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Ce -NeRV3D - a C. elegans Neuron RNA-seq Visualization tool in 3D.
Caenorhabditis elegans provides a tractable model for neural circuit studies, with complete connectomes and single-cell transcriptomic atlases available. Here, we present Ce -NeRV3D ( C. elegans Neuron RNA-seq Visualization tool in 3D), a Blender plug-in that allows visualizing the expression patterns of an unlimited number of genes within the worm's 3D nervous system. The tool enables users to explore the spatial distribution of gene co-expression with customizable color mapping, overlay single-cell RNA sequencing data onto the anatomical structure, and interactively examine transcriptomic datasets in the context of detailed neural anatomy.
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Transcriptional Dynamics of Hepatic Sinusoid-Associated Cells After Liver Injury.
BACKGROUND AND AIMS: Hepatic sinusoidal cells are known actors in the fibrogenic response to injury. Activated hepatic stellate cells (HSCs), liver sinusoidal endothelial cells, and Kupffer cells are responsible for sinusoidal capillarization and perisinusoidal matrix deposition, impairing vascular exchange and heightening the risk of advanced fibrosis. While the overall pathogenesis is well understood, functional relations between cellular transitions during fibrogenesis are only beginning to be resolved. At single-cell resolution, we here explored the heterogeneity of individual cell types and dissected their transitions and crosstalk during fibrogenesis. APPROACH AND RESULTS: We applied single-cell transcriptomics to map the heterogeneity of sinusoid-associated cells in healthy and injured livers and reconstructed the single-lineage HSC trajectory from pericyte to myofibroblast. Stratifying each sinusoidal cell population by activation state, we projected shifts in sinusoidal communication upon injury. Weighted gene correlation network analysis of the HSC trajectory led to the identification of core genes whose expression proved highly predictive of advanced fibrosis in patients with nonalcoholic steatohepatitis (NASH). Among the core members of the injury-repressed gene module, we identified plasmalemma vesicle-associated protein (PLVAP) as a protein amply expressed by mouse and human HSCs. PLVAP expression was suppressed in activated HSCs upon injury and may hence define hitherto unknown roles for HSCs in the regulation of microcirculatory exchange and its breakdown in chronic liver disease. CONCLUSIONS: Our study offers a single-cell resolved account of drug-induced injury of the mammalian liver and identifies key genes that may serve important roles in sinusoidal integrity and as markers of advanced fibrosis in human NASH.
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Spatial transcriptomics reveals unique metabolic profile and key oncogenic regulators of cervical squamous cell carcinoma.
BACKGROUND: As a prevalent and deadly malignant tumor, the treatment outcomes for late-stage patients with cervical squamous cell carcinoma (CSCC) are often suboptimal. Previous studies have shown that tumor progression is closely related with tumor metabolism and microenvironment reshaping, with disruptions in energy metabolism playing a critical role in this process. To delve deeper into the understanding of CSCC development, our research focused on analyzing the tumor microenvironment and metabolic characteristics across different regions of tumor tissue. METHODS: Utilizing spatial transcriptomics (ST) sequencing technology, we conducted a study on FFPE (formalin-fixed paraffin-embedded) tumor samples from CSCC patients. Coupled with single-cell RNA sequencing (scRNA-seq) data after deconvolution, we described spatial distribution maps of tumor leading edge and core regions in detail. Tumor tissues were classified into hypermetabolic and hypometabolic regions to analyze the metabolism profiles and tumor differentiation degree across different spatial areas. We also employed The Cancer Genome Atlas (TCGA) database to examine the analysis results of ST data. RESULTS: Our findings indicated a more complex tumor microenvironment in hypermetabolic regions. Cell-cell communication analysis showed that various cells in tumor microenvironment were influenced by the signalling molecule APP released by cancer cells and higher expression of APP was observed in hypermetabolic regions. Furthermore, our results revealed the correlation between APP and the transcription factor TRPS1. Both APP and TRPS1 demonstrated significant effects on cancer cell proliferation, migration, and invasion, potentially contributing to tumor progression. CONCLUSIONS: Utilizing ST, scRNA-seq, and TCGA database, we examined the spatial metabolic profiles of CSCC tissues, including metabolism distribution, metabolic variations, and the relationship between metabolism and tumor differentiation degree. Additionally, potential cancer-promoting factors were proposed, offering a valuable foundation for the development of more effective treatment strategies for CSCC.
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Comprehensive molecular characterization identifies therapeutic vulnerabilities in ovarian clear cell carcinoma.
BACKGROUND: Ovarian clear cell carcinoma (OCCC) is a rare aggressive, and chemo-resistant subtype of epithelial ovarian cancer. Current limitations in precisely characterizing its molecular features have resulted in restricted availability of clinical targeted therapies and significant therapeutic challenges. METHODS: To address this unmet need, we conducted an integrative multi-omics study of 82 OCCC cases, incorporating whole-exome sequencing (WES), bulk RNA sequencing, and single-cell RNA sequencing (scRNA-seq). RESULTS: Our analysis uncovered recurrent mutations in multiple epigenetic regulators including ARID1A, EP300, and SETD2B, reinforcing chromatin remodeling as a hallmark of OCCC pathogenesis. Strikingly, FOXA2 mutations were absent in early-stage tumors but specifically enriched in advanced-stage cases (19% frequency), with functional validation demonstrating their role in driving malignant progression. Copy number alteration profiling revealed frequent amplifications in chromosomal arms such as 17q, which contains the ERBB2 oncogene that potentially regulates OCCC progression. Chromosomal translocations were detected in 35.59% of cases, including a novel FGFR2/RPAP3 fusion with therapeutic implications. Notably, scRNA-seq delineated immune-rich subsets characterized by abundant cytotoxic T-cell and B-cell infiltration, suggesting immunotherapeutic opportunities in a patient subset. Moreover, molecular subtyping identified ERBB2 amplification/overexpression as a high-risk feature strongly associated with poor survival. Patient-derived xenograft (PDX) models and a retrospective analysis of two clinical cases demonstrated that HER2-targeted antibody-drug conjugates (HER2-ADCs) significantly suppressed tumor growth and progression in OCCC patients with HER2 expression. CONCLUSIONS: In summary, our study establishes the comprehensive molecular atlas and a targeted therapeutic subtyping framework, revealing therapeutic vulnerabilities and providing novel insights for advancing precision oncology in OCCC management.
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Functional genomics implicates natural killer cells in the pathogenesis of ankylosing spondylitis.
Multiple lines of evidence indicate that ankylosing spondylitis (AS) is a lymphocyte-driven disease. However, which lymphocyte populations are critical in AS pathogenesis is not known. In this study, we aimed to identify the key cell types mediating the genetic risk in AS using an unbiased functional genomics approach. We integrated genome-wide association study (GWAS) data with epigenomic and transcriptomic datasets of human immune cells. To quantify enrichment of cell type-specific open chromatin or gene expression in AS risk loci, we used three published methods-LDSC-SEG, SNPsea, and scDRS-that have successfully identified relevant cell types in other diseases. Natural killer (NK) cell-specific open chromatin regions are significantly enriched in heritability for AS, compared to other immune cell types such as T cells, B cells, and monocytes. This finding was consistent between two AS GWAS. Using RNA sequencing data, we validated that genes in AS risk loci are enriched in NK cell-specific gene expression. Using the human Space-Time Gut Cell Atlas, we also found significant upregulation of AS-associated genes predominantly in NK cells. We performed co-localization analyses between GWAS risk loci and genetic variants associated with gene expression (eQTL) to find putative target genes. This revealed four AS risk loci affecting regulation of candidate target genes in NK cells: two known loci, ERAP1 and TNFRSF1A, and two understudied loci, ENTR1 (SDCCAG3) and B3GNT2. Our findings suggest that NK cells may play a crucial role in AS development and highlight four putative target genes for functional follow-up in NK cells.
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Loss of wbp11 causes multi-system developmental defects: a zebrafish model of VACTERL association.
INTRODUCTION: VACTERL association is a congenital disorder characterized by the non-random co-occurrence of vertebral, anal, cardiac, tracheo-esophageal, renal, and limb anomalies. WBP11 has been identified as a candidate causative gene; however, existing heterozygous Wbp11 knockout mice recapitulate only a subset of the patient phenotypes, most notably lacking the cardiac defects, which limits a comprehensive understanding of the pathogenic mechanisms. Whether WBP11 loss of function is sufficient to induce the full multi-system spectrum of VACTERL association in a vertebrate model remains unexplored. METHODS: We established a wbp11 knockdown zebrafish model by microinjecting a translation-blocking morpholino (wbp11-MO) at the optimized concentration of 0.25 mM. Knockdown efficiency was validated by Western blot. Bioinformatics analysis of public single cell and expression atlas datasets was combined with whole-mount in situ hybridization to characterize the spatiotemporal expression of wbp11. Phenotypic defects across cardiac, vascular, spinal, fin, and renal systems were assessed by stereomicroscopy, transgenic reporter lines (Tg(myl7:EGFP) and Tg(flila:EGFP)), and whole mount in situ hybridization. Underlying molecular changes were interrogated by transcriptome sequencing (RNA-seq) coupled with differential alternative splicing analysis (rMATS) and quantitative real-time PCR validation. Rescue experiments were performed by co-injection of capped wbp11 mRNA. RESULTS: wbp11 is evolutionarily conserved and maternally expressed, peaking at the gastrula stage with elevated signals in the head, skeletal muscle, and heart. wbp11-MO injection reduced Wbp11 protein levels, induced a 70% overall malformation rate, and caused a general delay in embryonic development. wbp11-deficient larvae exhibited multi-system developmental defects that closely mirror the core clinical features of VACTERL association: cardiac malformations with pericardial edema and impaired heart looping; vascular defects including underdeveloped subintestinal vessels and reduced cranial vasculature; spinal curvature with aberrant notochord structure; hypoplasia of the pectoral, pelvic, anal, and caudal fins; and transcriptional dysregulation of kidney developmental markers. Transcriptomic and alternative splicing analyses revealed significant dysregulation of genes associated with cardiac function, angiogenesis, skeletal patterning, fin development, and kidney development, accompanied by widespread splicing aberrations. DISCUSSION: This study establishes the first wbp11-knockdown zebrafish model that partially recapitulates the key organ phenotypes of human VACTERL association notably including the cardiac defects absent in the mouse model and thereby provides a powerful platform for dissecting the splicing dependent molecular mechanisms underlying this disorder and for exploring potential therapeutic interventions.
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Spatial and functional characterization of IL1RL1+ mast cells reveals immune regulatory roles in renal cancer.
BACKGROUND: Interleukin-1 receptor-like 1 (IL1RL1, also known as ST2) plays a critical role in immune regulation. Pan-cancer analysis has revealed that IL1RL1 is closely associated with cellular immune functions; however, its role in clear cell renal cell carcinoma (ccRCC) and the tumor microenvironment (TME) remains poorly defined. METHODS: We analyzed IL1RL1 expression patterns using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) were employed to investigate the cellular localization and biological functions of IL1RL1 in ccRCC. In addition, IL1RL1 knockout experiments were conducted to explore its potential role in antigen presentation. RESULTS: Compared to adjacent normal tissues, IL1RL1 expression was significantly downregulated in renal cancer tissues. Higher IL1RL1 expression correlated with improved patient prognosis, suggesting its potential as an independent prognostic biomarker. IL1RL1 was predominantly expressed in mast cells, with higher levels observed in adjacent normal tissues than in tumor tissues, implying a regulatory role in tumor immunity. Subset analysis revealed that IL1RL1-high mast cells were enriched in immune-inflammatory functions, including leukocyte activation, chemokine production, and antigen presentation. Cell-cell communication analysis further demonstrated that IL1RL1+ mast cells may enhance CD8+ cytotoxic T cell activation via the MHC-I signaling pathway. Spatial transcriptomics and multiplex immunohistochemistry (mIHC) confirmed the spatial co-localization of IL1RL1+ mast cells and T cells within the TME. Furthermore, IL1RL1 knockout led to a reduction in HLA-A expression, providing functional evidence for its involvement in antigen presentation. CONCLUSION: Our findings highlight the immune-regulatory role of IL1RL1+ mast cells in ccRCC. IL1RL1 may contribute to anti-tumor immunity through the modulation of antigen presentation and CD8+ T cell activation, offering new insights into its potential as a prognostic biomarker and therapeutic target in renal cancer.
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Scalable high-performance single cell data analysis with BPCells.
The growth of single-cell datasets to multi-million cell atlases has uncovered major scalability problems for single-cell analysis software. Here, we present BPCells, a package for high-performance single-cell analysis of RNA-seq and ATAC-seq datasets. BPCells uses disk-backed streaming compute algorithms to reduce memory requirements by nearly 70-fold compared to in-memory workflows with little to no loss of execution speed. BPCells also introduces high-performance compressed formats based on bitpacking compression for ATAC-seq fragment files and single-cell sparse matrices. These novel compression algorithms help to accelerate disk-backed analysis by reducing data transfer from disk, while providing the lowest computational overhead of all compression algorithms tested. Using BPCells, we perform normalization and PCA of a 44 million cell dataset on a laptop, demonstrating that BPCells makes working with the largest contemporary single-cell datasets feasible on modest hardware, while leaving headroom on servers for future datasets an order of magnitude larger.
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Targeting Pan-Cancer Stemness: Core Regulatory lncRNAs as Novel Therapeutic Vulnerabilities.
Tumor stemness represents a key biological process that drives tumor progression and therapeutic resistance across various cancer types. To systematically elucidate the regulatory roles of long non-coding RNAs (lncRNAs) in this process, we integrated bulk transcriptomic data from The Cancer Genome Atlas (TCGA) with publicly available pan-cancer single-cell transcriptomic atlases. Using machine-learning-based stemness metrics, we successfully quantified stemness features and identified unique lncRNA gene sets for each cancer type at the bulk data level. The high-stemness subtype exhibited enhanced proliferation, an immunosuppressive microenvironment, and profound metabolic reprogramming. Based on these findings, we constructed a robust prognostic model with remarkable predictive performance across multiple cancer types. At the single-cell resolution, we reconstructed the dynamic trajectory of stemness evolution, uncovering distinctive metabolic and cell-communication patterns within cancer stem cells (CSCs). This multi-scale analysis consistently nominated a core set of regulatory lncRNAs, including NEAT1 and MALAT1. Our work not only nominates potential targets for stemness-directed therapy but also provides a comprehensive framework for understanding lncRNA-driven mechanisms of cancer aggressiveness and resistance.
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Integrated bulk RNA-seq and scRNA-seq identification of a novel "PET-SPI1-MYL9" transcriptional axis in lung adenocarcinoma driven by polyethylene terephthalate exposure.
BACKGROUND: Airborne microplastic polyethylene terephthalate (PET) accumulates in human lungs and is linked to respiratory pathologies; however, its molecular role in lung adenocarcinoma (LUAD) remains unclear. This study aims to explore the potential carcinogenic mechanisms of PET exposure in LUAD. METHODS: We integrated single-cell RNA sequencing, machine learning algorithms [including Classification and Regression Trees (CART), Naïve Bayes (NB), random forest (RF), and support vector machine (SVM)], molecular docking, survival analysis, and multi-omics data. Through differential expression screening across datasets combined with Venn analysis, we identified seven PET-associated oncogenic targets. Seven PET-associated oncogenic targets were identified via differential gene screening and Venn analysis. RESULTS: MYL9 was validated as a downregulated, LUAD-protective biomarker associated with significant survival benefit [hazard ratio (HR) =0.59, 0.16, 0.23; all P<0.05]. These findings were consistent across the Human Protein Atlas (HPA) database, co-expression networks, and three independent LUAD datasets. SPI1 was identified as a key transcriptional regulator, showing strong co-expression with MYL9 (R=0.556, P<0.05) and concurrent downregulation in LUAD. Molecular docking revealed that PET bound to the DNA-binding pocket of SPI1 (ΔG =-5.30 kcal·mol-1), suggesting its transcriptional inhibition of MYL9. CONCLUSIONS: Our integrated bioinformatics approach supports a novel "PET-SPI1-MYL9" transcriptional axis, revealing a potential non-genotoxic carcinogenic pathway for PET. While the computational evidence is robust, further wet-lab experiments are needed to validate the binding and transcriptional inhibition mechanism. This model provides a framework for understanding airborne microplastic toxicity in LUAD. We propose that PET promotes LUAD by disrupting the SPI1-MYL9 transcriptional axis, highlighting a potential environmental trigger and candidate targets for diagnostic and therapeutic strategies.