bims-sicarn Biomed News
on scRNA-seq
Issue of 2025–05–18
seventy papers selected by
Anna Zawada, International Centre for Translational Eye Research
  1. A Transfer Learning Framework for Predicting and Interpreting Drug Responses via Single-Cell RNA-Seq Data.
  2. Exploration the role of pro-inflammatory fibroblasts and related markers in periodontitis: combing with scRNA-seq and bulk-seq data.
  3. Integrative single-cell RNA sequencing and bulk RNA sequencing reveals the characteristics of glutathione metabolism and protective role of GSTA4 gene in pancreatic cancer.
  4. Integrating single-cell sequencing and transcriptome analysis to unravel the mechanistic role of sialylation-related genes in sepsis-induced acute respiratory distress syndrome.
  5. Single-cell analyses unravel ecosystem dynamics and intercellular crosstalk during gallbladder cancer malignant transformation.
  6. Identification and Validation of Potential Immune-Related Genes for Endometriosis.
  7. Landscape of spatial disruption of homeostasis in the middle temporal gyrus of epileptic patients.
  8. Single-Cell Transcriptomics Reveals Stem Cell-Derived Exosomes Attenuate Inflammatory Gene Expression in Pulmonary Oxygen Toxicity.
  9. Potential key genes for giant cell arteritis revealed based on single-cell sequencing and Mendelian randomization analysis.
  10. Integration of Single-Cell RNA Sequencing Data and Bulk Sequencing Data to Characterise the CD8+ T-Cell Exhaustion Mediated Immune Microenvironment in CRC.
  11. Single-cell transcription reveals hepatocyte-to-cholangiocyte reprogramming and biliary gene profile in biliary atresia.
  12. Deciphering the role of acetylation-related gene NAT10 in colon cancer progression and immune evasion: implications for overcoming drug resistance.
  13. Stromal heterogeneity in the adult lung delineated by single-cell genomics.
  14. Aboral cell types of Clytia and coral larvae have shared features and link taurine to the regulation of settlement.
  15. scRNA-seq and scATAC-seq reveal that Sertoli cell mediates spermatogenesis disorders through stage-specific communications in non-obstructive azoospermia.
  16. Identification and Exploration of Pyroptosis-Related Genes in Macrophage Cells Reveal Necrotizing Enterocolitis Heterogeneity Through Single-Cell and Bulk-Sequencing.
  17. Single-cell transcriptome reveals potential mechanisms for gout in children.
  18. Single-cell transcriptome analysis profiles cellular and molecular alterations in aortic tissue from patients with Behçet's syndrome.
  19. Dissecting Autophagy Gene Expression in Endothelial Cells of Pulmonary Arterial Hypertension at Single-Cell Resolution.
  20. What single-cell RNA sequencing taught us about MGMT expression in glioblastoma.
  21. Single-cell RNA sequencing reveals immunological link between house dust mite allergy and childhood asthma.
  22. Transcriptomic Plasticity of Human Alveolar Macrophages Revealed by Single-Cell RNA Sequencing Following Drug Exposure: Implications for Therapeutic Development.
  23. Integrating multi-omics data to identify the role of Aggrephagy-related genes in tumor microenvironment and key tumorigenesis factors of GB from the perspective of single-cell sequencing.
  24. Upregulation of YY1/EZH2 and MLH1 as Therapeutic Targets for Adult T-Cell Leukemia/Lymphoma.
  25. Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer.
  26. New Insights and Implications of Cell-Cell Interactions in Developmental Biology.
  27. Single-Cell RNA Sequencing Reveals Functional Exhaustion of T Cells in Oral Lichen Planus.
  28. Single-Cell Profiling of Mononuclear Cells Identifies Transcriptomics Signatures Differentiating Prostate Cancer From Benign Prostatic Hyperplasia.
  29. Arginine methylation modulates tumor fate and prognosis in clear cell renal cell carcinoma.
  30. MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.
  31. Potential mechanisms of epigenetic regulation in diabetic retinopathy from the perspectives of multi-omics.
  32. INHBA+ macrophages and Pro-inflammatory CAFs are associated with distinctive immunosuppressive tumor microenvironment in submucous Fibrosis-Derived oral squamous cell carcinoma.
  33. Alternative lengthening of telomeres confers favorable prognosis in chondrosarcomas.
  34. Exploring the Role of Circadian Rhythm-Related Genes in the Identification of Sepsis Subtypes and the Construction of Diagnostic Models Based on RNA-seq and scRNA-seq.
  35. Sepsis Important Genes Identification Through Biologically Informed Deep Learning and Transcriptomic Analysis.
  36. Harnessing Calmodulin-Related Genes to Build a Prognostic Model in Esophageal Squamous Cell Carcinoma for a Comprehensive Analysis of Single-Cell Immune Characteristics and Drug Efficacy.
  37. Dual oxic-anoxic co-culture enables direct study of anaerobe-host interactions at the airway epithelial interface.
  38. Comprehensive single-cell transcriptomic reveals different destinies of melanocytes and dynamic changes of immune microenvironment in a psychological stress-induced leukoderma and leukotrichia mouse model.
  39. Identification of novel potential biomarkers using bulk RNA and single cells to build a neural network model for diagnosis of liver cancer.
  40. Identifying Immunomodulatory Subpopulations of Adipose Stromal Vascular Fraction and Stem/Stromal Cells Through Single-Cell Transcriptomics and Bulk Proteomics.
  41. Overexpression of MMP14 is associated with poor prognosis and immune cell infiltration in colon cancer.
  42. Integrative Analysis Reveals Genes Causal Relation with Ovarian Cancer and aging.
  43. IGFBP3 enhances adipose-derived stem cell function in soft tissue injury repair via ITGB1 and ERK pathway activation.
  44. Single-cell combined transcriptome probes prognostic mechanisms of sialylation-related genes in cervical cancer.
  45. Single-Cell RNA-Seq Reveals Aging-Related Impairment of Microglial Efferocytosis Contributing to Apoptotic Cells Accumulation After Retinal Injury.
  46. Multi-omics identify ribosome related causal genes methylation, splicing, and expression in prostate cancer.
  47. Single-cell RNA sequencing reveals SLC31A1-mediated M2 polarization of macrophages promotes malignant progression in triple-negative breast cancer.
  48. Shh agonist enhances maturation in homotypic Lgr5-positive inner ear organoids.
  49. Deciphering Anticancer Mechanisms of Calycosin in Lung Adenocarcinoma Through Multi-Omics: Targeting SMAD3-Mediated NOTCH Signaling in the Tumor Microenvironment.
  50. Sialyltransferase gene signature as a predictor of prognosis and therapeutic response in kidney renal clear cell carcinoma.
  51. Quantitative Analysis of Tomato Flower Pedicel Abscission and Single-Cell Transcriptome Analysis.
  52. Microglia Single-Cell RNA-Seq Enables Robust and Applicable Markers of Biological Aging.
  53. Targeting mesenchymal monocyte-derived macrophages to enhance the sensitivity of glioblastoma to temozolomide by inhibiting TNF/CELSR2/p65/Kla-HDAC1/EPAS1 axis.
  54. Deciphering the role of pyroptosis-related genes and natural killer T cells in sepsis pathogenesis: a comprehensive bioinformatics and Mendelian randomization analysis.
  55. Characterization and prognostic of CD8 + TIM3 + CD101 + T cells in glioblastoma multiforme.
  56. Single-cell transcriptomics and functional validation revealed PLEKHA5-L as a promoter of growth and migration in brain metastatic melanoma cells.
  57. WFDC3 identified as a prognostic and immune biomarker in pancreatic cancer.
  58. Decoding the Tumor Microenvironment of Myoepithelial Cells in Triple-Negative Breast Cancer Through Single-Cell and Transcriptomic Sequencing and Establishing a Prognostic Model Based on Key Myoepithelial Cell Genes.
  59. An immune cell activation signature reflected hepatocellular carcinoma heterogeneity and predicted clinical outcomes.
  60. Thioredoxin: a key factor in cold tumor formation and a promising biomarker for immunotherapy resistance in NSCLC.
  61. Immune-endothelial cell crosstalk in hepatic endothelial injury of liver fibrotic mice.
  62. An analysis of prognostic risk and immunotherapy response of glioblastoma patients based on single-cell landscape and nitrogen metabolism.
  63. Unraveling the role of histone acetylation in sepsis biomarker discovery.
  64. Deciphering the Immunomodulatory Function of GSN+ Inflammatory Cancer-Associated Fibroblasts in Renal Cell Carcinoma Immunotherapy: Insights From Pan-Cancer Single-Cell Landscape and Spatial Transcriptomics Analysis.
  65. ARHGDIB as a prognostic biomarker and modulator of the immunosuppressive microenvironment in glioma.
  66. Uncovering potential biomarkers of endometriosis: transcriptomic and single-cell analysis.
  67. Dissection of the global responses of mandarin fish pyloric cecum to an acute ranavirus (MRV) infection reveals the formation of serositis and then ascites.
  68. Atf3 + senescent chondrocytes mediate meniscus degeneration in aging.
  69. Activated Schwann cells promote tumor growth in colon cancer.
  70. Temporal evolution of fibroblast responses following salivary gland ductal ligation injury.
  1. Int J Mol Sci. 2025 May 04. pii: 4365. [Epub ahead of print]26(9):
    A Transfer Learning Framework for Predicting and Interpreting Drug Responses via Single-Cell RNA-Seq Data.
    Yujie He, Shenghao Li, Hao Lan, Wulin Long, Shengqiu Zhai, Menglong Li, Zhining Wen.
      Chemotherapy is a fundamental therapy in cancer treatment, yet its effectiveness is often undermined by drug resistance. Understanding the molecular mechanisms underlying drug response remains a major challenge due to tumor heterogeneity, complex cellular interactions, and limited access to clinical samples, which also hinder the performance and interpretability of existing predictive models. Meanwhile, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for uncovering resistance mechanisms, but the systematic collection and utilization of scRNA-seq drug response data remain limited. In this study, we collected scRNA-seq drug response datasets from publicly available web sources and proposed a transfer learning-based framework to align bulk and single cell sequencing data. A shared encoder was designed to project both bulk and single-cell sequencing data into a unified latent space for drug response prediction, while a sparse decoder guided by prior biological knowledge enhanced interpretability by mapping latent features to predefined pathways. The proposed model achieved superior performance across five curated scRNA-seq datasets and yielded biologically meaningful insights through integrated gradient analysis. This work demonstrates the potential of deep learning to advance drug response prediction and underscores the value of scRNA-seq data in supporting related research.
    Keywords:  bulk RNA sequencing; deep learning; drug response; interpretability; single-cell RNA sequencing
    DOI:  https://doi.org/10.3390/ijms26094365
  2. Front Immunol. 2025 ;16 1537046
    Exploration the role of pro-inflammatory fibroblasts and related markers in periodontitis: combing with scRNA-seq and bulk-seq data.
    Erli Wu, Feihan Gu, Qiangqiang Zhuo, Ziyang Gao, Yu Zhang, Jingjing Li, Xuan Yin, Weimin Bao, Xianqing Zhou, Feng Liang, Shouxiang Yang, Yuanyin Wang, Qingqing Wang, Wei Shao.
       Background: Gingival fibroblasts (GFs), as a critical component of periodontal tissue, play a vital role in processes such as collagen synthesis, wound healing, and tissue repair, thereby maintaining the structural integrity of periodontal tissues. Interestingly, recent studies have revealed that GFs also contribute to the pathophysiology of periodontitis by promoting inflammatory responses. However, its specific molecular mechanism and clinical relevance are still not fully understood.
    Methods: To find pro-inflammatory gingival fibroblasts (PIGFs) in periodontitis, a comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data from normal and periodontitis patients was conducted. Then, the role of this celltype in periodontitis was further explored by using cell communication. By merging bulk transcriptome data and employing multiple machine learning algorithms, potential feature genes with PIGFs were further screened, which were verified by qPCR and immunofluorescence staining. Lastly, a cell function test was used to examine the part these genes play in the pathogenesis of periodontitis.
    Results: Through single-cell sequencing analysis, we identified PIGFs which were closely related to the development of periodontitis. Cell communication analysis revealed the specific role of PIGFs in periodontitis. Differential gene analysis, WGCNA, and machine learning algorithms identified two genes (MME and TSPAN11) as potential therapeutic targets for periodontitis. Immune infiltration analysis demonstrated a significant correlation between these genes and the immune response. Functionally, down-regulation of MME and TSPAN11 promoted the proliferation and migration of GFs and significantly inhibited the release of inflammatory cytokines and chemokines.
    Conclusion: This study identified a subpopulation of GFs closely associated with the inflammatory response through scRNA-seq analysis. These cells may contribute to the progression of periodontitis by interacting with various immune and non-immune cell types. Notably, MME and TSPAN11 were identified as key genes associated with this specific GFs subpopulation that may drive disease progression by exacerbating the inflammatory response, suggesting their potential as therapeutic targets for periodontitis.
    Keywords:  feature genes; fibroblasts; machine learning; periodontitis; pro-inflammatory
    DOI:  https://doi.org/10.3389/fimmu.2025.1537046
  3. Front Immunol. 2025 ;16 1571431
    Integrative single-cell RNA sequencing and bulk RNA sequencing reveals the characteristics of glutathione metabolism and protective role of GSTA4 gene in pancreatic cancer.
    Xinya Jia, Qiang Zhang, Zhe Wang, Jianliang Cao, Anran Song, Chao Lan, Yuepeng Hu.
       Background: Recent studies have increasingly reported abnormal glutathione (GSH) metabolism within the tumor microenvironment across various solid tumors. However, the specific mechanisms underlying aberrant GSH metabolism in pancreatic cancer (PC) remain unclear. This study aims to investigate the prognostic significance of GSH metabolism-related genes in PC and to identify key molecular targets, thereby providing novel perspectives for targeted PC therapy.
    Methods: The GSH metabolism gene set was retrieved from the KEGG database. Utilizing single-cell transcriptomic data from the GSE205049 dataset, this study analyzed the variation in GSH metabolic signaling intensity across distinct cell types within the tumor microenvironment of PC. Additionally, transcriptomic data from multiple repositories, including TCGA, ICGC, and GEO, comprising a total of 930 patients with PC, were integrated to construct a prognostic molecular classifier related to GSH metabolism. Furthermore, the role of the key gene GSTA4 in PC was experimentally validated through a series of in vitro assays.
    Results: Significant differences in GSH metabolic signaling intensity were observed across various cell types in both normal pancreatic and PC tissues. A prognostic signature comprising six GSH metabolism-related genes (GSTA5, PGD, IDH2, GSTA4, GPX2, and GPX3) was established, wherein a high-risk score was associated with a poorer patient prognosis. Notably, GSTA4 expression was significantly reduced in PC tissues, and higher GSTA4 levels were linked to a favorable prognosis. In vitro functional analyses demonstrated that GSTA4 overexpression markedly inhibited PC cell proliferation and migration.
    Conclusion: The GSH metabolism-associated prognostic signature developed in this study effectively identifies high-risk patients with PC. As a prognostic protective factor, GSTA4 exhibits downregulated expression in PC tissues and suppresses tumor proliferation and migration, highlighting its potential as a therapeutic target.
    Keywords:  GSH metabolism; GSTA4 gene; bulk RNA sequencing; pancreatic cancer; single-cell RNA sequencing
    DOI:  https://doi.org/10.3389/fimmu.2025.1571431
  4. Front Immunol. 2025 ;16 1528769
    Integrating single-cell sequencing and transcriptome analysis to unravel the mechanistic role of sialylation-related genes in sepsis-induced acute respiratory distress syndrome.
    Xiaobing Liu, Yake Huang, Hao Zhang, Xia Yang, Quanxing Liu, Jigang Dai.
       Background: Studies have shown that sialylation of C1 esterase inhibitors is crucial for their interaction with histones, and histone-C1 esterase inhibitor complexes are detected in acute respiratory distress syndrome (ARDS), suggesting a potential role of sialylation in ARDS. However, the specific function of sialylation in ARDS remains unclear. Therefore, this study aimed to investigate the mechanism of sialylation-related genes (SRGs) in sepsis-induced ARDS.
    Methods: The ARDS related datasets (GSE32707, GSE66890, and GSE151263) were included in this study. Candidate genes were identified by implementing differential expression analysis and weighted gene co-expression network analysis (WGCNA). Subsequently, further selection by machine learning and expression assessment confirmed the key genes related to sialylation in sepsis-induced ARDS. Following this, the predictive ability of key genes as a whole for sepsis-induced ARDS was evaluated by creating a nomogram model. Afterwards, enrichment analysis, construction of regulatory networks, and drug prediction analysis were implemented to further understand the molecular mechanisms of action of key genes. Furthermore, single-cell RNA sequencing (scRNA-seq) data analysis was conducted to obtain key cells. Additionally, cell communication and pseudo-time analyses were implemented. In the end, the expression levels of the key genes were assessed by collecting clinical samples.
    Results: CD19 and GPR65 were identified as key genes associated with sialylation in sepsis-induced ARDS. The constructed nomogram model demonstrated that CD19 and GPR65 as a whole exhibited robust predictive capability for sepsis-induced ARDS. Meanwhile, CD19 and GPR65 were also found to be significantly co-enriched in the apoptosis and B-cell receptor signaling pathway. In addition, some important regulators and drugs with targeting effects on key genes were predicted, such as NEAT1, OIP5-AS1, alprostadil, and tacrolimus. Further, the scRNA-seq data analysis identified nine cell types, among which CD14 monocytes (CD14Mono) was designated as the key cell. Importantly, GPR65 expression exhibited dynamic changes during differentiation of CD14Mono. Also, we found that CD19 was significantly up-regulated in ARDS group.
    Conclusion: We identified CD19 and GPR65 as key genes associated with sialylation in sepsis-induced ARDS, highlighting CD14Mono as key cell type implicated in sepsis-induced ARDS. These findings offered theoretical support for understanding the mechanism of sialylation on sepsis-induced ARDS.
    Keywords:  key genes; nomogram; sepsis-induced acute respiratory distress syndrome; sialylation; single-cell RNA sequencing
    DOI:  https://doi.org/10.3389/fimmu.2025.1528769
  5. Hepatol Commun. 2025 Jun 01. pii: e0697. [Epub ahead of print]9(6):
    Single-cell analyses unravel ecosystem dynamics and intercellular crosstalk during gallbladder cancer malignant transformation.
    Zhaobin He, Jianqiang Cao, Xiqiang Wang, Shengbiao Yang, Huijie Gao, Yongzhe Yu, Zequn Di, Cheng Peng.
       BACKGROUND: Gallbladder cancer (GBC) is a rare but aggressive malignancy, often detected late due to early asymptomatic stages. Understanding cellular and molecular changes from normal tissue to high-grade intraepithelial neoplasia (HGIN) and invasive GBC is vital for identifying early biomarkers and therapeutic targets.
    METHODS: We performed single-cell RNA sequencing on 98,113 cells derived from 2 normal adjacent tissues (NAT), 2 HGIN, and 6 GBC samples. The cellular diversity and heterogeneity, particularly within epithelial and immune cell populations in NAT-HGIN-GBC, were investigated utilizing single-cell RNA sequencing, bulk RNA sequencing (bulk RNA-seq), and 10 machine learning methodologies. Furthermore, the intercellular crosstalk between epithelial cells and tumor immune microenvironment cells was examined and validated through multiplex immunofluorescence staining.
    RESULTS: The constructed cell atlas elucidated alterations in the immune landscape across various states of NAT-HGIN-GBC, highlighting a more pronounced inhibitory immune microenvironment in GBC. The epithelial subtype TOP2A+ Epi is markedly elevated in GBC and is correlated with a poor prognosis. Key genes associated with this subtype may include GMNN, CYTOR, KLK6, and BIRC5. Similarly, immunosuppressive macrophages, identified as TOP2A+ Macro, also increase along the NAT-HGIN-GBC sequence and are linked to reduced patient survival. Furthermore, TOP2A+ Macro and CD8+ exhausted T cells (CD8+ Tex) engage in intercellular communication with epithelial TOP2A+Epi cells via the TWEAK/FN14 signaling pathway, thereby promoting tumor progression and immune evasion in GBC. The findings were further corroborated through multiplex immunofluorescence staining conducted on specimens from patients.
    CONCLUSIONS: This study elucidates significant alteration in the cellular ecosystems and intercellular signaling within the tumor immune microenvironment across the NAT-HGIN-GBC sequence. It identifies TOP2A, TWEAK, and FN14 as potential biomarkers and therapeutic targets for GBC.
    Keywords:  TOP2A; TWEAK/FN14 signaling; intercellular communication; single-cell RNA sequencing; tumor immune microenvironment
    DOI:  https://doi.org/10.1097/HC9.0000000000000697
  6. Am J Reprod Immunol. 2025 May;93(5): e70091
    Identification and Validation of Potential Immune-Related Genes for Endometriosis.
    Yi Zhang, Lulu Wu, Wanjing Yuan, Zhen Ren, Li Tang, Jilin Kuang, Lin Li, Yingying Liang.
       OBJECTIVE: This study aimed to identify and validate potential immune-related genes in endometriosis (Ems) through comprehensive bioinformatics analysis and immunohistochemistry (IHC) verification.
    DESIGN: Using data from the GEO database, single-cell RNA sequencing (scRNA) data and traditional bulk RNA sequencing data were analyzed to identify differentially expressed genes related to the immune system. Immunological analysis confirmed alterations in immune cells associated with Ems. Machine learning techniques were employed to identify characteristic immune genes of eutopic and ectopic endometria, which were then validated through IHC experiments.
    MAIN OUTCOME MEASURES: Immunological analysis revealed distinct variations in the enrichment of macrophages and NK cells in Ems. Functional enrichment analysis revealed a decrease in NK cell toxicity in both ectopic and eutopic endometria, activation of M2 macrophages in the ectopic endometrium supporting the survival of ectopic endothelial cells, and the presence of lipid antigens and signaling between immune cells facilitating the development of Ems. Machine learning algorithms revealed that TGFBR1 is a characteristic immune gene associated with the eutopic endometrium and that GIMAP4 is associated with the ectopic endometrium; this conclusion was also confirmed by IHC.
    RESULTS: Macrophage and NK cell enrichment was significantly increased in endometria from patients with Ems. TGFBR1 is a characteristic immune gene associated with the eutopic endometrium, whereas GIMAP4 is associated with the ectopic endometrium.
    CONCLUSION: These findings provide new insights for the clinical diagnosis and selection of immune-related targets for Ems.
    Keywords:  GIMAP4; TGFBR1; endometriosis; immune characteristic genes
    DOI:  https://doi.org/10.1111/aji.70091
  7. Brain Res. 2025 May 09. pii: S0006-8993(25)00247-1. [Epub ahead of print]1860 149688
    Landscape of spatial disruption of homeostasis in the middle temporal gyrus of epileptic patients.
    Lijian Han, Jianping Liu, Yuanying Song, Sufang Wang, Zevar Zeng, Haicun Shi.
      Epilepsy, a prevalent neurological disorder, significantly impacts cognitive function and quality of life, yet its underlying mechanisms remain incompletely understood. This study investigates the middle temporal gyrus (MTG) in epileptic patients using single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) to elucidate cellular and spatial disruptions associated with epilepsy. We identified distinct cellular clusters and layer-specific gene expression patterns that were significantly altered in epileptic patients compared to controls. Notably, L5_6-related neurons increased, and L2_4-related neurons decreased in epilepsy, highlighting a reorganization of neuronal networks. Spatial mapping revealed significant alterations in the spatial domains of key marker genes, including NPY and GFAP, particularly in L5_6 layers. Using the spatial transition tensor (STT) algorithm, we characterized the spatial dynamics and multistability of neuronal populations, identifying regions of spatial stability and instability. NPY and GFAP emerged as critical genes linked to spatial homeostasis disruption. Additionally, specific L5_6 cell subtypes, such as those expressing TMSB10 and RPS23, exhibited significant spatial homeostasis disruption in epilepsy. These findings underscore the importance of integrating single-cell and spatial transcriptomic data to map cellular and spatial changes at high resolution, providing a comprehensive understanding of the interactions between cell types and their microenvironments. This study enhances our understanding of the molecular and cellular underpinnings of epilepsy and identifies potential therapeutic targets for restoring spatial stability and neuronal function in the epileptic brain.
    Keywords:  Epilepsy; Middle temporal gyrus; Neuronal network reorganization; Single-cell RNA sequencing; Spatial homeostasis; Spatial transcriptomics
    DOI:  https://doi.org/10.1016/j.brainres.2025.149688
  8. Int J Mol Sci. 2025 May 07. pii: 4462. [Epub ahead of print]26(9):
    Single-Cell Transcriptomics Reveals Stem Cell-Derived Exosomes Attenuate Inflammatory Gene Expression in Pulmonary Oxygen Toxicity.
    Jing Shi, Yabin Li, Houyu Zhao, Chenyang Yan, Ruxia Cui, Yukun Wen, Xuhua Yu, Wei Ding, Yunpeng Zhao, Yiqun Fang.
      In recent years, the role played by exosomes in lung diseases has been investigated. Exosomes have been shown to contribute to reductions in lung inflammation and pulmonary fibrosis. However, the role played by exosomes in pulmonary oxygen toxicity and the mechanism involved have not yet been reported. In the present work, we aimed to investigate the mechanism by which stem cell exosomes protect lung tissue and the potential molecular regulatory network involved. In this study, we employed single-cell RNA sequencing techniques to elucidate the unique cellular and molecular mechanisms underlying the progression of exosome therapy for pulmonary oxygen toxicity. We found changes in cell populations after exosome treatment, characterized by the expression of different molecular markers. We also integrated single-cell RNA sequencing (scRNA-seq) and bulk analysis to identify the protective effects of mesenchymal stem cell exosomes (MSC-Exos) in a mouse pulmonary oxygen toxicity (POT) model. scRNA-seq revealed dynamic shifts in the lung cellular composition after exosome treatment, including a reduction in inflammatory lymphoid cells (NK, B cells, CD8+ T, CD4+ T) and restored alveolar epithelial populations (AT1/AT2). A comprehensive gene expression analysis showed that inflammatory pathways associated with oxidative stress were significantly upregulated. In addition, our analysis of the intercellular interaction network revealed that there was a significant reduction in intercellular signal transduction in the POT group compared to the exosome-treated group. These results not only shed light on the unique cellular heterogeneity and potential pathogenesis following exosome therapy, but they also deepen our understanding of molecular pathophysiology and provide new avenues for targeted therapeutic strategies.
    Keywords:  cell-derived exosomes; inflammatory; mesenchymal stem cell exosomes; pulmonary oxygen; single-cell transcriptomics
    DOI:  https://doi.org/10.3390/ijms26094462
  9. Int Arch Allergy Immunol. 2025 May 09. 1-22
    Potential key genes for giant cell arteritis revealed based on single-cell sequencing and Mendelian randomization analysis.
    Tao Cheng, Jiafan Chen, Xinjue Shan, Bochao Jia, Sulin Sang, Yunkai Wang, Yi Wei, Yuanhui Hu.
       INTRODUCTION: Giant cell arteritis (GCA) is an autoimmune disease affecting medium and large arteries. It varies in presentation and often recurs, potentially leading to blindness and aneurysms. The pathogenesis of GCA is not well understood. This study aims to identify key genes linked to GCA and explore potential pathogenic mechanisms.
    METHODS: This study integrated single-cell RNA sequencing, expression quantitative trait loci, and genome-wide association study data, employing a two-sample Mendelian randomization (MR) method to explore the causal effects of marker genes in CD4+ T cells on the development of GCA. Additionally, colocalization analysis was conducted to determine whether there was a shared causal variant.
    RESULTS: Through single-cell RNA sequencing and MR analysis, we identified three key genes, RCAN3, RPS6, and HLA-DQB1, that had a causal relationship with a reduced risk of GCA. Specifically, RCAN3 (OR = 0.49, 95% CI = 0.26-0.93, p = 0.03), RPS6 (OR = 0.21, 95% CI = 0.06-0.73, p = 0.01), and HLA-DQB1 (OR = 0.76, 95% CI = 0.62-0.93, p = 0.01) were inversely associated with the disease. Multiple sensitivity analysis methods showed no heterogeneity and pleiotropy, and ruled out potential reverse causality, demonstrating the robustness of MR analysis results. Colocalization analysis revealed that HLA-DQB1 and GCA were related to SNPs within the same genomic region but involved different causal variants.
    CONCLUSIONS: This study identified three potential key genes (RCAN3, RPS6, HLA-DQB1) linked to the causality of GCA, providing new perspectives on the pathogenesis of GCA and new avenues for therapeutic strategies.
    DOI:  https://doi.org/10.1159/000546323
  10. J Cell Mol Med. 2025 May;29(9): e70556
    Integration of Single-Cell RNA Sequencing Data and Bulk Sequencing Data to Characterise the CD8+ T-Cell Exhaustion Mediated Immune Microenvironment in CRC.
    Xiao-Hua Ling, Gang Chen, Nan-Nan Liu, Wen-Xin Xu, Ming-Feng Ding.
      CD8+ T cells are crucial for the anti-tumour immune response, and their exhaustion contributes to poor prognosis and limited immunotherapy efficacy in colorectal cancer (CRC). In this study, we examined the immune microenvironment of CRC by integrating single-cell RNA sequencing (scRNA-seq) and bulk sequencing data. T-cell subtypes in tumour tissues were analysed using CellMarker 2.0 and scType, and an intercellular communication network was constructed through CellChat. Our analysis revealed that exhausted CD8+ T cells exhibit strong interactions with epithelial cells, primarily via the MIF-(CD74 + CXCR4), MIF-(CD74 + CD44) and CD99-CD99 pathways. Based on CD8+ T-cell exhaustion markers, we developed a prognostic model using XGBoost, which demonstrated promising predictive capabilities for CRC prognosis and immunotherapy response. Functional assays showed that MIF knock-down significantly inhibited CRC cell proliferation and invasion. Our findings suggest that MIF and CD99 are key regulators of CD8+ T-cell exhaustion in CRC. This study provides novel insights into the mechanisms underlying T-cell exhaustion in CRC and offers potential biomarkers for improving immunotherapy outcomes.
    Keywords:  CD8+ T cells; colorectal cancer; prognostic model; scRNA‐seq
    DOI:  https://doi.org/10.1111/jcmm.70556
  11. Hepatol Commun. 2025 May 01. pii: e0710. [Epub ahead of print]9(5):
    Single-cell transcription reveals hepatocyte-to-cholangiocyte reprogramming and biliary gene profile in biliary atresia.
    Lingdu Meng, Min Du, Haodong Li, Fanyang Kong, Jiajian Yang, Rui Dong, Shan Zheng, Gong Chen, Zhen Shen, Junfeng Wang.
       BACKGROUND: Ductular reaction (DR), characterized by the expansion of biliary epithelial cells in the portal area, is a typical hepatic pathology for biliary atresia (BA). The cellular source and function of DR remain poorly understood. Herein, we performed single-cell RNA sequencing (scRNA-seq) in BA to resolve the complexity of DR in BA.
    METHODS: A total of 4 BA and 3 normal control livers underwent scRNA-seq. The epithelial cells were extracted from all cells for further analysis. The cell types, functions, and differentiational trajectory of epithelial cells were determined. The biliary markers and transcription factors (TFs) were identified by combing public bulk and scRNA-seq data and validated by immunohistochemistry.
    RESULTS: ScRNA-seq identified the existence of biliary reprogramming in BA, and the reprogrammed cells expressed both hepatocyte and cholangiocyte markers. When compared with hepatocytes, genes of epithelial-mesenchymal transition, fibrosis, inflammation, and RNA metabolism were enriched in cholangiocytes and upregulated in BA. Pseudotime analysis depicted a differentiation trajectory from hepatocytes across reprogrammed cells to cholangiocytes in BA. Matrix metalloproteinase 7 (MMP7), VTCN1, and LAMC2 were identified as the biliary markers, and KLF5 and HNF1B were determined as the biliary TFs in BA. All the biliary markers and TFs were upregulated in BA when compared with controls.
    CONCLUSIONS: Dissecting the cellular source and function of cholangiocytes is essential to understand the pathological role of DR in BA. The identified specific biliary markers and TFs provide important insights into its potential diagnosis and mechanism exploration for BA in the future.
    Keywords:  biliary atresia; biliary reprogramming; ductular reaction; single-cell RNA sequencing
    DOI:  https://doi.org/10.1097/HC9.0000000000000710
  12. Discov Oncol. 2025 May 15. 16(1): 774
    Deciphering the role of acetylation-related gene NAT10 in colon cancer progression and immune evasion: implications for overcoming drug resistance.
    Xuancheng Zhou, Xun Sang, Lai Jiang, Shengke Zhang, Chenglu Jiang, Yuheng Gu, Yipin Fu, Guanhu Yang, Jieyin Zhang, Hao Chi, Binbin Wang, Xiaolin Zhong.
       BACKGROUND: Colon cancer (CC) is one of the most common and lethal cancers worldwide, with rising incidence rates in both developed and developing countries. Although advances in treatments such as surgery, chemotherapy, and targeted therapies have been made, prognosis for advanced colon cancer, particularly with metastasis, remains poor. Recent studies highlight the significant role of post-transcriptional modifications like acetylation in cancer biology, affecting processes like gene transcription, metabolism, and tumor progression.
    METHODS: This study applied multi-omics analyses, including single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and Mendelian randomization. Data were obtained from public datasets like GSE132465, UCSC Xena, and GeneCards. We focused on acetylation-related genes, specifically NAT10 and GNE, using scoring methods, cell-cell interaction models, and survival analyses to investigate their role in colon cancer development, metastasis, and immune evasion.
    RESULTS: This study identifies that NAT10 is highly expressed in epithelial cells of colorectal cancer (CC) and is closely associated with tumor progression and metastasis. Single-cell RNA sequencing analysis revealed that NAT10-positive epithelial cells exhibited strong interactions with myeloid cells and T cells, with significant differences in cell-cell communication (p < 0.05). Based-on-summary-data Mendelian randomization (SMR) analysis further supports a causal relationship between NAT10 and colorectal cancer. In the MR analysis, a significant positive correlation was observed between NAT10 and colorectal cancer risk using summary data from genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies (β_SMR = 0.004, p_SMR = 0.041, p_HEIDI = 0.737). These findings suggest that NAT10 may serve as a pathogenic factor in colorectal cancer development, providing additional genetic evidence that links this acetylation-related gene to colorectal cancer. Survival analysis further demonstrated that NAT10-positive epithelial cells are associated with poorer prognosis. In the TCGA dataset, patients with NAT10-positive epithelial cells exhibited a significantly shorter disease-free survival (DFS) (p = 0.012). Unlike GNE-positive cells, NAT10-positive epithelial cells exhibited immune escape characteristics, and TIDE analysis indicated that NAT10-positive epithelial cells were associated with a lower response to immune checkpoint blockade therapy (p = 1.3e-5), suggesting that they may impair the efficacy of immunotherapy by promoting immune evasion. In contrast, GNE was also significantly expressed in epithelial cells of colorectal cancer, but its role differs from that of NAT10. GNE-positive epithelial cells demonstrated strong communication with immune cells, particularly in interactions between myeloid cells and T cells through receptor-ligand pairs. Despite the important role of GNE-positive epithelial cells in the tumor microenvironment, their association with immune escape is weaker compared to NAT10. Survival analysis revealed that GNE-positive epithelial cells were associated with a better prognosis (p = 0.015). In the TCGA dataset, patients with GNE-positive epithelial cells displayed longer disease-free survival (DFS), contrary to the results from the SMR analysis.
    CONCLUSIONS: Leveraging SMR and multi-omics analysis, this study highlights the significant role of acetylation-related genes, particularly NAT10, in colon cancer. The findings suggest that acetylation modifications in epithelial cells contribute to immune evasion and cancer progression. NAT10 could serve as a promising biomarker and therapeutic target for early diagnosis and targeted therapy, offering new avenues for improving colon cancer treatment and patient outcomes.
    Keywords:  Acetylation; Colon cancer; GNE; Immune evasion; Multi-omics analysis; NAT10; Prognosis; Single-cell RNA sequencing; Spatial transcriptomics; Tumor microenvironment
    DOI:  https://doi.org/10.1007/s12672-025-02617-w
  13. Am J Physiol Cell Physiol. 2025 May 12.
    Stromal heterogeneity in the adult lung delineated by single-cell genomics.
    Tatsuya Tsukui, Dean Sheppard.
      Stromal cells in the lung provide structural support to other cells and play critical roles in inflammation, repair, and fibrosis after injury. Recent technological advancements in single-cell genomics have tremendously improved our knowledge of stromal heterogeneity in the lung. Stromal heterogeneity in single-cell RNA sequencing data is often conserved across different studies despite the different annotation strategies. Spatial analyses suggest that each stromal subset is characterized by unique anatomical locations in the adult lung. This review overviews the stromal heterogeneity delineated by single-cell RNA sequencing studies and highlights the functional characteristics and locations of each population.
    Keywords:  fibroblast; fibrosis; injury; lung; stromal cell
    DOI:  https://doi.org/10.1152/ajpcell.00285.2025
  14. Sci Adv. 2025 May 16. 11(20): eadv1159
    Aboral cell types of Clytia and coral larvae have shared features and link taurine to the regulation of settlement.
    Julia Ramon-Mateu, Anna Ferraioli, Núria Teixidó, Isabelle Domart-Coulon, Evelyn Houliston, Richard R Copley.
      Larval settlement is of interest both for ecologists and for evolutionary biologists, who have proposed that anterior sensory systems for substrate selection provided the basis for animal brains. Nevertheless, the cellular and molecular regulation of settlement, including in Cnidaria (corals, jellyfish, sea anemones, and hydroids), is not well understood. We generated and compared anterior (aboral) transcriptomes and single-cell RNA sequencing datasets from the planula larvae of three cnidarian species: the jellyfish Clytia hemisphaerica and the corals Astroides calycularis and Pocillopora acuta. Integrating these datasets and characterizing aboral cell types, we defined common cellular features of the planula aboral end and identified clade-specific specializations in cell types. Among shared features were genes implicated in taurine uptake and catabolism expressed in distinct specialized aboral cell types. In functional assays using both Clytia and Astroides planulae, exogenous taurine inhibited settlement. These findings define the molecular and cellular architecture of the planula aboral pole and implicate localized taurine destruction in regulating settlement.
    DOI:  https://doi.org/10.1126/sciadv.adv1159
  15. Elife. 2025 May 15. pii: RP97958. [Epub ahead of print]13
    scRNA-seq and scATAC-seq reveal that Sertoli cell mediates spermatogenesis disorders through stage-specific communications in non-obstructive azoospermia.
    Shimin Wang, Hongxian Wang, Bicheng Jin, Hongli Yan, Qingliang Zheng, Dong Zhao.
      Non-obstructive azoospermia (NOA) belongs to male infertility due to spermatogenesis failure. However, evidence for cell type-specific abnormalities of spermatogenesis disorders in NOA remains lacking. We performed single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) on testicular tissues from patients with obstructive azoospermia (OA) and NOA. HE staining confirmed the structural abnormalities of the seminiferous tubules in NOA patients. We identified 12 germ cell subtypes (spermatogonial stem cell-0 [SSC0], SSC1, SSC2, diffing-spermatogonia [Diffing-SPG], diffed-spermatogonia [Diffed-SPG], pre-leptotene [Pre-Lep], leptotene-zygotene [L-Z], pachytene [Pa], diplotene [Di], spermatids-1 [SPT1], SPT2, and SPT3) and 8 Sertoli cell subtypes (SC1-SC8). Among them, three novel Sertoli cell subtype phenotypes were identified, namely SC4/immature, SC7/mature, and SC8/further mature Sertoli cells. For each germ or Sertoli cell subtype, we identified unique new markers, among which immunofluorescence confirmed co-localization of ST3GAL4, A2M, ASB9, and TEX19 and DDX4 (classical marker of germ cell). PRAP1, BST2, and CCDC62 were co-expressed with SOX9 (classical marker of Sertoli cell) in testes tissues also confirmed by immunofluorescence. The interaction between germ cell subtypes and Sertoli cell subtypes exhibits stage-specific-matching pattern, as evidenced by SC1/2/5/7 involving in SSC0-2 development, SC3 participating in the whole process of spermiogenesis, SC4/6 participating in Diffing and Diffed-SPG development, and SC8 involving in the final stage of SPT3. This pattern of specific interactions between subtypes of germ cell and Sertoli cell was confirmed by immunofluorescence of novel markers in testes tissues. The interaction was mainly regulated by the Notch1/2/3 signaling. Our study profiled the single-cell transcriptome of human spermatogenesis and provided many potential molecular markers for developing testicular puncture-specific marker kits for NOA patients.
    Keywords:  Sertoli cell; cell biology; germ cell; human; non-obstructive azoospermia; single cell ATAC-sequencing; single-cell RNA-sequencing
    DOI:  https://doi.org/10.7554/eLife.97958
  16. Int J Mol Sci. 2025 Apr 24. pii: 4036. [Epub ahead of print]26(9):
    Identification and Exploration of Pyroptosis-Related Genes in Macrophage Cells Reveal Necrotizing Enterocolitis Heterogeneity Through Single-Cell and Bulk-Sequencing.
    Peipei Zhang, Ying Li, Panpan Xu, Peicen Zou, Sihan Sheng, Ruiqi Xiao, Pu Xu, Ying Chen, Yue Du, Lishuang Ma, Yajuan Wang.
      Necrotizing enterocolitis (NEC) is an acute intestine dysfunction intestinal disorder characterized by inflammation and cell death, including pyroptosis. Previous studies have implicated pyroptosis, particularly via NLRP3 inflammatory activation, and contribute to the development of NEC. However, the genetic and molecular mechanisms underlying pyroptosis in NEC pathogenesis and sequelae remain unclear. Our study aimed to identify the pyroptosis-related cell populations and genes and explore potential therapeutic targets. Single-cell RNA sequencing (scRNA-seq) data were analyzed to identify the cell populations related to NEC and pyroptosis. Weighted gene correlation network analysis (WGCNA) of bulk RNA-seq was performed to identify gene modules associate with pyroptosis. Cell-cell communication was employed to investigate intercellular signaling networks. Gene Set Enrichment Analysis (GSEA) was conducted to compare the pathways enriched in the high and low TREM1-expressing subgroups. Immunofluorescence staining was performed to detect the TREM1+CD163+ macrophages in the intestines. PCR and Western blot were performed to detect the expression of mRNA and proteins in the intestine tissues and cells. scRNA-seq analysis revealed increased macrophage abundance in NEC, with one macrophage cluster (cluster 4) exhibiting a markedly elevated pyroptosis score. WGCNA identified a gene module (MEbrown) that positively correlated with pyroptosis. Five genes (TREM1, TLN1, NOTCH2, MPZL1, and ADA) within this module were identified as potential diagnostic markers of pyroptosis. Furthermore, we identified a novel macrophage subpopulation, TREM1+CD163+, in NEC. Cell-cell communication analysis suggested that TREM1+CD163+ macrophages interact with other cells primarily through the NAMPT/ITGA5/ITGB1 and CCL3/CCR1 pathways. GSEA revealed a significant association between high TREM1 expression and pathways related to pyroptosis, cell proliferation, and inflammation. In vivo and in vitro experiments confirmed an increase in TREM1+CD163+ macrophages in NEC-affected intestines. TREM1 inhibition in THP-1 cells significantly reduced the expression of pro-inflammatory cytokines and pyroptosis-related genes and proteins. We identified the TREM1+CD163+ macrophage population that plays a crucial role in pyroptosis during NEC progression. Our findings elucidate the biological functions and molecular mechanisms of TREM1, demonstrating its upregulation in vivo and pro-pyroptosis effects in vitro. These insights advance our understanding of the role of pyroptosis in NEC pathogenesis and suggest TREM1 is a potential therapeutic target for NEC.
    Keywords:  TREM1; bioinformatics; macrophage; necrotizing enterocolitis; pyroptosis
    DOI:  https://doi.org/10.3390/ijms26094036
  17. Front Immunol. 2025 ;16 1577109
    Single-cell transcriptome reveals potential mechanisms for gout in children.
    Shengyou Yu, Ren Qi, Liang Xiao, YiHui Huang, Li Yu.
       Objective: Pediatric gout is a condition that differs from traditional adult gout and has attracted significant attention. This study aims to explore the molecular mechanisms underlying pediatric gout.
    Methods: We analyzed peripheral blood samples from pediatric gout patients and healthy controls using single-cell RNA sequencing (scRNA-seq). Statistical tests were employed to analyze the data and identify significant differences between the groups.
    Results: Our findings revealed that CD14+ monocytes and DN T cells play crucial roles in pediatric gout. CD14+ monocytes are essential for recognizing and phagocytosing monosodium urate (MSU) crystals, triggering inflammation. DN T cells may be involved in the adaptive immune response within gouty joints. These cells not only contribute to the inflammatory response but also interact with other immune cells, amplifying the inflammatory cascade. Comparative analysis with adult gout studies highlighted both similarities and differences in cellular and molecular mechanisms between children and adults. The CD14+ monocytes may be interact with other immune cells through the TNF-α/NF-κB signaling pathway. Targeting this pathway may offer therapeutic potential for managing pediatric gout.
    Conclusion: The results provide a foundation for new diagnostic markers and therapeutic targets for pediatric gout. They also pave the way for future research and the development of targeted therapies that can effectively manage and potentially prevent the debilitating effects of gout in children. Understanding the unique molecular mechanisms in pediatric gout could influence treatment strategies and improve patient outcomes.
    Keywords:  CD14+ monocytes; DN T cells; inflammatory mechanisms children; pediatric gout; single-cell RNA sequencing
    DOI:  https://doi.org/10.3389/fimmu.2025.1577109
  18. Rheumatology (Oxford). 2025 May 15. pii: keaf252. [Epub ahead of print]
    Single-cell transcriptome analysis profiles cellular and molecular alterations in aortic tissue from patients with Behçet's syndrome.
    Cong Wang, Taotao Li, Junmin Zhu, Bokang Qiao, Zhiyu Qiao, Haiou Hu, Nan Zhang, Hai Yu, Honglei Zhao, Yongliang Zhong, Lili Pan, Na Gao.
       OBJECTIVES: This study aims to analyze the expression profiles, phenotypes, functions, and cell-cell communication of various cell subpopulations in the affected aortic tissues of patients with Behçet's syndrome (BS) at the transcriptomic level.
    METHODS: This study recruited six participants (three with Behçet's syndrome and three with atherosclerosis) from Beijing Anzhen Hospital between January 2023 and June 2024, collected their clinical information, and performed single-cell RNA sequencing on aortic tissue specimens using the SeekOne® MM High Flux Single Cell Transcriptome Kit V4.1. The data were analyzed with Seurat and Harmony in R, including quality control, cell clustering, differential gene expression analysis, GO and KEGG enrichment analyses, subgroup analyses focusing on specific cell types, and intercellular communication analysis using CellChat v1.6.1.
    RESULTS: The study identified eight major cell types in aortic tissues, with significant differences in cell proportions between BS patients and controls. Compared with controls, BS patients had increased endothelial cells, fibroblasts, and mesenchymal stem cells, while smooth muscle cells decreased. Subgroup analysis revealed significant differences between the BS and control groups in cell subpopulation distribution, enriched pathways, and cell interactions.
    CONCLUSION: Our study reveals cellular and molecular changes in the aortic tissues of patients with BS, laying the foundation for elucidating the pathogenesis of BS and identifying potential therapeutic targets.
    Keywords:  Behçet’s syndrome; aorta; cellular heterogeneity; single-cell RNA sequencing
    DOI:  https://doi.org/10.1093/rheumatology/keaf252
  19. Cardiol Res. 2025 Jun;16(3): 238-249
    Dissecting Autophagy Gene Expression in Endothelial Cells of Pulmonary Arterial Hypertension at Single-Cell Resolution.
    Chang Zhi Zhang, Qian Yu, Wei Jia Liu, Jing Han.
       Background: Endothelial cell (EC) dysfunction is one of the pathogeneses of pulmonary arterial hypertension (PAH); autophagy is an important conserved mechanism for maintaining cellular homeostasis. However, to date, transcriptional signatures of autophagy-related genes during PAH are not well characterized.
    Methods: We analyzed the single-cell RNA sequencing (scRNA-seq) data and revealed the relationship between autophagy and PAH in EC from the perspective of differential expression, transcriptional signature typing, comparative analysis, pseudo-temporal changes of autophagy genes, and high dimensional weighted gene co-expression network analysis (hdWGCNA) networks of autophagy genes. Moreover, we established an in vitro PAH model and verified the expression signatures of candidate autophagy-related genes by western blotting. Student's t-test was used to detect data differences.
    Results: Single-cell data showed that ECs had three different subgroups, namely Endo-Nor (normal state), Endo-Mid (transition state), and Endo-PAH (PAH disease group). Functional enrichment analysis of differentially expressed genes between Endo-PAH and Endo-Nor showed that autophagy and phosphatidylinositol 3-kinase (PI3K)-AKT signaling pathways were abnormal. Pseudo-temporal trajectory analysis showed that eight autophagy-related genes were involved in regulating PAH progression. Furthermore, the hdWGCNA network revealed six autophagy-related PAH progression genes. By comprehensively comparing different analysis methods, we identified Ddit4 as an autophagy-related PAH biomarker. Western blot observed that DDIT4 protein was significantly upregulated (P < 0.01) in the PAH model.
    Conclusion: This study dissected the expression signature of autophagy genes in PAH at single-cell resolution and identified DDIT4 as a potential biomarker.
    Keywords:  Autophagy; Ddit4; Endothelial cell; PAH; hdWGCNA
    DOI:  https://doi.org/10.14740/cr2055
  20. Neurooncol Adv. 2025 Jan-Dec;7(1):7(1): vdaf058
    What single-cell RNA sequencing taught us about MGMT expression in glioblastoma.
    Iyad Alnahhas, Mehak Majid Khan, Wenyin Shi.
       Background: The promoter methylation status of O-6-methylguanine-DNA methyltransferase (MGMTp) is an important prognostic marker in GBM. Previous studies showed that the expression of MGMT based on immunohistochemistry did not correlate with survival. This is partly because nontumor cells express MGMT. Single-cell sequencing assesses gene expression in tumor cells specifically.
    Methods: We used publicly available data from 3 recent single-cell/nucleus sequencing GBM studies that included MGMTp methylation status data for patients to evaluate MGMT expression at the single-cell level.
    Results: In the CPTAC study, a median of 0.82% and 5.7% of tumor cells expressed MGMT in the MGMTp methylated group and MGMTp unmethylated group, respectively (P-value .001). In the Neftel study, a median of 0.59% and 14.01% of tumor cells expressed MGMT in the MGMTp methylated group and MGMTp unmethylated group, respectively (P-value .01). Three unmethylated samples (out of 16) had MGMT expression <2%. It is unclear if this is due to technical inaccuracies as the Neftel paper did not specify the detection method for MGMTp methylation. Alternatively, the percentage of GBM cells expressing MGMT as a continuous variable may be more relevant than the dichotomous MGMTp status. The Wang study confirmed that MGMT expression can increase or decrease between paired primary and recurrent samples. The gene set enrichment analysis shows that MGMT expressing and negative cells are enriched with mesenchymal and proneural genes, respectively.
    Conclusion: Single-cell data suggest that MGMT expression falls on a continuous spectrum. A smaller percentage of tumor cells express MGMT when MGMTp is methylated.
    Keywords:  MGMT; glioblastoma; single-cell sequencing; spatial transcriptomics
    DOI:  https://doi.org/10.1093/noajnl/vdaf058
  21. Sci Rep. 2025 May 14. 15(1): 16812
    Single-cell RNA sequencing reveals immunological link between house dust mite allergy and childhood asthma.
    Lingyun Zou, Kang Chen, Xianou Hong, Bo Ye.
      Allergic asthma in children is typically associated with house dust mites (HDM) as the key allergen. Nevertheless, the diagnostic rate remains below 60% due to the absence of specific symptoms and diagnostic markers, which hinders the implementation of targeted personalized therapies. This study investigates immunological features of asthma with house dust mite (HDM) sensitisation in children, aiming to uncover diagnostic markers at single-cell resolution. The cohort comprised 8 children with physician-diagnosed asthma (age range: 4-11 years), stratified into groups based on HDM sensitization status. Single-cell RNA sequencing of peripheral blood mononuclear cells (PBMCs) was conducted, employing Seurat for cell identification and differential gene expression analysis. Enrichment analyses and LASSO regression identified signature genes related to cellular origin, with protein-protein interaction networks elucidating cellular communication differences between groups. A total of 11 distinct cell types were identified, with classical monocytes and monocytes being the predominant cell types that differentiated the two groups. Among these, 12 genes were up-regulated, and 40 down-regulated, mainly involving MHC-II complex and antigen presentation pathways, as validated by Gene Ontology and Gene Set Enrichment Analysis. The machine learning model accurately predicted cellular groupings, evidenced by an area under the curve of 0.83. Enhanced communication signals in HDM allergy cases involved monocytes, contrasting with reduced interactions in naive CD8 + cells. HLA-DR and HLA-DP were identified as the primary hallmark receptors, and the innate immunity differences with non-dust mite allergic asthma were characterized by 18 genes including top candidates MT-ND4 and RPS3A. Individuals with HDM-sensitized asthma exhibited altered expression of MHC-II complex genes in their PBMCs and distinct gene expression patterns in antigen-presenting cells, highlighting the critical role of HLA-DR and HLA-DP in the HDM allergen presentation.
    Keywords:  Allergic asthma; Diagnostic genes; House dust mites; Machine learning; Peripheral blood mononuclear cells; Single-cell RNA sequencing
    DOI:  https://doi.org/10.1038/s41598-025-01538-6
  22. Int J Mol Sci. 2025 May 07. pii: 4439. [Epub ahead of print]26(9):
    Transcriptomic Plasticity of Human Alveolar Macrophages Revealed by Single-Cell RNA Sequencing Following Drug Exposure: Implications for Therapeutic Development.
    Penny L Groves, Levi Hockey, Brendan J O'Sullivan, Lai-Ying Zhang, Zherui Xiong, Quan H Nguyen, Maxine E Tan, Viviana P Lutzky, Rohan A Davis, Daniel C Chambers, Simon H Apte.
      Alveolar macrophages (AM) must perform three seemingly opposing roles including homeostasis, driving inflammation, and facilitating tissue repair. Whilst there is now consensus (supported by a large body of human single cell RNA sequencing (scRNA-seq) data) that the cell subsets that perform these tasks can readily be found based on their transcriptome, their ontogeny has remained unclear. Moreover, there is agreement that in all types of pulmonary fibrosis (PF) there is an expanded population of profibrotic AM that may aberrantly drive PF. From a therapeutic viewpoint, there is great appeal in the notion that the transcriptional program in different AM subsets is not fixed but remains plastic and amenable to pharmacological reprogramming. Accordingly, this study addresses this question by performing scRNA-seq on human AM following treatment with drugs or perturbagens including pioglitazone, trametinib, nintedanib, lipopolysaccharide and the natural compound endiandrin A. Each treatment induced a unique global transcriptional change, driving the cells towards distinct subsets, further supported by trajectory analysis, confirming a high level of plasticity. Confirmatory experiments using qPCR demonstrated that single exposure to a compound induced a relatively stable transcriptome, whereas serial exposure to a different compound allowed the cells to be reprogrammed yet again to a different phenotype. These findings add new insight into the biology of AM and support the development of novel therapies to treat PF.
    Keywords:  LPS; drug discovery; endiandrin A; lung airway macrophages; natural products; nintedanib; phytochemistry; pioglitazone; profibrotic macrophages; pulmonary fibrosis; trametinib; transcriptional plasticity
    DOI:  https://doi.org/10.3390/ijms26094439
  23. Discov Oncol. 2025 May 16. 16(1): 777
    Integrating multi-omics data to identify the role of Aggrephagy-related genes in tumor microenvironment and key tumorigenesis factors of GB from the perspective of single-cell sequencing.
    Zipei Chen, Shengke Zhang, Chenglu Jiang, Lai Jiang, Haiqing Chen, Jinbang Huang, Jie Liu, Guanhu Yang, Xiufang Luo, Hao Chi, Jiangping Fu.
      This study presents a pioneering exploration into the role of aggrephagy-related genes (ARGs) in glioblastoma (GB), a kind of malignant tumor which is highly invasive and resistant to a series of therapy. Utilizing single-cell sequencing to dissect their influence on the tumor microenvironment (TME) and tumorigenesis. By applying non-negative matrix factorization for dimensionality reduction and clustering of single-cell data, distinct cellular subtypes within the TME influenced by ARGs were identified, uncovering their functions and interactions. The investigation extends to validating the prognostic significance of ARGs and their potential in predicting immunotherapy outcomes. Molecular docking analysis of key ARGs further highlights TUBA1C and UBB as promising therapeutic targets, offering novel insights into GB's complex biology and suggesting a targeted approach for therapy, which is characterized by some crucial pathways in our analysis, including PI3k-akt and TGF-beta pathways. This comprehensive single-cell level examination not only advances our understanding of aggrephagy's role in GB but also proposes new avenues for prognosis and treatment strategies, emphasizing the critical impact of ARGs on the TME and GB progression.
    Keywords:  Aggrephagy; Aggrephagy-related genes; Drug target; GB; Molecular docking; scRNA-seq
    DOI:  https://doi.org/10.1007/s12672-025-02431-4
  24. Cancer Sci. 2025 May 12.
    Upregulation of YY1/EZH2 and MLH1 as Therapeutic Targets for Adult T-Cell Leukemia/Lymphoma.
    Takuya Shimizu, Takero Shindo, Hanako Ogawa, Kaori Teranaka, Akira Watanabe, Akifumi Takaori-Kondo.
      The clinical and genetic presentation of adult T-cell leukemia/lymphoma (ATLL) ranges from indolent to aggressive, making it difficult to identify common therapeutic targets. Inhibiting EZH1/2 suppresses ATLL through epigenetic modulation; however, the diverse genetic background of ATLL precludes its mode of action from being clearly elucidated. We conducted single-cell RNA sequencing (scRNA-seq) of primary ATLL cells and identified an epigenetic regulative axis. First, flow cytometry showed that the proliferative potential of CADM1+ HTLV-1-infected cells ranges from stable to treatment-required. Second, scRNA-seq identified a CCR4+CD48- cluster, the population of which increased in treatment-required patients. In silico promoter analysis of this cluster identified a transcription factor YY1 as a candidate regulator. Intracellular flow cytometry confirmed that YY1 and EZH2 were upregulated in acute-type. By contrast, MLH1 but not MSH2 within CADM1+ cells was downregulated in remitted ATLL (p < 0.05), suggesting that MLH1 is associated with YY1/EZH2. Notably, lentiviral YY1 knockdown and the EZH1/2 inhibitor valemetostat downregulated MLH1 in ATLL cell lines and primary ATLL cells. Finally, knockdown of YY1 or MLH1 suppressed the proliferation of ATLL cells. Our findings suggest that YY1/EZH2 overexpression in the ATLL subpopulation defines aggressiveness and that MLH1 downregulation through YY1/EZH2 inhibition may be an effective treatment for aggressive ATLL.
    Keywords:  EZH2; MLH1; YY1; adult T‐cell leukemia/lymphoma (ATLL); single‐cell RNA sequencing
    DOI:  https://doi.org/10.1111/cas.70095
  25. Discov Oncol. 2025 May 13. 16(1): 744
    Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer.
    Zhenwei Wang, Zhihong Dai, Yuren Gao, Zhongxiang Zhao, Zhen Li, Liang Wang, Xiang Gao, Qiuqiu Qiu, Xiaofu Qiu, Zhiyu Liu.
      Prostate cancer (PCa) remains a leading cause of cancer-related mortality, necessitating robust prognostic models and personalized therapeutic strategies. This study integrated bulk RNA sequencing, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics to construct a prognostic model based on genes shared between ferroptosis and fatty acid metabolism (FAM). Using the TCGA-PRAD dataset, we identified 73 differentially expressed genes (DEGs) at the intersection of ferroptosis and FAM, of which 19 were significantly associated with progression-free survival (PFS). A machine learning-based prognostic model, optimized using the Lasso + Random Survival Forest (RSF) algorithm, achieved a high C-index of 0.876 and demonstrated strong predictive accuracy (1-, 2-, and 3-year AUCs: 0.77, 0.75, and 0.78, respectively). The model, validated in the DFKZ cohort, stratified patients into high- and low-risk groups, with the high-risk group exhibiting worse PFS and higher tumor mutation burden (TMB). Functional enrichment analysis revealed distinct pathway activities, with high-risk patients showing enrichment in immune-related and proliferative pathways, while low-risk patients were enriched in metabolic pathways. Immune microenvironment analysis revealed heightened immune activity in high-risk patients, characterized by increased infiltration of CD8 + T cells, regulatory T cells, and M2 macrophages, alongside elevated TIDE scores, suggesting immune evasion and resistance to immunotherapy. In contrast, low-risk patients exhibited higher infiltration of plasma cells and neutrophils and demonstrated better responses to immune checkpoint inhibitors (ICIs). Spatial transcriptomics and scRNA-seq further elucidated the spatial distribution of model genes, highlighting the central role of macrophages in mediating risk stratification. Additionally, chemotherapy sensitivity analysis identified potential therapeutic agents, such as Erlotinib and Picolinic acid, for low-risk patients. In vitro experiments showed that overexpression of CD38 in the PC-3 cell line led to elevated lipid peroxidation (C11-BODIPY) and reactive oxygen species (ROS), suggesting increased cell ferroptosis. These findings provide a comprehensive framework for risk stratification and personalized treatment in PCa, bridging molecular mechanisms with clinical outcomes.
    Keywords:  Fatty acid metabolism; Ferroptosis; Machine learning; Multi-omics; Prostate cancer; Tumor microenvironment
    DOI:  https://doi.org/10.1007/s12672-025-02484-5
  26. Int J Mol Sci. 2025 Apr 23. pii: 3997. [Epub ahead of print]26(9):
    New Insights and Implications of Cell-Cell Interactions in Developmental Biology.
    Guanhao Wu, Yuchao Liang, Qilemuge Xi, Yongchun Zuo.
      The dynamic and meticulously regulated networks established the foundation for embryonic development, where the intercellular interactions and signal transduction assumed a pivotal role. In recent years, high-throughput technologies such as single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have advanced dramatically, empowering the systematic dissection of cell-to-cell regulatory networks. The emergence of comprehensive databases and analytical frameworks has further provided unprecedented insights into embryonic development and cell-cell interactions (CCIs). This paper reviewed the exponential increased CCIs works related to developmental biology from 2008 to 2023, comprehensively collected and categorized 93 analytical tools and 39 databases, and demonstrated its practical utility through illustrative case studies. In parallel, the article critically scrutinized the persistent challenges within this field, such as the intricacies of spatial localization and transmembrane state validation at single-cell resolution, and underscored the interpretative limitations inherent in current analytical frameworks. The development of CCIs' analysis tools with harmonizing multi-omics data and the construction of cross-species dynamically updated CCIs databases will be the main direction of future research. Future investigations into CCIs are poised to expeditiously drive the application and clinical translation within developmental biology, unlocking novel dimensions for exploration and progress.
    Keywords:  cell–cell interactions; embryo; mother-to-fetus binding interface
    DOI:  https://doi.org/10.3390/ijms26093997
  27. Mol Oral Microbiol. 2025 May 14.
    Single-Cell RNA Sequencing Reveals Functional Exhaustion of T Cells in Oral Lichen Planus.
    Xin Chen, Xin-Wen Wu, Ruo-Wen Zhao, Pan Xu, Ping-Yi Zhu, Kai-Lin Tang, Yuan He.
       BACKGROUND: Oral lichen planus (OLP) is a common T-cell-mediated chronic inflammatory disease of the oral mucosa. Different T-cell subsets play distinct roles in the pathogenesis of OLP. This study aims to reveal the composition and heterogeneity of T cells in the immune microenvironment of OLP using single-cell RNA sequencing (scRNA-seq), thus providing new insights into the pathogenesis of OLP.
    MATERIALS AND METHODS: Oral mucosal tissues were collected from three OLP patients and three healthy individuals for scRNA-seq. Data were processed using R software for dimensionality reduction, clustering, annotation, proportion analysis, gene expression visualization, and pseudotime analysis. A chronic inflammation model was established by injecting Prevotella melaninogenica bacteria solution into the buccal mucosa of mice. RT-qPCR was used to detect the expression levels of OLP-related inflammatory factors (Tnf-α, Il-1b, and Il-6) and the exhaustion marker Pd1. HE and immunofluorescence staining were employed to assess histopathological changes in oral mucosal tissues and the quantity of CD8+-exhausted T cells (CD8+Tex).
    RESULTS: ScRNA-seq results showed a significant increase in T cell numbers in the oral mucosal tissues of OLP patients compared to healthy individuals. The average expression levels of effector molecules (GZMB, PRF1, TNFA, IL2, and IFNG) in CD8+ T cells were reduced. The number of CD8+Tex significantly increased, and these cells were in the terminal stage of CD8+ T-cell differentiation, thereby expressing high levels of terminal exhaustion-related genes (PDCD1, LAG3, and TIGIT). Compared to the control group, the P. melaninogenica chronic inflammation group exhibited epithelial thickening and inflammatory cell infiltration in the lamina propria, with significantly upregulated expression of OLP-related inflammatory factors and Pd1. Immunofluorescence staining revealed increased CD8+Tex in the oral mucosa of OLP patients and P. melaninogenica mice model.
    CONCLUSIONS: During the pathogenesis of OLP, the overall ability of T cells to clear antigens is decreased, leading to an inadequate ability to promptly eliminate pathogens and infected cells, which may cause the chronicity of OLP inflammation.
    Keywords:  Inflammation; T cell exhaustion; T cells; lichen planus, oral
    DOI:  https://doi.org/10.1111/omi.12495
  28. Genes Chromosomes Cancer. 2025 May;64(5): e70051
    Single-Cell Profiling of Mononuclear Cells Identifies Transcriptomics Signatures Differentiating Prostate Cancer From Benign Prostatic Hyperplasia.
    Kadriia Enikeeva, Vyacheslav Korobeynikov, Yuliya Sharifyanova, Elina Akramova, Polina Shmelkova, Diana Gainullinа, Liliia Kalimullina, Valentin Pavlov.
      Prostate cancer (PCa) and benign prostatic hyperplasia (BPH) share overlapping etiological factors but differ molecularly. In the study, 4 patients with prostate cancer and 3 patients with BPH were included. All patients with prostate cancer and BPH had a histologically confirmed diagnosis. Among the prostate cancer group were 3 patients with acinar prostate adenocarcinoma and 1 patient with small-acinar prostate adenocarcinoma. Using single-cell RNA sequencing (scRNA-seq) on peripheral blood mononuclear cells (PBMCs) from PCa and BPH patients, we identified 16 immune cell clusters, with elevated CD14+ monocytes, NK cells, and γδ T cells in PCa. Differential gene expression analysis revealed 40 overexpressed genes in PCa monocytes, including CSMD1, ZBTB16, ZNF217, and SERPINI2, linked to tumor progression, cell cycle regulation, EMT, androgen signaling, and metabolism. SCN2A was highly expressed in PCa B cells, while ABO, FMN1, and TXNIP in CD4+ T cells modulated immune evasion, cytoskeletal regulation, and oxidative stress. Pathway analysis showed PCa monocytes had heightened interleukin-27 signaling, whereas BPH monocytes exhibited increased cholesterol storage and Notch signaling. CellChat analysis highlighted monocytes' central role in immune regulation, with distinct interactions via MIF, galectin, and TGF-β pathways in PCa and BPH. These findings reveal unique immune microenvironments and transcriptional heterogeneity between PCa and BPH, offering potential biomarkers for differentiation and insights into prostate pathology mechanisms.
    Keywords:  benigh prostatic hyperplasia; prostate cancer; single‐cell sequencing; transcriptome
    DOI:  https://doi.org/10.1002/gcc.70051
  29. Discov Oncol. 2025 May 13. 16(1): 756
    Arginine methylation modulates tumor fate and prognosis in clear cell renal cell carcinoma.
    Jiahao Wang, Dan Bao, Xiaochao Chen, Zijie Yu, Weiyu Kong, Chen Xu, Songtao Li, Yulin Yue.
       BACKGROUND: Arginine methylation, a key post-translational modification, plays a pivotal role in regulating various cellular processes and has been implicated in cancer progression. However, the potential of arginine methylation-related genes as prognostic markers in clear cell renal cell carcinoma (ccRCC) remains underexplored.
    METHODS: We utilized public transcriptomic datasets from TCGA, E-MTAB-1980 and ICGC, for model construction and validation. Single-cell RNA sequencing datasets were employed to evaluate gene expression patterns at the cellular level. Consensus clustering, KM survival analysis, and GSVA were applied to identify molecular subtypes and related pathways. Univariate and multivariate Cox regression analyses were applied to develop an arginine methylation-related signature (AMS). Immune profiling, mutation landscape, and drug sensitivity prediction were also employed to explore the model's association with clinical features, immune infiltration, mutation burden, and therapeutic responses.
    RESULTS: The AMS demonstrated robust prognostic performance, with consistent validation across external cohorts. High-risk patients exhibited significantly worse survival, elevated TMB, and an immunosuppressive tumor microenvironment characterized by increased infiltration of regulatory immune cells. Single-cell RNA sequencing revealed key prognostic genes expressed predominantly in cancer and immune cells, supporting their role in tumor progression and immune interactions.
    CONCLUSION: The arginine methylation-based prognostic model provides a reliable framework for survival risk stratification in ccRCC and holds promise for guiding personalized therapeutic strategies. Future research should emphasize clinical validation of this model and explore its potential role in optimizing immunotherapy and targeted treatment strategies for ccRCC.
    Keywords:  Arginine methylation; Clear cell renal cell carcinoma (ccRCC); Immune infiltration; Prognostic model; Tumor microenvironment (TME)
    DOI:  https://doi.org/10.1007/s12672-025-02505-3
  30. Front Mol Biosci. 2025 ;12 1591446
    MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.
    Yan Jiang, Zhengyu Shu, Lei Cheng, Haowei Wang, Taiping He, Liwen Fu, Chao Zhao, Xuefei Li, Weicheng Zeng.
       Background: Lung adenocarcinoma (LUAD) represents the most common form of lung cancer, contributing to significant global mortality. Metabolic reprogramming in tumor cells has been increasingly recognized as a hallmark of tumorigenesis, contributing to an immunosuppressive microenvironment. Given the promising prediction value of metabolism-related genes in LUAD, this study aims to explore the role of MS4A7, a member of the MS4A gene family, in LUAD prognosis and immune microenvironment dynamics.
    Methods: A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. Genes with differential expression linked to metabolic pathways were identified, and 20 genes were included to develop a risk signature. Further functional enrichment analysis was conducted to compare the biological pathways activated in high-risk versus low-risk groups. Single-cell RNA sequencing was employed to identify the expression profile and role of MS4A7 in different macrophage populations within the LUAD.
    Results: The constructed prognostic model displayed high predictive accuracy, outperforming single gene-based predictions. High-risk patients exhibited significantly poorer survival outcomes. Pathway enrichment analysis revealed dysregulated metabolic pathways in high-risk patients, including activation of glycolysis, mTORC1 signaling, and ROS production. Single-cell RNA sequencing revealed that MS4A7 expression was predominantly found in macrophage populations, with high expression localized in MS4A7+ macrophages. These macrophages exhibited distinct metabolic reprogramming and key immune functions, particularly in crosstalk with T cells and neutrophils.
    Conclusion: The MS4A7 gene plays a critical role in LUAD prognosis, particularly through its involvement in immune modulation within the TME. MS4A7+ macrophages, characterized by distinct metabolic reprogramming and immune interactions, are pivotal in shaping LUAD progression and immune response. The findings highlight the potential of MS4A7 as a novel prognostic biomarker and therapeutic target for LUAD. Further investigation into the metabolic and immune regulatory mechanisms of MS4A7+ macrophages could offer new insights into LUAD treatment strategies.
    Keywords:  MS4A7; lung adenocarcinoma; metabolism-related genes; prognosis prediction; tumor microenvironment
    DOI:  https://doi.org/10.3389/fmolb.2025.1591446
  31. Diabetol Metab Syndr. 2025 May 14. 17(1): 155
    Potential mechanisms of epigenetic regulation in diabetic retinopathy from the perspectives of multi-omics.
    Xin Luo, Daxi Xue.
       PURPOSE: Diabetic retinopathy (DR) is a significant complication of diabetes, with complex pathogenesis involving epigenetic modifications. This study aimed to explore the epigenetic regulatory mechanisms contributing to DR.
    METHODS: DR-related data, including DNA methylation, mRNA, and miRNA expression datasets, were obtained from the Gene Expression Omnibus database. Differential gene expression analysis was performed to identify differentially methylated genes and expressed mRNAs and miRNAs. Cross-analysis established the methylation-expression and miRNA-mRNA regulatory networks. A comprehensive DR-related epigenetic regulatory network was constructed, identifying hub genes. The expression characteristics of these hub genes in various immune cells were examined using single-cell RNA sequencing.
    RESULTS: We identified 10,716 differentially methylated genes, 1,181 differentially expressed mRNAs, and 615 differentially expressed miRNAs in DR. The methylation-expression regulatory network was associated with pathways such as TGF-beta and ErbB signaling. The miRNA regulatory network was linked to pathways related to cellular senescence, adherents junctions, and endocytosis. Five hub genes were identified: TFRC, AP2M1, AP2A1, DAB2, and PPP1CB. Single-cell RNA sequencing revealed specific expression of these genes in particular immune cells, highlighting their potential roles in DR pathogenesis.
    CONCLUSION: This study constructed a comprehensive epigenetic regulatory network for DR and identified key regulatory genes, offering new insights into the molecular mechanisms underlying DR and potential therapeutic targets for diagnosis and treatment.
    Keywords:  DNA methylation; Diabetic retinopathy; Epigenetic regulation; Single-cell RNA sequencing; miRNA
    DOI:  https://doi.org/10.1186/s13098-025-01723-7
  32. BMC Cancer. 2025 May 12. 25(1): 857
    INHBA+ macrophages and Pro-inflammatory CAFs are associated with distinctive immunosuppressive tumor microenvironment in submucous Fibrosis-Derived oral squamous cell carcinoma.
    Simin Zhao, Yu Zhang, Xiaoqin Meng, Ye Wang, Yahui Li, Hao Li, Xingyu Zhao, Pishan Yang, Shaopeng Liu, Chengzhe Yang.
      Transcriptomic and metabolic profiles of tumor cells and stromal cells in oral squamous cell carcinoma (OSCC)-derived from oral submucosal fibrosis (OSF) (ODSCC) have been reported. However, the complex intercellular regulatory network within the tumor immunosuppressive microenvironment (TISME) in ODSCC remains poorly elucidated. Here, we utilized single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) data from GEO database and multiple immunofluorescence staining (mIF) to reveal distinctive TISME of ODSCC. Results found that compared to OSCC without OSF history (NODSCC), OSCC derived from OSF (ODSCC) showed a significant increase in exhausted CD8+T and Treg cells (Ro/e > 1, p < 0.05) and a decrease in cytotoxic T (CTL) (Ro/e < 1). ODSCC enriched in more Inhibin subunit beta A+ Macrophages (INHBA+Mac) and Proinflammatory Cancer-associated Fibroblast (iCAF) versus NODSCC. INHBA+Mac possessed strongest immune-suppressive functions, evidenced by highest immune checkpoint scores, lowest MHC scores and highest expression of SPP1 among macrophages. Moreover, INHBA+Mac in ODSCC presented stronger immune-suppressive functions than that in NODSCC. iCAF differentially highly expressed INHBA and enriched in immune-related pathways and collagen/ECM pathways across CAF subsets, and possessed stronger immune-suppressive functions, as shown by up-regulated gene expression of TDO2, IDO1 and DUSP4 in ODSCC versus in NODSCC. Furthermore, INHBA expression was higher in ODSCC than in NODSCC (p < 0.01). The classic OSF-inducing molecule arecoline significantly increases the expression of INHBA (p < 0.0001) in vitro experiments stimulating THP-1 cells. ST analysis revealed a close co-location of INHBA+Mac, iCAF and Treg and SpaGene identified INHBA-ACVR1/ACVR2A/ACVR2B interaction regions overlapping with distribution of three types of cells. Collectively, ODSCC shows a more severe TISME and potentially poorer sensitivity to immunotherapy than NODSCC. The increased INHBA+Mac and iCAF in ODSCC are associated with the observed more severe TISME. The upregulated INHBA in ODSCC and its interaction with INHBA-ACVR1/ACVR2A/ACVR2B may mediate the modulation effect of INHBA+ Mac and iCAF on Treg differentiation and functionality.
    Keywords:  Immunosuppressive microenvironment; Inhibin subunit beta A; Macrophage; Oral squamous cell carcinoma; Submucosal fibrosis
    DOI:  https://doi.org/10.1186/s12885-025-14261-2
  33. J Transl Med. 2025 May 12. 23(1): 536
    Alternative lengthening of telomeres confers favorable prognosis in chondrosarcomas.
    Ji-Yong Sung, Jin-Hong Kim, Yi-Jun Kim.
       BACKGROUND: Cancer cells achieve replicative immortality through telomere maintenance mechanisms (TMMs), primarily via telomerase activation or alternative lengthening of telomeres (ALT). Sarcomas frequently employ the ALT pathway, which traditionally correlates with adverse clinical outcomes. However, chondrosarcomas represent a unique context where the role and prognostic significance of ALT remain largely unexplored.
    METHODS: We performed comprehensive analyses of single-cell RNA-sequencing data from patients with chondrosarcoma and integrated this with 90 bulk RNA-seq datasets. This approach enabled detailed characterization of TMM at single-cell resolution, identification of ALT-specific signatures, and evaluation of the tumor microenvironment in chondrosarcomas.
    RESULTS: Patients with ALT-like chondrosarcomas exhibited significantly improved survival compared to those with non-ALT-like chondrosarcomas. Analysis of the tumor immune microenvironment revealed distinct metabolic and immune landscapes between the ALT-like and non-ALT-like groups. Single-cell analysis showed that high-entropy stem-like cells in high-grade chondrosarcomas predominantly adopted telomerase activation over the ALT pathway as their TMM. Additionally, we identified a 100-gene signature that reliably distinguishes ALT-like chondrosarcomas, providing a robust molecular marker for classification and prognosis.
    CONCLUSIONS: Our study reveals ALT-like state as a marker of favorable prognosis in chondrosarcomas-contrasting with its typically adverse implications in other sarcomas. We establish a robust 100-gene signature that reliably identifies ALT-like chondrosarcomas and characterize their distinct immune microenvironment profile.
    Keywords:  Alternative lengthening of telomeres; Chondrosarcoma; Prognosis; Signature genes; Tumor immune microenvironment
    DOI:  https://doi.org/10.1186/s12967-025-06539-7
  34. Int J Mol Sci. 2025 Apr 23. pii: 3993. [Epub ahead of print]26(9):
    Exploring the Role of Circadian Rhythm-Related Genes in the Identification of Sepsis Subtypes and the Construction of Diagnostic Models Based on RNA-seq and scRNA-seq.
    Xuesong Wang, Zhe Guo, Ziwen Wang, Xinrui Wang, Yuxiang Xia, Dishan Wu, Zhong Wang.
      Sepsis is a severe systemic response to infection that may lead to the dysfunction of multiple organ systems and may even be life-threatening. Circadian rhythm-related genes (CRDRGs) regulate the circadian clock and affect many physiological processes, including immune responses. In patients with sepsis, circadian rhythms may be disrupted, thus leading to problems such as immune responses. RNA-seq datasets of sepsis and control groups were downloaded from the Gene Expression Omnibus (GEO) database, and two sepsis subtypes were identified based on differentially expressed CRDRGs. Two gene modules related to sepsis diagnosis and subtypes were obtained using the weighted co-expression network (WGCNA) algorithm. Subsequently, using four machine learning algorithms (random forest, support vector machine, a generalized linear model, and xgboost), genes related to sepsis diagnosis were identified from the intersection genes of the two modules, and a diagnostic model was constructed. Single-cell sequencing (scRNA-seq) data were obtained from the GEO database to explore the expression landscape of diagnostic-related genes in different cell types. Finally, an RT-qPCR analysis of diagnosis-related genes confirmed the differences in expression trends between the two groups. Multiple differentially expressed CRDRGs were observed in the sepsis and control groups, and two subtypes were identified based on their expression levels. There were apparent differences in the distribution of samples of the two subtypes in two-dimensional space and the pathways involved. Using multiple machine learning algorithms, the intersection genes in the two most relevant modules of the WGCNA were identified, and a robust diagnostic model was constructed with five genes (ARHGEF18, CHD3, PHC1, SFI1, and SPOCK2). The AUC of this model reached 0.987 on the validation set, showing an excellent prediction performance. In this study, two sepsis subtypes were identified, and a sepsis diagnostic model was constructed via consensus clustering and machine learning algorithms. Five genes were identified as diagnostic markers for sepsis and can thus assist in clinical diagnosis and guide personalized treatment.
    Keywords:  circadian rhythm-related genes; machine learning; scRNA-seq; sepsis; subtype identification
    DOI:  https://doi.org/10.3390/ijms26093993
  35. Clin Exp Pharmacol Physiol. 2025 Jul;52(7): e70031
    Sepsis Important Genes Identification Through Biologically Informed Deep Learning and Transcriptomic Analysis.
    Ruichen Li, Qiushi Wang, Ru Gao, Rutao Shen, Qihao Wang, Xiuliang Cui, Zhiming Jiang, Lijie Zhang, Jingjing Fang.
      Sepsis is a life-threatening disease caused by the dysregulation of the immune response. It is important to identify influential genes modulating the immune response in sepsis. In this study, we used P-NET, a biologically informed explainable artificial intelligence model, to evaluate the gene importance for sepsis. About 688 important genes were identified, and these genes were enriched in pathways involved in inflammation and immune regulation, such as the PI3K-Akt signalling pathway, necroptosis and the NF-κB signalling pathway. We further selected differentially expressed genes both at bulk and single-cell levels and found TIMP1, GSTO1 and MYL6 exhibited significant different expressions in multiple cell types. Moreover, the expression levels of these 3 genes were correlated with the abundance of important immune cells, such as M-MDSC cells. Further analysis demonstrated that these three genes were highly expressed in sepsis patients with worse outcomes, such as severe, non-survived and shock sepsis patients. Using a drug repositioning strategy, we found navitoclax, curcumin and rotenone could down-regulate and bind to these genes. In conclusion, TIMP1, GSTO1 and MYL6 may serve as promising biomarkers and targets for sepsis treatment.
    Keywords:  biomarkers; explainable artificial intelligence; immune infiltration analysis; molecular docking; sepsis
    DOI:  https://doi.org/10.1111/1440-1681.70031
  36. J Immunother. 2025 May 16.
    Harnessing Calmodulin-Related Genes to Build a Prognostic Model in Esophageal Squamous Cell Carcinoma for a Comprehensive Analysis of Single-Cell Immune Characteristics and Drug Efficacy.
    Shasha Cao, Shumin Lun, Lijuan Duan, Zhaowei Gao, Xiaoxiao Wang, Yutong Li, Yaowen Zhang.
       SUMMARY: Calmodulin (CALM) has a bearing on the prognosis of various cancers. However, the prognostic value of CALM in esophageal squamous cell carcinoma (ESCC) remains unelucidated. Differentially expressed genes (DEGs) were screened between normal and tumor groups of TCGA-ESCC sets. The intersection of DEGs with calmodulin-related genes (CRGs) yielded differentially expressed CRGs (DE-CRGs). A prognostic model was established using LASSO Cox regression analysis and multivariate Cox regression analysis. qPCR validated the expression of prognostic feature genes. Analysis of gene expression patterns of different cellular clusters was based on single-cell sequencing data. Lastly, GSEA enrichment, immune infiltration, mutational profiling, drug sensitivity, and molecular docking as well as cellular thermal shift assay (CETSA) were conducted for ESCC patients. A prognosis model with excellent predictive capability was created based on 4 feature genes (ATP2B3, CALB1, KCNQ1, and MYO1G). The qPCR results demonstrated that ATP2B3 and KCNQ1 were significantly downregulated in human ESCC cells, whereas CALB1 and MYO1G were upregulated (P<0.05). Single-cell analysis uncovered that MYO1G and KCNQ1 were mainly expressed in different cell clusters. Furthermore, this risk model was strongly associated with functional pathway enrichment, immune cell infiltration, and somatic mutations. We also identified AZD-8055 may be potential therapy for ESCC patients. The CETSA experiment demonstrated the existence of a favorable binding thermal stability between AZD-8055 and MYO1G. This research may identify potential biomarkers for predicting the prognosis of ESCC patients.
    Keywords:  calmodulin; esophageal squamous cell carcinoma; immunity; prognosis; single cells
    DOI:  https://doi.org/10.1097/CJI.0000000000000561
  37. mBio. 2025 May 14. 16(5): e0133824
    Dual oxic-anoxic co-culture enables direct study of anaerobe-host interactions at the airway epithelial interface.
    Patrick J Moore, Kayla Hoffman, Sara Ahmed, Joshua R Fletcher, Talia D Wiggen, Sarah K Lucas, Sabrina J Arif, Adam J Gilbertsen, Leslie A Kent, Jessica K Fiege, Ryan A Langlois, Scott M O'Grady, Ryan C Hunter.
      Strict and facultative anaerobic bacteria are widely associated with both acute and chronic airway diseases. However, their potential role(s) in disease pathophysiology remains poorly understood due to inherent limitations of existing laboratory models and conflicting oxygen demands between anaerobes and host cells. To address these limitations, here, we describe a dual oxic-anoxic culture (DOAC) approach that maintains an oxygen-limited microenvironment at the apical epithelial interface while host cells are oxygenated basolaterally. This platform enables epithelial-anaerobe co-culture for ~48 h, and we demonstrate its utility by evaluating reciprocal interactions between the oxygen-sensitive anaerobic bacterium, Fusobacterium nucleatum, and oxygen-demanding airway epithelial cells at the transcriptional level. Using bulk RNAseq, we demonstrate that epithelial colonization results in altered gene expression by F. nucleatum, highlighted by the differential expression of genes associated with virulence, ethanolamine and lysine metabolism, metal uptake, and other transport processes. We also combine DOAC with single-cell RNA sequencing to reveal a cell type-specific transcriptional response of the airway epithelium to F. nucleatum infection, including the increased expression of inflammatory marker genes and cancer-associated pathways. Together, these data illustrate the versatility of DOAC while revealing new insights into anaerobe-host interactions and their mechanistic contributions to airway disease pathophysiology.IMPORTANCEConflicting oxygen demands between anaerobes and host cells present a significant barrier to in vitro modeling of how these cell types interact. To this end, the significance of our dual oxic-anoxic culture (DOAC) approach lies in its ability to maintain anaerobe and epithelial viability during co-culture, paving the way for new insights into the role(s) of anaerobic microbiota in disease. We use DOAC to interrogate reciprocal interactions between the airway epithelium and Fusobacterium nucleatum-an anaerobic commensal with pathogenic potential. Given its link to a range of diseases, from localized infections to various cancers, these data showing how F. nucleatum bacterium re-shapes its metabolism and virulence upon epithelial colonization provide new mechanistic insight into F. nucleatum physiology and how the host responds. We use F. nucleatum as our model, but the DOAC platform motivates additional studies of the gut, lung, and oral cavity, where host-anaerobe interactions and the underlying mechanisms of pathogenesis are poorly understood.
    Keywords:  Fusobacterium nucleatum; RNAseq; airway epithelium; single-cell RNA sequencing
    DOI:  https://doi.org/10.1128/mbio.01338-24
  38. Mol Med. 2025 May 14. 31(1): 186
    Comprehensive single-cell transcriptomic reveals different destinies of melanocytes and dynamic changes of immune microenvironment in a psychological stress-induced leukoderma and leukotrichia mouse model.
    Xuechen Cao, Yongkai Yu, Hang Yao, Yujie Zheng, Jiawei Lu, Yifei Feng, Tongxin Pei, Ziyu Li, Ming Lu, Yan Lu.
       BACKGROUND: Vitiligo is an acquired skin depigmentation disorder often accompanied by leukoderma and leukotrichia. Half of vitiligo patients experience episodes of stress.
    METHODS: We established a chronic unpredictable mild stimulation (CUMS) model in C57BL/6 J mice to simulate chronic mental stress-induced leukoderma and leukotrichia. Single-cell RNA sequencing was performed to determine the immune landscape and to characterize the relationship between immune-stromal cells. Immunohistochemistry was employed for validation.
    RESULTS: We discovered a similar pro-inflammatory micro-environment composed of keratinocytes and fibroblasts similar to that in human vitiligo. Macrophages in CUMS mice expressed high levels of inflammatory factors and were inclined to an M1 pro-inflammatory phenotype. Two distinct clusters of melanocytes were also identified: Mel2, defined as melanocyte stem cells, and Mel3, defined as mature melanocytes. Mel2 cells were prone to pyroptosis and necroptosis, while Mel3 cells were susceptible to oxidative stress, mitochondrial dysfunction, and ferroptosis. Compared with control mice, higher expression of CXCL16 on dendritic cells and of the CXCL16 ligand, CXCR6, on γδT cells were observed in leukoderma. Dendritic cells and natural killer T cells in the CUMS mouse spleen exhibited elevated levels of CXCL16 and CXCR6, respectively. Activation of the CXCL16-CXCR6 axis and a non-specific immune response in our CUMS model might imitate chronic mental stress-induced vitiligo in humans better than CD8 + cytotoxic T lymphocyte-mediated models.
    CONCLUSIONS: We discovered two melanocyte clusters with distinct fates and a pro-inflammatory micro-environment with CXCL16-CXCR6 axis activation of antigen-presenting cells and other innate immunocytes that might provide new insights into the pathogenesis of stress-induced vitiligo.
    Keywords:  CXCL16; CXCR6; Chronic unpredictable mild stress; Innate immunity; Melanocyte stem cells; Single-cell sequencing
    DOI:  https://doi.org/10.1186/s10020-025-01236-z
  39. Discov Oncol. 2025 May 12. 16(1): 728
    Identification of novel potential biomarkers using bulk RNA and single cells to build a neural network model for diagnosis of liver cancer.
    Yingzheng Gao, Jiahao Chen, Weidong Du.
       BACKGROUND: As a common cancer, liver cancer imposes an unacceptable burden on patients, but its underlying molecular mechanisms are still not fully understood. Therefore, there is an urgent need to potential biomarkers and diagnostic models for liver cancer.
    METHODS: In this study, transcriptome and single-cell datasets related to liver cancer were downloaded from the UCSC Xena database and the Mendeley database, and differential analysis and weighted gene co-expression network analysis were used to find differentially expressed genes related to liver cancer. We used multiple machine algorithms to find hub genes related to liver cancer, and constructed new artificial neural network models based on their transcriptome expression patterns to assist in the diagnosis of liver cancer. Subsequently, we conducted survival analysis and immune infiltration analysis to explore the correlation between hub genes and immune cells, and used single-cell data to verify hub genes related to liver cancer.
    RESULTS: This study identified MARCO, KCNN2, NTS, TERT and SFRP4 as central genes associated with liver cancer, and constructed a new artificial neural network model for molecular diagnosis of liver cancer. The diagnostic performance of the training cohort and the validation cohort was good, with the areas under the ROC curves of 1.000 and 0.986, respectively. Immune infiltration analysis determined that these central genes were closely associated with different types of immune cells. The results of immunohistochemistry and the results at the single cell level were consistent with those at the transcriptome level, and also showed obvious differences between different cell types in liver cancer and healthy states.
    CONCLUSION: This study identified MARCO, KCNN2, NTS, TERT, and SFRP4 from multiple dimensions and highlighted their key roles in the diagnosis and treatment of liver cancer from multiple dimensions, providing promising biomarkers for the diagnosis of liver cancer.
    Keywords:  Artificial neural network; Liver cancer; Machine learning algorithm; Molecular marker; Single cell analysis
    DOI:  https://doi.org/10.1007/s12672-025-02420-7
  40. Stem Cell Rev Rep. 2025 May 14.
    Identifying Immunomodulatory Subpopulations of Adipose Stromal Vascular Fraction and Stem/Stromal Cells Through Single-Cell Transcriptomics and Bulk Proteomics.
    Adrienne M Parsons, Nagib Ahsan, Eric M Darling.
      A primary therapeutic characteristic of mesenchymal stem/stromal cells (MSCs) is their immunomodulatory activity. Adipose-derived stem/stromal cells (ASCs) are an abundant and easily isolated source of MSCs shown to have high immunosuppressive activity, making them attractive for therapy. Understanding the heterogeneous immunomodulatory potential of ASCs within the stromal vascular fraction (SVF) of adipose tissue could better inform treatment strategies. In this study, we integrate single-cell RNA sequencing (scRNA seq) with bulk proteomics to characterize subpopulations of SVF-derived ASCs that are phenotypically similar to cytokine-licensed, cultured ASCs. To better define the licensing process, we present scRNA seq and bulk proteomics data of cultured (P2) ASCs exposed to inflammatory cytokines, showing enrichment of pathways related to inflammation and apoptosis that positively correlate to the cytokine-mediated, trajectory-derived pseudotime. Using the Scissor algorithm, we integrate the proteomics data with uncultured (P0) SVF scRNA seq data, identifying an ASC subpopulation that is phenotypically like the cytokine-stimulated ASCs (Scissor-positive). Interactome analysis identifies Scissor-positive ASCs as stress adaptive immune regulators that function through IL6 and broad SEMA4 interactions and higher Visfatin signaling, while Scissor-negative ASCs show strong signatures of ECM remodeling through FN1 and immunosuppression through THY1 and MIF signaling. Our multimodal, integrative approach enabled identification of previously unidentified, distinct ASC subpopulations with differing immunomodulatory phenotypes that are present in, and can potentially be selected from, P0 SVF ASCs.
    Keywords:  Adipose-derived stem/stromal cells; Cellular heterogeneity; Culture conditions; Cytokine-stimulus; Mesenchymal stem cell immunomodulation; Multimodal -omic integration
    DOI:  https://doi.org/10.1007/s12015-025-10889-6
  41. Front Oncol. 2025 ;15 1564375
    Overexpression of MMP14 is associated with poor prognosis and immune cell infiltration in colon cancer.
    Na Li, Nan Zhang, Guanghui Wang.
       Introduction: Colorectal cancer (CRC) poses a significant risk of recurrence and distant metastases. This study investigated the regulatory role of Matrix metalloproteinase-14 (MMP14) in immune function and its impact on CRC prognosis.
    Methods: we performed transcriptome sequencing on tumor and adjacent non-cancerous samples from four pairs of patients diagnosed with colorectal cancer. Single-cell transcriptome data were analyzed to explore MMP14 expression and immune microenvironment changes. mRNA expression profiles and clinical data were retrieved from public databases (TCGA and GEO). The association between MMP14 and pathways as well as immune regulators was analyzed. Co-expression genes of MMP14 relevant to prognosis were identified. A prognostic model was then constructed. MMP14 expression was examined using real-time fluorescence quantification PCR (qRT-PCR) and Western blotting (WB). Immunofluorescence was utilized to demonstrate MMP14 expression in colon cancer tissues, while Hematoxylin and eosin (HE) staining was employed to observe the histology of normal tissue and colon cancer tissue.
    Results: Machine learning identified MMP14 as a candidate gene. MMP14 was overexpressed in CRC tissues and COLO205 cells. Single-cell transcriptome analysis revealed that MMP14 was highly expressed in fibrocyte cells within the liver metastasis group. Increased MMP14 levels correlated with poor overall survival (OS), progression-free survival (PFS), and advanced TNM stages. Functional assays indicated that silencing MMP14 in COLO205 cells enhanced apoptosis and upregulated the expression of the immune-related cytokine IL-1β. Furthermore, MMP14 exhibited significant correlations with immunomodulators, particularly immunostimulants and immunosuppressants, and was associated with immune cell infiltration within tumor tissues. Additionally, by utilizing co-expressed genes of MMP14 and conducting Cox regression analysis, we developed a risk prediction model comprising three genes (LIMK1, SPOCK3, SLC2A3). The risk scores derived from this model were found to correlate with OS and PFS.
    Discussion: MMP14 plays a crucial role in CRC progression. Its overexpression is related to poor prognosis and immune cell infiltration. The prognostic model based on MMP14 co-expression genes may help predict CRC prognosis. However, further studies are needed to validate these findings, such as more in-vitro and in-vivo experiments. In conclusion, MMP14 can serve as a biomarker for evaluating CRC prognosis and immune cell infiltration.
    Keywords:  CRC; MMP14; RNA-seq; immune cell infiltration; machine learning; prognosis
    DOI:  https://doi.org/10.3389/fonc.2025.1564375
  42. Curr Top Med Chem. 2025 May 09.
    Integrative Analysis Reveals Genes Causal Relation with Ovarian Cancer and aging.
    Lanhui Qin, Chongze Yang, Rui Song, Pei-Yin Chen, Zijian Jiang, Weihui Xu, Guanzhen Zeng, Jin-Yuan Liao, Liling Long.
       BACKGROUND: Exploring the correlation between ovarian cancer and aging has great significance for understanding the pathogenesis of ovarian cancer and formulating targeted therapeutic regimens.
    OBJECTIVE: This computational study aims to identify and validate key genes in monocyte subtypes related to ovarian cancer and aging, exploring potential causal relationships.
    METHOD: We collected single-cell RNA sequencing data (GSE157007, GSE184880), GWAS data (14,049 samples and 40,941 controls from a European population), and eQTL data of ovarian cancer and aging. Using R software packages like Seurat and singleR, we conducted data integration, quality control, cell classification, and differential gene expression analysis to identify intersecting monocyte subtype genes in ovarian cancer and aging. We employed summary data-based Mendelian randomization (SMR) analysis and Heterogeneity in Dependent Instruments (HEIDI) tests to pinpoint causal genes. Further single-cell functional analyses (gene switching, cell communication, metabolic pathway analysis), Bulk RNA sequencing validation, functional enrichment, and protein- protein interaction (PPI) analyses elucidated these genes' biological roles.
    RESULTS: The dataset included 123,280 cells, revealing differential gene expression in classical monocytes (104 genes), intermediate monocytes (43 genes), and myeloid dendritic cells (39 genes). SMR and HEIDI identified causal relationships for 7 genes in classical monocytes, 3 in intermediate monocytes, and 3 in myeloid dendritic cells with ovarian cancer. Bulk RNA seq validation confirmed six monocyte genes as causal in ovarian cancer and aging. TREM1, SERPINB2, and CD44 were upregulated, while DST was downregulated; SLC11A1 and PNRC1 showed contradictory patterns. Interactions with NK and T cells involved LGALS9 - CD44/45 receptors. Riboflavin metabolism was a common enriched pathway.
    CONCLUSION: This study identified six specific monocyte genes as potential therapeutic targets for ovarian cancer and aging.
    Keywords:  Ovarian cancer; aging; genome-wide association study.; single-cell RNA sequencing; summary data-based Mendelian randomization
    DOI:  https://doi.org/10.2174/0115680266358687250507041056
  43. Cell Biol Toxicol. 2025 May 15. 41(1): 85
    IGFBP3 enhances adipose-derived stem cell function in soft tissue injury repair via ITGB1 and ERK pathway activation.
    Sirui Tian, Haiyang Yu, Ruoxuan Yang, Heshi Wang, Baohong Zhao, Danning Wang.
      Soft tissue injury (STI) is a prevalent condition that requires effective therapeutic approaches. The focus of this investigation was to elucidate the molecular mechanisms linked to the IGFBP3 protein in adipose-derived stem cells (ADSCs) for STI repair, utilizing single-cell multiomics technology and a 3D bioprinting model. Establishment of a mouse-based STI model facilitated the comparison of cellular compositions and communication variances between wounded and normal tissues through single-cell RNA sequencing (scRNA-seq). High-throughput transcriptomics and bioinformatics analysis pinpointed IGFBP3 as a key target in ADSCs related to STI repair. In vitro experiments assessed IGFBP3's effects on ADSCs' epithelial cell differentiation, proliferation, and migration using various assays and lentivirus transfection to manipulate IGFBP3 expression. A 3D bioprinting technique was used to create an ADSCs-IGFBP3 peptide self-assembling hydrogel scaffold, characterized by Fourier-transform infrared spectroscopy, X-ray diffraction, SEM, and TEM. The scaffold's efficacy was validated in an animal model. Results showed nine cell subtypes in both normal and injured tissues, with increased ADSCs in STI tissues exhibiting enhanced connectivity and interactions. RNA-seq analysis confirmed IGFBP3 as crucial for ADSCs and STI. In vitro and 3D bioprinting experiments, along with animal model validation, confirmed IGFBP3's role in STI repair. Upregulation of IGFBP3 in ADSCs promoted epithelial cell differentiation by enhancing ITGB1 expression, activating the ERK pathway to boost cell proliferation and migration. This study highlights IGFBP3's significant role in ADSCs for STI repair, providing potential molecular targets for developing new treatments. The findings offer valuable insights into IGFBP3's mechanisms, aiding in advancing STI therapeutic strategies.
    Keywords:  3D bioprinting; Adipose-derived stem cells; Epithelial cell differentiation; IGFBP3 protein; Single-cell multiomics; Soft tissue injury
    DOI:  https://doi.org/10.1007/s10565-025-10024-8
  44. Front Oncol. 2025 ;15 1534247
    Single-cell combined transcriptome probes prognostic mechanisms of sialylation-related genes in cervical cancer.
    Gulinigaer Muhetaer, Xinyi He, Chenqing Yang, Fenglan Guo, Ruifang An.
       Introduction: Sialylation has been linked to cervical dysplasia, while its involvement in cervical cancer is uncertain. Hence , the aim of this study was to develop a prognostic model based on sialylation-related characteristics for cervical cancer patients and investigate how sialylation-related genes are altered in cervical cancer via analyses of transcriptome and single-cell RNA sequencing (scRNA-seq) data.
    Methods: The current work incorporated 4 transcriptome datasets relevant to cervical cancer (including scRNA-seq) and 110 sialylation-related genes (SRGs). Initially, differentially expressed SRGs (DE-SRGs) were discovered by differential expression analysis, among other methods. Subsequently, least absolute shrinkage and selection operator (LASSO) and Cox regression analysis was applied using DE-SRGs to detect prognostic genes and build prognostic models. Next, independent prognosis test was conducted, and a nomogram model was built using clinical characteristics and risk scores. Meanwhile, scRNA-seq was applied to examine the cellular composition and cell-to-cell regulation in cervical cancer vs normal group, and key cells were determined via prognostic genes and their differentiation process was investigated. Finally, the immunological microenvironment, mutant genes, and medication sensitivity were assessed. Clinical samples were taken to assess the expression of prognostic genes by quantitative reverse transcriptase PCR (qRT-PCR).
    Results: First, we detected 19 DE-SRGs related with sialylation. Three prognostic genes, GALNT12, GCNT4, and NPL, were discovered by LASSO cox regression. A risk model constructed with prognostic genes revealed that patients in high-risk group had a much poorer survival rate than those in group with low risk. Meanwhile, low-risk cervical cancer patients were more likely to respond to immunotherapy and chemotherapy, depending on immunology, tumor microenvironment, and drug sensitivity. ScRNA-seq data suggests that the expression of prognostic genes was higher in key cells, macrophages and fibroblasts, and played a more critical role in cervical cancer. The findings from qRT-PCR demonstrated that GCNT4 and NPL were considerably overexpressed in the cervical cancer group.
    Discussion: In this research, GALNT12, GCNT4 and NPL were discovered as sialylation-related prognostic genes in cervical cancer, providing novel pathways for detection and treatment.
    Keywords:  cervical cancer; immunotherapy; mechanisms; prognostic features; sialylation
    DOI:  https://doi.org/10.3389/fonc.2025.1534247
  45. Aging Cell. 2025 May 15. e70097
    Single-Cell RNA-Seq Reveals Aging-Related Impairment of Microglial Efferocytosis Contributing to Apoptotic Cells Accumulation After Retinal Injury.
    Pan Liu, Qi Wang, Shuimiao Wang, Ying Liu, Qiqi Chen, Wanyun Qin, Xinna Liu, Xinqi Ye, Yexuan Jiao, Huiping Yuan, Zhengbo Shao.
      Aging is associated with increased retinal cell apoptosis, which contributes to decreases in retinal function. Apoptotic retinal cell clearance relies on microglial efferocytosis, but the impact of aging on this process has not been fully elucidated. In this study, we aimed to shed light on this by using single-cell RNA sequencing (sc-RNA-seq) to compare young and aged mouse retinal transcriptional profiles, in which 74,412 retinal cells from young and aged mice were classified into 10 transcriptionally distinct retinal cell types, and differentially expressed genes between young versus aged retinas were mainly associated with cellular senescence and apoptosis. Furthermore, ligand-receptor interactions (e.g., AXL-GAS6, MERTK-GAS6) between microglia and other retinal cells were strengthened in aged, compared to young retinas. Additionally, among microglia, Subcluster 4 was found under partial clustering to be associated with efferocytosis, of which aged microglia had downregulated efferocytosis-associated genes. The impact of aging on microglial efferocytosis was further verified in vitro by doxorubicin (DOX)-induced senescent BV2 microglia, and in vivo by a retinal ischemia/reperfusion (I/R) injury mouse model. In vitro, DOX-treated BV2 microglia had significantly lowered efferocytosis, as well as efferocytosis-related MerTK and Axl protein expression; this was also present in vivo in aged retinas post-I/R injury, with increased co-localization of ionized calcium-binding adapter molecule 1+ microglia with apoptotic retinal cells, along with reduced efferocytosis-related protein expression. Overall, microglial efferocytosis of apoptotic cells decreased with aging, suggesting that modulating this process could serve as a possible therapeutic target for age-related retinal diseases.
    Keywords:  aging; apoptosis; efferocytosis; microglia; retina; single‐cell RNA sequencing
    DOI:  https://doi.org/10.1111/acel.70097
  46. Discov Oncol. 2025 May 12. 16(1): 740
    Multi-omics identify ribosome related causal genes methylation, splicing, and expression in prostate cancer.
    Chengcheng Wei, Jingke He, Yunfan Li, Yu Luo, Liangdong Song, Kun Han, Jindong Zhang, Shuai Su, Delin Wang.
       BACKGROUND: Understanding the molecular underpinnings of prostate cancer remains a critical challenge in oncology. Ribosomes, essential cellular organelles responsible for protein synthesis, have emerged as potential regulators in cancer development. Previous studies suggest that dysfunction in ribosomal processes may contribute significantly to prostate cancer progression. We used summary-data-based Mendelian randomization (SMR) and colocalization analysis, as well as single-cell analysis, to investigate the association between ribosome-related genes and prostate cancer by integrating multi-omics.
    METHOD: In this study, we employed a multi-omics approach integrating genomics and transcriptomics data to investigate the role of ribosome-related genes in prostate cancer. Summary-level data for prostate cancer were obtained from The Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome and FinnGen studies. SMR analyses were performed to assess the relevance of ribosomal gene-related molecular signatures to prostate cancer. We further performed colocalization analysis to assess whether the identified signal pairs shared causal genetic variants. Genes were then validated with single-cell sequencing analysis.
    RESULTS: We identified significant causal effects of ribosome gene methylation on prostate cancer. After integrating the multi-omics data of mQTL, sQTL and eQTL, we identified two ribosomal genes, NSUN4 and MPHOSPH6. Methylation and splicing at different sites on the NSUN4 gene showed increased and decreased risks for prostate cancer, indicating complex gene regulation mechanisms. For instance, NSUN4 methylation site of cg10215817 was genetically associated with the increased prostate cancer risk (OR 1.20, 95% CI 1.10,1.30), while NSUN4 methylation site of cg00937489 was genetically associated with the decreased prostate cancer risk (OR 0.84, 95% CI 0.74,0.94); NSUN4 chr1:46341497:46344801 splicing (OR 1.11, 95% CI 1.05-1.17) were positively associated with prostate cancer risk, while NSUN4 chr1:46340919:46344801 splicing (OR 0.95, 95% CI 0.92-0.97) were negatively associated with prostate cancer risk. Expression analysis indicated significant associations between prostate cancer risk and increased expression levels of NSUN4 (OR 1.06, 95% CI 1.03-1.09; PPH4 = 0.79) and MPHOSPH6 (OR 1.07, 95% CI 1.04-1.10; PPH4 = 0.70). In-depth single-cell analysis showed that NSUN4 highly expresses in epithelial cells, while MPHOSPH6 highly expresses in myeloid cells.
    CONCLUSION: The study found that ribosome NSUN4 and MPHOSPH6 genes were associated with prostate cancer risk. This integrative multi-omics study underscores the significance of ribosome-related genes in prostate cancer etiology. By elucidating the molecular mechanisms underlying ribosome dysfunction, our research identifies potential therapeutic targets for mitigating disease progression. These findings not only enhance our understanding of prostate cancer biology but also pave the way for personalized therapeutic strategies targeting ribosomal pathways to improve clinical outcomes.
    Keywords:  Multi-omics; Prostate cancer; Ribosome; Single cell analysis; Summary-data-based Mendelian randomization (SMR)
    DOI:  https://doi.org/10.1007/s12672-025-02584-2
  47. J Cancer Res Clin Oncol. 2025 May 14. 151(5): 163
    Single-cell RNA sequencing reveals SLC31A1-mediated M2 polarization of macrophages promotes malignant progression in triple-negative breast cancer.
    Xiwei Zhang, Guoqing Li, Tieyan Chen, Haohang Sun, Ji Dai, Qi Chen, Mengze Chen, Meidi Yan.
       BACKGROUND: Among the various types of breast cancer that endanger women's lives, triple-negative breast cancer (TNBC) stands out due to its extreme heterogeneity, aggressive nature, and high likelihood of recurrence. The absence of unique targets and targeted drugs is a major factor contributing to the failure of cancer treatments and the eventual death of patients.
    METHODS: Single-cell RNA sequencing (scRNA-seq) was applied to investigate the immune microenvironment of TNBC, facilitating the detection of key cell subpopulations and regulatory genes. The mRNA expression of SLC31A1 in macrophages was measured by qPCR. Flow cytometry was utilized to ascertain the M2 macrophage proportion and cancer cell apoptosis. Transwell and scratch assays were conducted to gauge cancer cell migration and invasion. Copper ion and H2O2 detection kits were employed to evaluate the copper ion content and oxidative stress levels in macrophages.
    RESULTS: SLC31A1 overexpression in TNBC myeloid cells, particularly macrophage subpopulations, was identified through scRNA-seq analysis. Cluster and pseudotime analyses showed that macrophages with high SLC31A1 expression are often in advanced stages of cell growth, accompanied by notable changes in oxidative stress. Functional studies revealed that knocking down SLC31A1 in macrophages significantly reduced M2-type polarization. The conditioned medium from these macrophages markedly inhibited TNBC cell migration and invasion, while promoting apoptosis. Furthermore, SLC31A1 knockdown resulted in decreased copper ion content and H2O2 levels in macrophages.
    CONCLUSION: SLC31A1 enhances the malignant phenotype of TNBC cells by inducing M2 polarization in macrophages.
    Keywords:  M2 polarization; Macro-SLC31A1 + cells; Single-cell sequencing; Triple-negative breast cancer
    DOI:  https://doi.org/10.1007/s00432-025-06191-0
  48. Theranostics. 2025 ;15(12): 5543-5565
    Shh agonist enhances maturation in homotypic Lgr5-positive inner ear organoids.
    Nathaniel T Carpena, So-Young Chang, Seyoung Mun, Kyung Wook Kim, Hyun C Yoon, Phil-Sang Chung, Ji-Hun Mo, Jin-Chul Ahn, Ji On Park, Kyudong Han, Ji Eun Choi, Jae Yun Jung, Min Young Lee.
      Background: The regeneration of functional hair cells (HCs) remains a critical challenge in addressing sensorineural hearing loss. This study aimed to investigate the molecular and functional mechanisms driving stereocilia maturation within inner ear organoids (IEO) derived from homogenic Lgr5-positive progenitor cells (LPCs) and to compare outcomes with traditional heterotypic cultures. Methods: Mouse cochlear LPCs were isolated via magnetic-activated cell sorting (MACS) to establish homotypic cultures, ensuring purity and eliminating the heterotypic influences present in traditional manual isolation (MI) methods. Differentiation into HCs was induced through Wnt and Notch signaling modulation. Transcriptomic profiling using bulk and single-cell RNA sequencing (scRNA-seq) identified gene expression changes linked to stereocilia development. A Sonic Hedgehog (Shh) agonist was applied to enhance structural maturation of HCs. Functional assessment included electron microscopy, FM1-43 uptake assays, and microelectrode array recordings in assembloids of IEO with primary spiral ganglion neurons (SGN) co-cultures. Results: While homotypic LPC-derived IEOs successfully differentiated into HC-like cells, initial morphological assessment revealed immature stereocilia structures. Bulk RNA-seq analysis highlighted a downregulation of morphogenesis-related genes in these organoids. The application of a Shh agonist, acting as a key morphogen, promoted stereocilia development, as evidenced by enhanced ultrastructural features and increased expression of cuticular plate-associated genes (Pls1, Lmo7 and Lrba). Single-cell RNA sequencing (scRNA-seq) further identified distinct cell clusters, which exhibited robust expression of stereocilia-related genes (Espn, Lhfpl5, Loxhd1 and Tmc1), indicative of advanced HC maturation. Electrophysiological assessments of IEO-SGN assembloids using microelectrode arrays confirmed functional mechanoelectrical transduction between cells. Conclusion: This integrated approach elucidates critical pathways and cellular dynamics underpinning stereocilia maturation and functional HC development in EIOs. These findings provide new insights into the molecular regulation of HC maturation and support the utility of Shh-modulated IEOs as a promising platform for inner ear regeneration and therapeutic development for inner ear regenerative therapies.
    Keywords:  Lgr5; RNA sequencing; inner ear organoid; microelectrode array; sonic hedgehog
    DOI:  https://doi.org/10.7150/thno.107345
  49. Cancers (Basel). 2025 Apr 26. pii: 1455. [Epub ahead of print]17(9):
    Deciphering Anticancer Mechanisms of Calycosin in Lung Adenocarcinoma Through Multi-Omics: Targeting SMAD3-Mediated NOTCH Signaling in the Tumor Microenvironment.
    Bi-Tian Zhang, Xiaoyu Song, Chi-Shing William Cho, Chun-Kwok Wong, Dongjie Wang.
       OBJECTIVE: Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality, particularly in advanced stages. This study investigates the anticancer mechanisms of calycosin, an isoflavonoid derived from Astragalus membranaceus, in LUAD.
    METHODS: Using integrative approaches including bulk and single-cell RNA sequencing, network pharmacology, and molecular docking, we identified SMAD3 as a critical biomarker associated with LUAD staging and prognosis.
    RESULTS: Calycosin targets SMAD3, modulating the NOTCH signaling pathway in monocytes/macrophages to suppress tumor growth, invasion, and immune evasion. Enrichment analyses revealed significant involvement of NOTCH signaling components in SMAD3-correlated genes, particularly in advanced-stage LUAD. Single-cell RNA sequencing further demonstrated NOTCH pathway enrichment in tumor-associated monocytes/macrophages. Additionally, KMT2A was identified as a key transcriptional regulator in these cells.
    CONCLUSIONS: These findings highlight the potential effects of calycosin and provide novel insights into targeting the tumor-immune microenvironment in LUAD.
    Keywords:  KMT2A; LUAD; NOTCH signaling; SMAD3; calycosin; macrophages; monocytes
    DOI:  https://doi.org/10.3390/cancers17091455
  50. Discov Oncol. 2025 May 16. 16(1): 785
    Sialyltransferase gene signature as a predictor of prognosis and therapeutic response in kidney renal clear cell carcinoma.
    Huiyu Liu, Changwei Zhou, Zaichun Yan, Hairong Yang, Yun Zhao, Rui Tian, Xuejun Bo, Leizuo Zhao, Wei Ren.
       BACKGROUND: Sialyltransferases are enzymes involved in the addition of sialic acid to glycoproteins and glycolipids, influencing various physiological and pathological processes. The expression and function of sialyltransferases in tumors, particularly in kidney renal clear cell carcinoma (KIRC) remained underexplored. This study aimed to develop a prognostic model based on sialyltransferase-related genes (SRGs) to predict the prognosis and treatment response of patients with KIRC.
    METHODS: We utilized RNA-Seq data of KIRC from The Cancer Genome Atlas (TCGA) database, selecting samples with survival data and clinical outcomes. Somatic mutation and neoantigen data were analyzed using the "maftools" package, and genes involved in the sialylation process were identified through the Molecular Signatures Database. Validation cohorts of KIRC samples were obtained from the International Cancer Genome Consortium (ICGC) database. Single-cell RNA sequencing (scRNA-seq) data were downloaded from the Gene Expression Omnibus (GEO) platform, and preprocessing, normalization, and dimensionality reduction analyses were conducted using the "Seurat" package. Differentially expressed sialylation genes were identified using the "limma" package, and their functional enrichment was assessed via Gene Ontology GO and KEGG analyses. Consensus clustering analysis was performed to identify molecular subtypes of KIRC based on sialylation, and drug sensitivity of different subtypes was evaluated using the "pRRophetic" package. A risk signature model comprising 5 SRGs was constructed through univariate and multivariate Cox regression analyses and validated in both the TCGA and ICGC cohorts. The "estimate" package was utilized to calculate immune and stromal scores for each KIRC sample, assessing the tumor immune microenvironment characteristics of different subtypes.
    RESULTS: Analysis of scRNA-seq data identified 25 cell subtypes, categorized into 9 cell types. CD4 + memory cells exhibited the highest potential interactions with other cell subtypes. We identified 14 differentially expressed sialylation genes and confirmed their enrichment in various biological pathways through GO and KEGG analyses. Consensus clustering analysis based on sialylation identified 2 molecular subtypes: C1 and C2. The C2 subtype demonstrated higher sialylation scores and poorer prognosis. Drug sensitivity analysis indicated that the C1 subtype had better responses to Dasatinib and Lapatinib, whereas the C2 subtype was more sensitive to Epothilone B and Vinorelbine. The risk signature model, constructed with five distinct SRGs, exhibited strong predictive accuracy, as indicated by Area Under the Curve (AUC) values of 0.68, 0.69, and 0.70 for 1-, 3-, and 5-year survival, respectively, across both the TCGA and ICGC validation cohorts. Immune microenvironment analysis revealed that the C1 subtype exhibited higher immune and stromal scores, while the C2 subtype showed significantly enhanced expression of immune checkpoint genes.
    CONCLUSION: This study successfully developed a prognostic model based on SRGs, effectively predicting the prognosis and drug response of KIRC patients. The model demonstrated significant predictive performance and potential clinical application value. Furthermore, the study highlighted the critical role of sialylation in KIRC, offering new insights into its underlying mechanisms in tumor biology. These findings could guide personalized treatment strategies for KIRC patients, emphasizing the importance of sialylation in cancer prognosis and therapy.
    Keywords:  Biomarker; Immunotherapy; Kidney renal clear cell carcinoma; Prognostic signature; Sialyltransferase
    DOI:  https://doi.org/10.1007/s12672-025-02566-4
  51. Methods Mol Biol. 2025 ;2916 179-188
    Quantitative Analysis of Tomato Flower Pedicel Abscission and Single-Cell Transcriptome Analysis.
    Tao Xu, Lina Cheng, Ruizhen Li, Cai-Zhong Jiang.
      Plant organ abscission is a highly organized biological process in response to developmental and environmental cues. The understanding of the regulation of abscission is of great importance for the improvement of crop productivity and quality. The abscission process can be quantitatively analyzed by investigating the abscission of the tomato flower pedicel of different genotypes at a specific period. Single-cell transcriptomics is a novel approach to dissect the characteristics of pedicel abscission zone cells. In this chapter, we provide a detailed description of an abscission assay of flower pedicel explants and the method of single-cell transcriptome sequencing, including sample preparation, data determination, and analysis.
    Keywords:  Abscission; Single-cell transcriptome; Tomato flower pedicel
    DOI:  https://doi.org/10.1007/978-1-0716-4470-6_16
  52. Aging Cell. 2025 May 15. e70095
    Microglia Single-Cell RNA-Seq Enables Robust and Applicable Markers of Biological Aging.
    Natalie Stanley, Luvna Dhawka, Sneha Jaikumar, Yu-Chen Huang, Anthony S Zannas.
      "Biological aging clocks"-composite molecular markers thought to capture an individual's biological age-have been traditionally developed through bulk-level analyses of mixed cells and tissues. However, recent evidence highlights the importance of gaining single-cell-level insights into the aging process. Microglia are key immune cells in the brain shown to adapt functionally in aging and disease. Recent studies have generated single-cell RNA-sequencing (scRNA-seq) datasets that transcriptionally profile microglia during aging and development. Leveraging such datasets in humans and mice, we develop and compare computational approaches for generating transcriptome-wide summaries from microglia to establish robust and applicable aging clocks. Our results reveal that unsupervised, frequency-based summarization approaches, which encode distributions of cells across molecular subtypes, strike a balance in accuracy, interpretability, and computational efficiency. Notably, our computationally derived microglia markers achieve strong accuracy in predicting chronological age across three diverse single-cell datasets, suggesting that microglia exhibit characteristic changes in gene expression during aging and development that can be computationally summarized to create robust markers of biological aging. We further extrapolate and demonstrate the applicability of single-cell-based microglia clocks to readily available bulk RNA-seq data with an environmental input (early life stress), indicating the potential for broad utility of our models across genomic modalities and for testing hypotheses about how environmental inputs affect brain age. Such single-cell-derived markers can yield insights into the determinants of brain aging, ultimately promoting interventions that beneficially modulate health and disease trajectories.
    Keywords:  markers of biological aging; microglia; single‐cell RNA sequencing; transcriptomics
    DOI:  https://doi.org/10.1111/acel.70095
  53. J Adv Res. 2025 May 13. pii: S2090-1232(25)00351-0. [Epub ahead of print]
    Targeting mesenchymal monocyte-derived macrophages to enhance the sensitivity of glioblastoma to temozolomide by inhibiting TNF/CELSR2/p65/Kla-HDAC1/EPAS1 axis.
    Wei Gao, Xinmiao Long, Xiang Lin, Kun Deng, Danyang Li, Meng Huang, Xiangyu Wang, Qing Liu, Minghua Wu.
       INTRODUCTION: Temozolomide (TMZ) resistance poses a significant challenge to the treatment of aggressive and highly lethal glioblastomas (GBM). Monocyte-derived Macrophages (MDM) within the tumor microenvironment are key factors contributing to TMZ resistance in GBM. Lactate-mediated histone lysine lactylation (Kla) plays a crucial role in the regulation of tumor progression. However, the mechanism through which MDM-induced Kla expression promotes TMZ resistance in GBM remains unclear.
    OBJECTIVES: The objective of this study s to identify a subtype of MDM with therapeutic potential target and to elucidate the mechanisms through which this subtype of MDM contributes to tumor malignant progression and TMZ resistance.
    METHODS: We integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics data to evaluate whether mesenchymal (MES) MDM is associated with poor prognosis. By establishing a subtype model of GBM cells for the first time, we validated the mechanism by which MES-MDM promotes subtype conversion of tumor cells. Using patient-derived GBM organoids and an intracranial orthotopic GBM model, we demonstrated that targeting MES-MDMs increased GBM sensitivity to TMZ treatment.
    RESULTS: We identified a novel MDM subtype, MES-MDM, in the hypoxic niches of the perinecrotic region characterized by high TREM1 expression, which fueled GBM progression. Hypoxia drived MES-MDM signatures by activating ATF3 transcription. MES-MDM facilitated the transition from the NPC to the MES subtype in GBM cells, in which Histone Deacetylase 1 (HDAC1) Kla, induced by the TNF-CELSR2/p65 signaling pathway, promoted this conversion, thereby promoting TMZ resistance. Targeting MES-MDM with TREM1 inhibitory peptides amplified TMZ sensitivity, offering a potential strategy for overcoming resistance to therapy in GBM. Targeting TREM1 enhanced the effectiveness of anti-PD-1 immunotherapy.
    CONCLUSION: This study provides a potential therapeutic strategy for patients with MES-subtype GBM by targeting MES-MDMs in combination with TMZ or PD-1 antibody treatment.
    Keywords:  Glioblastoma; Hypoxia; Lactylation; Monocyte-derived macrophages; Temozolomide resistance
    DOI:  https://doi.org/10.1016/j.jare.2025.05.032
  54. J Physiol Pharmacol. 2025 Apr;76(2):
    Deciphering the role of pyroptosis-related genes and natural killer T cells in sepsis pathogenesis: a comprehensive bioinformatics and Mendelian randomization analysis.
    L Zhou, W Dong, Y Liu.
      Pyroptosis is increasingly recognized as crucial in sepsis development, but the specific roles of pyroptosis-related genes (PRGs) in sepsis remain underexplored. Gene expression profiles of sepsis and control samples were retrieved from the Gene Expression Omnibus (GEO) database for analysis (GSE57065, GSE95233). Differentially expressed genes (DEGs) were identified, followed by functional enrichment analysis. Weighted gene co-expression network analysis (WGCNA) was employed to identify genes associated with sepsis, with intersecting DEGs and PRGs highlighted via Venn diagrams. Hub genes were further analyzed across both the training and validation datasets (GSE65682) for differential expression, receiver operating characteristic (ROC) analysis, correlation analysis, and Kaplan-Meier (KM) survival analysis. Immune cell infiltration was evaluated in both datasets using the single-sample gene set enrichment analysis (ssGSEA) algorithm. Machine learning approaches were applied to identify critical immune cell types involved in sepsis regulation, which were subsequently correlated with the hub genes. Single-cell RNA sequencing (scRNA-seq) analysis of sepsis samples was conducted using the GSE167363 dataset. Finally, Mendelian randomization (MR) was utilized to investigate causal relationships between exposures and outcomes. In results eight hub PRGs were identified, including NLRC4, PLCG1, TP53, AIM2, GZMB, GZMA, ELANE, and CASP5. Functional enrichment analysis implicated dysregulated immune responses in sepsis progression, aligning with established pathophysiological mechanisms. These eight key genes exhibited consistent expression patterns. Several genes (NLRC4, PLCG1, AIM2, GZMB, and ELANE) emerged as promising diagnostic biomarkers (AUC>0.85). Machine learning revealed that 15 immune cell types may play important roles in sepsis. Correlation analysis indicated a positive relationship between granzyme B (GZMB) and natural killer T (NKT) cells, a finding further corroborated by scRNA-seq analysis. In the validation cohort, GZMB and ELANE were linked to patient prognosis (p<0.05). MR analysis using the inverse variance weighting (IVW) method demonstrated a positive causal relationship between GZMB and NKT cells (OR=1.063, 95% CI=1.013-1.115, p=0.013). Moreover, elevated NKT cell levels were associated with a reduced risk of sepsis (OR=0.977, 95% CI=0.955-1.000, p=0.046), and NKT cells served as protective factors for 28-day mortality in sepsis (OR=0.938, 95% CI=0.881-0.997, p=0.040). This study provides a comprehensive analysis of the roles of PRGs and NKT cells in sepsis, offering valuable insights for diagnostic and therapeutic approaches in sepsis immunotherapy.
    DOI:  https://doi.org/10.26402/jpp.2025.2.10
  55. Cell Biosci. 2025 May 15. 15(1): 60
    Characterization and prognostic of CD8 + TIM3 + CD101 + T cells in glioblastoma multiforme.
    Hong-Liang Wang, Sai Li, Chun-Chun Ma, Xiang-Hu Zheng, Hao-Yuan Wu, Chen-Xi Chang, Zhi-Hao Yang, Jia-Wei Wang, Fa-Ming Pan, Bing Zhao.
       BACKGROUND: Glioblastoma multiforme (GBM) is a pervasive and aggressive malignant brain tumor. In the tumor immune microenvironment, CD8 + TIM3 + CD101 + T cells (CCT cells) play a pivotal role in tumor progression and immune evasion. This study aimed to characterize differentially expressed genes (DEGs) in CCT cells, establish a prognostic model for GBM, and explore clinical implications.
    METHODS: Analysis of data from TCGA, CGGA, and GEO databases included whole-genome expression profiles, clinical data, single nucleotide mutations, and single-cell RNA sequencing. DEGs were identified, and cell trajectories were constructed using Seurat, Monocle 2, and CellChat packages. Functional enrichment analysis was conducted with clusterProfiler, and a prognostic model was developed. Immune infiltration and drug sensitivity analyses were performed to evaluate therapeutic implications.
    RESULTS: Eight distinct cell types were distinguished, encompassing T cells, macrophages, neurons, mural cells, endothelial cells, oligodendrocytes, fibroblasts, and B cells. Comparative analysis revealed differences in these cell types between GBM samples with new adjuvant therapy and initial diagnosis controls. Pseudotime analysis indicated CD8 + TIM3 + CD101-T cells as precursors to CCT cells, unveiling unique gene expression patterns during this transition. The prognostic model, incorporating 22 gene features via LASSO regression, demonstrated strong predictive ability through Receiver Operating Characteristic (ROC) curves. Analysis of 28 immune cell types revealed differences between high-risk and low-risk groups, providing insights into GBM's immune evasion mechanisms. Drug sensitivity analysis proposed potential therapeutic strategies for high-risk patients.
    CONCLUSION: This study offers an in-depth understanding of CCT cells in GBM, introducing a novel prognostic model and suggesting promising therapeutic approaches.
    Keywords:  CD8 + TIM3 + CD101 + T cells; Glioblastoma multiforme; Immune microenvironment; Prognostic model; Single- cell RNA sequencing
    DOI:  https://doi.org/10.1186/s13578-025-01390-1
  56. Front Oncol. 2025 ;15 1560954
    Single-cell transcriptomics and functional validation revealed PLEKHA5-L as a promoter of growth and migration in brain metastatic melanoma cells.
    Xiaogen Tang, Tingting Lei, Boya Huang, Guangjie Wu, Yizhen Tian, Jian Xiang, Dongwei Fu, Hongyi Zhang.
       Background: Melanoma brain metastasis is an lethal event. Investigating the molecules that potentially promoted melanoma metastasis is important for targeted therapy.
    Methods: The transcriptional profiles of totaling 7 melanoma samples, including 4 primary and 3 brain metastatic tissues were studied on the single-cell RNA sequencing level, and the expression of PLEKHA5 was examined in tumor clusters. Then PLEKHA5 expression was validated in brain Metastatic model by left ventricular injections in nude mice. The functional effect of PLEKHA5 isoforms (Long or Short) on proliferation and migration of melanoma was studied by RNA interference, overexpression by lentivirus vector, CCK8 test, colony formation test, transwell chamber assay. The targets and signal pathways that was potentially regulated by PLEKHA5 was studied by RNA-sequencing.
    Result: PLEKHA5 expression increased in brain metastatic melanoma at single cell level. PLEKH5 was constantly upregulated in brain metastatic tissue of melanoma in animal model. PLEKHA5-L had the potential for melanoma migration and proliferation by upregulating oncogenes such as HRAS, AKT3 etc. PLEKHA5-L also upregulated expression of PD-L1 and ABC transporters that were associated with therapy resistant.
    Conclusion: PLEKHA5-L was potential therapeutic target for metastatic melanoma.
    Keywords:  PLEKHA-L; PLEKHA5; brain metastasis; melanoma; single-cell RNA sequencing
    DOI:  https://doi.org/10.3389/fonc.2025.1560954
  57. Biomol Biomed. 2025 May 08.
    WFDC3 identified as a prognostic and immune biomarker in pancreatic cancer.
    Bohan Liu, Xuqing Shi, Tianqi Liu, Huanwen Wu, Zhiyong Liang.
      The whey acidic protein four-disulfide core (WFDC) family comprises key modulators of tumor initiation and progression, offering significant potential for diagnostic, prognostic, and therapeutic applications. However, the specific role of WFDCs in the oncogenesis of pancreatic cancer (pancreatic adenocarcinoma [PAAD]) remains incompletely understood. To address this, we conducted an initial investigation using comprehensive bioinformatic analyses to evaluate WFDCs expression patterns across multiple tumor types, with a focus on PAAD. Bulk and single-cell RNA sequencing datasets from the TCGA and GEO repositories were analyzed to assess WFDC3 expression in PAAD tissues. Kaplan-Meier survival analysis was employed to determine the prognostic significance of WFDC3. To explore its biological functions and underlying mechanisms, we performed functional enrichment analyses in combination with immune infiltration assessments. Experimental validation included CCK-8 and EdU proliferation assays, transwell migration and invasion tests, immunofluorescence staining, flow cytometry, LDH release assays, Western blotting, and quantitative reverse transcription PCR. A LASSO regression model was also developed to predict PAAD outcomes. Our findings reveal that WFDCs exhibit context-dependent roles in tumor progression. Specifically, WFDC3 expression was significantly elevated in PAAD and associated with poorer patient prognosis. Functionally, WFDC3 promoted PAAD cell metastasis by inducing epithelial-mesenchymal transition and contributed to immune evasion by suppressing T cell cytotoxicity. In conclusion, our study identifies WFDC3 as a pro-oncogenic factor in PAAD progression, highlighting its potential as both a prognostic biomarker and a therapeutic target for regulating metastasis and immune responses in this malignancy.
    DOI:  https://doi.org/10.17305/bb.2025.12444
  58. Int J Genomics. 2025 ;2025 6454413
    Decoding the Tumor Microenvironment of Myoepithelial Cells in Triple-Negative Breast Cancer Through Single-Cell and Transcriptomic Sequencing and Establishing a Prognostic Model Based on Key Myoepithelial Cell Genes.
    Xiaocheng Yu, Ye Tian, Rui Zhang, Yong Yang.
      Background: Triple-negative breast cancer (TNBC) is an aggressive subtype with high malignancy, rapid progression, and a poor 5-year survival rate of ~77%. Due to the lack of targeted therapies, treatment options are limited, highlighting the urgent need for novel therapeutic strategies. Myoepithelial cells (MECs) in the tumor microenvironment may significantly influence TNBC development and progression. Methods: This study used single-cell RNA sequencing to compare the MEC gene expression in the normal versus TNBC tissues. TNBC-associated MECs showed increased expression of proliferation- and immune-related genes (e.g., FDCSP, KRT14, and KRT17) and decreased expression of inflammatory and extracellular matrix-related genes (e.g., CXCL8, SRGN, and DCN). Copy number variation and pseudotime analyses revealed genomic alterations and phenotypic dynamics in MECs. A CoxBoost-based prognostic model was developed and validated across 20 survival cohorts, integrating immune profiling, pathway enrichment, and drug sensitivity analyses. Mendelian randomization identified TPD52 as a TNBC risk-associated gene. siRNA knockdown of TPD52 was performed in TNBC cell lines to evaluate its effects on proliferation and migration. Results: TNBC MECs displayed significant changes in the gene expression and genomic integrity, impacting immune responses and tumor invasion. The prognostic model effectively predicted 1-, 3-, and 5-year survival outcomes, stratifying high-risk patients with enriched cell cycle and DNA replication pathways, reduced immune checkpoint expression, and chemotherapy resistance. TPD52 was identified as a tumor-promoting gene, and its knockdown suppressed TNBC cell proliferation and migration. Conclusion: This study highlights MECs' role in TNBC progression, provides a CoxBoost prognostic model for personalized treatment, and identifies TPD52 as a potential therapeutic target for TNBC intervention.
    Keywords:  TNBC; myoepithelial cells; prognosis
    DOI:  https://doi.org/10.1155/ijog/6454413
  59. Front Immunol. 2025 ;16 1534611
    An immune cell activation signature reflected hepatocellular carcinoma heterogeneity and predicted clinical outcomes.
    Xiaofeng Wang, Dongli Liu, Shuai Wang, Rui He.
       Background: The prognosis of hepatocellular carcinoma (HCC) remains challenging, and immune activation plays a critical role in cancer treatment. Identifying reliable immune activation-related prognostic markers is critical for predicting HCC patient outcomes.
    Method: A six-gene signature was developed. The prognostic value was assessed by correlating the signature and survival. The robustness of the signature was validated in three independent Gene Expression Omnibus (GEO) datasets. Associations with clinical, genomic, and transcriptomic features were also evaluated. Additionally, single-cell sequencing data were analyzed to explore cell-cell interaction heterogeneity reflected by the signature. The biological role of candidate gene RORC was investigated, including chemotherapy resistance and detailed regulatory mechanism in affecting progression. The clinical potential role of RORC and its downstream gene was also evaluated by immunohistochemical (IHC) microarray.
    Results: The six-gene signature stratified patients into high-risk and low-risk groups, with high-risk samples exhibiting significantly shorter overall survival (median: 23.8 months, 95% CI: 20.6-41.8) than low-risk samples (median: 83.2 months, 95% CI: 69.6-NA, p < 0.001). Validation in independent GEO datasets confirmed the robustness of the signature. The signature was significantly associated with the pathological stage and negatively correlated with PD-L1 expression, outperforming clinical indicators in predicting 3-year survival. The signature was significantly associated with TP53 mutations, genomic stability, and canonical cancer-related pathways. Single-cell sequencing data indicated that the signature revealed cell-cell interaction heterogeneity in HCC. Candidate gene RORC promotes proliferation and migration by regulating CDC6 gene expression as a transcription factor. Furthermore, RORC is also associated with multiple drug resistance, especially docetaxel and paclitaxel. IHC revealed that RORC and candidate gene CDC6 were valuable predictive biomarkers for prognosis.
    Conclusion: The six-gene signature provides valuable insights into the biological status of HCC patients and is a robust tool for clinical application.
    Keywords:  HCC; immune cell activation; microenvironment; prognosis; single-cell sequencing
    DOI:  https://doi.org/10.3389/fimmu.2025.1534611
  60. Respir Res. 2025 May 10. 26(1): 179
    Thioredoxin: a key factor in cold tumor formation and a promising biomarker for immunotherapy resistance in NSCLC.
    Jiayi Hu, Yilimunuer Abulimiti, Haiyang Wang, Dianyu Yang, Xu Wang, Yang Wang, Ping Ji.
      Immune checkpoint blockade (ICB) therapy has shown promising clinical efficacy in cancer treatment, but only a subset of patients experience significant therapeutic responses. Tumor cells respond to internal and external stresses, such as hypoxia and nutrient deprivation, by activating the unfolded protein response (UPR) in the tumor microenvironment. This response helps maintain homeostasis, promoting malignant progression, chemotherapy resistance, and immune escape. In this study, single-cell RNA sequencing (scRNA-seq) data from non-small cell lung cancer (NSCLC) patients treated with ICB revealed upregulation of thioredoxin (TXN) expression in the epithelial tissues of LUAD (lung adenocarcinoma) and LUSC (lung squamous cell carcinoma) patients with minimal pathological remission. High TXN expression was also associated with "cold tumors," characterized by a lack of T cells and low levels of chemokine receptors and immunomodulators. Experimental results showed that TXN was highly expressed in NSCLC tissues, and its knockdown significantly inhibited the proliferation and migration of A549 and SK-MES-1 cells. Furthermore, TXN knockdown enhanced T-cell-mediated cytotoxicity against these tumor cells, suggesting that TXN contributes to immune escape in NSCLC by promoting tumor cell proliferation and migration while inhibiting immune killing. Notably, TXN knockdown also upregulated CD40 expression, indicating that TXN may regulate immune escape in lung cancer through CD40 modulation.
    Keywords:  Immune checkpoint Blockade (ICB) therapy; NSCLC; Thioredoxin (TXN)
    DOI:  https://doi.org/10.1186/s12931-025-03259-w
  61. Eur J Pharmacol. 2025 May 13. pii: S0014-2999(25)00484-4. [Epub ahead of print] 177730
    Immune-endothelial cell crosstalk in hepatic endothelial injury of liver fibrotic mice.
    Xue Fan, Qianhui Tang, Ninglin Xia, Jiwei Wang, Wen Zhao, Ming Jin, Qian Lu, Jinyu Hu, Rongmi Zhang, Luyong Zhang, Zhenzhou Jiang, Qinwei Yu.
       INTRODUCTION: Liver fibrosis is a common pathological process in chronic liver disease, reflecting the advanced stage of the disease. Liver endothelial cells (ECs), especially liver sinusoidal endothelial cells (LSECs), are recognized as critical modulators of liver homeostasis and play essential roles in the recruitment and function of liver immune cells. In this study, we aimed to explore the mechanism of hepatic EC injury and the potential regulatory pathways of intercellular communication in liver fibrosis.
    METHODS: In this study, C57BL/6 male mice were treated with CCl4 for 6 weeks to establish a liver fibrosis model. Masson staining and immunohistochemistry were performed to assess the extent of liver fibrosis. Hepatic endothelial injury was detected by using scanning electron microscopy (SEM) and PCR technology. Single-cell RNA sequencing (scRNA-seq) was performed to analyze phenotypic changes in nonparenchymal cells and dissect intercellular crosstalk.
    RESULTS: A total of 24,534 cells were clustered into 10 main cell subsets. The LSEC fenestrae and surface receptor expression were reduced, and the expression of Cd34 was upregulated. Liver ECs exhibited dense cellular crosstalk with immune cells (macrophages, T and B cells). The analysis of intercellular signaling pathways revealed that immune cells targeted liver ECs through the Ptprc-Mrc1 and Sell-Podxl signaling pathways to maintain cellular interactions during liver fibrosis.
    CONCLUSION: We revealed apparent damage and capillarization of liver ECs and demonstrated the cell-cell communications among liver immune cells and ECs during the development of liver fibrosis. The Ptprc-Mrc1 and Sell-Podxl signaling pathways exerted prominent roles in liver immune cell-EC interactions.
    Keywords:  Cell-cell crosstalk; Hepatic fibrosis; Immune cells; Liver endothelial cells; Single-cell RNA sequencing
    DOI:  https://doi.org/10.1016/j.ejphar.2025.177730
  62. Neurobiol Dis. 2025 May 08. pii: S0969-9961(25)00151-2. [Epub ahead of print]211 106935
    An analysis of prognostic risk and immunotherapy response of glioblastoma patients based on single-cell landscape and nitrogen metabolism.
    Minfeng Tong, Zhijian Xu, Lude Wang, Huahui Chen, Xing Wan, Hu Xu, Song Yang, Qi Tu.
      Glioblastoma (GBM) is a highly invasive brain tumor of astrocytic origin. Nitrogen metabolism plays an instrumental role in the growth and progression of various tumors, including GBM. This study intended to mine nitrogen metabolism-related biomarkers for GBM-related research of prognosis and immunotherapy. Through single-cell data analysis of GBM, we identified four cell types (Astrocytes, Macrophages, Fibroblasts, and Endothelial cells). We calculated the nitrogen metabolism scores and conducted trajectory analysis for the most abundant cells, Astrocytes, revealing 6 differentiation directions of Astrocytes, which included the main differentiation direction from cells with low nitrogen metabolism scores to cells with high nitrogen metabolism scores. Furthermore, based on the differentially expressed genes (DEGs) with high/low nitrogen metabolism scores, we constructed a 7-gene prognostic model by utilizing regression analysis. qRT-PCR analysis showed that IGFBP2, CHPF, CTSZ, UPP1, TCF12, ZBTB20 and RBP1 were all significantly up-regulated in the GBM cells. Through differential analysis, a protein-protein interaction (PPI) network, and enrichment analyses, we identified and analyzed the DEGs in the high RiskScore subgroup, revealing complex interactions among DEGs, which were mainly related to pathways such as TNF signaling pathway and NF-κB signaling pathway. By leveraging univariate analysis, survival-related genes were selected from the nitrogen metabolism-related gene sets. Clustering, survival, immune, and mutation analyses manifested that the collected nitrogen metabolism-related genes had good classification performance, presenting notable differences in survival rates, immune levels, gene mutations, and sensitivity to drugs between cluster1 and cluster2. In conclusion, the project investigated the prognosis and classification value of nitrogen metabolism-related genes in GBM from multiple perspectives, predicting the sensitivity of different subtypes of patients to immunotherapy response and drug sensitivity. These findings are expected to show new research directions for further exploration in these fields.
    Keywords:  Glioblastoma; Immune infiltration; Nitrogen metabolism; Prognostic model; Single cell; Subtype
    DOI:  https://doi.org/10.1016/j.nbd.2025.106935
  63. Front Mol Biosci. 2025 ;12 1582181
    Unraveling the role of histone acetylation in sepsis biomarker discovery.
    Feng Cheng, Juxin Deng, Zhaoyang Du, Lei Li, Zhaolei Qiu, Min Zhu, Hongchang Zhao, Zhenjie Wang.
       Introduction: Sepsis is a life-threatening condition caused by a dysregulated immune response to infection. Despite advances in clinical care, effective biomarkers for early diagnosis and prognosis remain lacking. Emerging evidence suggests that histone acetylation plays a crucial role in the pathophysiology of sepsis.
    Methods: Transcriptomic and single-cell RNA sequencing data were used to identify histone acetylation-related genes. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed, followed by machine learning algorithms (LASSO, SVM-RFE, and Boruta) to screen for potential biomarkers. Mendelian randomization (MR), RT-qPCR, and functional assays were conducted for validation.
    Results: BLOC1S1, NDUFA1, and SFT2D1 were identified as key biomarkers. A predictive nomogram demonstrated strong diagnostic potential. Immune infiltration and single-cell analyses linked the biomarkers to macrophage activity. MR analysis confirmed SFT2D1 as a causal factor in sepsis. Functional assays showed that knockdown of SFT2D1 suppressed CXCL10 and IL-6 expression, indicating its pro-inflammatory role.
    Discussion: This study identifies novel biomarkers associated with histone acetylation and immune dysregulation in sepsis. These findings deepen our understanding of sepsis pathogenesis and may facilitate the development of improved diagnostic and therapeutic strategies.
    Keywords:  Mendelian randomization; biomarkers; histone acetylation; sepsis; single-cell RNA sequencing
    DOI:  https://doi.org/10.3389/fmolb.2025.1582181
  64. Cell Prolif. 2025 May 15. e70062
    Deciphering the Immunomodulatory Function of GSN+ Inflammatory Cancer-Associated Fibroblasts in Renal Cell Carcinoma Immunotherapy: Insights From Pan-Cancer Single-Cell Landscape and Spatial Transcriptomics Analysis.
    Shan Li, Xinwei Zhou, Haoqian Feng, Kangbo Huang, Minyu Chen, Mingjie Lin, Hansen Lin, Zebing Deng, Yuhang Chen, Wuyuan Liao, Zhengkun Zhang, Jinwei Chen, Bohong Guan, Tian Su, Zihao Feng, Guannan Shu, Anze Yu, Yihui Pan, Liangmin Fu.
      The heterogeneity of cancer-associated fibroblasts (CAFs) could affect the response to immune checkpoint inhibitor (ICI) therapy. However, limited studies have investigated the role of inflammatory CAFs (iCAFs) in ICI therapy using pan-cancer single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics sequencing (ST-seq) analysis. We performed pan-cancer scRNA-seq and ST-seq analyses to identify the subtype of GSN+ iCAFs, exploring its spatial distribution characteristics in the context of ICI therapy. The pan-cancer scRNA-seq and bulk RNA-seq data are incorporated to develop the Caf.Sig model, which predicts ICI response based on CAF gene signatures and machine learning approaches. Comprehensive scRNA-seq analysis, along with in vivo and in vitro experiments, investigates the mechanisms by which GSN+ iCAFs influence ICI efficacy. The Caf.Sig model demonstrates well performances in predicting ICI therapy response in pan-cancer patients. A higher proportion of GSN+ iCAFs is observed in ICI non-responders compared to responders in the pan-cancer landscape and clear cell renal cell carcinoma (ccRCC). Using real-world immunotherapy data, the Caf.Sig model accurately predicts ICI response in pan-cancer, potentially linked to interactions between GSN+ iCAFs and CD8+ Tex cells. ST-seq analysis confirms that interactions and cellular distances between GSN+ iCAFs and CD8+ exhausted T (Tex) cells impact ICI efficacy. In a co-culture system of primary CAFs, primary tumour cells and CD8+ T cells, downregulation of GSN on CAFs drives CD8+ T cells towards a dysfunctional state in ccRCC. In a subcutaneously tumour-grafted mouse model, combining GSN overexpression with ICI treatment achieves optimal efficacy in ccRCC. Our study provides the Caf.Sig model as an outperforming approach for patient selection of ICI therapy, and advances our understanding of CAF biology and suggests potential therapeutic strategies for upregulating GSN in CAFs in cancer immunotherapy.
    Keywords:  cancer‐associated fibroblasts; clear cell renal cell carcinoma; immune checkpoint inhibitors; machine learning; multi‐omics analysis; pan‐cancer analysis
    DOI:  https://doi.org/10.1111/cpr.70062
  65. Cancer Immunol Immunother. 2025 May 15. 74(7): 204
    ARHGDIB as a prognostic biomarker and modulator of the immunosuppressive microenvironment in glioma.
    Xuejun Yan, Rongnian Li, Jing Xu, Hua Liu, Minmin He, Xingjun Jiang, Caiping Ren, Quanwei Zhou.
       BACKGROUND: Glioma, a prevalent malignant intracranial tumor, exhibits limited therapeutic efficacy due to its immunosuppressive microenvironment, leading to a poor prognosis for patients. ARHGDIB is implicated in the remodeling of the tumor microenvironment and plays a significant role in the pathogenesis of various tumors. However, its regulatory effect within the immune microenvironment of glioma remains unclear.
    METHODS: The mRNA expression pattern of ARHGDIB was analyzed using public databases, and its expression was further validated in our collected cohort through quantitative PCR (qPCR) and immunohistochemistry (IHC). Kaplan-Meier survival analysis and LASSO-Cox regression were employed to ascertain the clinical significance of ARHGDIB in glioma. Subsequently, we systematically evaluated the association between ARHGDIB expression and immune characteristics within the glioma microenvironment, as well as its potential to predict treatment response in glioma. Additionally, in vitro experiments were conducted to elucidate the role of ARHGDIB in remodeling the glioma microenvironment and promoting tumor malignancy progression.
    RESULTS: Combined with bioinformatics analysis of public databases and validation with qPCR and IHC on our cohort, our findings indicate that ARHGDIB is markedly overexpressed in glioma and correlates with poor patient prognosis, thereby serving as a potential biomarker for adverse outcomes in glioma. Functional enrichment and immune infiltration analyses reveal that ARHGDIB is implicated in the recruitment of immunosuppressive cells, such as M2 macrophages and neutrophils, contributing to the alteration of the glioma immunosuppressive microenvironment and hindering the immune response. Further investigations through single-cell sequencing, immunohistochemistry, immunofluorescence, and in vitro experiments demonstrate that ARHGDIB exhibits an expression pattern akin to CD163, with its overexpression inducing M2 macrophage polarization and facilitating glioma cell proliferation and migration.
    CONCLUSIONS: ARHGDIB emerges as a novel marker for tumor-associated macrophages, playing a crucial role in shaping the immunosuppressive microenvironment and representing a promising prognostic biomarker for glioma.
    Keywords:  ARHGDIB; Glioma; Immunosuppressive microenvironment; Prognosis; Tumor-associated macrophages
    DOI:  https://doi.org/10.1007/s00262-025-04063-7
  66. Front Med (Lausanne). 2025 ;12 1528434
    Uncovering potential biomarkers of endometriosis: transcriptomic and single-cell analysis.
    Yuqiu Liu, Guanwen Gao, Wei Tian, Qingfeng Lv, Degao Liu, Changzhong Li.
       Background: The link between programmed cell death (PCD) and mitochondria has been documented in various diseases. However, its role in endometriosis (EMS) remains unexplored. This study aims to identify potential biomarkers in EMS associated with both PCD and mitochondrial functions.
    Methods: This analysis incorporates datasets related to EMS, PCD-related genes (PCD-RGs), and mitochondria-related genes (MRGs) sourced from public repositories. To uncover potential biomarkers, differential expression analysis, weighted gene co-expression network analysis (WGCNA), Boruta feature selection, expression validation, and diagnostic assessments were conducted. Functional analyses, immune infiltration profiling, and the construction of regulatory networks further elucidated the mechanisms through which these biomarkers may influence EMS. Finally, single-cell data were leveraged to examine the expression and functionality of these biomarkers at a granular level.
    Results: Apoptosis-inducing factor mitochondria-associated 1 (AIFM1) and pyruvate dehydrogenase kinase 4 (PDK4) were identified as potential biomarkers, with PDK4 upregulated and AIFM1 downregulated in EMS. Both genes demonstrated strong diagnostic potential. Enrichment analyses indicated their involvement in pathways associated with the cell cycle. Immune infiltration analyses revealed that AIFM1 had a significant positive correlation with resting dendritic cells and a negative correlation with M2 macrophages, whereas PDK4 was positively associated with M2 macrophages and inversely related to follicular helper T cells. Moreover, AIFM1 and PDK4 were regulated by 16 miRNAs (e.g., hsa-mir-16-5p) and 18 lncRNAs (e.g., LINC00294). Single-cell analysis further revealed dynamic expression trends of these potential biomarkers across cell differentiation stages, including gametocytes, monocytes, mesenchymal stem cells, and neutrophils.
    Conclusion: In this study, potential biomarkers (AIFM1 and PDK4) related to PCD and mitochondria were identified in EMS, offering valuable insights for the diagnosis and therapeutic strategies for the disease.
    Keywords:  AIFM1; PDK4; endometriosis; mitochondria; programmed cell death; single-cell
    DOI:  https://doi.org/10.3389/fmed.2025.1528434
  67. J Virol. 2025 May 14. e0230824
    Dissection of the global responses of mandarin fish pyloric cecum to an acute ranavirus (MRV) infection reveals the formation of serositis and then ascites.
    Wenfeng Zhang, Yong Li, Xiaosi Wu, Qianqian Sun, Yuting Fu, Shaoping Weng, Jianguo He, Chuanfu Dong.
      Mandarin fish ranavirus (MRV), a new member of the species Ranavirus micropterus1, sharing over 98% whole-genome nucleotide identity with the well-known largemouth bass virus (LMBV), is a distinct member of the genus Ranavirus within the family Iridoviridae. Our recent work showed that acute MRV infection predominantly affects the pyloric cecum, a critical visceral organ in mandarin fish, and was hypothesized to drive the characteristic external clinical sign of severe ascites. In this study, we reveal that acute MRV infection initially targets the serosal layer of the pyloric cecum of mandarin fish, leading to rapid progression into fibrinous serositis characterized by serosal hypertrophy, fibrosis, hyperemia, edema, and tissue adhesions. Using single-cell RNA sequencing, we dissect the cellular composition of epithelial, immune, and stromal populations, identifying significant enrichment of macrophages and granulocytes, alongside T and natural killer cells, as key mediators of acute cytokine and inflammatory responses. Then, robust experimental evidence demonstrates that MRV infects specific immune cell subsets of T and B cells and stromal cells of fibroblasts, myofibroblasts, endothelial cells, and pericytes, resulting in upregulation of genes and pathways associated with extracellular matrix (ECM) formation, collagen biosynthesis, and vascular remodeling in the hyperplastic serosal zone. Additionally, both host-derived type V collagens and MRV-encoded collagens are implicated in ECM formation in the hypertrophic serosa. Collectively, this study provides a comprehensive single-cell resolution analysis of the pyloric cecum's response to acute MRV infection and highlights virus-driven serositis as the underlying cause of severe ascites in mandarin fish.IMPORTANCEThe pyloric cecum is a vital digestive and immune organ in many bony fish species, including the mandarin fish, a carnivorous species with an exceptionally developed pyloric cecum comprising 207-326 ceca per individual. While MRV/LMBV infects various fish species, severe ascites is uniquely observed in infected mandarin fish. This study demonstrates that acute MRV infection induces fibrinous serositis in the pyloric cecum, characterized by hyperemia, edema, and hyperplasia, ultimately resulting in ascites and mortality. Leveraging single-cell RNA sequencing, we provide a detailed landscape of the cell types affected or involved in the inflammatory response, revealing their roles in the pathogenesis of serositis. These findings advance our understanding of MRV-induced pathology and its species-specific manifestations.
    Keywords:  ScRNA transcription; ascites syndrome; mandarin fish ranavirus (MRV); pyloric cecum; serositis
    DOI:  https://doi.org/10.1128/jvi.02308-24
  68. Arthritis Res Ther. 2025 May 15. 27(1): 105
    Atf3 + senescent chondrocytes mediate meniscus degeneration in aging.
    Jing-Yi Wang, Yao-Hui Liu, Xiao Wang, Min Ma, Zhang-Yi Pan, Ao-Yuan Fan, Lai-Ya Lu, Zheng Liu, Kun Tao, Feng Yin.
       BACKGROUND: Meniscus degeneration contributes to knee arthritis progression, but the cellular and molecular mechanisms of meniscus aging remain poorly understood. We aimed to characterize age-related changes in the rat meniscus using single-cell RNA sequencing (scRNA-seq) and identify key pathogenic cell populations and pathways.
    METHODS: Meniscal tissues from young (12 weeks) and aged (24 months) rats were processed for histology, flow cytometry, and scRNA-seq. Bioinformatics tools, including Seurat, Monocle 2, and CellChat, were used to analyze cellular composition, pseudotime trajectories, and intercellular communication. Senescence-related features and signaling pathways were evaluated.
    RESULTS: Knee joint of aged rats exhibited higher Osteoarthritis Research Society International (OARSI) scores and synovial inflammation. scRNA-seq revealed three major chondrocyte subpopulations: Sox9 + stable chondrocytes, Fndc1 + fibrochondrocytes, and Atf3 + senescent chondrocytes. Aging caused a significant increase in Atf3 + senescent chondrocytes, characterized by the expression of senescence markers (Cdkn1a/Cdkn2a) and activation of inflammatory pathways such as tumor necrosis factor (TNF) and nuclear factor-κB (NF-κB). These cells were predominantly located at the endpoint of differentiation trajectories. CellChat analysis identified the ANGPTL4-SDC4 axis as a key signaling pathway mediated by Atf3 + cells. Immunostaining confirmed elevated Angiopoietin-Like Protein 4 (ANGPTL4) expression in aged menisci.
    CONCLUSION: We identified Atf3 + senescent chondrocytes as a key pathogenic population in the aging meniscus, driving degeneration via the ANGPTL4 pathway. Targeting Atf3 + cells or ANGPTL4 signaling may offer new therapeutic strategies for age-related meniscus degeneration and arthritis.
    Keywords:  Arthritis; Chondrocyte; Meniscus; Senescence; scRNA-seq
    DOI:  https://doi.org/10.1186/s13075-025-03566-z
  69. Cancer Lett. 2025 May 10. pii: S0304-3835(25)00358-1. [Epub ahead of print]626 217791
    Activated Schwann cells promote tumor growth in colon cancer.
    Kexin He, Hao Wang, Hao Wu, Weihan Li, Ruixue Huo, Luju Jiang, Minhao Yu, Junli Xue.
      Schwann cells, traditionally recognized as glial cells of the peripheral nervous system, have emerged as pivotal cellular constituents within the tumor microenvironment. Colon cancer exhibits significant nerve dependence; however, the roles of Schwann cells in colon cancer progression remain insufficiently understood. Here, we identified a significant increase in tumor-associated nonmyelinating Schwann cells within colon tumor samples compared to their normal tissue counterparts. Furthermore, the elevated abundance of these cells was associated with poorer clinical outcomes in colon cancer. Within colon tumor tissues, Schwann cells displayed elevated expression of c-Jun, a key gene involved in their activation and reprogramming. Knocking down c-Jun hampered Schwann cell activation. Single-cell RNA sequencing analysis uncovered that glial cells engage in the most robust cell-cell interactions with malignant cells and fibroblasts. Co-culture experiments demonstrated that tumor cells and cancer-associated fibroblasts specifically promoted c-Jun activation in Schwann cells, whereas co-culture with immune cells did not elicit a similar response. Under In vivo conditions, Schwann cells enhance tumor growth in a c-Jun-dependent manner. Moreover, c-Jun knockout in Schwann cells orchestrated a reprogramming of their secretome, exemplified by a notable reduction in IL-6, a key effector of their tumor-promoting activity. Collectively, our study elucidates the critical role of activated Schwann cells in colon cancer, which may offer a novel therapeutic strategy for treatment.
    Keywords:  Cancer neuroscience; Colon adenocarcinoma; Colorectal cancer; Tumor-associated schwann cells
    DOI:  https://doi.org/10.1016/j.canlet.2025.217791
  70. Front Dent Med. 2025 ;6 1581376
    Temporal evolution of fibroblast responses following salivary gland ductal ligation injury.
    Joey R Tavarez, James Kenney, Sergo Gabunia, Deirdre A Nelson, Melinda Larsen.
      Extracellular matrix remodeling is a natural response to injury but, excessive extracellular matrix accumulation, or fibrosis, is a causative factor in hundreds of diseases that limit organ function, regenerative responses, and can interfere with regenerative therapies. Fibrosis is closely related to inflammation, both of which occur in the salivary glands of patients treated with radiation for head and neck cancers and in patients suffering from autoimmune conditions, such as Sjögren's Disease. Despite the known involvement of fibrosis in disease and the inhibitory effects of fibrosis on tissue regeneration, the mechanisms through which extracellular matrix is elaborated in the salivary gland are poorly understood. Stromal fibroblasts are the primary matrix-producing cells and are known to drive both fibrosis and inflammation. To define the temporal responses of fibroblasts to injury, we induced a temporary obstructive injury though ligation of the primary submandibular and sublingual salivary gland ducts and then performed single-cell RNA sequencing and pathway analysis at timepoints immediately following the injury. Using bioinformatic approaches, we identified three unique fibroblast groups that dynamically respond to the injury. We characterized the changes in matrisomal and inflammatory gene expression over a 7-day time course and identified one group of fibroblasts to be the primary injury-responsive fibrogenic cell type. Understanding how fibroblasts respond at the early and later injury timepoints, along with defining signaling pathways regulated by fibroblasts, could lead to a better understanding of the contribution of fibroblast to acute injury responses to facilitate the development of therapeutics that minimize fibrosis and promote regenerative gland responses in chronic disease states.
    Keywords:  extracellular matrix (ECM); fibroblasts; inflammation; injury response; salivary glands; single cell RNA-seq
    DOI:  https://doi.org/10.3389/fdmed.2025.1581376
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