Single-cell RNA-seq Data Research Articles

Lhx2 specifically expressed in hepatic stellate cells promotes liver regeneration and inhibits liver fibrosis.

Promoting liver regeneration while inhibiting fibrogenesis represented an attractive strategy for treating liver diseases, with hepatic stellate cells (HSCs) being crucial to both processes. This study aimed to identify specific targets in HSCs that simultaneously facilitated regeneration and suppressed fibrosis, and elucidated their molecular mechanisms. Through comparing acute and chronic liver injury mouse models induced by CCl4 injections, we revealed that HSCs exhibited dual functionality, expressing pro-regenerative and pro-fibrogenic genes following injury. Analyzing RNA-seq data from primary HSCs of these models, along with publicly available single-cell RNA-seq data of HSCs, we identified transcription factor Lhx2, specifically expressed in HSCs, emerged as a potential regulator of the dual functions. Notably, Lhx2 showed significantly higher expression in HSCs from healthy liver tissue compared to fibrotic liver, in both mouse and human models. Lhx2 knockdown impaired liver function recovery and cellular proliferation after acute liver injury. Consistent changes were observed in mice with HSC-specific Lhx2 overexpression. Additionally, Lhx2 overexpression not only promoted hepatocyte proliferation but also exhibited an anti-fibrogenic function after chronic injury. Mechanistically, Lhx2 suppressed multiple functions of activated HSCs, including fibrogenesis, proliferation and migration, and up-regulated SMAD6 to block TGF-β signaling pathway. Moreover, Lhx2 was an upstream regulator of various pro-regenerative factors, especially HGF, which is crucial for liver regeneration. We demonstrated that Lhx2 had pro-regenerative and anti-fibrogenic functions, and elucidated its regulatory mechanism. The study provided a potential target with dual effects for treating liver diseases.

Complete Genomic Landscape Reveals Hidden Evolutionary History and Selection Signature in Asian Water Buffaloes (Bubalus bubalis).

To identify the genetic determinants of domestication and productivity of Asian water buffaloes (Bubalus bubalis), 470 genomes of domesticated river and swamp buffaloes along with their putative ancestors, the wild water buffaloes (Bubalus arnee) are sequenced and integrated. The swamp buffaloes inherit the morphology of the wild buffaloes. In contrast, most river buffaloes are unique in their morphology, but their genomes cluster with the wild buffaloes. The levels of genomic diversity in Italian river and Indonesian swamp buffaloes decrease at opposite extremes of their distribution range. Purifying selection prevented the accumulation of harmful loss-of-function variants in the Indonesian buffaloes. Genes that evolved rapidly (e.g., GKAP1) following differential selections in the river and swamp buffaloes are involved in their reproduction. Genes related to milk production (e.g., CSN2) and coat color (e.g., MC1R) underwent strong selections in the dairy river buffaloes via soft and hard selective sweeps, respectively. The selective sweeps and single-cell RNA-seq data revealed the luminal cells as the key cell type in response to artificial selection for milk production of the dairy buffaloes. These findings show how artificial selection has been driving the evolutionary divergence and genetic differentiation in morphology and productivity of Asian water buffaloes.

Identification of SPP1 + macrophages as an immune suppressor in hepatocellular carcinoma using single-cell and bulk transcriptomics.

Macrophages and T cells play crucial roles in liver physiology, but their functional diversity in hepatocellular carcinoma (HCC) remains largely unknown. Two bulk RNA-sequencing (RNA-seq) cohorts for HCC were analyzed using gene co-expression network analysis. Key gene modules and networks were mapped to single-cell RNA-sequencing (scRNA-seq) data of HCC. Cell type fraction of bulk RNA-seq data was estimated by deconvolution approach using single-cell RNA-sequencing data as a reference. Survival analysis was carried out to estimate the prognosis of different immune cell types in bulk RNA-seq cohorts. Cell-cell interaction analysis was performed to identify potential links between immune cell types in HCC. In this study, we analyzed RNA-seq data from two large-scale HCC cohorts, revealing a major and consensus gene co-expression cluster with significant implications for immunosuppression. Notably, these genes exhibited higher enrichment in liver macrophages than T cells, as confirmed by scRNA-seq data from HCC patients. Integrative analysis of bulk and single-cell RNA-seq data pinpointed SPP1 + macrophages as an unfavorable cell type, while VCAN + macrophages, C1QA + macrophages, and CD8 + T cells were associated with a more favorable prognosis for HCC patients. Subsequent scRNA-seq investigations and in vitro experiments elucidated that SPP1, predominantly secreted by SPP1 + macrophages, inhibits CD8 + T cell proliferation. Finally, targeting SPP1 in tumor-associated macrophages through inhibition led to a shift towards a favorable phenotype. This study underpins the potential of SPP1 as a translational target in immunotherapy for HCC.

Comparison of CD30L and OX40L Reveals CD30L as a Promising Therapeutic Target in Atopic Dermatitis.

Blocking IL-13 is highly efficacious in patients with Th2-biased atopic dermatitis (AD), and recent clinical data have highlighted that targeting the T cell costimulatory molecules OX40 and OX40L (TNFSF4) holds promise for future treatment of AD. We asked whether targeting another T cell costimulatory molecule, CD30L (TNFSF8), might also be a possible treatment option in AD. Single-cell RNA-seq data from human AD skin lesions was analyzed to identify pathogenic IL-13- or IL-22-producing T cells and assess expression of CD30 and its ligand in comparison to OX40 and its ligand. Additionally, a murine model of AD with repetitive exposure to house dust mite allergen was used to compare neutralizing antibodies against CD30L with those against IL-13 or OX40L. Analysis of several scRNA-seq datasets from skin lesions of AD patients showed that transcripts for CD30 or CD30L were found expressed with OX40 or OX40L in the primary T cell populations that also expressed mRNA for IL13 and/or IL22. Suggesting that this could be therapeutically relevant, mice treated prophylactically with a blocking CD30L antibody were protected from developing maximal allergen-induced AD features, including epidermal and dermal thickening, immune cell infiltration, and expression of AD-related genes, similar to mice treated with a blocking IL-13 antibody. Moreover, therapeutic neutralization of CD30L in mice with experimental AD also reduced all of the pathological skin lesion features to a comparable extent as blocking OX40L. These data suggest that targeting the CD30-CD30L axis might hold promise as a future therapeutic intervention in human AD, similar to targeting the OX40-OX40L axis.

ScDCA: deciphering the dominant cell communication assembly of downstream functional events from single-cell RNA-seq data.

Cell-cell communications (CCCs) involve signaling from multiple sender cells that collectively impact downstream functional processes in receiver cells. Currently, computational methods are lacking for quantifying the contribution of pairwise combinations of cell types to specific functional processes in receiver cells (e.g. target gene expression or cell states). This limitation has impeded understanding the underlying mechanisms of cancer progression and identifying potential therapeutic targets. Here, we proposed a deep learning-based method, scDCA, to decipher the dominant cell communication assembly (DCA) that have a higher impact on a particular functional event in receiver cells from single-cell RNA-seq data. Specifically, scDCA employed a multi-view graph convolution network to reconstruct the CCCs landscape at single-cell resolution, and then identified DCA by interpreting the model with the attention mechanism. Taking the samples from advanced renal cell carcinoma as a case study, the scDCA was successfully applied and validated in revealing the DCA affecting the crucial gene expression in immune cells. The scDCA was also applied and validated in revealing the DCA responsible for the variation of 14 typical functional states of malignant cells. Furthermore, the scDCA was applied and validated to explore the alteration of CCCs under clinical intervention by comparing the DCA for certain cytotoxic factors between patients with and without immunotherapy. In summary, scDCA provides a valuable and practical tool for deciphering the cell type combinations with the most dominant impact on a specific functional process of receiver cells, which is of great significance for precise cancer treatment. Our data and code are free available at a public GitHub repository: https://github.com/pengsl-lab/scDCA.git.

BioDSNN: a dual-stream neural network with hybrid biological knowledge integration for multi-gene perturbation response prediction.

Studying the outcomes of genetic perturbation based on single-cell RNA-seq data is crucial for understanding genetic regulation of cells. However, the high cost of cellular experiments and single-cell sequencing restrict us from measuring the full combination space of genetic perturbations and cell types. Consequently, a bunch of computational models have been proposed to predict unseen combinations based on existing data. Among them, generative models, e.g. variational autoencoder and diffusion models, have the superiority in capturing the perturbed data distribution, but lack a biologically understandable foundation for generalization. On the other side of the spectrum, Gene Regulation Networks or gene pathway knowledge have been exploited for more reasonable generalization enhancement. Unfortunately, they do not reach a balanced processing of the two data modalities, leading to a degraded fitting ability. Hence, we propose a dual-stream architecture. Before the information from two modalities are merged, the sequencing data are learned with a generative model while three types of knowledge data are comprehensively processed with graph networks and a masked transformer, enforcing a deep understanding of single-modality data, respectively. The benchmark results show an approximate 20% reduction in terms of mean squared error, proving the effectiveness of the model.

Less is more: relative rank is more informative than absolute abundance for compositional NGS data.

High-throughput gene expression data have been extensively generated and utilized in biological mechanism investigations, biomarker detection, disease diagnosis and prognosis. These applications encompass not only bulk transcriptome, but also single cell RNA-seq data. However, extracting reliable biological information from transcriptome data remains challenging due to the constrains of Compositional Data Analysis. Current data preprocessing methods, including dataset normalization and batch effect correction, are insufficient to address these issues and improve data quality for downstream analysis. Alternatively, qualification methods focusing on the relative order of gene expression (ROGER) are more informative than the quantification methods that rely on gene expression abundance. The Pairwise Analysis of Gene expression method is an enhancement of ROGER, designed for data integration in either sample space or feature space. In this review, we summarize the methods applied to transcriptome data analysis and discuss their potentials in predicting clinical outcomes.

Mutual information for detecting multi-class biomarkers when integrating multiple bulk or single-cell transcriptomic studies.

Biomarker detection plays a pivotal role in biomedical research. Integrating omics studies from multiple cohorts can enhance statistical power, accuracy and robustness of the detection results. However, existing methods for horizontally combining omics studies are mostly designed for two-class scenarios (e.g., cases versus controls) and are not directly applicable for studies with multi-class design (e.g., samples from multiple disease subtypes, treatments, tissues, or cell types). We propose a statistical framework, namely Mutual Information Concordance Analysis (MICA), to detect biomarkers with concordant multi-class expression pattern across multiple omics studies from an information theoretic perspective. Our approach first detects biomarkers with concordant multi-class patterns across partial or all of the omics studies using a global test by mutual information. A post hoc analysis is then performed for each detected biomarkers and identify studies with concordant pattern. Extensive simulations demonstrate improved accuracy and successful false discovery rate control of MICA compared to an existing MCC method. The method is then applied to two practical scenarios: four tissues of mouse metabolism-related transcriptomic studies, and three sources of estrogen treatment expression profiles. Detected biomarkers by MICA show intriguing biological insights and functional annotations. Additionally, we implemented MICA for single-cell RNA-Seq data for tumor progression biomarkers, highlighting critical roles of ribosomal function in the tumor microenvironment of triple-negative breast cancer and underscoring the potential of MICA for detecting novel therapeutic targets. The source code is available on Figshare at https://doi.org/10.6084/m9.figshare.27635436. Additionally, the R package can be installed directly from GitHub at https://github.com/jianzou75/MICA. Supplementary data are available at Bioinformatics online.

Abstract C016: Age dictates immune response within the tumor microenvironment of triple negative breast cancer

Abstract Age is the biggest risk factor for developing most forms of cancer. In breast cancer, over 50% of patients are over 60 years old; however, less than 25% of patients enrolled in clinical trials are in this age bracket. Furthermore, most mouse modeling is performed in young mice, meaning that from preclinical through clinical stages patients ages are not accurately reflected in trials designs. Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer with no targeted therapies, so many treatment strategies utilize chemotherapy in combination with immunotherapy – which relies on a functional immune response. It is well known that immune function declines as we age, and thus therapeutic responses may differ with age. It is yet unclear how the tumor immune microenvironment changes with age, and how this may impact therapeutic response. Here, we utilize a mouse model which mimics hallmarks of human immune aging to understand how age impacts TNBC immune responses to dictate disease progression and therapeutic response. Immunologically young (8 weeks old) and aged (∼12 months old) FVB mice were orthotopically injected with syngeneic Met1 TNBC cells. Once tumors became palpable, mice were treated with paclitaxel chemotherapy or vehicle control and/or anti-PDL1 immunotherapy to mimic first-line therapeutic strategies. Tumors grew significantly faster in young control mice compared to aged, but young mice had a more robust response to therapy. Notable, only young mice had a significant benefit of combo therapy over monotherapy alone. Despite aged mice having more circulating CD8+ and CD4+ T cells, tumors in aged mice had significantly more infiltration of CD8+ cytotoxic T cells and FOXP3+ inhibitory T-regulatory cells compared to young control mice, yet only tumors in young mice exhibited an increase in T cell infiltration with therapy. Additionally, the ratio of CD8+ T cells and FOXP3+ Tregs was unchanged with age or treatment. Depletion of either CD8+ or CD4+ T cells led to a complete loss of age-associated differences in tumor growth. RNA sequencing analysis suggests that infiltrating T cells in aged mice may be exhausted due to a chronic interferon (IFN) phenotype, indicated by enrichment of IFN-alpha, IFN-gamma, and IL2 pathways, as well as increased expression of immune exhaustion markers PD1, CTLA4, TIM3 and LAG3. Neutralization of IFN-gamma blocks therapeutic response to anti-PDL1 in young mice but has no impact on aged mice. Analysis of published single cell RNAseq data indicated the same IFN response pathways enriched with age in human TNBC. These results demonstrate that the aging tumor immune microenvironment significantly impacts tumor progression and therapeutic response and suggest that targeting IFN signaling may lead to improved therapeutic responses. Together these findings establish a significant impact of immune aging on TNBC disease progression and response to therapy, highlighting the importance of developing age- stratified treatment strategies to improve responses in patients of all ages. Citation Format: Milos Spasic, Adrienne Parsons, Abigail Recko, Elizabeth Mittendorf, Peter van Galen, Sandra McAllister. Age dictates immune response within the tumor microenvironment of triple negative breast cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr C016.

CSIG-08. AGGRESSIVE HIGH-GRADE NF2 MUTANT MENINGIOMAS DOWNREGULATE ONCOGENIC YAP SIGNALING VIA THE UPREGULATION OF VGLL4 AND FAT3/4

Abstract Meningiomas are the most common primary brain tumors in adults. Although generally benign, a subset is of higher grade, shows aggressive growth behavior and recurs even after multiple surgeries. Around half of all meningiomas harbor inactivating mutations in NF2. While benign low-grade NF2 mutant meningiomas exhibit few genetic events in addition to NF2 inactivation, aggressive high-grade NF2 mutant meningiomas frequently harbor a highly aberrant genome. We and others have previously shown that NF2 inactivation leads to YAP1 activation and that YAP1 acts as the pivotal oncogenic driver in benign NF2 mutant meningiomas. Using bulk and single-cell RNA-Seq data from a large cohort of human meningiomas, we show that aggressive NF2 mutant meningiomas harbor decreased levels YAP1 activity compared to their benign counterparts. Furthermore, decreased expression levels of YAP target genes are significantly associated with an increased risk of recurrence. We then identify the increased expression of the YAP1 competitor VGLL4 as well as the YAP1 upstream regulators FAT3/4 as a potential mechanism for the downregulation of YAP activity in aggressive NF2 mutant meningiomas. High expression of these genes is significantly associated with an increased risk of recurrence. In vitro, overexpression of VGLL4 resulted in the downregulation of YAP activity in benign NF2 mutant meningioma cells, confirming the direct link between VGLL4 expression and decreased levels of YAP activity observed in aggressive NF2 mutant meningiomas. Our results shed new insight on the biology of benign and aggressive NF2 mutant meningiomas and may have important implications for the efficacy of therapies targeting oncogenic YAP1 in NF2 mutant meningiomas.

TLR8 agonist selgantolimod regulates Kupffer cell differentiation status and impairs HBV entry into hepatocytes via an IL-6-dependent mechanism

ObjectiveAchieving HBV cure will require novel combination therapies of direct-acting antivirals and immunomodulatory agents. In this context, the toll-like receptor 8 (TLR8) agonist selgantolimod (SLGN) has been investigated in preclinical...

EPCO-20. MUTANT IDH INHIBITORS INDUCE LINEAGE DIFFERENTIATION IN IDH-MUTANT OLIGODENDROGLIOMA

Abstract IDH-mutant gliomas exhibit variable responses to mutant-IDH inhibitor (IDHi) therapy; yet, the molecular mechanisms underlying these responses remain poorly understood. Here, we investigate the cellular underpinnings of response by leveraging single cell/nuclei RNA-sequencing of on-treatment IDH-mutant oligodendroglioma tumor samples resected from three patients who benefited clinically from treatment. We integrate these findings with single cell and bulk RNA-seq data from independent cohorts and experimental models. We find that IDHi treatment promotes robust differentiation towards the astrocytic lineage, accompanied by stem-like cell depletion and reduced proliferation. Notably, NOTCH1 mutations are associated with impaired astrocytic differentiation, potentially negatively impacting response to IDHi. This study unveils the differentiating effects of IDHi on oligodendroglioma cellular hierarchies and identifies a potential genetic marker for optimizing patient selection. Paper was recently published in Cancer Cell (10.1016/j.ccell.2024.03.008).

EPCO-11. BIASES IN HEALTHY BRAIN SINGLE-CELL DATASETS: FINDING THE BEST COMPARISON FOR GLIOBLASTOMA STUDIES

Abstract Tumor cells undergo metabolic alterations that support their proliferation and simultaneously modify immune populations, resulting in an immunosuppressive tumor microenvironment. This study aims to compare the metabolic expression of immune cells within the tumor microenvironment to those in a healthy environment. However, there is a lack of single-cell transcriptomic data for normal brain cells, necessitating an analysis of different methods to compare immune cells in tumors with those in a healthy brain. To address this, we explored cell-to-cell metabolic variability using public single-cell RNA-seq (scRNA-seq) data of glioblastoma (n=338564), and from immune cells in the brains of post-mortem individuals (n=14177), fetuses (n=40000), and epilepsy patients (n=466), as well as from immune blood cells (n=329762). We employed ssGSEA to generate activity scores for 70 key metabolic pathways from KEGG for each individual cell. Known marker genes were utilized to identify normal cell populations (macrophages, T cells, oligodendrocytes) in datasets lacking cell type annotations. Our results revealed that blood cells exhibited high metabolic activity in macrophages but showed moderate activity in other cell types. Immune blood cells also demonstrated high oxidative phosphorylation (OXPHOS) but low fatty acid activity. Fetal brain cells displayed a lack of heterogeneity and showed high fatty acid activity with low OXPHOS activity. Brain cells from post-mortem individuals displayed heterogeneity but exhibited low metabolic activity across nearly all cells and pathways. Additionally, the hierarchy of pathway activity differed from the other datasets. Epilepsy data revealed a metabolic activity pattern similar to tumor-infiltrating immune cells, with comparable activity hierarchy and heterogeneity, although the sample size was limited for detailed comparison. Understanding the differences between types of datasets is important to choose the most appropriate comparison, allowing us to observe the metabolic alterations in immune cells caused by glioblastoma and to develop better immunotherapy strategies.

STEM-07. UNVEILING THE ROLE OF HYPOXIA AND TAM-SECRETED TGF-Β1 IN PROMOTING GLIOMA STEM CELL MAINTENANCE VIA YAP/TAZ ACTIVATION IN GLIOBLASTOMA PERI-NECROTIC NICHE

Abstract Glioblastoma (GBM) is a highly malignant brain tumor with rapid growth and poor outcomes. In the tumor microenvironment (TME), necrosis triggers significant reshaping and rapid progression, marked by tumor-associated macrophages (TAMs) and glioma stem cells (GSCs) accumulation in peri-necrotic zones. Analysis of Ivy-GAP and single-cell RNA-Seq data revealed consistent Hippo pathway activation in the hypoxic peri-necrotic zone, despite canonical stem-cell transcription factors such as SOX2, OLIG2, and FOXM1 not being upregulated. We hypothesize that Hippo transcription activation may promote GSC stemness via direct effects of hypoxia and/or TAM-secreted cytokines. Exposing patient-derived GBM neurospheres to 1% hypoxia increased nuclear YAP1 and TAZ expression, along with CYR61, a Hippo pathway readout, compared to normoxia at 48 hours. Single-cell RNA-Seq identified potential hypoxia-regulated genes upstream of YAP/TAZ, including Zyxin, upregulated in 1% hypoxia-treated cultures, possibly facilitating nuclear YAP/TAZ transport. Culturing GBM cells with primary macrophage-conditioned media activated Hippo transcription, with TGF-β1 identified as a hypoxia-specific driver of malignant cell gene expression with single-cell RNA-Seq analysis using NichenetR. Treating GBM cells with TGF-β1 increased CYR61 expression, signifying Hippo transcription activation. Furthermore, we showed that hypoxia and TGF-β1 synergistically maintained GSCs with extreme limiting dilution assays. In the immunocompetent RCAS/tv-a mouse model, Verteporfin, a YAP/TAZ inhibitor, significantly reduced tumor size and prolonged mouse lifespan. TAZ knockdown similarly extended lifespan and reduced tumor growth, with flow cytometry showing a decrease in CD133/CD44 positive GSC populations in knockdown mice. These findings suggest the conclusion that hypoxia and TAM-secreted TGF-β1 directly stimulate YAP/TAZ activation and potentially promote GSC stemness in the GBM peri-necrotic niche.

Bendamustine–rituximab elicits dual tumoricidal and immunomodulatory responses via cGAS–STING activation in diffuse large B-cell lymphoma

BackgroundBendamustine–rituximab (BR) therapy stands out as a promising alternative for elderly patients with diffuse large B-cell lymphoma (DLBCL), demonstrating notable efficacy when conventional regimens pose challenges. Despite its clinical success,...

Single-cell sequencing combined with transcriptomics and invivo and invitro analysis reveals the landscape offerroptosis in myocardial ischemia-reperfusion injury.

Myocardial ischemia-reperfusion injury (MIRI) is a significant risk factor for acute myocardial infarction and is closely associated with ferroptosis. This study aimed to identify key ferroptosis-related genes as potential diagnostic markers for MIRI and to explore their roles in immune infiltration and therapeutic targeting in myocardial tissue. We obtained single-cell RNA sequencing (scRNA-seq) and RNA-seq data on MIRI from the GEO database, applied Seurat and UMAP for data processing and clustering, and analyzed ligand-receptor interactions using CellPhoneDB. By scoring ferroptosis in cardiomyocytes, we identified differentially expressed genes and conducted GO and KEGG pathway analyses. A protein interaction network was then constructed using the STRING database, and seven key genes (Atp5h, Vdac2, Pkm, Cycs, Hspa8, Tpi1, Ldha) were identified through Lasso regression modeling, showing significant associations with immune responses. Invivo experiments in a mouse ischemia-reperfusion model confirmed the roles of these seven genes in MIRI via RT-qPCR. To further investigate the role of Hspa8 in ferroptosis and MIRI, siRNA knockdown experiments were performed in H9C2 rat cardiomyocytes, and its involvement in ferroptosis was validated by JC-1 staining and PCR analysis. This study reveals the importance of ferroptosis-related genes in MIRI through integrated bioinformatics and experimental approaches, offering new insights into diagnostic markers and immune-related therapeutic targets for MIRI.

Exploring Extracellular Vesicle Surface Protein Markers Produced by Glioblastoma Tumors: A Characterization Study Using In Vitro 3D Patient-Derived Cultures.

Glioblastoma (GBM) is an aggressive brain cancer with limited treatment options. Extracellular vesicles (EVs) derived from GBM cells contain important biomarkers, such as microRNAs, proteins, and DNA mutations, which are involved in tumor progression, invasion, and resistance to treatment. Identifying surface markers on these EVs is crucial for their isolation and potential use in noninvasive diagnosis. This study aimed to use tumor-derived explants to investigate the surface markers of EVs and explore their role as diagnostic biomarkers for GBM. Tumor explants from nine GBM patients without IDH1/IDH2 mutations or 1p-19q co-deletion were cultured to preserve both tumor viability and cytoarchitecture. EVs were collected from the tumor microenvironment using differential centrifugation, filtration, and membrane affinity binding. Their surface protein composition was analyzed through multiplex protein assays. RNA-Seq data from TCGA and GTEx datasets, along with in silico single-cell RNA-seq data, were used to assess EV surface biomarker expression across large GBM patient cohorts. The in vitro model successfully replicated the tumor microenvironment and produced EVs with distinct surface markers. Biomarker analysis in large datasets revealed specific expression patterns unique to GBM patients compared with healthy controls. These markers demonstrated potential as a GBM-specific signature and were correlated with clinical data. Furthermore, in silico single-cell RNA-seq provided detailed insights into biomarker distribution across different cell types within the tumor. This study underscores the efficacy of the tumor-derived explant model and its potential to advance the understanding of GBM biology and EV production. A key innovation is the isolation of EVs from a model that faithfully mimics the tumor's original cytoarchitecture, offering a deeper understanding of the cells involved in EV release. The identified EV surface markers represent promising targets for enhancing EV isolation and optimizing their use as diagnostic tools. Moreover, further investigation into their molecular cargo may provide crucial insights into tumor characteristics and evolution.

Joint representation and visualization of derailed cell states with Decipher.

Biological insights often depend on comparing conditions such as disease and health, yet we lack effective computational tools for integrating single-cell genomics data across conditions or characterizing transitions from normal to deviant cell states. Here, we present Decipher, a deep generative model that characterizes derailed cell-state trajectories. Decipher jointly models and visualizes gene expression and cell state from normal and perturbed single-cell RNA-seq data, revealing shared and disrupted dynamics. We demonstrate its superior performance across diverse contexts, including in pancreatitis with oncogene mutation, acute myeloid leukemia, and gastric cancer.

Recruitment of homodimeric proneural factors by conserved CAT-CAT E-boxes drives major epigenetic reconfiguration in cortical neurogenesis.

Proneural factors of the basic helix-loop-helix family coordinate neurogenesis and neurodifferentiation. Among them, NEUROG2 and NEUROD2 subsequently act to specify neurons of the glutamatergic lineage. Disruption of these factors, their target genes and binding DNA motifs has been linked to various neuropsychiatric disorders. Proneural factors bind to specific DNA motifs called E-boxes (hexanucleotides of the form CANNTG, composed of two CAN half sites on opposed strands). While corticogenesis heavily relies on E-box activity, the collaboration of proneural factors on different E-box types and their chromatin remodeling mechanisms remain largely unknown. Here, we conducted a comprehensive analysis using chromatin immunoprecipitation followed bysequencing (ChIP-seq) data for NEUROG2 and NEUROD2, along with time-matched single-cell RNA-seq, ATAC-seq and DNA methylation data from the developing mouse cortex. Our findings show that these factors are highly enriched in transiently active genomic regions during intermediate stages of neuronal differentiation. Although they primarily bind CAG-containing E-boxes, their binding in dynamic regions is notably enriched in CAT-CAT E-boxes (i.e. CATATG, denoted as 5'3' half sites for dimers), which undergo significant DNA demethylation and exhibit the highest levels of evolutionary constraint. Aided by HT-SELEX data reanalysis, structural modeling and DNA footprinting, we propose that these proneural factors exert maximal chromatin remodeling influence during intermediate stages of neurogenesis by binding as homodimers to CAT-CAT motifs. This study provides an in-depth integrative analysis of the dynamic regulation of E-boxes during neuronal development, enhancing our understanding of the mechanisms underlying the binding specificity of critical proneural factors.

Liver transcriptome analysis reveals PSC-attributed gene set associated with fibrosis progression

BackgroundPrimary Sclerosing Cholangitis (PSC) is a chronic heterogenous cholangiopathy with unknown etiology where chronic inflammation of the bile ducts leads to multifocal biliary strictures and biliary fibrosis with consecutive cirrhosis development. We here aimed to identify a PSC-specific gene signature associated with biliary fibrosis development. MethodsWe performed RNA-sequencing of 47 liver biopsies from people with PSC (n = 16), primary biliary cholangitis (PBC, n = 15), and metabolic dysfunction-associated steatotic liver disease (MASLD, n = 16) with different fibrosis stages to identify a PSC-specific gene signature associated with biliary fibrosis progression. For validation, we compared an external transcriptome data set of liver biopsies from people with PSC (n = 73) with different fibrosis stages (DOI: 10.1002/hep.31488; baseline samples from NCT01672853). ResultsDifferential gene expression analysis of the liver transcriptome from PSC patients with advanced versus early fibrosis revealed 431 genes associated with fibrosis development. Of those, 367 were identified as PSC-associated when compared to PBC or MASLD. Validation against an external data set of 73 liver biopsies from PSC patients with different fibrosis stages led to a condensed set of 150 (out of 367) DEGs. Cell type specificity assignment of those genes by using published single cell RNA-seq data revealed genetic disease drivers expressed by cholangiocytes (e.g. CXCL1, SPP1), fibroblasts, innate and adaptive immune cells while deconvolution along fibrosis progression of the PSC, PBC, MASLD samples highlighted an early involvement of macrophage- and neutrophil-associated genes in PSC fibrosis. ConclusionWe reveal a PSC-attributed gene signature associated with biliary fibrosis development that may enable the identification of potential new biomarkers and therapeutic targets in PSC-related fibrogenesis. IMPACT AND IMPLICATIONSPrimary sclerosing cholangitis (PSC) is an inflammatory liver disease that is characterized by multifocal inflammation of bile ducts and subsequent biliary fibrosis. Herein, we identify a PSC-specific gene set of biliary fibrosis progression attributing to a uniquely complex milieu of different cell types, including innate and adaptive immune cells while neutrophils and macrophages showed an earlier involvement in fibrosis initiation in PSC in contrast to PBC and MASLD. Thus, our unbiased approach lays an important groundwork for further mechanistic studies for research into PSC-specific fibrosis.