Spatial Transcriptomics Research Articles

Multi-omics Analysis Reveals the Propagation Mechanism of Ferroptosis in Acute Kidney Injury.

Acute kidney injury (AKI) is a prevalent and critical clinical condition characterized by high morbidity and mortality. Recently, numerous studies have implicated ferroptosis, an iron-dependent programmed cell death process, in the pathophysiology of AKI. Despite this, the mechanism underlying the widespread occurrence of ferroptosis in AKI remains elusive. To address this, our study analyzed snRNA-seq data from AKI and healthy renal tissues. The analysis revealed notable differences in ferroptosis activity within proximal tubule (PT) cells of AKI patients, specifically highlighting a strong correlation between ferroptosis and the expression of genes GPX4, FTH1, and FTL. Spatial transcriptomics confirmed that the genes GPX4, FTH1, and FTL play a crucial role in driving ferroptosis propagation in AKI. Furthermore, utilizing a mouse model of bilateral renal ischemia-reperfusion injury, we validated the emergence of ferroptosis mediated by these key genes following AKI. The findings from our in vivo experiments were consistent with the spatial transcriptomics data. Chromatin accessibility and transcription factor analysis identified KLF6 as a repressor of ferroptosis-related genes. An in-depth analysis of PT revealed a subpopulation closely associated with ferroptosis. The cellular microenvironment within this subpopulation may regulate ferroptosis through the SPP1 signaling pathway, ultimately influencing the outcome of PT following AKI. In conclusion, this study elucidates the crucial role of GPX4, FTH1, and FTL in ferroptosis propagation during AKI and underscores the potential therapeutic benefits of targeting ferroptosis in the management of AKI.

Single-cell and spatial transcriptomics reveals an anti-tumor neutrophil subgroup in microwave thermochemotherapy-treated lip cancer

Microwave thermochemotherapy (MTC) has been applied to treat lip squamous cell carcinoma (LSCC), but a deeper understanding of its therapeutic mechanisms and molecular biology is needed. To address this, we used single-cell transcriptomics (scRNA-seq) and spatial transcriptomics (ST) to highlight the pivotal role of tumor-associated neutrophils (TANs) among tumor-infiltrating immune cells and their therapeutic response to MTC. MNDA+ TANs with anti-tumor activity (N1-phenotype) are found to be abundantly infiltrated by MTC with benefit of increased blood perfusion, and these TANs are characterized by enhanced cytotoxicity, ameliorated hypoxia, and upregulated IL1B, activating T&NK cells and fibroblasts via IL1B-IL1R. In this highly anti-tumor immunogenic and hypoxia-reversed microenvironment under MTC, fibroblasts accumulated in the tumor front (TF) can recruit N1-TANs via CXCL2-CXCR2 and clear N2-TANs (pro-tumor phenotype) via CXCL12-CXCR4, which results in the aggregation of N1-TANs and extracellular matrix (ECM) deposition. In addition, we construct an N1-TANs marker, MX2, which positively correlates with better prognosis in LSCC patients, and employ deep learning techniques to predict expression of MX2 from hematoxylin-eosin (H&E)-stained images so as to conveniently guide decision making in clinical practice. Collectively, our findings demonstrate that the N1-TANs/fibroblasts defense wall formed in response to MTC effectively combat LSCC.

Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer

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.

INHBA+ macrophages and Pro-inflammatory CAFs are associated with distinctive immunosuppressive tumor microenvironment in submucous Fibrosis-Derived oral squamous cell carcinoma

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.

STCC enhances spatial domain detection through consensus clustering of spatial transcriptomics data.

The rapid advance of spatially resolved transcriptomics technologies has yielded substantial spatial transcriptomics data. Deriving biological insights from these data poses nontrivial computational and analysis challenges, of which the most fundamental step is spatial domain detection (or spatial clustering). Although a number of tools for spatial domain detection have been proposed in recent years, their performance varies across data sets and experimental platforms. It is thus an important task to take full advantage of different tools to get a more accurate and stable result through consensus strategy. In this work, we developed STCC, a novel consensus clustering framework for spatial transcriptomics data that aggregates outcomes from state-of-the-art tools using a variety of consensus strategies, including Onehot-based, average-based, hypergraph-based, and wNMF-based methods. Comprehensive assessments on simulated and real data from distinct experimental platforms show that consensus clustering significantly improves clustering accuracy over individual methods under varied input parameters. For normal tissue samples exhibiting clear layered structure, consensus clustering by integrating multiple baseline methods leads to improved results. Conversely, when analyzing tumor samples that display scattered cell type distribution patterns, integration of a single baseline method yields satisfactory performance. For consensus strategies, average-based and hypergraph-based approaches demonstrate optimal precision and stability. Overall, STCC provides a scalable and practical solution for spatial domain detection in spatial transcriptomics data, laying a solid foundation for future research and applications in spatial transcriptomics.

High-resolution spatial transcriptomics and cell lineage analysis reveal spatiotemporal cell fate determination during craniofacial development

The differentiation of post-migratory cranial neural crest cells (CNCCs) into distinct mesenchymal lineages is crucial for craniofacial development. Here we report a high-resolution spatiotemporal transcriptomic and cell-type atlas of CNCC-derived mesenchymal lineage diversification during mouse palatogenesis. We systematically defined each mesenchymal cell type by mapping their transcriptomic profiles to spatial identities. Integrative analysis of spatial transcriptomic data from E12.5 to E15.5 further revealed mesenchymal lineage establishment at or prior to initiation of palatogenesis. We also identified a heterogeneous Sox9+ mesenchymal progenitor population at the onset of palatal development, with subpopulations already activating early lineage-specific markers. In vivo lineage tracing using these early lineage-specific markers demonstrated that distinct mesenchymal populations are established as early as E10.5 to E11.5, preceding palatal development, and contribute to their respective lineages. Together, our findings reveal the comprehensive, dynamic molecular and cellular landscape of palate development and shed light on cell fate regulation during embryogenesis.

Major Facilitator Superfamily (MFS) transporters balance sugar metabolism in peach.

Sugar content is a key determinant of peach (Prunus persica) fruit quality, influencing taste, consumer preferences, and market value. However, the roles of Major Facilitator Superfamily (MFS) transporters in sugar metabolism and regulation remain largely unexplored. This study employed a combination of spatial metabolomics, quantitative genetics, transcriptomics, comparative genomics, and functional genomics to investigate the role of 67 MFS members in balancing sugar metabolism during peach fruit development. Spatial metabolomics revealed dynamic sugar distribution patterns, with ERD6-like transporters (PpERDL16-1) and tonoplastic sugar transporters 1 (PpTST1) promoting sucrose accumulation and Polyol/monosaccharide transporters 5 (PpPMT5-1) and sucrose transporters 4 (PpSUT4) reducing sucrose transport during fruit ripening. Functional studies confirmed these roles: PpERDL16-1 overexpression enhanced sucrose transport, and PpPMT5-1 or PpSUT4 silencing reduced sugar levels in peach fruit. Quantitative trait locus (QTL) mapping identified a major locus on chromosome 5, upstream of PpTST1, forming distinct haplotypes (Hap1 and Hap2). Hap1 was associated with lower PpTST1 expression and higher sugar and soluble solids content (SSC), while Hap2 was linked to higher PpTST1 expression and lower sugar content. This inverse relationship suggests that upstream genetic variants fine-tune PpTST1 expression in a context-dependent manner, potentially through interactions with transcription factors or epigenetic modifiers. Notably, PpTST1 overexpression increased sugar content but did not alter SSC, indicating compensatory mechanisms such as changes in organic acid metabolism or water content. These results illuminate the molecular mechanisms regulating sugar homeostasis in peach fruits, providing valuable targets for the genetic improvement of fruit quality through breeding programs.

Gas Bubbles from Biodegradable Magnesium Implants Convey Mechanical Cues and Promote Immune Cell Stimulation

AbstractIn ever‐increasing numbers, patients are treated with biodegradable magnesium implants. While gas bubbles frequently arise in soft tissue overlying magnesium implants, their biological implications remain uncertain. This study investigates how bubble accumulation and evolution across various biological lengths and time scales influence adjacent tissue and cell behavior in rats. Bubbles accumulate in tissues around magnesium during initial postimplantation days, then fully resorb. Alterations in tissue and cell geometry around bubbles coincide with accumulation of cells, many with macrophage phenotypes, and increased expression of the mechanosensitive ion‐channel Piezo1. Using spatially resolved transcriptomics, strong proinflammatory pathway activation is revealed near bubbles with marked expression of the proliferative macrophage marker secreted phosphoprotein 1 (Spp1). Spatial transcriptomics also reveals strong enrichment of cytoskeletal rearrangement genes, demonstrating that cells respond to mechanical cues from bubbles. Notably, both time and bubble–implant distance strongly influence the cellular response. Over time, as bubbles are located farther from the implant, regenerative processes decline, and inflammation predominates. These findings suggest that bubbles from magnesium implant degradation create an intricate local response influencing tissue healing through inflammatory and mechanical pathways. This study underscores the need for magnesium implants with controlled gas release and meticulous monitoring of bubble evolution in patients.

Mapping the molecular signature of ABA-regulated gene expression in germinating barley embryos

BackgroundAbscisic acid (ABA) regulates key plant processes, including seed germination, dormancy, and abiotic stress responses. While its physiological role in germination is well-documented, the molecular mechanisms are still poorly understood. To address this, we analyzed transcriptomic and metabolomic changes in ABA-treated germinating barley (Hordeum vulgare) embryos. To map ABA-responsive gene expression across embryonic tissues, we employed the Visium Spatial Transcriptomics (10× Genomics). This approach, which remains technically challenging to be applied in plant tissues, enabled the precise localization of gene expression across six embryo regions, offering insights into tissue-specific expression patterns that cannot be resolved by traditional RNA-seq.ResultsTranscriptomic analysis indicated that ABA acts primarily as a germination repressor. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses linked ABA-inhibited genes to energy metabolism, lignin biosynthesis, cell wall organization, and photosynthesis, while induced genes were associated with environmental adaptation and phytohormone signaling. Differentially expressed genes (DEGs) correlated with metabolites involved in phytohormone pathways, including gibberellins, jasmonates, brassinosteroids, salicylic acid, auxins, and ABA metabolism. Comparisons with developing seed transcriptomes suggested an ABA-associated gene expression signature in embryos. Spatial transcriptomics technique made possible the precise identification of ABA-induced transcriptional changes within distinct embryonic tissues.ConclusionsIntegrating transcriptomics, metabolomics and spatial transcriptomics defined the molecular signature of ABA-induced modulation of phytohormonal crosstalk, energy metabolism, and tissue-specific gene activity in germinating seeds. The successful use of spatial transcriptomics adds a novel layer of resolution for understanding tissue-specific ABA responses during barley seed germination. These findings offer new insights into the ABA role in seed germination and potential strategies for enhancing crop resilience.

Perspective on recent developments and challenges in regulatory and systems genomics

Abstract Predicting how genetic variation affects phenotypic outcomes at the organismal, cellular, and molecular levels requires deciphering the cis-regulatory code, the sequence rules by which non-coding regions regulate genes. In this perspective, we discuss recent computational progress and challenges towards solving this fundamental problem. We describe how cis-regulatory elements are mapped with various genomics assays and how studies of the 3D chromatin organization could help identifying long-range regulatory effects. We discuss how the cis-regulatory sequence rules can be learned and interpreted with sequence-to-function neural networks, with the goal of identifying genetic variants in human disease. We also describe current methods for mapping gene regulatory networks to describe biological processes. We point out current gaps in knowledge along with technical limitations and benchmarking challenges of computational methods. Finally, we discuss newly emerging technologies, such as spatial transcriptomics, and outline strategies for creating a more general model of the cis-regulatory code that is more broadly applicable across cell types and individuals.

Single-cell and spatial transcriptomics reveal correlation between RNA methylation-related miRNA risk model and immune infiltration in hepatocellular carcinoma

IntroductionIncreasing evidence highlights the pivotal role of RNA methylation and miRNAs in hepatocellular carcinoma (HCC). However, the risk associated with RNA methylation-related miRNAs (RMRMs) in the HCC immune microenvironment remains largely unknown. Here, we predicted the correlation between RMRM risk and immune cell infiltration in HCC using machine learning. MethodsMiRNA sequencing data was used to identify RMRMs. A risk score model of HCC was developed utilizing four RMRMs, including miR-551a, miR-4739, miR-326, and miR-210-3p.ResultsPatients with high-risk scores exhibited poorer prognoses. Single-cell RNA sequencing (scRNA-seq) analysis revealed the high-risk group exhibited increased infiltration levels of several immune cell subtypes, including myeloid-derived suppressor cell (MDSC), macrophage, and T cells. The data integration of scRNA-seq and bulk RNA-seq showed the decreased TIDE score in the high-risk patients and the elevated levels of Macro-secreted phosphoprotein 1 (SPP1), MDSC-meiotic nuclear divisions 1 (MND1), γδ T cells, and Macro-complement C1q C chain (C1QC) predicted adverse prognosis. ScRNA-seq and spatial transcriptomics data integration unveiled the spatial distribution of RMRMs risk scores and their correlation with immune cell subtype localization. Risk model-based clustering of HCC samples revealed that cluster 2, characterized by a higher risk score, correlated with a poorer prognosis and reduced immune and stromal scores. In vitro, the overexpression of miR-4739 in Huh-7 cells significantly induced SPP1+ macrophages, and the culture medium derived from SPP1+ macrophages further promoted the proliferation and migration of Huh-7 cells. Furthermore, miR-4739 reduced m1A methylation by inhibiting tRNA methyltransferase 61A (TRMT61A) expression. DiscussionOur study reveals that the RMRM risk model could effectively predict the prognosis of HCC, and SPP1+ macrophages regulated by miR-4739-RNA methylation promote the proliferation and migration of HCC cells. These results highlight the potential of RMRMs in predicting the prognosis of HCC.

Single-cell, single-nucleus, and spatial transcriptomics reveal the cellular atlas and developmental mechanisms of aldosterone-producing micronodules and adenomas

Single-cell, single-nucleus, and spatial transcriptomics reveal the cellular atlas and developmental mechanisms of aldosterone-producing micronodules and adenomas

Hypoxia-induced RHCG as a key regulator in psoriasis and its modulation by secukinumab.

The interaction between keratinocytes (KCs) and immune cells is essential in the pathogenesis of psoriasis. Understanding this crosstalk is crucial for developing effective treatment strategies. Recent studies indicate that Rh family C-type glycoprotein (RHCG) enhances cell proliferation and alters cell differentiation; however, its exact pathogenic mechanisms in psoriasis remain unclear. We employed bioinformatics approaches, including spatial transcriptomics analysis, single-cell transcriptomics analysis, and bulk data analysis, to elucidate the biological functions of RHCG. These predictions were validated through ex vivo experiments and analysis of clinical specimens. In psoriatic skin, RHCG protein levels were significantly upregulated, with an expanded expression area. Notably, RHCG expression was induced under hypoxic conditions. Furthermore, the upregulation of RHCG enhanced the expression of KC markers S100 Calcium Binding Protein A family (S100A) and Keratin 17 (KRT17), while decreasing Keratin 1 (KRT1) expression. Additionally, RHCG overexpression increased the secretion of C-X-C motif chemokine ligand 14 (CXCL14) from KCs, which subsequently activated dendritic cells. Importantly, treatment with secukinumab effectively ameliorated psoriasis by downregulating RHCG expression and inhibiting associated signaling pathways, whereas glucocorticoid and methotrexate treatments resulted in elevated RHCG expression. These findings indicate that RHCG plays a significant role in hypoxia-induced cellular crosstalk and suggest that RHCG-associated signaling may contribute to the superior efficacy of biological agents compared to conventional hormonal and immunosuppressive therapies.

Spatially resolved transcriptomic profiling for glomerular and tubulointerstitial gene expression in C3 glomerulopathy

Abstract Background C3 glomerulopathy (C3G) is a rare but clinically significant glomerulopathy. However, little is known about its transcriptomic profile. We investigated the substructure-specific gene expression profile of C3G using the recently introduced spatial transcriptomics technology. Methods We performed spatial transcriptomic profiling using GeoMx Digital Spatial Profiler with formalin-fixed paraffin-embedded kidney biopsy specimens of three C3G cases and seven controls from donor kidney biopsy. Additionally, 41 samples of other glomerulonephritis, including focal segmental glomerulosclerosis, membranous nephropathy, and minimal change disease, were included as disease controls. We identified differentially expressed genes (DEGs) specific to C3G, followed by in vitro validation analysis of consistently upregulated DEGs in human glomerular endothelial cells through a co-culture with complement-stimulated macrophages. Results We found 229 and 157 highly expressed DEGs in the glomeruli of C3G compared to those of donor and disease controls, respectively, including POSTN, COL1A2, and IFI44L. Protease binding, structural molecule activity, and extracellular matrix structural constituent were among the top enriched gene ontology terms in the glomeruli of C3G. Specifically, genes related to the extracellular matrix and interferon activity were the most upregulated, with network analysis suggesting possible interactions between complement C3 and the extracellular matrix through CD11c. The in vitro experimental validation using iC3b-stimulated CD11c + macrophages supported these findings, inducing elevated expression of fibrosis markers and extracellular matrix components in glomerular endothelial cells. Conclusions Significant disease-specific transcriptomic alterations in C3G, including upregulation of genes related to the extracellular matrix, provide potential insights into the pathophysiology.

Hepatic stellate cell heterogeneity: Functional aspects and therapeutic implications.

Hepatic stellate cell heterogeneity: Functional aspects and therapeutic implications.

Identification of Prognostic Biomarkers of Ovarian High-Grade Serous Carcinoma: A Preliminary Study Using Spatial Transcriptome Analysis and Multispectral Imaging

Ovarian cancer is a lethal malignancy, with most patients initially responding to chemotherapy but frequently experiencing recurrence. Previous studies primarily examined tumor characteristics using limited genetic markers or bulk RNA sequencing. Here, we used spatial transcriptomics via the GeoMx® platform, alongside multispectral immune cell immunofluorescence (IF), to identify biomarkers associated with disease progression following first-line treatment of high-grade serous carcinoma (HGSC). We identified several spatial biomarkers linked to non-recurrence, including elevated NKG7 expression in CD45+ immune cell regions (p = 0.0011) and higher TFPI2 and PIGR expression in tumor areas (p = 2.09 × 10−6), both associated with improved progression-free survival. Multispectral IF revealed significantly higher regulatory T cell (Treg) to CD8+ T cell ratios in the tumor nests and stroma of recurrent patients (p = 0.016, 0.048). Tregs were also found closer to cancer cells or macrophages than CD8+ T cells in recurrent tumors (p = 0.048), correlating with poor survival. Integrated analysis showed that immune cell density and immune pathway scores in the recurrent group positively correlated with cancer pathway scores, except for NF-κB. This comprehensive analysis revealed clues to interactions between different immune cells and identified biomarkers that may be useful for predicting recurrence of HGSC.

Unraveling Tissue Complexity Through Single-Cell and Spatial Transcriptomics.

Unraveling Tissue Complexity Through Single-Cell and Spatial Transcriptomics.

Integrated analysis of MIOX gene in prognosis of clear-cell renal cell carcinoma

Clear-cell renal cell carcinoma (ccRCC) is a highly aggressive malignancy that originates in the kidney. It often exhibits a limited response or can be refractory to a wide range of anti-cancer therapies, including tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors. Ferroptosis is a form of oxidative, iron-dependent cell death characterized by lipid peroxidation. Targeting ferroptosis may offer a promising alternative therapeutic strategy for cancer cells that are resistant to existing treatments. The impact of ferroptosis-related genes on the prognosis of ccRCC patients is still not fully understood. In this study, we identified 30 differentially expressed ferroptosis-related genes in ccRCC samples compared to normal tissues using data from The Cancer Genome Atlas (TCGA). Lasso regression analyses, along with Kaplan-Meier analysis, were conducted to identify genes associated with prognosis. Based on scRNA-seq and spatial transcriptome analysis, we identified specificity of MIOX in ccRCC. Furthermore, MIOX demonstrated the highest significance, highlighting its independent prognostic value as a single gene in ccRCC. Our findings suggest that MIOX could serve as potential targets for therapeutic interventions in ccRCC.

DDX24 spatiotemporally orchestrates VEGF and Wnt signaling during developmental angiogenesis

Vascular development is a precisely controlled process, yet how it is spatiotemporally orchestrated remains enigmatic. We previously identified DEAD-box RNA helicase 24 (DDX24) as a pathogenic gene for multiorgan vascular anomalies. Here, we show that DDX24 is expressed in the endothelium during embryonic angiogenesis in zebrafish. DDX24 deficiency causes intersegmental vessel hyperbranching in the trunk, but inhibits central artery angiogenesis in the brain. Mechanistically, DDX24 deficiency enhances VEGFR2 expression by direct binding to its mRNA in nonbrain endothelial cells (ECs), while suppressing GPR124/RECK-mediated Wnt signaling in brain ECs. Additionally, spatial transcriptome analysis profiles DDX24-mediated crosstalk between ECs and neighboring cells. Finally, pharmacological targeting of these two pathways in a temporal manner can rescue the phenotypes induced by DDX24 deficiency. Overall, our findings highlight an essential role for DDX24 in the spatiotemporal regulation of developmental angiogenesis.

ABCC3 Is a Differential Marker of CYP11B2-Negative Zona Glomerulosa Cells in Human Adrenal Cortex.

ATP Binding Cassette Subfamily C Member 3 (ABCC3) is a membrane transporter that exports diverse compounds, influencing drug resistance in cancers and impacting metabolic and malignant diseases. We previously reported ABCC3 upregulation in human adrenal cells under lipid peroxidation-induced oxidative stress. We investigated ABCC3 expression and function in the human adrenal cortex in the context of primary aldosteronism, focusing on its relationship to CYP11B2 (aldosterone synthase) in zona glomerulosa (ZG) cells and aldosterone-producing lesions. ABCC3 expression in aldosterone-producing adenomas (APAs) was markedly reduced compared to the adjacent adrenal cortex, cortisol-producing adenomas, and non-functioning adenomas. The reduction in APAs showed genotypic variability: in APAs harboring KCNJ5 mutations-known drivers of autonomous aldosterone production via altered potassium channel function-ABCC3 mRNA/protein levels were significantly higher than in wild-type KCNJ5 APAs. Spatial transcriptomics and immunofluorescence colocalization revealed an inverse expression pattern between ABCC3 and CYP11B2 (aldosterone synthase) in APAs and aldosterone-producing micronodules (APMs). Notably, high ABCC3 expression was exclusively observed in adrenal ZG cells that lacked CYP11B2 expression. This expression pattern distinguishes ABCC3 from common ZG markers such as KCNJ5 and DAB2, which are expressed across adrenal ZG cells, APMs, and APA tumor cells. In cultured human adrenocortical cells, both angiotensin II stimulation and induced expression of the KCNJ5-L168R mutation resulted in upregulation of CYP11B2 transcription while concomitantly suppressing ABCC3 expression. In conclusion, ABCC3 serves as a novel marker of CYP11B2-negative ZG cells, providing a histopathological tool to differentiate normal adrenal zonation from aldosterone-producing lesions in primary aldosteronism, as well as from cortisol-producing and nonfunctional adenomas.