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In recent years, data-driven inference of cell-cell communication has helped reveal coordinated biological processes across cell types. Here, we integrate two tools, LIANA and Tensor-cell2cell, which, when combined, can deploy multiple existing methods and resources to enable the robust and flexible identification of cell-cell communication programs across multiple samples. In this work, we show how the integration of our tools facilitates the choice of method to infer cell-cell communication and subsequently perform an unsupervised deconvolution to obtain and summarize biological insights. We explain how to perform the analysis step by step in both Python and R and provide online tutorials with detailed instructions available at https://ccc-protocols.readthedocs.io/. This workflow typically takes ∼1.5 h to complete from installation to downstream visualizations on a graphics processing unit-enabled computer for a dataset of ∼63,000 cells, 10 cell types, and 12 samples.

BACKGROUND: A traditional view is that stem cells (SCs) divide slowly. Meanwhile, both embryonic and pluripotent SCs display a shorter cell cycle duration (CCD) in comparison to more committed progenitors (CPs). METHODS: We examined the in vitro proliferation and cycling behavior of somatic adult human cells using live cell imaging of passage zero keratinocytes and single-cell RNA sequencing. RESULTS: We found two populations of keratinocytes: those with short CCD and protracted near exponential growth, and those with long CCD and terminal differentiation. Applying the ergodic principle, the comparative numbers of cycling cells in S phase in an enriched population of SCs confirmed a shorter CCD than CPs. Further, analysis of single-cell RNA sequencing of cycling adult human keratinocyte SCs and CPs indicated a shortening of both G1 and G2M phases in the SC. CONCLUSIONS: Contrary to the pervasive paradigm, SCs progress through cell cycle more quickly than more differentiated dividing CPs. Thus, somatic human adult keratinocyte SCs may divide infrequently, but divide rapidly when they divide. Additionally, it was found that SC-like proliferation persisted in vitro.

Background Methods Results Conclusion Keloids, characterized by an aberrant wound‐healing process and a highly complex immune microenvironment, pose significant challenges for clinical management. Fibroblasts and vascular endothelial cells (VEC) were identified as the leading cells of keloid development. However, their roles in the keloid immune landscape have yet to be thoroughly elucidated.To explore the functional state of cells in the immune landscape of keloids, we conducted a single‐cell RNA sequencing analysis on the tissue from three keloid lesions and two specimens of healthy skin. We simultaneously utilized available keloid data from the public database for external validation.Specific subsets, such as proinflammatory fibroblasts (piF) and VEC, were markedly elevated in lesional skin compared to normal skin. Subsequent differential gene expression and Gene Ontology analyses indicated that these subsets may be involved in shaping the microenvironment. In keloids, there is an increased expression of immune‐associated genes (P < 0.05), including TNFRSF6B, HGF, and TGFB3, alongside a decreased expression of inflammatory chemokines in the piF. Moreover, the significant upregulation of immune suppressive genes (P < 0.05), including CD39, CD73, and HIF1A, suggested the potential involvement of VEC as a conditional immune subpopulation in the keloid microenvironment. Immune cell communication analysis revealed preferential enrichment of macrophages and Tregs, highlighting intensified macrophage‐centered interactions within the keloid microenvironment.Our study highlighted the role of piF and VEC in the immune microenvironment of keloids for the first time, providing potential targets for therapeutic development. [ABSTRACT FROM AUTHOR]

Background: The manipulation of CD8+ T cell functions through genetic modifications presents a novel approach to cancer immunotherapy. This study aimed to explore the effects of IL2RG-overexpressing CD8+ T cells and assess the efficacy of delivering IL2RG mRNA via nanoparticles (NPs) to the tumor microenvironment in triple-negative breast cancer (TNBC). Methods: Single-cell RNA sequencing (scRNA-seq) was conducted on tissue from early and late-stage TNBC, followed by a meta-analysis of six breast cancer arrays from the GEO database to identify candidate genes. CRISPR/Cas9 was employed for gene knockout and overexpression in CD8+ T cells, which were then analyzed using flow cytometry, ELISA, immunofluorescence, and metabolic assays. A 3D cancer cell spheroid model was used for co-culture experiments. Lipid-coated calcium-phosphate (LCP)@IL2RG NPs were synthesized and injected into TNBC mouse models. Results: IL2RG was identified as significantly associated with late-stage TNBC. Overexpression of IL2RG in CD8+ T cells led to increased cell activation, cytotoxicity, and glycolysis, while knockout reduced these effects. Overexpressing IL2RG in CD8+ T cells co-cultured with 3D cancer spheroids resulted in enhanced apoptosis and reduced cancer cell invasion. Injection of LCP@IL2RG NPs into TNBC mouse models significantly mitigated tumor growth. Conclusions: Overexpressing IL2RG in CD8+ T cells enhances tumor immunotherapy. Delivering IL2RG mRNA via NPs further amplifies this effect, offering a promising strategy for the treatment of late-stage TNBC. [ABSTRACT FROM AUTHOR]

Single-cell RNA sequencing (scRNA-seq) methods are widely used in life sciences, including immunology. Typical scRNA-seq analysis pipelines quantify the abundance of particular transcripts without accounting for alternative splicing. However, a well-established pan-leukocyte surface marker, CD45, encoded by the PTPRC gene, presents alternatively spliced variants that define different immune cell subsets. Information about some of the splicing patterns in particular cells in the scRNA-seq data can be obtained using isotype-specific DNA oligo-tagged anti-CD45 antibodies. However, this requires generation of an additional sequencing DNA library. Here, we present IDEIS, an easy-to-use software for CD45 isoform quantification that uses single-cell transcriptomic data as the input. We showed that IDEIS accurately identifies canonical human CD45 isoforms in datasets generated by 10× Genomics 5' sequencing assays. Moreover, we used IDEIS to determine the specificity of the Ptprc splicing pattern in mouse leukocyte subsets. [ABSTRACT FROM AUTHOR]

Background: Neurodegenerative diseases are progressive disorders that severely diminish the quality of life of patients. However, research on neurodegenerative diseases needs to be refined and deepened. Single-cell polyomics is a technique for obtaining transcriptomic, proteomic, and other information from a single cell. In recent years, the heat of single-cell multiomics as an emerging research tool for brain science has gradually increased. Therefore, the aim of this study was to analyze the current status and trends of studies related to the application of single-cell multiomics in neurodegenerative diseases through bibliometrics. Result: A total of 596 publications were included in the bibliometric analysis. Between 2015 and 2022, the number of publications increased annually, with the total number of citations increasing significantly, exhibiting the fastest rate of growth between 2019 and 2022. The country/region collaboration map shows that the United States has the most publications and cumulative citations, and that China and the United States have the most collaborations. The institutions that produced the greatest number of articles were Harvard Medical School, Skupin, Alexander, and Wiendl. Among the authors, Heinz had the highest output. Mathys, H accumulated the most citations and was the authoritative author in the field. The journal Nature Communications has published the most literature in this field. A keyword analysis reveals that neurodegenerative diseases and lesions (e.g., Alzheimer's disease, amyloid beta) are the core and foundation of the field. Conversely, single-cell multiomics related research (e.g., single-cell RNA sequencing, bioinformatics) and brain nerve cells (e.g., microglia, astrocytes, neural stem cells) are the hot frontiers of this specialty. Among the references, the article "Single-cell transcriptomic analysis of Alzheimer's disease" is the most frequently cited (1,146 citations), and the article "Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq" was the most cited article in the field. Conclusion: The objective of this study is to employ bibliometric methods to visualize studies related to single-cell multiomics in neurodegenerative diseases. This will enable us to summarize the current state of research and to reveal key trends and emerging hotspots in the field. [ABSTRACT FROM AUTHOR]

Background: Esophageal cancer (EC) is a major health issue, ranking seventh in incidence and sixth in mortality worldwide. Despite advancements in multidisciplinary treatment approaches, the 5-year survival rate for EC remains low at 21%. Challenges in EC treatment arise from late-stage diagnosis, high malignancy, and poor prognosis. Understanding the tumor microenvironment is critical, as it includes various cellular and extracellular components that influence tumor behavior and treatment response. Mast cells (MCs), as tissue-resident immune cells, play dual roles in tumor dynamics. High-throughput single-cell RNA sequencing offers a powerful tool for analyzing tumor heterogeneity and immune interactions, although its application in EC is limited. Methods: In this study, we investigated the immune microenvironment of EC using single-cell RNA sequencing and established a comprehensive immune profile. We also performed analysis of upstream transcription factors and downstream pathway enrichment to further comprehensively decipher MCs in EC. Besides, we performed knockdown experiments to explore the role of epidermal growth factor receptor (EGFR) signaling pathway in MCs-tumor cell interactions, highlighting its potential as a prognostic marker. Finally, we constructed a prognostic model for EC, which provided valuable suggestions for the diagnosis and prognosis of EC. Results: Our analysis identified 11 major cell types, of which MCs were particularly present in pericarcinoma tissues. Further grouping of the 5,001 MCs identified 8 distinct subtypes, including SRSF7-highly expressed MCs, which showed strong tumor preference and potential tumor-promoting properties. Moreover, we identified the key signaling receptor EGFR and validated it by in vitro knockdown experiments, demonstrating its cancer-promoting effects. In addition, we established an independent prognostic indicator, SRSF7+ MCs risk score (SMRS), which showed a correlation between high SMRS group and poor prognosis. Conclusion: These findings illuminate the complex interactions within the tumor microenvironment of EC and suggest that targeting specific MCs subtypes, particularly via the EGFR signaling pathway, may present novel therapeutic strategies. This study establishes a comprehensive immune map of EC, offering insights for improved treatment approaches. [ABSTRACT FROM AUTHOR]

Introduction: Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by persistent synovitis, systemic inflammation, and autoantibody production. This study aims to explore the role of lactylation in plasma cells and its impact on RA pathogenesis. Methods: We utilized single-cell RNA sequencing (scRNA-seq) data and applied bioinformatics and machine learning techniques. A total of 10,163 cells were retained for analysis after quality control. Clustering analysis identified 13 cell clusters, with plasma cells displaying the highest lactylation scores. We performed pathway enrichment analysis to examine metabolic activity, such as oxidative phosphorylation and glycolysis, in highly lactylated plasma cells. Additionally, we employed 134 machine learning algorithms to identify seven core lactylation-promoting genes and constructed a diagnostic model with an average AUC of 0.918. Results: The RA lactylation score (RAlac_score) was significantly elevated in RA patients and positively correlated with immune cell infiltration and immune checkpoint molecule expression. Differential expression analysis between two plasma cell clusters revealed distinct metabolic and immunological profiles, with cluster 2 demonstrating increased immune activity and extracellular matrix interactions. qRT-PCR validation confirmed that NDUFB3, NGLY1, and SLC25A4 are highly expressed in RA. Conclusion: This study highlights the critical role of lactylation in plasma cells for RA pathogenesis and identifies potential biomarkers and therapeutic targets, which may offer insights for future therapeutic strategies. [ABSTRACT FROM AUTHOR]

Lupus nephritis (LN), a complex complication of systemic lupus erythematosus, requires in-depth cellular and molecular analysis for advanced treatment strategies, including mRNA vaccine development. In this study, we analyzed single-cell RNA sequencing data from 24 LN patients and 10 healthy controls, supplemented by bulk RNA-seq data from additional LN patients and controls. By applying non-negative matrix factorization (NMF), we identified four distinct leukocyte meta-programs in LN, highlighting diverse immune functions and potential mRNA vaccine targets. Utilizing 12 machine learning algorithms, we developed 417 predictive models incorporating gene sets linked to key biological pathways, such as MTOR signaling, autophagy, Toll-like receptor, and adaptive immunity pathways. These models were instrumental in identifying potential targets for mRNA vaccine development. Our functional network analysis further revealed intricate gene interactions, providing novel insights into the molecular basis of LN. Additionally, we validated the mRNA expression levels of potential vaccine targets across multiple cohorts and correlated them with clinical parameters such as the glomerular filtration rate (GFR) and pathological stage. This study represents a significant advance in LN research by merging single-cell genomics with the precision of NMF and machine learning, broadening our understanding of LN at the cellular and molecular levels. More importantly, our findings shed light on the development of targeted mRNA vaccines, offering new possibilities for diagnostics and therapeutics for this complex autoimmune disease. [ABSTRACT FROM AUTHOR]

Liver transplantation is the definitive treatment for end-stage liver disease, yet T-cell mediated rejection (TCMR) remains a major challenge. This study aims to identify key genes associated with TCMR and their potential biological processes and mechanisms. The GSE145780 dataset was subjected to differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms to pinpoint key genes associated with TCMR. Gene Set Enrichment Analysis (GSEA), immune infiltration analysis, and regulatory networks were constructed to ascertain the biological relevance of these genes. Expression validation was performed using single-cell RNA-seq (scRNA-seq) data and liver biopsy tissues from patients. We identified 5 key genes (ITGB2, FCER1G, IL-18, GBP1, and CD53) that are associated with immunological functions, such as chemotactic activity, antigen processing, and T cell differentiation. GSEA highlighted enrichment in chemokine signaling and antigen presentation pathways. A lncRNA-miRNA-mRNA network was delineated, and drug target prediction yielded 26 potential drugs. Evaluation of expression levels in non-rejection (NR) and TCMR groups exhibited significant disparities in T cells and myeloid cells. Tissue analyses from patients corroborated the upregulation of GBP1, IL-18, CD53, and FCER1G in TCMR cases. Through comprehensive analysis, this research has identified 4 genes intimately connected with TCMR following liver transplantation, shedding light on the underlying immune activation pathways and suggesting putative targets for therapeutic intervention. [ABSTRACT FROM AUTHOR]

High‐grade serous tubo‐ovarian cancer (HGSTOC) is an aggressive gynecological malignancy including homologous recombination deficient (HRD) and homologous recombination proficient (HRP) groups. Despite the therapeutic potential of poly (ADP‐ribose) polymerase inhibitors (PARPis) and anti‐PDCD1 antibodies, acquired resistance in HRD and suboptimal response in HRP patients necessitate more precise treatment. Herein, single‐cell RNA and single‐cell T‐cell receptor sequencing on 5 HRD and 3 HRP tumors are performed to decipher the heterogeneous tumor immune microenvironment (TIME), along with multiplex immunohistochemistry staining and animal experiments for validation. HRD tumors are enriched with immunogenic epithelial cells, FGFR1+PDGFRβ+ myCAFs, M1 macrophages, tumor reactive CD8+/CD4+ Tregs, whereas HRP tumors are enriched with HDAC1‐expressing epithelial cells, indolent CAFs, M2 macrophages, and bystander CD4+/CD8+ T cells. Significantly, customized therapies are proposed. For HRD patients, targeting FGFR1+PDGFRβ+ myCAFs via tyrosine kinase inhibitors, targeting Tregs via anti‐CCR8 antibodies/TNFRSF4 stimulation, and targeting CXCL13+ exhausted T cells by blocking PDCD1/CTLA‐4/LAG‐3/TIGIT are proposed. For HRP patients, targeting indolent CAFs, targeting M2 macrophages via CSF‐1/CSF‐1R inhibitors, targeting bystander T cells via tumor vaccines, and targeting epithelial cells via HDAC inhibitors. The study provides comprehensive insights into HRD and HRP TIME and tailored therapeutic approaches, addressing the challenges of PARPi‐resistant HRD and refractory HRP tumors. [ABSTRACT FROM AUTHOR]

Tumor-infiltrating B cells play a significant role in tumor development, progression, and prognosis, yet a comprehensive classification system is lacking. To address this gap, we present a pan-cancer single-cell RNA sequencing (scRNA-seq) atlas of tumor-infiltrating B and plasma cells across a large sample cohort. We identify key B cell subset signatures, revealing distinct subpopulations and highlighting the heterogeneity and functional diversity of these cells in the tumor microenvironment. We explore associations between B cell subsets and checkpoint inhibitor therapy responses, finding subset-specific effects on overall response. Additionally, we examine B and T cell crosstalk, identifying unique ligand-receptor pairs for specific B cell subsets, spatially validated. This comprehensive dataset serves as a valuable resource, providing a detailed atlas that enhances the understanding of B cell complexity in tumors and opens new avenues for research and therapeutic strategies. [Display omitted] • A scRNA-seq atlas identifies ten clusters of intratumoral B and plasma cells • Specific B cell subsets are associated with checkpoint inhibitor therapy responses • Atlas-derived B cell gene signatures validated in spatial analyses • Publicly available Shiny tool enables users to interactively explore the atlas Fitzsimons et al. present a comprehensive pan-cancer single-cell RNA-seq atlas of intratumoral B cells, identifying ten distinct B and plasma cell clusters. They uncover associations with checkpoint inhibitor therapy response, explore B-T cell crosstalk, validate findings with spatial data, and offer an interactive tool for further research. [ABSTRACT FROM AUTHOR]

Early identification of resistant cancer cells is currently a major challenge, as their expansion leads to refractoriness. To capture the dynamics of these cells, we made a comprehensive analysis of disease progression and treatment response in a chronic lymphocytic leukemia (CLL) patient using a combination of single‐cell and bulk genomic methods. At diagnosis, the patient presented with unfavorable genetic markers, including notch receptor 1 (NOTCH1) mutation and loss(11q). The initial and subsequent treatment lines did not lead to a durable response and the patient developed refractory disease. Refractory CLL cells featured substantial dysregulation in B‐cell phenotypic markers such as human leukocyte antigen (HLA) genes, immunoglobulin (IG) genes, CD19 molecule (CD19), membrane spanning 4‐domains A1 (MS4A1; previously known as CD20), CD79a molecule (CD79A) and paired box 5 (PAX5), indicating B‐cell de‐differentiation and disease transformation. We described the clonal evolution and characterized in detail two cell populations that emerged during the refractory disease phase, differing in the presence of high genomic complexity. In addition, we successfully tracked the cells with high genomic complexity back to the time before treatment, where they formed a rare subpopulation. We have confirmed that single‐cell RNA sequencing enables the characterization of refractory cells and the monitoring of their development over time. [ABSTRACT FROM AUTHOR]

Background: Exhaustion is a key factor that influences the efficacy of chimeric antigen receptor T (CAR-T) cells. Our previous study demonstrated that a bromodomain protein 4 (BRD4) inhibitor can revise the phenotype and function of exhausted T cells from leukemia patients. This study aims to elucidate the mechanism by which a BRD4 inhibitor reduces CAR-T cell exhaustion using single-cell RNA sequencing (scRNA-Seq). Methods: Exhausted CD123-specific CAR-T cells were prepared by co-culture with CD123 antigen-positive MV411 cells. After elimination of MV411 cells and upregulation of inhibitory receptors on the surface, exhausted CAR-T cells were treated with a BRD4 inhibitor (JQ1) for 72 h. The CAR-T cells were subsequently isolated, and scRNA-Seq was conducted to characterize phenotypic and functional changes in JQ1-treated cells. Results: Both the proportion of exhausted CD8+ CAR-T cells and the exhausted score of CAR-T cells decreased in JQ1-treated compared with control-treated cells. Moreover, JQ1 treatment led to a higher proportion of naïve, memory, and progenitor exhausted CD8+ CAR-T cells as opposed to terminal exhausted CD8+ CAR-T cells accompanied by enhanced proliferation, differentiation, and activation capacities. Additionally, with JQ1 treatment, BATF activity and expression in naïve, memory, and progenitor exhausted CD8+ CAR-T cells decreased, whereas EGR1 activity and expression increased. Interestingly, AML patients with higher EGR1 and EGR1 target gene ssGSEA scores, coupled with lower BATF and BATF target gene ssGSEA scores, had the best prognosis. Conclusions: Our study reveals that a BRD4 inhibitor can reduce CAR-T cell exhaustion and block exhausted T cell terminal differentiation by downregulating BATF activity and expression together with upregulating EGR1 activity and expression, presenting an approach for improving the effectiveness of CAR-T cell therapy. [ABSTRACT FROM AUTHOR]

Introduction: Illicit drug use, particularly the synthetic opioid fentanyl, presents a significant global health challenge. Previous studies have shown that fentanyl enhances viral replication; yet, the mechanisms by which it affects HIV pathogenesis remain unclear. This study investigated the impact of fentanyl on HIV replication in CD4+ T lymphocytes. Methods: CD4+ T lymphocytes from HIV-negative donors were activated, infected with HIVNL4-3, and treated with fentanyl. HIV proviral DNA and p24 antigen expression were quantified using real-time PCR and ELISA, respectively. Single-cell RNA libraries were analyzed to identify differentially expressed genes. Results: Results indicated that fentanyl treatment increased HIV p24 expression and proviral DNA levels, and naltrexone mitigated these effects. Single-cell RNAseq analysis identified significantly altered gene expression in CD4+ T lymphocytes. Discussion: The results of our findings suggest that fentanyl promotes HIV replication ex vivo, emphasizing the need for a deeper understanding of opioid-virus interactions to develop better treatment strategies for individuals with HIV and opioid use disorder. [ABSTRACT FROM AUTHOR]

Introduction: There are considerable similarities between the pathophysiology of gout flare and the dysregulated inflammatory response in severe COVID-19 infection. Monocytes are the key immune cells involved in the pathogenesis of both diseases. Therefore, it is critical to elucidate the molecular basis of the function of monocytes in gout and COVID-19 in order to develop more effective therapeutic approaches. Methods: The single-cell RNA sequencing (scRNA-seq), large-scale genomewide association studies (GWAS), and expression quantitative trait loci (eQTL) data of gout and severe COVID-19 were comprehensively analyzed. Cellular heterogeneity and intercellular communication were identified using the scRNA-seq datasets, and the monocyte-specific differentially expressed genes (DEGs) between COVID-19, gout and normal subjects were screened. In addition, the correlation of the DEGs with severe COVID-19 and gout flare was analyzed through GWAS statistics and eQTL data. Results: The scRNA-seq analysis exhibited that the proportion of classical monocytes was increased in both severe COVID-19 and gout patient groups compared to healthy controls. Differential expression analysis and MR analysis showed that NLRP3 was positively associated with the risk of severe COVID-19 and involved 11 SNPs, of which rs4925547 was not significantly co-localized. In contrast, IER3 was positively associated with the risk of gout and involved 9 SNPs, of which rs1264372 was significantly co-localized. Discussion: Monocytes have a complex role in gout flare and severe COVID-19, which underscores the potential mechanisms and clinical significance of the interaction between the two diseases. [ABSTRACT FROM AUTHOR]

The incidence of central nervous system (CNS) disease has persistently increased over the last several years. There is an urgent need for effective methods to improve the cure rates of CNS disease. However, the precise molecular basis underlying the development and progression of major CNS diseases remains elusive. A complete molecular map will contribute to research on CNS disease treatment strategies. Emerging technologies such as single-cell RNA sequencing (scRNA-seq) and Spatial Transcriptomics (ST) are potent tools for exploring the molecular complexity, cell heterogeneity, and functional specificity of CNS disease. scRNA-seq and ST can provide insights into the disease at cellular and spatial transcription levels. This review presents a survey of scRNA-seq and ST studies on CNS diseases, such as chronic neurodegenerative diseases, acute CNS injuries, and others. These studies offer novel perspectives in treating and diagnosing CNS diseases by discovering new cell types or subtypes associated with the disease, proposing new pathophysiological mechanisms, uncovering novel therapeutic targets, and identifying putative biomarkers. Implications of scRNA-seq and ST for CNS diseases. A comprehensive understanding of cellular information and spatial context using scRNA-seq and ST, helping to elucidate the biological functions, the intricate connection between crucial regulatory pathways, and cell communication after CNS diseases. [ABSTRACT FROM AUTHOR]

Background: Topoisomerase II α(TOP2A) is usually highly expressed in rapidly proliferating cells, and its expression is regulated by cell cycle. The relationship between TOP2A and oral squamous cell carcinoma (OSCC) needs further study. Methods: TOP2A immunoreactivity was analyzed using immunohistochemical (IHC) staining analysis in specimens from 20 OSCC patients. Based on the high-throughput sequencing and gene microarray database, the expression of TOP2A mRNA in OSCC was calculated and its ability to identify OSCC tissues was evaluated by diagnostic analysis. CRISPR screen was used to select the genes necessary for OSCC cell growth, and the gene set was analyzed for function enrichment. Single-cell RNA sequencing analysis was conducted to evaluate the expression level of TOP2A mRNA in OSCC cells. Results: Compared with normal oral tissues, the expression of TOP2A protein was up-regulated in OSCC tissues. A total of 1240 OSCC and 428 non-OSCC oral tissue samples were included based on high-throughput dataset retrieval, and it was confirmed that TOP2A mRNA was highly expressed in OSCC tissues [SMD = 1.51 (95% CI 0.94–2.07), sROC AUC = 0.96 (95% CI 0.94–0.98)]. As an essential gene for OSCC cell growth, single-cell RNA sequencing data also confirmed that TOP2A mRNA expression was up-regulated in OSCC cells. Conclusion: The up-regulation of TOP2A may play a pivotal role in OSCC. [ABSTRACT FROM AUTHOR]

Background: Quiescent self-renewal of leukemia stem cells (LSCs) and resistance to conventional chemotherapy are the main factors leading to relapse of acute myeloid leukemia (AML). Alpha-enolase (ENO1), a key glycolytic enzyme, has been shown to regulate embryonic stem cell differentiation and promote self-renewal and malignant phenotypes in various cancer stem cells. Here, we sought to test whether and how ENO1 influences LSCs renewal and chemoresistance within the context of AML. Methods: We analyzed single-cell RNA sequencing data from bone marrow samples of 8 relapsed/refractory AML patients and 4 healthy controls using bioinformatics and machine learning algorithms. In addition, we compared ENO1 expression levels in the AML cohort with those in 37 control subjects and conducted survival analyses to correlate ENO1 expression with clinical outcomes. Furthermore, we performed functional studies involving ENO1 knockdown and inhibition in AML cell line. Results: We used machine learning to model and infer malignant cells in AML, finding more primitive malignant cells in the non-response (NR) group. The differentiation capacity of LSCs and progenitor malignant cells exhibited an inverse correlation with glycolysis levels. Trajectory analysis indicated delayed myeloid cell differentiation in NR group, with high ENO1-expressing LSCs at the initial stages of differentiation being preserved post-treatment. Simultaneously, ENO1 and stemness-related genes were upregulated and co-expressed in malignant cells during early differentiation. ENO1 level in our AML cohort was significantly higher than the controls, with higher levels in NR compared to those in complete remission. Knockdown of ENO1 in AML cell line resulted in the activation of LSCs, promoting cell differentiation and apoptosis, and inhibited proliferation. ENO1 inhibitor can impede the proliferation of AML cells. Furthermore, survival analyses associated higher ENO1 expression with poorer outcome in AML patients. Conclusions: Our findings underscore the critical role of ENO1 as a plausible driver of LSC self-renewal, a potential target for AML target therapy and a biomarker for AML prognosis. [ABSTRACT FROM AUTHOR]

Immunological priming—in the context of either prior infection or vaccination—elicits protective responses against subsequent Mycobacterium tuberculosis (Mtb) infection. However, the changes that occur in the lung cellular milieu post-primary Mtb infection and their contributions to protection upon reinfection remain poorly understood. Using clinical and microbiological endpoints in a non-human primate reinfection model, we demonstrated that prior Mtb infection elicited a long-lasting protective response against subsequent Mtb exposure and was CD4+ T cell dependent. By analyzing data from primary infection, reinfection, and reinfection-CD4+ T cell-depleted granulomas, we found that the presence of CD4+ T cells during reinfection resulted in a less inflammatory lung milieu characterized by reprogrammed CD8+ T cells, reduced neutrophilia, and blunted type 1 immune signaling among myeloid cells. These results open avenues for developing vaccines and therapeutics that not only target lymphocytes but also modulate innate immune cells to limit tuberculosis (TB) disease. [Display omitted] • CD4+ T cells are required for protection against Mtb reinfection in macaques • Mtb reinfection promotes immuno-modulatory CD8+ T cell-biased immunity • Myeloid-derived cells downregulate gene networks implicated in TB susceptibility • Self-reinforcing cellular circuits balance host immunity in reinfection granulomas Th1 CD4+ T cells mediate protective anti- Mtb immunity across biological systems and organisms. Bromley, Ganchua, et al. demonstrate that CD4+ T cells regulate immune tone in TB granulomas and are necessary for immune recall and protection against reinfection. Following reinfection, CD4+ T cells facilitate the development of a growth restrictive niche via the induction of immuno-modulatory genes and cellular interaction networks. [ABSTRACT FROM AUTHOR]

Single-cell RNA sequencing technology takes a single cell as research object, counts and analyzes the gene expression level of each transcript and heterogeneity between cells. This technology makes up for the defects of traditional sequencing technology to some extent. Autoimmune disease is the damage or dysfunction of autotissue cells caused by autoimmune tolerance or abnormal regulation of autoimmunity cells. In this paper, the research results on application of single-cell RNA sequencing technology in autoimmune disease in recent years are reviewed, which provides valuable clues for early realization of precise medical treatment. [ABSTRACT FROM AUTHOR]

Identification and isolation of antigen-specific T cells for downstream transcriptomic analysis is key for various immunological studies. Traditional methods using major histocompatibility complex (MHC) multimers are limited by the number of predefined immunodominant epitopes and MHC matching of the study subjects. Activation-induced markers (AIM) enable highly sensitive detection of rare antigen-specific T cells irrespective of the availability of MHC multimers. Herein, we have developed an AIM assay for the detection, sorting and subsequent single-cell RNA sequencing (scRNA-seq) analysis of hepatitis C virus (HCV)-specific T cells. We examined different combinations of the activation markers CD69, CD40L, OX40, and 4-1BB at 6, 9, 18 and 24 h post stimulation with HCV peptide pools. AIM+ CD4 T cells exhibited upregulation of CD69 and CD40L as early as 6 h post-stimulation, while OX40 and 4-1BB expression was delayed until 18 h. AIM+ CD8 T cells were characterized by the coexpression of CD69 and 4-1BB at 18 h, while the expression of CD40L and OX40 remained low throughout the stimulation period. AIM+ CD4 and CD8 T cells were successfully sorted and processed for scRNA-seq analysis examining gene expression and T cell receptor (TCR) usage. scRNA-seq analysis from this one subject revealed that AIM+ CD4 T (CD69+ CD40L+) cells predominantly represented Tfh, Th1, and Th17 profiles, whereas AIM+ CD8 T (CD69+ 4-1BB+) cells primarily exhibited effector and effector memory profiles. TCR analysis identified 1023 and 160 unique clonotypes within AIM+ CD4 and CD8 T cells, respectively. In conclusion, this approach offers highly sensitive detection of HCV-specific T cells that can be applied for cohort studies, thus facilitating the identification of specific gene signatures associated with infection outcome and vaccination. [ABSTRACT FROM AUTHOR]

Juvenile-onset recurrent respiratory papillomatosis (JORRP) is caused by persistent infection of epithelial cells by low-risk human papillomavirus (HPV) types 6 and 11. While multiple infiltrated immune cells have been reported to mediate disease progress, knowledge of HPV-reactive T-cell subsets in papillomas remains elusive. Through single-cell RNA sequencing and RNA microarray, we found that CD8+ tissueresident memory T (CD8+ TRM) cells with strong interferon-gamma (IFN-γ) production expanded, and were negatively correlated to the disease severity in the frequency of surgery. These IFN-γ+ CD8+ memory T cells were readily activated and expanded in vitro by autologous dendritic cells loaded with HPV11 E7 peptide pool. Moreover, T cell receptor (TCR) clonal expansion was observed in JORRP papilloma tissues, indicating a biased TCR repertoire toward HPV-specific recognition. Finally, we identified and characterized HPV11 E7-specific candidate TCR clonotypes from IFN-γ+ CD8+ memory T cells, suggesting their potential application in TCR-engineered T cells (TCR-T) therapy for HPV11-related diseases. Our findings provided insights into the specific local immune response to HPV6/11 infection and highlighted the importance of IFN-γ+ CD8+ TRM cells in anti-HPV6/11 T-cell immunity. [ABSTRACT FROM AUTHOR]

Background: Gastric cancer patients with peritoneal metastasis (GCPM) experience a rapidly deteriorating clinical trajectory characterized by therapeutic resistance and dismal survival, particularly following the development of malignant ascites. However, the intricate dynamics within the peritoneal microenvironment (PME) during the treatment process remain largely unknown. Methods: Matched samples from primary tumours (PT), peritoneal metastases (PM), and paired pre‐treatment and post‐chemo/immunotherapy (anti‐PD‐1/PD‐L1) progression malignant ascites samples, were collected from 48 patients. These samples were subjected to single‐cell RNA sequencing (n = 30), multiplex immunofluorescence (n = 30), and spatial transcriptomics (n = 3). Furthermore, post hoc analyses of a phase 1 clinical trial (n = 20, NCT03710265) and an in‐house immunotherapy cohort (n = 499) were conducted to validate the findings. Results: Tracing the evolutionary trajectory of epithelial cells unveiled the terminally differentially MUC1+ cancer cells with a high epithelial‐to‐mesenchymal transition potential, and they demonstrated spatial proximity with fibroblasts and endothelial cells, correlating with poor prognosis. A significant expansion of macrophage infiltrates, which exhibited the highest proangiogenic activity, was observed in the ascites compared with PT and PM. Besides, higher C1Q+ macrophage infiltrates correlated with significantly lower GZMA+ T‐lymphocyte infiltrates in therapeutic failure cases, potentially mediated by the LGALS9‐CD45 and SPP1‐CD44 ligand–receptor interactions. In the chemoresistant group, intimate interactions between C1Q+ macrophages and fibroblasts through the complement activation pathway were found. In the group demonstrating immunoresistance, heightened TGF‐β production activity was detected in MUC1+ cancer cells, and they were skewed to interplay with C1Q+ macrophages through the GDF15‐TGF‐βR2 axis. Ultimately, post hoc analyses indicated that co‐targeting TGF‐β and PDL1 pathways may confer superior clinical benefits than sole anti‐PD‐1/PD‐L1 therapy for patients presenting with GCPM at the time of diagnosis. Conclusions: Our findings elucidated the cellular differentiation trajectories and crucial drug resistance features within PME, facilitating the exploration of effective targets for GCPM treatment. Highlights: MUC1+ cancer cells with a high epithelial‐to‐mesenchymal transition potential and exhibiting spatial proximity to fibroblasts and endothelial cells constitute the driving force of gastric cancer peritoneal metastasis (GCPM).Higher C1Q+ macrophage infiltrates correlated with significantly lower GZMA+ T‐lymphocyte infiltrates within the peritoneal microenvironment in therapeutic failure cases.Co‐targeting TGF‐β and PDL1 pathways may confer superior clinical benefits than sole anti‐PD‐1/PD‐L1 therapy for patients presenting with GCPM at diagnosis. [ABSTRACT FROM AUTHOR]

Background: Breast cancer's complex transcriptional landscape requires an improved understanding of cellular diversity to identify effective treatments. The study of genetic variations among breast cancer subtypes at single‐cell resolution has potential to deepen our insights into cancer progression. Methods: In this study, we amalgamate single‐cell RNA sequencing data from patient tumours and matched lymph metastasis, reduction mammoplasties, breast cancer patient‐derived xenografts (PDXs), PDX‐derived organoids (PDXOs), and cell lines resulting in a diverse dataset of 117 samples with 506 719 total cells. These samples encompass hormone receptor positive (HR+), human epidermal growth factor receptor 2 positive (HER2+), and triple‐negative breast cancer (TNBC) subtypes, including isogenic model pairs. Herein, we delineated similarities and distinctions across models and patient samples and explore therapeutic drug efficacy based on subtype proportions. Results: PDX models more closely resemble patient samples in terms of tumour heterogeneity and cell cycle characteristics when compared with TNBC cell lines. Acquired drug resistance was associated with an increase in basal‐like cell proportions within TNBC PDX tumours as defined with SCSubtype and TNBCtype cell typing predictors. All patient samples contained a mixture of subtypes; compared to primary tumours HR+ lymph node metastases had lower proportions of HER2‐Enriched cells. PDXOs exhibited differences in metabolic‐related transcripts compared to PDX tumours. Correlative analyses of cytotoxic drugs on PDX cells identified therapeutic efficacy was based on subtype proportion. Conclusions: We present a substantial multimodel dataset, a dynamic approach to cell‐wise sample annotation, and a comprehensive interrogation of models within systems of human breast cancer. This analysis and reference will facilitate informed decision‐making in preclinical research and therapeutic development through its elucidation of model limitations, subtype‐specific insights and novel targetable pathways. Key points: Patient‐derived xenografts models more closely resemble patient samples in tumour heterogeneity and cell cycle characteristics when compared with cell lines.3D organoid models exhibit differences in metabolic profiles compared to their in vivo counterparts.A valuable multimodel reference dataset that can be useful in elucidating model differences and novel targetable pathways. [ABSTRACT FROM AUTHOR]

Craniectomy is a lifesaving procedure to alleviate dangerously high intracranial pressure by removing a bone flap from the calvarium. However, the osteointegration of reimplanted bone flap with the existing bone tissue is still a clinical challenge. Hyperbaric oxygen (HBO) therapy has shown efficacy in promoting bone repair and could be a promising treatment for accelerating postoperative recovery. However, the specific cell types that are responsive to HBO treatment are not well understood. In this study, we created a murine model of craniectomy, with reimplantation of the cranial flap after 1 week. The effects of HBO treatment on bone formation and blood vessel formation around reimplanted bone were examined by micro‐computed tomography, histological staining, and immunofluorescence staining. Single‐cell RNA sequencing (scRNAseq) was utilized to identify key cell subtypes and signaling pathways after HBO treatment. We found that HBO treatment increased bone volume around reimplanted cranial flaps. HBO also increased the volume of Osterix‐expressing cells and type H vessels. scRNAseq data showed more mature osteoblasts and endothelial cells, with higher expressions of adhesion and migration‐related genes after HBO treatment. Cell–cell interaction analysis revealed a higher expression level of genes between mature osteoblasts and endothelial cells from the angiopoietin 2‐integrin α5β1 pathway. Taken together, HBO therapy promotes the healing process of craniectomy by regulating the crosstalk between vascular endothelial cells and osteogenic cells. These findings provide evidence in a preclinical model that HBO therapy enhances osteointegration by regulating angiogenesis–osteogenesis coupling, providing a scientific basis for utilizing HBO therapy for accelerating postoperative recovery after craniectomy. [ABSTRACT FROM AUTHOR]

Dorsal neural tube-derived retinoic acid promotes the end of neural crest production and transition into a definitive roof plate. Here, we analyze how this impacts the segregation of central and peripheral lineages, a process essential for tissue patterning and function. Localized in ovo inhibition in quail embryos of retinoic acid activity followed by single-cell transcriptomics unraveled a comprehensive list of differentially expressed genes relevant to these processes. Importantly, progenitors co-expressed neural crest, roof plate and dI1 interneuron markers, indicating a failure in proper lineage segregation. Furthermore, separation between roof plate and dI1 interneurons is mediated by Notch activity downstream of retinoic acid, highlighting their crucial role in establishing the roof plate-dI1 boundary. Within the peripheral branch, where absence of retinoic acid resulted in neural crest production and emigration extending into the roof plate stage, sensory progenitors failed to separate from melanocytes, leading to formation of a common glia-melanocyte cell with aberrant migratory patterns. In summary, the implementation of single-cell RNA sequencing facilitated the discovery and characterization of a molecular mechanism responsible for the segregation of dorsal neural fates during development. [ABSTRACT FROM AUTHOR]

Localized scleroderma (LS) is an autoimmune disease characterized by inflammation and fibrosis, leading to severe cutaneous manifestations such as skin hardening, tightness, discoloration, and other textural changes that may result in disability. While LS shares similar histopathologic features and immune-fibroblast interactions with systemic sclerosis (SSc), its molecular mechanisms remain understudied. Endothelial cells (EC) are known to play a crucial role in SSc but have not been investigated in LS. Single-cell RNA sequencing (scRNA-seq) now allows for detailed examination of this cell type in the primary organ of interest for scleroderma, the skin. In this study, we analyzed skin-isolated cells from 27 LS patients (pediatric and adult) and 17 healthy controls using scRNA-seq. Given the known role of EC damage as an initial event in SSc and the histologic and clinical skin similarities to LS, we focused primarily on endothelial cells. Our analysis identified eight endothelial subclusters within the dataset, encompassing both disease and healthy samples. Interaction analysis revealed that signaling from diseased endothelial cells was predicted to promote fibrosis through SELE interaction with FGFBP1 and other target genes. We also observed high levels of JAG in arterial endothelial cells and NOTCH in capillary endothelial cells, indicating the activation of a signaling pathway potentially responsible for epidermal abnormalities and contributing to LS pathogenesis. In summary, our scRNA-seq analysis identified potential disease-propagating endothelial cell clusters with upregulated pathways in LS skin, highlighting their importance in disease progression. [ABSTRACT FROM AUTHOR]

Simple Summary: Head and neck squamous cell carcinoma (HNSCC) is a complex and varied cancer that is difficult to treat due to its biological diversity. Single-cell RNA sequencing (scRNAseq) offers a way to study HNSCC by examining individual cells within tumors. This technology helps identify different cell types and their roles in cancer development, diagnosis, and treatment. By understanding how various cells respond to treatments like chemotherapy and immunotherapy, scRNAseq can enhance the study of cancer biology and improve therapeutic outcomes. This review highlights the significant impact of scRNAseq on HNSCC research and its potential to advance the study of other cancers. Background/Objectives: Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous and the most common form of head and neck cancer, posing significant challenges for disease management. The objective of this review is to assess the utility of single-cell RNA sequencing (scRNAseq) in addressing these challenges by enabling a detailed characterization of the tumor microenvironment (TME) at the cellular level. Methods: This review compiles and analyzes current strategies that utilize scRNAseq and other single-cell technologies in HNSCC research. Results: For HNSCC etiology, scRNAseq allows for the construction of cellular atlases, characterization of different cell types, and investigation of genes and processes involved in cancer initiation, development, and progression within the TME. In terms of HNSCC diagnosis and prognosis, the resolution offered by scRNAseq enables the identification of cell type-specific signatures, enhancing prognostic models and disease stratifiers for patient outcome assessments. Regarding HNSCC treatment, scRNAseq provides insights into cellular responses to various treatments, including radiotherapy, chemotherapy, and immunotherapy, contributing to a better understanding of treatment efficacy and patient outcomes. Conclusions: This review highlights the contributions of scRNAseq to HNSCC research, addressing its cellular and biological complexity, and emphasizes its potential for advancing research and clinical practice in other cancer types. [ABSTRACT FROM AUTHOR]

Background: Gynecomastia denotes the benign proliferation of glandular breast tissue and stands as a recognized risk factor for male breast cancer. Nonetheless, the underlying carcinogenic mechanisms orchestrating the progression from gynecomastia to cancer remain poorly understood. Methods: This study employed single-cell RNA sequencing (scRNA-seq) to meticulously dissect the cellular landscape of gynecomastia and unravel potential associations with male breast cancer at a single-cell resolution. Pseudotime and evolutionary analyses were executed to delineate the distinct features characterizing gynecomastia and male breast cancer. The TCGA database, along with cell-cell communication analysis and immunohistochemistry staining, was harnessed to validate differential gene expression, specifically focusing on CD13. Result: From the copy number variation profiles and evolutionary tree, we inferred shared mutation characteristics (18p+ and 18q+) underpinning both conditions. The developmental trajectory unveiled an intriguing overlap between gynecomastia and malignant epithelial cells. Moreover, the differential gene CD13 emerged as a common denominator in both gynecomastia and male breast cancer when compared with normal mammary tissue. Cell-cell interaction analysis and communication dynamics within the tumor microenvironment spotlighted distinctions between CD13+ and CD13− subsets, with the former exhibiting elevated expression of FGFR1-FGF7. Conclusions: Our investigation provides novel insights into the evolutionary progression from gynecomastia to male breast cancer, shedding light on the pivotal role of CD13 in driving this transition. The identification of CD13 as a potential therapeutic target suggests the feasibility of CD13-targeted interventions, specifically tailored for male breast cancer treatment. [ABSTRACT FROM AUTHOR]

Background: Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer with lower survival rates. Recent advancements in targeted therapies and immunotherapies targeting immune checkpoints have achieved remarkable success, there is still a large percentage of LUAD that lacks available therapeutic options. Due to tumor heterogeneity, the diagnosis and treatment of LUAD are challenging. Exploring the biology of LUAD and identifying new biomarker and therapeutic targets options are essential. Method: We performed single-cell RNA sequencing (scRNA-seq) of 6 paired primary and adjacent LUAD tissues, and integrative omics analysis of the scRNA-seq, bulk RNA-seq and whole-exome sequencing data revealed molecular subtype characteristics. Our experimental results confirm that CDC25C gene can serve as a potential marker for poor prognosis in LUAD. Results: We investigated aberrant gene expression in diverse cell types in LUAD via the scRNA-seq data. Moreover, multi-omics clustering revealed four subgroups defined by transcriptional profile and molecular subtype 4 (MS4) with poor survival probability, and immune cell infiltration signatures revealed that MS4 tended to be the immunosuppressive subtype. Our study revealed that the CDC25C gene can be a distinct prognostic biomarker that indicates immune infiltration levels and response to immunotherapy in LUAD patients. Our experimental results concluded that CDC25C expression affects lung cancer cell invasion and migration, might play a key role in regulating Epithelial-Mesenchymal Transition (EMT) pathways. Conclusions: Our multi-omics result revealed a comprehensive set of molecular attributes associated with prognosis-related genes in LUAD at the cellular and tissue level. Identification of a subtype of immunosuppressive TME and prognostic signature for LUAD. We identified the cell cycle regulation gene CDC25C affects lung cancer cell invasion and migration, which can be used as a potential biomarker for LUAD. [ABSTRACT FROM AUTHOR]

This study integrates pharmacology databases with bulk RNA-seq and scRNA-seq to reveal the latent anti-PDAC capacities of BBR. Target genes of BBR were sifted through TargetNet, CTD, SwissTargetPrediction, and Binding Database. Based on the GSE183795 dataset, DEG analysis, GSEA, and WGCNA were sequentially run to build a disease network. Through sub-network filtration acquired PDAC-related hub genes. A PPI network was established using the shared genes. Degree algorithm from cytoHubba screened the key cluster in the network. Analysis of differential mRNA expression and ROC curves gauged the diagnostic performance of clustered genes. CYBERSORT uncovered the potential role of the key cluster on PDAC immunomodulation. ScRNA-seq analysis evaluated the distribution and expression profile of the key cluster at the single-cell level, assessing enrichment within annotated cell subpopulations to delineate the target distribution of BBR in PDAC. We identified 425 drug target genes and 771 disease target genes, using 57 intersecting genes to construct the PPI network. CytoHubba anchored the top 10 highest contributing genes to be the key cluster. mRNA expression levels and ROC curves confirmed that these genes showed good robustness for PDAC. CYBERSORT revealed that the key cluster influenced immune pathways predominantly associated with Macrophages M0, CD8 T cells, and naïve B cells. ScRNA-seq analysis clarified that BBR mainly acted on epithelial cells and macrophages in PDAC tissues. BBR potentially targets CDK1, CCNB1, CTNNB1, CDK2, TOP2A, MCM2, RUNX2, MYC, PLK1, and AURKA to exert therapeutic effects on PDAC. The mechanisms of action appear to significantly involve macrophage polarization-related immunological responses. [ABSTRACT FROM AUTHOR]

Background: Single-cell RNA sequencing (scRNAseq) offers powerful insights, but the surge in sample sizes demands more computational power than local workstations can provide. Consequently, high-performance computing (HPC) systems have become imperative. Existing web apps designed to analyze scRNAseq data lack scalability and integration capabilities, while analysis packages demand coding expertise, hindering accessibility. Results: In response, we introduce scRNAbox, an innovative scRNAseq analysis pipeline meticulously crafted for HPC systems. This end-to-end solution, executed via the SLURM workload manager, efficiently processes raw data from standard and Hashtag samples. It incorporates quality control filtering, sample integration, clustering, cluster annotation tools, and facilitates cell type-specific differential gene expression analysis between two groups. We demonstrate the application of scRNAbox by analyzing two publicly available datasets. Conclusion: ScRNAbox is a comprehensive end-to-end pipeline designed to streamline the processing and analysis of scRNAseq data. By responding to the pressing demand for a user-friendly, HPC solution, scRNAbox bridges the gap between the growing computational demands of scRNAseq analysis and the coding expertise required to meet them. [ABSTRACT FROM AUTHOR]

Objective: Allergic asthma (AA) is common in children. Excess copper is observed in AA patients. It is currently unclear whether copper imbalance can cause cuproptosis in pediatric AA. Methods: The datasets about pediatric AA (GSE40732 and GSE40888) were obtained from Gene Expression Omnibus (GEO) database. The expression of cuproptosis-related genes (CRGs) and immune cell infiltration in pediatric AA samples were analyzed. Single-cell RNA sequencing (scRNA-seq) data (GSE193816) were used to evaluate the expression patterns of CRGs in AA. The identification of differentially expressed genes within clusters was conducted using weighted gene co-expression network analysis. Subsequently, disease progression and cuproptosis-related models were screened using random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and general linear model (GLM) algorithms. Results: Four CRGs were notably increased in pediatric AA samples. CD4+ T cells, macrophages and mast cells exhibited a lower cuproptosis score in AA samples, indicating that these immune cells may be closely associated with cuproptosis in AA development. Co-expression network of CRGs in AA was constructed. AA samples were divided into two cuprotosis clusters. Following construction of four machine-learning models, SVM model exhibited the highest efficacy of prediction in the testing set (AUC = 0.952). SVM model containing five important variables can be used for prediction of AA. Conclusion: This work provided a machine learning model containing five important variables, which may have good diagnostic efficiency for pediatric AA. [ABSTRACT FROM AUTHOR]

Vascular dementia (VaD) causes progressive cognitive decline in the elderly population, but there is short of available therapeutic measures. Microglia-mediated neuroinflammation is vigorously involved in the pathogenesis of VaD, but the traditional classification of microglial M1/M2 phenotypes remains restrictive and controversial. This study aims to investigate whether microglia transform into novel subtypes in VaD. Chronic cerebral hypoperfusion (CCH) rat model was constructed to mimic VaD. Microglia were isolated via magnetic-activated cell sorting and analyzed by single-cell RNA sequencing (scRNA-seq) and bioinformatics. The findings inferred from scRNA-seq and bioinformatics were further validated through in vivo experiments. In this study, microglia were divided into eight clusters. The proportion of MG5 cluster was significantly increased in the white matter of the CCH group compared with the Sham group and was named chronic ischemia-associated microglia (CIAM). Immunity- and inflammation-related genes, including RT1-Db1, RT1-Da, RT1-Ba, Cd74, Spp1, C3, and Cd68, were markedly upregulated in CIAM. Enrichment analysis illustrated that CIAM possessed the function of evoking neuroinflammation. Further studies unveiled that Cd74 is associated with the most abundant GO terms involved in inflammation as well as cell proliferation and differentiation. In addition, microglia-specific Cd74 knockdown mediated by adeno-associated virus decreased the abundance of CIAM in the white matter, thereby mitigating inflammatory cytokine levels, alleviating white matter lesions, and improving cognitive impairment for CCH rats. These findings indicate that Cd74 is the core molecule of CIAM to trigger neuroinflammation and induce microglial differentiation to CIAM, suggesting that Cd74 may be a potential therapeutic target for VaD. [ABSTRACT FROM AUTHOR]

The heart is the central organ of the circulatory system, and its proper development is vital to maintain human life. As fetal heart development is complex and poorly understood, we use single-cell RNA sequencing to profile the gene expression landscapes of human fetal hearts from the four-time points: 8, 10, 11, 17 gestational weeks (GW8, GW10, GW11, GW17), and identified 11 major types of cells: erythroid cells, fibroblasts, heart endothelial cells, ventricular cardiomyocytes, atrial cardiomyocytes, macrophage, DCs, smooth muscle, pericytes, neural cells, schwann cells. In addition, we identified a series of differentially expressed genes and signaling pathways in each cell type between different gestational weeks. Notably, we found that ANNEXIN, MIF, PTN, GRN signalling pathways were simple and fewer intercellular connections in GW8, however, they were significantly more complex and had more intercellular communication in GW10, GW11, and GW17. Notably, the interaction strength of OSM signalling pathways was gradually decreased during this period of time (from GW8 to GW17). Together, in this study, we presented a comprehensive and clear description of the differentiation processes of all the main cell types in the human fetal hearts, which may provide information and reference data for heart regeneration and heart disease treatment. [Display omitted] • Gene expression map of human fetal hearts from the four-time points were identified. • Dynamic alteration of cell subpopulations and gene expression during heart development. • ANNEXIN, MIF, PTN, GRN, OSM signalling pathways are crucial in heart development. [ABSTRACT FROM AUTHOR]

Oral lichen planus (OLP) is a chronic inflammatory disease with obscure etiopathogenesis. Macrophages play an important role in interaction between innate and adaptive immunity. This study aimed to investigate the macrophage phenotypes and obtain more comprehensive gene characteristics of macrophages in OLP. Double cluster of differentiation (CD) 68/CD86 and CD68/CD206 immunofluorescence staining was conducted in 11 biopsy-proven OLP tissue samples and 5 health control (HC) to represent M1 and M2 macrophages, respectively. The number of positively stained cells was manually counted, and the density was calculated. Furtherly, OLP single-cell dataset GSE211630 was downloaded from Gene Expression Omnibus. Gene characteristics and functional analysis of the macrophages were elucidated. In the OLP group, the densities of M1 (P < 0.001), M2 macrophages (P < 0.001) and M1/M2 ratio (P = 0.001) were significantly higher than those in HC group. Single-cell RNA sequencing revealed that proportions of CXCL10 macrophages (P = 0.003), IL1B/MMP19 macrophages (P < 0.001) were increased in OLP tissues compared with those in HC. Macrophages in OLP tissues had a stronger ability to cell chemotaxis, positive regulation of cell adhesion and antigen processing and presentation. Functional analysis revealed macrophages in OLP tissues could interact with multiple immune cells, and multiple signaling pathways were associated with macrophages in OLP. A pro-inflammatory status of macrophages with different gene characteristics was found in the microenvironment of OLP by integrating immunofluorescence double staining and single-cell RNA sequencing, which provided a potential target for clinical treatment of OLP. [ABSTRACT FROM AUTHOR]

To unravel the heterogeneity and function of microenvironmental neutrophils during intervertebral disc degeneration (IDD). Single-cell RNA sequencing (scRNA-seq) was utilized to dissect the cellular landscape of neutrophils in intervertebral disc (IVD) tissues and their crosstalk with nucleus pulposus cells (NPCs). The expression levels of macrophage migration inhibitory factor (MIF) and ACKR3 in IVD tissues were detected. The MIF/ACKR3 axis was identified and its effects on IDD were investigated in vitro and in vivo. We sequenced here 71520 single cells from 5 control and 9 degenerated IVD samples using scRNA-seq. We identified a unique cluster of neutrophils abundant in degenerated IVD tissues that highly expressed MIF and was functionally enriched in extracellular matrix organization (ECMO). Cell-to-cell communication analyses showed that this ECMO-neutrophil subpopulation was closely interacted with an effector NPCs subtype, which displayed high expression of ACKR3. Further analyses revealed that MIF was positively correlated with ACKR3 and functioned via directly binding to ACKR3 on effector NPCs. MIF inhibition attenuated degenerative changes of NPCs and extracellular matrix, which could be partially reversed by ACKR3 overexpression. Clinically, a significant correlation of high MIF/ACKR3 expression with advanced IDD grade was observed. Furthermore, we also found a positive association between MIF+ ECMO-neutrophil counts and ACKR3+ effector NPCs density as well as higher expression of the MIF/ACKR3 signaling in areas where these two cell types were neighbors. These data suggest that ECMO-neutrophil promotes IDD progression by their communication with NPCs via the MIF/ACKR3 axis, which may shed light on therapeutic strategies. [ABSTRACT FROM AUTHOR]

Background: Cigarette smoking is considered as a major risk factor for esophageal carcinoma (ESCA) patients. Neutrophil activation plays a key role in cancer development and progression. However, the relationship between cigarette smoking and neutrophils in ESCA patients remained unclear. Methods: Single‐cell RNA sequencing (scRNA‐seq) and bulk RNA sequencing data were obtained from public databases. Uniform manifold approximation and projection (UMAP) was used to perform downscaling and clustering based on scRNA‐seq data. The module genes associated with smoking in ESCA patients were filtered by weighted gene co‐expression network analysis (WGCNA). Using the "AUCell" package, the enrichment of different cell subpopulations and gene collections were assessed. "CellChat" and "CellphoneDB" were used to infer the probability and significance of ligand–receptor interactions between different cell subpopulations. Results: WGCNA was performed to screened module genes associated with smoking in ESCA patients from MEdarkquosie, MEturquoise, and MEgreenyellow. Next, eight cell clusters were identified, and using the AUCell score, we determined that neutrophil clusters were more active in the gene modules associated with smoking in ESCA patients. Two neutrophil subtypes, Neutrophils 1 and Neutrophils 2, exhibited greater enrichment in inflammatory response regulation, intercellular adhesion, and regulation of T cell activation. Furthermore, we found that neutrophils may pass through AMPT‐(ITGA5 + ITGB1) and ICAM1‐AREG in order to promote the development of ESCA, and that the expression levels of the receptor genes insulin‐degrading enzyme and ITGB1 were significantly and positively correlated with cigarette smoking per day. Conclusion: Combining smoking‐related gene modules and scRNA‐seq, the current findings revealed the heterogeneity of neutrophils in ESCA and a tumor‐promoting role of neutrophils in the tumor microenvironment of smoking ESCA patients. [ABSTRACT FROM AUTHOR]

Background This study aims to address challenges in dental pulp regeneration therapy. The heterogeneity of DPSCs poses challenges, especially in stem cell transplantation for clinical use, particularly when sourced from donors of different ages and conditions. Methods Pseudotime analysis was employed to analyze single-cell sequencing data, and immunohistochemical studies were conducted to investigate the expression of fibronectin 1 (FN1). We performed in vitro sorting of PDGFRβ+ DPSCs using flow cytometry. A series of functional assays, including cell proliferation, scratch, and tube formation assays, were performed to experimentally validate the vasculogenic capabilities of the identified PDGFRβ+ DPSC subset. Furthermore, gene-edited mouse models were utilized to demonstrate the importance of PDGFRβ+ DPSCs. Transcriptomic sequencing was conducted to compare the differences between PDGFRβ+ DPSCs and P1-DPSCs. Results Single-cell sequencing analysis unveiled a distinct subset, PDGFRβ+ DPSCs, characterized by significantly elevated FN1 expression during dental pulp development. Subsequent cell experiments demonstrated that this subset possesses remarkable abilities to promote HUVEC proliferation, migration, and tube formation. Gene-edited mouse models confirmed the vital role of PDGFRβ+ DPSCs in dental pulp development. Transcriptomic sequencing and in vitro experiments demonstrated that the PDGFR/PI3K/AKT signaling pathway is a crucial factor mediating the proliferation rate and pro-angiogenic properties of PDGFRβ+ DPSCs. Conclusion We defined a new subset, PDGFRβ+ DPSCs, characterized by strong proliferative activity and pro-angiogenic capabilities, demonstrating significant clinical translational potential. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the functions of exocrine islet cell subtypes in the early stage of obesity induced by high-fat diet (HFD), which is accompanied with deterioration of the systemic insulin response and islet subpopulation abnormalities. Methods: In this study, we analyzed published islet single-cell RNA sequencing (scRNA-seq) datasets from the early stage induced by HFD feeding. Bioinformatics tools such as findMarkers, Cellchat, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and Gene Ontology (GO) terms were applied to identify the different functions of exocrine cell clusters. Results: A total of 26 cell clusters were obtained were identified from this dietary intervention model. Most proportions of cell subtypes were consistent between high-fat diet (HFD) and low-fat diet (LFD) groups, except for partial endocrine islet clusters and exocrine clusters. Most differentiated expression of genes in the HFD group was found in exocrine cluster. And we also found that the cell–cell interactions between ductal and endothelial cells were reduced in the HFD group, with the significant alteration in C17 (ductal) cluster. By further analyzing the co-expression regulatory network of transcription in the C17 cluster, we speculate that differentially expressed transcription factors affected the function of duct cells by affecting the expression of related genes in intercellular interaction networks, thereby promoting insulin resistance (IR) development. Conclusion: Our results provide a reference for the function and regulatory mechanisms of exocrine cells in the obesity induced by HFD and probably influence the process of following insulin resistance. [ABSTRACT FROM AUTHOR]

Background: Gliomas are aggressive brain tumors associated with a poor prognosis. Cancer stem cells (CSCs) play a significant role in tumor recurrence and resistance to therapy. This study aimed to identify and characterize glioma stem cells (GSCs), analyze their interactions with various cell types, and develop a prognostic signature. Methods: Single-cell RNA sequencing data from 44 primary glioma samples were analyzed to identify GSC populations. Spatial transcriptomics and gene regulatory network analyses were performed to investigate GSC localization and transcription factor activity. CellChat analysis was conducted to infer cell-cell communication patterns. A GSC signature (GSCS) was developed using machine learning algorithms applied to bulk RNA sequencing data from multiple cohorts. In vitro and in vivo experiments were conducted to validate the role of TUBA1C, a key gene within the signature. Results: A distinct GSC population was identified, characterized by high proliferative potential and an enrichment of E2F1, E2F2, E2F7, and BRCA1 regulons. GSCs exhibited spatial proximity to myeloid-derived suppressor cells (MDSCs). CellChat analysis revealed an active MIF signaling pathway between GSCs and MDSCs. A 26-gene GSCS demonstrated superior performance compared to existing prognostic models. Knockdown of TUBA1C significantly inhibited glioma cell migration, and invasion in vitro, and reduced tumor growth in vivo. Conclusion: This study offers a comprehensive characterization of GSCs and their interactions with MDSCs, while presenting a robust GSCS. The findings offer new insights into glioma biology and identify potential therapeutic targets, particularly TUBA1C, aimed at improving patient outcomes. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) poses a global health threat, with the oral microbiome increasingly implicated in its pathogenesis. This study leverages Mendelian Randomization (MR) to explore causal links between oral microbiota and CRC using data from the China National GeneBank and Biobank Japan. By integrating multi-omics approaches, we aim to uncover mechanisms by which the microbiome influences cellular metabolism and cancer development. Methods: We analyzed microbiome profiles from 2017 tongue and 1915 saliva samples, and GWAS data for 6692 CRC cases and 27178 controls. Significant bacterial taxa were identified via MR analysis. Single-cell RNA sequencing and enrichment analyses elucidated underlying pathways, and drug predictions identified potential therapeutics. Results: MR identified 19 bacterial taxa significantly associated with CRC. Protective effects were observed in taxa like RUG343 and Streptococcus_umgs_2425, while HOT-345_umgs_976 and W5053_sp000467935_mgs_712 increased CRC risk. Single-cell RNA sequencing revealed key pathways, including JAK-STAT signaling and tyrosine metabolism. Drug prediction highlighted potential therapeutics like Menadione Sodium Bisulfite and Raloxifene. Conclusion: This study establishes the critical role of the oral microbiome in colorectal cancer development, identifying specific microbial taxa linked to CRC risk. Single-cell RNA sequencing and drug prediction analyses further elucidate key pathways and potential therapeutics, providing novel insights and personalized treatment strategies for CRC. [ABSTRACT FROM AUTHOR]

Introduction: Ferroptosis plays a significant role in intervertebral disc degeneration (IDD). Understanding the key genes regulating ferroptosis in IDD could reveal fundamental mechanisms of the disease, potentially leading to new diagnostic and therapeutic targets. Methods: Public datasets (GSE23130 and GSE70362) and the FerrDb database were analyzed to identify ferroptosis-related genes (DE-FRGs) involved in IDD. Single-cell RNA sequencing data (GSE199866) was used to validate the specific roles and expression patterns of these genes. Immunohistochemistry and Western blot analyses were subsequently conducted in both clinical samples and mouse models to assess protein expression levels across different tissues. Results: The analysis identified seven DE-FRGs, including MT1G, CA9, AKR1C1, AKR1C2, DUSP1, CIRBP, and KLHL24, with their expression patterns confirmed by single-cell RNA sequencing. Immunohistochemistry and Western blot analysis further revealed that MT1G, CA9, AKR1C1, AKR1C2, DUSP1, and KLHL24 exhibited differential expression during the progression of IDD. Additionally, the study highlighted the potential immune-modulatory functions of these genes within the IDD microenvironment. Discussion: Our study elucidates the critical role of ferroptosis in IDD and identifies specific genes, such as MT1G and CA9, as potential targets for diagnosis and therapy. These findings offer new insights into the molecular mechanisms underlying IDD and present promising avenues for future research and clinical applications. [ABSTRACT FROM AUTHOR]

Background: Gliomas, originating from the most common non-neuronal cells in the brain (glial cells), are the most common brain tumors and are associated with high mortality and poor prognosis. Glioma cells exhibit a tendency to disrupt normal cell-cycle regulation, leading to abnormal proliferation and malignant growth. This study investigated the predictive potential of GJC1 in gliomas and explored its relationship with the cell cycle. Methods: Retrospective analysis of RNA-seq and single-cell sequencing data was conducted using the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases. The differential expression of GJC1 in gliomas with various pathological features and in different non-neuronal cell groups was analyzed. Functional data were examined using gene set variation analysis (GSVA). Furthermore, CellMiner was used to evaluate the relationship between GJC1 expression and predicted treatment response across these databases. Results: GJC1 expression was enriched in high-grade gliomas and 1p/19q non-codeletion gliomas. GJC1 enrichment was observed in classical and mesenchymal subtypes within the TCGA glioma subtype group. In single-cell subgroup analysis, GJC1 expression was higher in glioma tissues compared to other non-neuronal cells. Additionally, the TCGA classical subtype of glioma cells exhibited more GJC1 expression than the other subgroups. GJC1 emerged as an independent prognostic factor for overall survival in glioma. GSVA unveiled potential mechanisms by which GJC1 may impact cell-cycle regulation in glioma. Finally, a significant correlation was observed between GJC1 expression and the sensitivity of multiple anti-cancer drugs. Conclusion: These findings confirmed GJC1 as a novel biomarker and provided insights into the differential gene expression in non-neuronal cells and the impact of the cell cycle on gliomas. Consequently, GJC1 may be used to predict glioma prognosis and has potential therapeutic value. [ABSTRACT FROM AUTHOR]

Background: This study investigates the role of CXXC5 in the self-renewal and differentiation of hematopoietic stem cells (HSCs) within the bone marrow microenvironment, utilizing advanced methodologies such as single-cell RNA sequencing (scRNA-seq), CRISPR-Cas9, and proteomic analysis. Methods: We employed flow cytometry to isolate HSCs from bone marrow samples, followed by scRNA-seq analysis using the 10x Genomics platform to examine cell clustering and CXXC5 expression patterns. CRISPR-Cas9 and lentiviral vectors facilitated the knockout and overexpression of CXXC5 in HSCs. The impact on HSCs was assessed through qRT-PCR, Western blot, CCK-8, CFU, and LTC-IC assays, alongside flow cytometry to measure apoptosis and cell proportions. A mouse model was also used to evaluate the effects of CXXC5 manipulation on HSC engraftment and survival rates. Results: Our findings highlight the diversity of cell clustering and the significant role of CXXC5 in HSC regulation. Knockout experiments showed reduced proliferation and accelerated differentiation, whereas overexpression led to enhanced proliferation and delayed differentiation. Proteomic analysis identified key biological processes influenced by CXXC5, including cell proliferation, differentiation, and apoptosis. In vivo results demonstrated that CXXC5 silencing impaired HSC engraftment in a bone marrow transplantation model. Conclusion: CXXC5 is crucial for the regulation of HSC self-renewal and differentiation in the bone marrow microenvironment. Its manipulation presents a novel approach for enhancing HSC function and provides a potential therapeutic target for hematological diseases. [ABSTRACT FROM AUTHOR]

Background: Breast cancer (BC) exhibits remarkable heterogeneity. However, the transcriptomic heterogeneity of BC at the single-cell level has not been fully elucidated. Methods: We acquired BC samples from 14 patients. Single-cell RNA sequencing (scRNA-seq), bioinformatic analyses, along with immunohistochemistry (IHC) and immunofluorescence (IF) assays were carried out. Results: According to the scRNA-seq results, 10 different cell types were identified. We found that Cancer-Associated Fibroblasts (CAFs) exhibited distinct biological functions and may promote resistance to therapy. Metabolic analysis of tumor cells revealed heterogeneity in glycolysis, gluconeogenesis, and fatty acid synthetase reprogramming, which led to chemotherapy resistance. Furthermore, patients with multiple metastases and progression were predicted to benefit from immunotherapy based on a heterogeneity analysis of T cells and tumor cells. Conclusions: Our findings provide a comprehensive understanding of the heterogeneity of BC, provide comprehensive insight into the correlation between cancer metabolism and chemotherapy resistance, and enable the prediction of immunotherapy responses based on T-cell heterogeneity. [ABSTRACT FROM AUTHOR]

Background: Autism spectrum disorder (ASD) is a class of complex neurodevelopment disorders with high genetic heterogeneity. Long non-coding RNAs (lncRNAs) are vital regulators that perform specific functions within diverse cell types and play pivotal roles in neurological diseases including ASD. Therefore, exploring lncRNA regulation would contribute to deciphering ASD molecular mechanisms. Existing computational methods utilize bulk transcriptomics data to identify lncRNA regulation in all of samples, which could reveal the commonalities of lncRNA regulation in ASD, but ignore the specificity of lncRNA regulation across various cell types. Results: Here, we present Cycle (Cell type-specificlncRNA regulatory network) to construct the landscape of cell type-specific lncRNA regulation in ASD. We have found that each ASD cell type is unique in lncRNA regulation, and more than one-third and all cell type-specific lncRNA regulatory networks are characterized as scale-free and small-world, respectively. Across 17 ASD cell types, we have discovered 19 rewired and 11 stable modules, along with eight rewired and three stable hubs within the constructed cell type-specific lncRNA regulatory networks. Enrichment analysis reveals that the discovered rewired and stable modules and hubs are closely related to ASD. Furthermore, more similar ASD cell types tend to be connected with higher strength in the constructed cell similarity network. Finally, the comparison results demonstrate that Cycle is a potential method for uncovering cell type-specific lncRNA regulation. Conclusion: Overall, these results illustrate that Cycle is a promising method to model the landscape of cell type-specific lncRNA regulation, and provides insights into understanding the heterogeneity of lncRNA regulation between various ASD cell types. [ABSTRACT FROM AUTHOR]

Primordial germ cells (PGCs) in avian species exhibit unique developmental features, including the ability to migrate through the bloodstream and colonize the gonads, allowing their isolation at various developmental stages. Several methods have been developed for the isolation of avian PGCs, including density gradient centrifugation, size-dependent separation, and magnetic-activated cell sorting (MACS) or fluorescence-activated cell sorting (FACS) using a stage-specific embryonic antigen-1 (SSEA-1) antibody. However, these methods present limitations in terms of efficiency and applicability across development stages. In particular, the specificity of SSEA-1 decreases in later developmental stages. Furthermore, surface markers that can be utilized for isolating or utilizing PGCs are lacking for wild birds, including zebra finches, and endangered avian species. To address this, we used single-cell RNA sequencing (scRNA-seq) to uncover novel PGC-specific surface markers in chicken and zebra finch. We screened for genes that were primarily expressed in the PGC population within the gonadal cells. Analyses of gene expression patterns and levels based on scRNA-seq, coupled with validation by RT-PCR, identified NEGR1 and SLC34A2 as novel PGC-specific surface markers in chickens and ESYT3 in zebra finches. Notably, these newly identified genes exhibited sustained expression not only during later developmental stages but also in reproductive tissues. [ABSTRACT FROM AUTHOR]