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Multi-Omics Integrative Analysis Identifies the NK Cell-STAT3 Axis as a Shared Immunogenetic Hub Underlying the Comorbidity of Primary Sclerosing Cholangitis and Ulcerative Colitis.
Primary sclerosing cholangitis (PSC) and ulcerative colitis (UC) exhibit a striking clinical comorbidity, with 60-80% of PSC patients concurrently harboring UC, yet the shared immunogenetic mechanisms remain poorly understood. Here, we constructed a multi-omics integrative framework to systematically dissect the cellular and molecular basis of this comorbidity. GWAS meta-analyses were performed for each disease, followed by tissue-level enrichment assessment using QTLEnrich, MAGMA, and gsMap spatial mapping. Single-cell transcriptomic atlases were constructed, and cell-type prioritization was conducted using four complementary methods. Core genes were identified through cross-validation of five algorithms, with subsequent genomic fine-mapping via FUMA and GCTA-COJO. Tissue-level analyses consistently identified the intestine and immune-related tissues as commonly affected. Multi-dimensional evidence integration prioritized natural killer (NK) cells as the core effector cell type for both diseases, supported principally by CELLECT (Cell-type Expression-specific Integration for Complex Traits) heritability enrichment and single-cell differential analysis. Convergence of five gene-level algorithms pinpointed STAT3 as the sole high-confidence comorbidity gene, broadly expressed across immune cell populations and exhibiting tissue-differential alternative splicing. Colocalization identified a high-risk variant (rs3736161) within the STAT3 locus, with conditional analysis revealing 35 additional independent signals. These findings identify the NK cell-STAT3 axis as a central immunogenetic hub connecting PSC and UC, offering potential therapeutic targets for comorbidity management.
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From COVID to fibrosis: lessons from single-cell analyses of the human lung.
The increased resolution of single-cell RNA-sequencing technologies has led to major breakthroughs and improved our understanding of the normal and pathologic conditions of multiple tissues and organs. In the study of parenchymal lung disease, single-cell RNA-sequencing has better delineated known cell populations and identified novel cells and changes in cellular phenotypes and gene expression patterns associated with disease. In this review, we aim to highlight the advances and insights that have been made possible by applying these technologies to two seemingly very different lung diseases: fibrotic interstitial lung diseases, a group of relentlessly progressive lung diseases leading to pulmonary fibrosis, and COVID-19 pneumonia, an acute viral disease with life-threatening complications, including pulmonary fibrosis. We discuss changes in cell populations and gene expression, highlighting potential common features, such as alveolar cell epithelial injury and aberrant repair and monocyte-derived macrophage populations, as well as relevance and implications to mechanisms of disease and future directions.
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Single-cell and spatial transcriptome sequencing analysis reveals characteristics of a unique subpopulation in high-grade IDH-mutant astrocytoma.
INTRODUCTION: (Isocitrate dehydrogenase) IDH-mutant astrocytoma is classified as World Health Organization (WHO) grade 2-4 and is second only to IDH wild-type glioblastoma in the incidence of adult glioma. However, few studies use single-cell and spatial transcriptome sequencing to analyze its malignant progression. METHODS: Intraoperative navigation and yellow fluorescence visualization were utilized to accurately isolate high-grade (WHO grade 3-4) and low-grade (WHO grade 2) samples of IDH-mutant astrocytoma for single-cell and spatial transcriptome sequencing. By combining single-cell, spatial transcriptome, The Cancer Genome Atlas (TCGA), and The Chinese Glioma Genome Atlas (CGGA) data, analyses of survival, enriched pathways, transcription factors, intercellular communication, differentiation trajectories, and immune response were performed to identify the characteristics of a unique subpopulation of high-grade IDH-mutant astrocytoma. RESULTS: Our single-cell RNA sequencing analysis identified a distinct subpopulation (Cluster 7) present in high-grade IDH-mutant astrocytoma, which was localized to the terminus of the pseudotime trajectory. Importantly, this cluster not only exhibited an immunosuppressive phenotype correlated with poor clinical prognosis, but also demonstrated significant enrichment in Developmental Biology and Calcium Signaling pathways. Furthermore, this subpopulation engaged in prominent ligand-receptor interactions, particularly through PTN_PTPRZ1 and MIF_CD74 pairs. Notably, comparative analysis revealed that high-grade astrocytoma displayed both quantitatively and qualitatively enhanced communication networks when compared to their low-grade counterparts. CONCLUSIONS: Our single-cell RNA sequencing analysis identifies a distinct tumor cell subpopulation present in high-grade (WHO grade 3-4) adult IDH-mutant astrocytoma. This cluster, which likely arises from malignant progression in adult astrocytoma, may provide new insights for developing therapeutic strategies against this clinically challenging disease.
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SigFuge: single gene clustering of RNA-seq reveals differential isoform usage among cancer samples.
High-throughput sequencing technologies, including RNA-seq, have made it possible to move beyond gene expression analysis to study transcriptional events including alternative splicing and gene fusions. Furthermore, recent studies in cancer have suggested the importance of identifying transcriptionally altered loci as biomarkers for improved prognosis and therapy. While many statistical methods have been proposed for identifying novel transcriptional events with RNA-seq, nearly all rely on contrasting known classes of samples, such as tumor and normal. Few tools exist for the unsupervised discovery of such events without class labels. In this paper, we present SigFuge for identifying genomic loci exhibiting differential transcription patterns across many RNA-seq samples. SigFuge combines clustering with hypothesis testing to identify genes exhibiting alternative splicing, or differences in isoform expression. We apply SigFuge to RNA-seq cohorts of 177 lung and 279 head and neck squamous cell carcinoma samples from the Cancer Genome Atlas, and identify several cases of differential isoform usage including CDKN2A, a tumor suppressor gene known to be inactivated in a majority of lung squamous cell tumors. By not restricting attention to known sample stratifications, SigFuge offers a novel approach to unsupervised screening of genetic loci across RNA-seq cohorts. SigFuge is available as an R package through Bioconductor.
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Single-nucleus RNA sequencing reveals heterogenous microenvironments and specific drug response between cervical squamous cell carcinoma and adenocarcinoma.
BACKGROUND: Cervical squamous cell carcinoma (CSCC) and adenocarcinoma (CAde) are two major pathological types of cervical cancer (CC), but their high-resolution heterogeneity of tumor and immune microenvironment remains elusive. METHODS: Here, we performed single-nucleus RNA sequencing (snRNA-seq) from five CSCC and three CAde samples, and systematically outlined their specific transcriptome atlas. FINDINGS: We found CD8+ T cells in CSCC were more cytotoxic but lower exhausted compared to those in CAde, and phagocytic MRC1+ macrophages were specifically enriched in CSCC. Interestingly, we discovered that pro-tumoral cancer-associated myofibroblasts (myoCAFs) and cancer-associated vascular-fibroblasts (vCAFs) were more abundant in CSCC, and further verified their pro-metastatic roles in vitro. Furthermore, we also identified some specific chemotherapy drugs for CSCC (Dasatinib and Doramapimod) and CAde (Pyrimethamine and Lapatinib) by revealing their heterogeneity in transcriptomic profiles of malignant epithelial cells, and further verified their specific sensitivity in cell lines and constructed CC-derived organoids. Cell-cell communication networks revealed that the pathways of NRG1-ERBB2, and FN1-ITAG3 were specific for CAde and CSCC, respectively, which may partly explain the specificities of identified chemotherapy drugs. INTERPRETATION: Our study described the immune heterogeneity and specific cellular interactions between CSCC and CAde, which could provide insights for uncovering pathogenesis and designing personalized treatment. FUNDINGS: National Key R&D Program of China (2021YFC2701201), National Natural Science Foundation of China (82072895, 82141106, 82103134, 81903114).
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Single-cell transcriptome analysis profiles cellular dynamics and transcriptional changes in diabetic wound tissues following ESWT treatment.
INTRODUCTION: Diabetic wounds (DWs) remain a major complication of diabetes mellitus, characterized by impaired healing and limited therapeutic options. Extracorporeal shock wave therapy (ESWT), a non-invasive physical modality, has recently shown promise in accelerating chronic wound repair, yet the underlying cellular mechanisms remain poorly understood. METHODS: Here, we employed single-cell RNA sequencing (scRNA-seq) to construct a comprehensive cellular atlas of DW tissues treated with ESWT, profiling approximately 39,475 cells. RESULTS: Our analysis identified 12 major cell populations, including macrophages, fibroblasts, endothelial cells, keratinocytes, and immune subsets, and revealed widespread transcriptional reprogramming associated with ESWT treatment. ESWT promoted the expansion of reparative macrophages, activated proregenerative fibroblast states, and restored angiogenic programs in endothelial cells. Moreover, cell-cell communication analysis revealed that ESWT not only attenuates pro-inflammatory signaling but also activates immune cell communication networks, thereby enhancing T cell, NK cell, and dendritic cell interactions. These changes collectively promote immune regulation and tissue repair, contributing to the restoration of a balanced wound microenvironment. DISCUSSION: Together, these findings provide a high-resolution single-cell map of ESWT mediated cellular and molecular alterations in DWs and uncover key cellular pathways contributing to improved tissue repair. This study offers new insights into the mechanisms of ESWT and supports its translational potential as a therapeutic strategy for chronic wound management.
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Single-Cell RNA Sequencing Reveals an Atlas of Meihua Pig Testis Cells.
Mammalian spermatogenesis is a complex biological process that is regulated by multiple types of cells. The heterogeneity of these cells poses a challenge for analyzing different cell types at different developmental stages. To characterize the transcriptomic landscape of porcine spermatogenesis and identify potential marker genes for spermatogonia, an unbiased transcriptomic study of spermatogenesis in neonatal and sexually mature six-month-old Meihua pigs was performed using 10× Genomics single-cell RNA sequencing (scRNA-seq). Through the collection of scRNA-seq data from 13,839 cells from Meihua pig testes, three germ cells (spermatogonia, spermatocytes and spermatids) and eight somatic cells (Sertoli cells, Leydig cells, myoid/stromal cells, endothelial cells, T cells/macrophages and erythroblasts) were identified. Pseudo-timing analysis showed that myoid cells and stromal cells originated from common progenitors in Meihua pigs. Functional enrichment analysis revealed that the differentially expressed genes (DEGs) in testicular somatic cells were enriched in the pathways of Ribosome, Oxidative phosphorylation, Protein processing in endoplasmic reticulum, Retrograde endocannabinoid signaling, Cellular senescence and Insulin signaling. Meanwhile, in the three different germ cells, except for pathways which were the same as the first three pathways for somatic cells, DEGs were also enriched in the Spliceosome, Cell cycle, Autophagy and Mitophagy pathways. Furthermore, the candidate marker gene TKTL1 in spermatogonia was identified using immunohistochemistry and immunofluorescence. In conclusion, we collected transcription datasets and constructed single-cell developmental maps of germ cells and somatic cells during the testicular development of Meihua pigs, which provided new insights into the spermatogenesis of Meihua pigs and the development of various types of cells in their testes.
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Altered Monocyte Subsets in Kawasaki Disease Revealed by Single-cell RNA-Sequencing.
BACKGROUND: Kawasaki disease (KD) is characterized by a disorder of immune response, and its etiology remains unknown. Monocyte is an important member of the body's innate immune system; however its role in KD is still elusive due to its ambiguous heterogeneity and complex functions. We aim to comprehensively delineate monocyte heterogeneity in healthy and KD infants and to reveal the underlying mechanism for KD. METHODS: Peripheral monocytes were enriched from peripheral blood samples of two healthy infants and two KD infants. scRNA-seq was performed to acquire the transcriptomic atlas of monocytes. Bio-information analysis was utilized to identify monocyte subsets and explore their functions and differentiation states. SELL+CD14+CD16- monocytes were validated using flow cytometry. RESULTS: Three monocyte subsets were identified in healthy infants, including CD14+CD16- monocytes, CD14+CD16+ monocytes, and CD14LowCD16+ monocytes. Cell trajectory analysis revealed that the three monocyte subsets represent a linear differentiation, and possess different biological functions. Furthermore, SELL+CD14+CD16- monocytes, which were poorly differentiated and relating to neutrophil activation, were found to be expanded in KD. CONCLUSION: Our findings provide a valuable resource for deciphering the monocyte heterogeneity in healthy infants and uncover the altered monocyte subsets in KD patients, suggesting potential biomarkers for KD diagnosis and treatment.
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A single-nucleus transcriptomic characterization of EGFR G719X/S768I double-mutant lung adenocarcinoma identifies an immunosuppressive niche defined by COL4A3-CD44 interaction.
EGFR double mutations (G719X/S768I) represent a clinically recalcitrant subtype of lung adenocarcinoma (LUAD) characterized by diminished tyrosine kinase inhibitor (TKI) sensitivity. However, the specific tumor microenvironment (TME) features and intercelluar crosstalk driving this therapeutic resistance poorly defined. We performed single-nucleus RNA sequencing (snRNA-seq) on formalin-fixed paraffin-embedded (FFPE) tissues from six EGFR G719X/S768I double-mutant (EGFR_double) and five no EGFR mutation (Non_EGFR) LUAD patients. To provide a comprehensive reference, we integrated our FFPE data with publicly fresh-tissue single cell RNA sequencing (scRNA-seq) data with seven EGFR single-mutant LUAD (EGFR_single) and five adjacent normal (Adjacent), generated a comprehensive atlas of 246,086 cells. Findings were further validated using multiplex immunohistochemistry (mIHC) and pharmacogenomic profiling. We identified a specialized EMT-like malignant subpopulation (MP4) uniquely enriched in EGFR_double, which exhibits a distinct lipid-glycosylation metabolic profile that stabilizes CD44 expression. Cell-cell communication analysis revealed enhanced COL4A3-CD44 interactions between EMT-like malignant MP4 cells and metabolically reprogrammed, immunosuppressive alveolar macrophages in EGFR_double compared with Non_EGFR. MIHC confirmed in situ proximity of this significantly increased COL4A3-CD44 co-localization in EGFR_double. Furthermore, drug sensitivity analysis identified specific vulnerabilities of this subtype. Our study identifies a previously unrecognized malignant-myeloid niche and TME in EGFR_double. These findings provide a translational framework for identifying a potential novel therapeutic targets and suggest that combinatorial strategies targeting the COL4A3-CD44 interaction may overcome therapeutic recalcitrance in this challenging clinical population.
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Mouse Retinal Cell Atlas: Molecular Identification of over Sixty Amacrine Cell Types.
Amacrine cells (ACs) are a diverse class of interneurons that modulate input from photoreceptors to retinal ganglion cells (RGCs), rendering each RGC type selectively sensitive to particular visual features, which are then relayed to the brain. While many AC types have been identified morphologically and physiologically, they have not been comprehensively classified or molecularly characterized. We used high-throughput single-cell RNA sequencing to profile >32,000 ACs from mice of both sexes and applied computational methods to identify 63 AC types. We identified molecular markers for each type and used them to characterize the morphology of multiple types. We show that they include nearly all previously known AC types as well as many that had not been described. Consistent with previous studies, most of the AC types expressed markers for the canonical inhibitory neurotransmitters GABA or glycine, but several expressed neither or both. In addition, many expressed one or more neuropeptides, and two expressed glutamatergic markers. We also explored transcriptomic relationships among AC types and identified transcription factors expressed by individual or multiple closely related types. Noteworthy among these were Meis2 and Tcf4, expressed by most GABAergic and most glycinergic types, respectively. Together, these results provide a foundation for developmental and functional studies of ACs, as well as means for genetically accessing them. Along with previous molecular, physiological, and morphologic analyses, they establish the existence of at least 130 neuronal types and nearly 140 cell types in the mouse retina.SIGNIFICANCE STATEMENT The mouse retina is a leading model for analyzing the development, structure, function, and pathology of neural circuits. A complete molecular atlas of retinal cell types provides an important foundation for these studies. We used high-throughput single-cell RNA sequencing to characterize the most heterogeneous class of retinal interneurons, amacrine cells, identifying 63 distinct types. The atlas includes types identified previously as well as many novel types. We provide evidence for the use of multiple neurotransmitters and neuropeptides, and identify transcription factors expressed by groups of closely related types. Combining these results with those obtained previously, we proposed that the mouse retina contains ∼130 neuronal types and is therefore comparable in complexity to other regions of the brain.