. Whole exome sequencing (16 patients), whole genome sequencing (16 patients), bulk RNA sequencing (RNA‐seq) (19 patients), and single‐cell RNA‐seq (5 patients) were conducted for the specimens. Correlation analysis, survival analysis, and t‐tests were also performed. Prevalent T>A substitutions were observed among somatic mutations, and major trinucleotide contexts included 5'‐CTC‐3' and 5'‐CTG‐3'. This pattern was mainly contributed by COSMIC signature 22 related to chemical carcinogen exposure (probably aristolochic acid), which has not been reported in bladder adenocarcinoma. Moreover, genes with copy number changes were also enriched in the KEGG term 'chemical carcinogenesis'. Transcriptomic analysis suggested high immune cell infiltration and luminal‐like features in the majority of samples. Interestingly, a small fraction of samples with an APOBEC‐derived mutational signature exhibited a higher risk of disease progression compared with samples with only a chemical carcinogen‐related signature, confirming the molecular and prognostic heterogeneity of bladder adenocarcinoma. This study presents mutational and transcriptomic landscapes of bladder adenocarcinoma, and indicates that a chemical carcinogen‐related mutational signature may be related to a better prognosis compared with an APOBEC signature in adenocarcinoma of the bladder. © 2024 The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

Background: Cryptorchidism is a condition in which one or both of a baby's testicles do not fully descend into the bottom of the scrotum. Newborns with cryptorchidism are at increased risk of developing infertility later in life. The aim of this study was to develop a novel diagnostic model for cryptorchidism and to identify new biomarkers associated with cryptorchidism. Methods: The study data were obtained from RNA sequencing data of cryptorchid patients from Nantong University Hospital and the Gene Expression Omnibus (GEO) database. Differential expression analysis was used to obtain differentially expressed genes (DEGs) between the control and cryptorchid groups. These DEGs were analyzed for their functions by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment using GSEA software. Random Forest algorithm was used to screen central genes based on these DEGs. Neuralnet software package was used to develop artificial neural network models. Based on clinical data, receiver operating characteristic (ROC) was used to validate the models. Single‐cell sequencing analysis was used for the pathogenesis of cryptorchidism. Results: We obtained a total of 525 important DEGs related to cryptorchidism, which are mainly associated with biological functions such as supramolecular complexes and microtubule cytoskeleton. Random forest approach screening obtained eight hub genes. A neural network based on the hub genes showed a 100% success rate of the model. Finally, single‐cell sequencing analysis validated the hub genes. Conclusion: We developed a novel diagnostic model for cryptorchidism using artificial neural networks and validated its utility as an effective diagnostic tool. [ABSTRACT FROM AUTHOR]

Background: Intervertebral disc degeneration (IDD) is a significant cause of low back pain and poses a significant public health concern. Genetic factors play a crucial role in IDD, highlighting the need for a better understanding of the underlying mechanisms. Aim: The aim of this study was to identify potential IDD‐related biomarkers using a comprehensive bioinformatics approach and validate them in vitro. Materials and Methods: In this study, we employed several analytical approaches to identify the key genes involved in IDD. We utilized weighted gene coexpression network analysis (WGCNA), MCODE, LASSO algorithms, and ROC curves to identify the key genes. Additionally, immune infiltrating analysis and a single‐cell sequencing dataset were utilized to further explore the characteristics of the key genes. Finally, we conducted in vitro experiments on human disc tissues to validate the significance of these key genes in IDD. Results: we obtained gene expression profiles from the GEO database (GSE23130 and GSE15227) and identified 1015 DEGs associated with IDD. Using WGCNA, we identified the blue module as significantly related to IDD. Among the DEGs, we identified 47 hub genes that overlapped with the genes in the blue module, based on criteria of |logFC| ≥ 2.0 and p.adj <0.05. Further analysis using both MCODE and LASSO algorithms enabled us to identify five key genes, of which CKAP4 and SSR1 were validated by GSE70362, demonstrating significant diagnostic value for IDD. Additionally, immune infiltrating analysis revealed that monocytes were significantly correlated with the two key genes. We also analyzed a single‐cell sequencing dataset, GSE199866, which showed that both CKAP4 and SSR1 were highly expressed in fibrocartilage chondrocytes. Finally, we validated our findings in vitro by performing real time polymerase chain reaction (RT‐PCR) and immunohistochemistry (IHC) on 30 human disc samples. Our results showed that CKAP4 and SSR1 were upregulated in degenerated disc samples. Taken together, our findings suggest that CKAP4 and SSR1 have the potential to serve as disease biomarkers for IDD. [ABSTRACT FROM AUTHOR]

Aim: To reveal the cellular composition and molecular environment of the periodontal and peri‐implant inflammatory infiltrates through a single‐cell sequencing technique, which may explain the pathological difference between these two diseases. A special focus was placed on the phenotypes and potential roles of neutrophils and fibroblasts in peri‐implant/periodontal tissue immunity. Materials and Methods: High‐throughput single‐cell transcriptomic profiling of peri‐implant tissues from patients with peri‐implantitis as well as periodontal tissues from patients with periodontitis and healthy donors was performed. Immunofluorescence analysis was carried out to further validate the identified cell subtypes and their involvement in peri‐implantitis and periodontitis. Results: Based on our single‐cell resolution analysis, a quantified proportional increase of neutrophil (Neu) subtypes was shown in peri‐implantitis. Among these, a predominance of Neutro_CXCR2 was revealed. We also found the involvement of inflammation‐promoting fibroblasts as well as a predominance of CXCL8+ fibroblast–CXCR2+ neutrophil interaction in peri‐implantitis. Conclusions: Our study indicated that the predominance of CXCL8+ fibroblast–CXCR2+ neutrophil interaction might underline the enhanced host response in peri‐implantitis compared with periodontitis. This information offers a molecular basis by which fibroblast and neutrophil subtypes might be diagnostically and therapeutically targeted in peri‐implantitis. [ABSTRACT FROM AUTHOR]

Despite substantial advances in cancer biology and treatment, the clinical outcomes of patients with lung cancer remain unsatisfactory. The tumor microenvironment (TME) is a potential target. Using single‐cell RNA sequencing, we could distinguish eight distinct cell types in the lung cancer microenvironment, demonstrating substantial intratumoral heterogeneity in 19 different lung cancer tumor samples. Through the re‐dimensional grouping of cancer‐associated fibroblasts (CAFs), myeloid cells, epithelial cells, natural killer (NK) cells, and T cells, the difference in the TME of lung cancer was revealed. We discovered SFTPB, SFN, and KRT8 as possible predictive biomarkers for lung cancer by assessing the gene expression patterns in epithelial cells. Examining cell‐to‐cell communications showed a robust association between the quantity of matrix CAFs, epithelial cells, and macrophages in the thrombospondin signaling pathway. Additionally, we found that the amyloid precursor protein signaling pathway primarily originated from the matrix, and inflammatory cancer‐associated endothelial and fibroblast cells showed a co‐expression relationship with myeloid cells and B cells. Through cell‐to‐cell correlation analysis, we found positive regulation between NK cells, regulatory T cells, GZMB‐CD8 T cells, and GZMK‐CD8 T cells, which could play a role in developing immune TMEs. These findings support studies on cancer heterogeneity and add to our understanding of lung cancer's cellular microenvironment. [ABSTRACT FROM AUTHOR]

Breast cancer is the most common malignancy in the world and one of the leading causes of cancer death, which is a heterogeneous disease involving genetic and environmental factors. Breast cancer stem cells (BCSCs) are the main players in the aggressiveness of different tumors, at the same time, these cells are the main challenge for cancer treatment. There are multiple treatment options for breast cancer (BC) patients and the lack of understanding of prognostic and predictive biomarkers for breast cancer is a potential research direction for us to develop better treatments in the future. In this paper, we conducted a correlation analysis between SIK2 and clinical traits by searching numerous BRCA datasets in the GEO database. The model was constructed and validated by incorporating tumor samples from the TCGA‐BRCA cohort. Surprisingly, we found differential expression of SIK2 gene in individual tumor samples from the UCSC database. Subsequently, we found significantly high expression of SIK2 in epithelial cells by comparing the differential expression of SIK2 in different cell subpopulations and performed subsequent immune infiltration and pathway correlation analysis. Differential genes in SIK2+ epithelial cells, which may be potential therapeutic targets for breast cancer. In conclusion, our results suggest that SIK2 may be a potential prognostic and predictive biomarker that could serve as an oncogenic messenger for breast cancer. This discovery of SIK2 may provide more valuable references for potential therapeutic tools for breast cancer. [ABSTRACT FROM AUTHOR]

Simultaneous profiling of DNA methylation and gene expression within single cells is a powerful technology to dissect complex gene regulatory network of cells. However, existing methods are based on picking a single‐cell in a tube and split single‐cell lysate into two parts for transcriptome and methylome library construction, respectively, which is costly and cumbersome. Here, DIRECT is proposed, a digital microfluidics‐based method for high‐efficiency single‐cell isolation and simultaneous analysis of the methylome and transcriptome in a single library construction. The accuracy of DIRECT is demonstrated in comparison with bulk and single‐omics data, and the high CpG site coverage of DIRECT allows for precise analysis of copy number variation information, enabling expansion of single cell analysis from two‐ to three‐omics. By applying DIRECT to monitor the dynamics of mouse embryonic stem cell differentiation, the relationship between DNA methylation and changes in gene expression during differentiation is revealed. DIRECT enables accurate, robust, and reproducible single‐cell DNA methylation and gene expression co‐analysis in a more cost‐effective, simpler library preparation and automated manner, broadening the application scenarios of single‐cell multi‐omics analysis and revealing a more comprehensive and fine‐grained map of cellular regulatory landscapes. [ABSTRACT FROM AUTHOR]

Background: The role of genes associated with the cuproptosis cell signaling pathway in prognosis and immunotherapy in ovarian cancer (OC) has been extensively investigated. In this study, we aimed to explore these mechanisms and establish a prognostic model for patients with OC using bioinformatics techniques. Methods: We obtained the single cell sequencing data of ovarian cancer from the Gene Expression Omnibus (GEO) database and preprocessed the data. We analyzed a variety of factors including cuproptosis cell signal score, transcription factors, tumorigenesis and progression signals, gene set variation analysis (GSVA) and intercellular communication. Differential gene analysis was performed between groups with high and low cuproptosis cell signal scores, as well as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Using bulk RNA sequencing data from The Cancer Genome Atlas, we used the least absolute shrinkage and selection operator (LASSO)‐Cox algorithm to develop cuproptosis cell signaling pathword‐related gene signatures and validated them with GEO ovarian cancer datasets. In addition, we analyzed the inherent rules of the genes involved in building the model using a variety of bioinformatics methods, including immune‐related analyses and single nucleotide polymorphisms. Molecular docking is used to screen potential therapeutic drugs. To confirm the analysis results, we performed various wet experiments such as western blot, cell counting kit 8 (CCK8) and clonogenesis tests to verify the role of the Von Willebrand Factor (VWF) gene in two ovarian cancer cell lines. Results: Based on single‐cell data analysis, we found that endothelial cells and fibroblasts showed active substance synthesis and signaling pathway activation in OC, which further promoted immune cell suppression, cancer cell proliferation and metastasis. Ovarian cancer has a high tendency to metastasize, and cancer cells cooperate with other cells to promote disease progression. We developed a signature consisting of eight cuproptosis‐related genes (CRGs) (MAGEF1, DNPH1, RARRES1, NBL1, IFI27, VWF, OLFML3 and IGFBP4) that predicted overall survival in patients with ovarian cancer. The validity of this model is verified in an external GEO validation set. We observed active infiltrating states of immune cells in both the high‐ and low‐risk groups, although the specific cells, genes and pathways of activation differed. Gene mutation analysis revealed that TP53 is the most frequently mutated gene in ovarian cancer. We also predict small molecule drugs associated with CRGs and identify several potential candidates. VWF was identified as an oncogene in ovarian cancer, and the protein was expressed at significantly higher levels in tumor samples than in normal samples. The high‐score model of the cuproptosis cell signaling pathway was associated with the sensitivity of OC patients to immunotherapy. Conclusions: Our study provides greater insight into the mechanisms of action of genes associated with the cuproptosis cell signaling pathway in ovarian cancer, highlighting potential targets for future therapeutic interventions. [ABSTRACT FROM AUTHOR]

Immune responses induced by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection play a critical role in the pathogenesis and outcome of coronavirus disease 2019 (COVID‐19). However, the dynamic profile of immune responses postinfection by SARS‐CoV‐2 variants of concern (VOC) is not fully understood. In this study, peripheral blood mononuclear cells single‐cell sequencing was performed to determine dynamic profiles of immune response to Prototype, Alpha, Beta, and Delta in a rhesus monkey model. Overall, all strains induced dramatic changes in both cellular subpopulations and gene expression levels at 1 day postinfection (dpi), which associated function including adaptive immune response, innate immunity, and IFN response. COVID‐19‐related genes revealed different gene profiles at 1 dpi among the four SARS‐CoV‐2 strains, including genes reported in COVID‐19 patients with increased risk of autoimmune disease and rheumatic diseases. Delta‐infected animal showed inhibition of translation pathway. B cells, T cells, and monocytes showed much commonality rather than specificity among the four strains. Monocytes were the major responders to SARS‐CoV‐2 infection, and the response lasted longer in Alpha than the other strains. Thus, this study reveals the early immune responses induced by SARS‐CoV‐2 Proto or its variants in nonhuman primates, which is important information for controlling rapidly evolving viruses. [ABSTRACT FROM AUTHOR]

Up to 80% of children with autism spectrum disorder have at least one other neuropsychiatric comorbidity. The causes of such disorders are highly genetic, yet many studies fail to take analysis further than risk gene discovery to see cellular and mechanistic changes occurring. Therefore, the goal of this study was to unveil novel gene expression signatures involved in important neurodevelopmental processes that, when disrupted, lead to each of the autism comorbidities of interest. We achieved this by analysing a single‐nuclei RNA sequencing dataset with prefrontal cortex samples from autism spectrum disorder plus comorbidities for differentially expressed genes. The highest number of alterations was seen in excitatory neurons, which also showed differential population and cell–cell interactions across disorders and an increase in expression of genes involved in neurodevelopmental pathways. Interestingly, the group without comorbidities displayed an increase in neuron–neuron interactions yet a decrease in population number, suggesting a major rewiring of neuronal connections. Further analysis of the topmost significant genes from this cell type in developing prefrontal cortex datasets revealed interesting expression trajectories corresponding to important time points during corticogenesis. This further identified four novel candidate genes that show a potential link to developmental pathways that may contribute to autism and its comorbidities when dysregulated. The study provides a better understanding of co‐occurring conditions at a transcriptomic and cell‐type level and thereby aid future research in providing earlier diagnosis, care and intervention. [ABSTRACT FROM AUTHOR]

In multiple sclerosis (MS), the bone marrow hematopoietic system supplies immune cells to orchestrate central nervous system (CNS) inflammation and autoimmunity. Understanding the metabolic processes within the bone marrow is essential for unraveling the phenotype and function of immune cells. However, a comprehensive exploration of the metabolic landscape and its association with systemic immune response in MS at the single‐cell level has yet to be elucidated. Herein, we conducted an analysis of 70 289 bone marrow cells obtained from seven patients with MS and seven health controls (referenced as HRA001783) to address this question. Our focus was primarily on investigating the metabolic preferences of diverse immune cell populations and delineating their metabolic manifestations in the bone marrow microenvironment of MS. Through our analysis, we observed the activation of carbohydrate and amino acid metabolic pathways in the bone marrow cells of MS patients. Notably, we discovered significant metabolic alterations in cell–cell communication within the plasma cell population in the MS bone marrow. These findings shed light on the complex metabolic landscape within the bone marrow niche during MS and highlight the distinctive metabolic characteristics of plasma cells in this context, which may provoke novel understanding of MS pathogenesis and promote future design of immune therapies. [ABSTRACT FROM AUTHOR]

Background: Rheumatoid arthritis (RA) is a multifactorial systemic autoimmune disease characterized by ongoing synovial inflammation, leading to the degradation of cartilage. Cuproptosis, as a newly characterized form of cell death, may influence RA progression by regulating immune cells and chondrocytes. This study sets out to identify the hub cuproptosis‐related gene (CRG) associated with the pathogenesis of RA. Methods: A series of bioinformatic analyses were performed to evaluate the expression score of CRGs and the immune infiltration landscape between RA and normal samples. The hub gene was screened through the correlation analysis of CRGs, and the interaction network between the hub gene and transcription factors (TFs) was constructed. Finally, the hub gene was validated through quantitative real‐time polymerase chain reaction (qRT‐PCR) of patient samples and cell experiments. Results: Drolipoamide S‐acetyltransferase (DLAT) was screened as the hub gene. Correlation analysis between the hub gene and immune microenvironment demonstrated that DLAT had the highest correlation with T follicular helper cells. Eight pairs of DLAT–TF interaction networks were constructed. Single‐cell sequencing showed that CRGs were highly expressed in RA chondrocytes, and chondrocytes could be classified into three different subsets. qRT‐PCR was used to validate the above results. Dlat knockdown in immortalized human chondrocytes led to significantly improved mitochondrial membrane potentials and reduced levels of intracellular reactive oxygen species (ROS), mitochondrial ROS and apoptosis. Conclusions: This study rudimentarily demonstrates the correlation between CRGs and immune cell infiltration in RA. The biomarker DLAT may provide comprehensive insights into the pathogenesis and drug targets of RA. [ABSTRACT FROM AUTHOR]

Endometriosis consists of ectopic endometrial epithelial cells (EEECs) and ectopic endometrial stromal cells (EESCs) mixed with heterogeneous stromal cells. To address how endometriosis‐constituting cells are different from normal endometrium and among endometriosis subtypes and how their molecular signatures are related to phenotypic manifestations, we analyzed ovarian endometrial cyst (OEC), superficial peritoneal endometriosis (SPE), and deep infiltrating endometriosis (DIE) from 12 patients using single‐cell RNA‐sequencing (scRNA‐seq). We identified 11 cell clusters, including EEEC, EESC, fibroblasts, inflammatory/immune, endothelial, mesothelial, and Schwann cells. For hormonal signatures, EESCs, but not EEECs, showed high estrogen signatures (estrogen response scores and HOXA downregulation) and low progesterone signatures (DKK1 downregulation) compared to normal endometrium. In EEECs, we found MUC5B+TFF3low cells enriched in endometriosis. In lymphoid cells, evidence for both immune activation (high cytotoxicity in NK) and exhaustion (high checkpoint genes in NKT and cytotoxic T) was identified in endometriosis. Signatures and subpopulations of macrophages were remarkably different among endometriosis subtypes with increased monocyte‐derived macrophages and IL1B expression in DIE. The scRNA‐seq predicted NRG1 (macrophage)‐ERBB3 (Schwann cell) interaction in endometriosis, expressions of which were validated by immunohistochemistry. Myofibroblast subpopulations differed according to the location (OECs from fibroblasts and SPE/DIEs from mesothelial cells and fibroblasts). Endometriosis endothelial cells displayed proinflammation, angiogenesis, and leaky permeability signatures that were enhanced in DIE. Collectively, our study revealed that (1) many cell types—endometrial, lymphoid, macrophage, fibroblast, and endothelial cells—are altered in endometriosis; (2) endometriosis cells show estrogen responsiveness, immunologic cytotoxicity and exhaustion, and proinflammation signatures that are different in endometriosis subtypes; and (3) novel endometriosis‐specific findings of MUC5B+ EEECs, mesothelial cell‐derived myofibroblasts, and NRG1‐ERBB3 interaction may underlie the pathogenesis of endometriosis. Our results may help extend pathologic insights, dissect aggressive diseases, and discover therapeutic targets in endometriosis. © 2023 The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

How to develop highly informative serology assays to evaluate the quality of immune protection against coronavirus disease‐19 (COVID‐19) has been a global pursuit over the past years. Here, a microfluidic high‐plex immuno‐serolomic assay is developed to simultaneously measure50 plasma or serum samples for50 soluble markers including 35proteins, 11 anti‐spike/receptor binding domian (RBD) IgG antibodies spanningmajor variants, and controls. This assay demonstrates the quintuplicate test in a single run with high throughput, low sample volume, high reproducibilityand accuracy. It is applied to the measurement of 1012 blood samples including in‐depth analysis of sera from 127 patients and 21 healthy donors over multiple time points, either with acute COVID infection or vaccination. The protein analysis reveals distinct immune mediator modules that exhibit a reduced degree of diversity in protein‐protein cooperation in patients with hematologic malignancies or receiving B cell depletion therapy. Serological analysis identifies that COVID‐infected patients with hematologic malignancies display impaired anti‐RBD antibody response despite high level of anti‐spike IgG, which can be associated with limited clonotype diversity and functional deficiency in B cells. These findings underscore the importance to individualize immunization strategies for these high‐risk patients and provide an informative tool to monitor their responses at the systems level. [ABSTRACT FROM AUTHOR]

A microdroplet co‐culture system is useful for the parallel assessment of numerous possible cell–cell interactions by generating isolated subcommunities from a pool of heterogeneous cells. However, the integration of single‐cell sequencing into such analysis has been limited due to the lack of effective molecular identifiers for each in‐droplet subcommunity. Herein, we present a strategy for generating in‐droplet subcommunity identifiers using DNA‐functionalized microparticles encapsulated within microdroplets. These microparticles serve as initial information carriers, where their combinations act as distinct identifiers for in‐droplet subcommunity. Upon optical trigger, DNA barcoding molecules encoding the microparticle information are once released in the microdroplets and then tag cell membranes. The tagged DNA molecules then serve as a second information carrier readable by single‐cell sequencing to reconstitute the community in silico in the single‐cell RNA sequencing data space. [ABSTRACT FROM AUTHOR]

Background: This study aimed to investigate the potential mechanism of paeonol in the treatment of neuropathic pain. Methods: Relevant mechanisms were explored through microglial pseudotime analysis and the use of specific inhibitors in cell experiments. In animal experiments, 32 SD rats were randomly divided into the sham operation group, the chronic constrictive injury (CCI) group, the ibuprofen group, and the paeonol group. We performed behavioral testing, ELISA, PCR, Western blotting, immunohistochemistry, and immunofluorescence analysis. Results: The pseudotime analysis of microglia found that RhoA, Rock1, and p38MAPK were highly expressed in activated microglia, and the expression patterns of these genes were consistent with the expression trends of the M1 markers CD32 and CD86. Paeonol decreased the levels of M1 markers (IL1β, iNOS, CD32, IL6) and increased the levels of M2 markers (IL10, CD206, ARG‐1) in LPS‐induced microglia. The expression of iNOS, IL1β, RhoA, and Rock1 was significantly increased in LPS‐treated microglia, while paeonol decreased the expression of these proteins. Thermal hyperalgesia occurred after CCI surgery, and paeonol provided relief. In addition, paeonol decreased the levels of IL1β and IL8 and increased the levels of IL4 and TGF‐β in the serum of CCI rats. Paeonol decreased expression levels of M1 markers and increased expression levels of M2 markers in the spinal cord. Paeonol decreased IBA‐1, IL1β, RhoA, RhoA‐GTP, COX2, Rock1, and p‐p38MAPK levels in the spinal dorsal horn. Conclusion: Paeonol relieves neuropathic pain by modulating microglial M1 and M2 phenotypes through the RhoA/p38 MAPK pathway. [ABSTRACT FROM AUTHOR]

Rapid expansion of the probiotics industry demands fast, sensitive, comprehensive, and low-cost strategies for quality assessment. Here, we introduce a culture-free, one-cell-resolution, phenome-genome-combined strategy called Single-Cell Identification, Viability and Vitality tests, and Source-tracking (SCIVVS). For each cell directly extracted from the product, the fingerprint region of D2O-probed single-cell Raman spectrum (SCRS) enables specieslevel identification with 93% accuracy, based on a reference SCRS database from 21 statutory probiotic species, whereas the C-D band accurately quantifies viability, metabolic vitality plus their intercellular heterogeneity. For source-tracking, single-cell Raman-activated Cell Sorting and Sequencing can proceed, producing indexed, precisely one-cell-based genome assemblies that can reach ~99.40% genome-wide coverage. Finally, we validated an integrated SCIVVS workflow with automated SCRS acquisition where the whole process except sequencing takes just 5 h. As it is >20-fold faster, >10-time cheaper, vitality-revealing, heterogeneity-resolving, and automation-prone, SCIVVS is a new technological and data framework for quality assessment of live-cell products. (SCIVVS). For each cell directly extracted from the product, the fingerprint region of D2O-probed single-cell Raman spectrum (SCRS) enables specieslevel identification with 93% accuracy, based on a reference SCRS database from 21 statutory probiotic species, whereas the C-D band accurately quantifies viability, metabolic vitality plus their intercellular heterogeneity. For source-tracking, single-cell Raman-activated Cell Sorting and Sequencing can proceed, producing indexed, precisely one-cell-based genome assemblies that can reach ~99.40% genome-wide coverage. Finally, we validated an integrated SCIVVS workflow with automated SCRS acquisition where the whole process except sequencing takes just 5 h. As it is >20-fold faster, >10-time cheaper, vitality-revealing, heterogeneity-resolving, and automation-prone, SCIVVS is a new technological and data framework for quality assessment of live-cell products. [ABSTRACT FROM AUTHOR]