Spatial Transcriptomics Research Articles

344.1: Single-cell and spatial transcriptomics elucidate Spp1/Cd44-mediated tubular damage and neutrophil migration in acute kidney injury.

344.1: Single-cell and spatial transcriptomics elucidate Spp1/Cd44-mediated tubular damage and neutrophil migration in acute kidney injury.

Abstract P205: Single-nucleus Sequencing Reveals Endothelial Cell-specific Dysregulation in the Kidney in Multiple Models of Hypertension

The kidney plays a crucial role in the onset and progression of hypertension. To investigate the roles of different renal cell types in hypertension, we applied single-nucleus sequencing and spatial transcriptome sequencing to kidney samples from three well-established hypertension models: C57BL/6 mice treated with Ang II, the Dahl salt-sensitive (SS) rat on high-salt diets, and the spontaneously hypertensive rat (SHR), along with their respective controls including Sprague-Dawley (SD) and Wistar Kyoto (WKY) rats. Our dataset comprised 179,637 nuclei from 24 samples across 12 experimental conditions, identifying 17 major cell types including various epithelial cells, endothelial cells, vascular smooth muscle cells, fibroblasts, and immune cells. At baseline, differentially expressed genes between the SS and SD groups were specifically enriched in endothelial cell pathways related to vascular development. This included expression deficiencies in genes involved in angiogenesis in SS rats, such as Arhgap24 and Nox4. Compensatory expression changes in these genes were observed in the SS rats after a high-salt diet and in 26-week-old SHR, but not in their respective controls. These genes were also associated with multiple blood pressure-associated single-nucleotide polymorphisms (SNPs). Furthermore, changes in endothelial cell communication were most prominent upon stimuli, with impaired PTPRM (Protein Tyrosine Phosphatase Receptor Type M) signaling being a robust feature in hypertension models, involving angiogenic endothelial cells in the SS model and proliferating capillary endothelial cells in the SHR model. Our study highlights the critical role of renal endothelial cell angiogenic dysfunction in the pathogenesis of hypertension and suggests a link between specific renal endothelial cell subtype dysregulation and hypertension development.

Predicting spatially resolved gene expression via tissue morphology using adaptive spatial GNNs.

Spatial transcriptomics technologies, which generate a spatial map of gene activity, can deepen the understanding of tissue architecture and its molecular underpinnings in health and disease. However, the high cost makes these technologies difficult to use in practice. Histological images co-registered with targeted tissues are more affordable and routinely generated in many research and clinical studies. Hence, predicting spatial gene expression from the morphological clues embedded in tissue histological images provides a scalable alternative approach to decoding tissue complexity. Here, we present a graph neural network based framework to predict the spatial expression of highly expressed genes from tissue histological images. Extensive experiments on two separate breast cancer data cohorts demonstrate that our method improves the prediction performance compared to the state-of-the-art, and that our model can be used to better delineate spatial domains of biological interest. https://github.com/song0309/asGNN/.

Inactivated cGAS-STING Signaling Facilitates Endocrine Resistance by Forming a Positive Feedback Loop with AKT Kinase in ER+HER2- Breast Cancer.

Endocrine-resistant ER+HER2- breast cancer (BC) is particularly aggressive and leads to poor clinical outcomes. Effective therapeutic strategies against endocrine-resistant BC remain elusive. Here, analysis of the RNA-sequencing data from ER+HER2- BC patients receiving neoadjuvant endocrine therapy and spatial transcriptomics analysis both show the downregulation of innate immune signaling sensing cytosolic DNA, which primarily occurs in endocrine-resistant BC cells, not immune cells. Indeed, compared with endocrine-sensitive BC cells, the activity of sensing cytosolic DNA through the cGAS-STING pathway is attenuated in endocrine-resistant BC cells. Screening of kinase inhibitor library show that this effect is mainly mediated by hyperactivation of AKT1 kinase, which binds to kinase domain of TBK1, preventing the formation of a trimeric complex TBK1/STING/IRF3. Notably, inactivation of cGAS-STING signaling forms a positive feedback loop with hyperactivated AKT1 to promote endocrine resistance, which is physiologically important and clinically relevant in patients with ER+HER2- BC. Blocking the positive feedback loop using the combination of an AKT1 inhibitor with a STING agonist results in the engagement of innate and adaptive immune signaling and impairs the growth of endocrine-resistant tumors in humanized mice models, providing a potential strategy for treating patients with endocrine-resistant BC.

OS02-09 Spatial transcriptomics reveals proximal tubular ER stress in alcohol-induced renal toxicity

OS02-09 Spatial transcriptomics reveals proximal tubular ER stress in alcohol-induced renal toxicity

Microglia LILRB4 upregulation reduces brain damage after acute ischemic stroke by limiting CD8+ T cell recruitment

BackgroundLeukocyte immunoglobulin-like receptor B4 (LILRB4) plays a significant role in regulating immune responses. LILRB4 in microglia might influence the infiltration of peripheral T cells. However, whether and how LILRB4 expression aggravates brain damage after acute ischemic stroke remains unclear. This study investigates the role of LILRB4 in modulating the immune response and its potential protective effects against ischemic brain injury in mice.Methods and resultsMicroglia-specific LILRB4 conditional knockout (LILRB4-KO) and overexpression transgenic (LILRB4-TG) mice were constructed by a Cre-loxP system. Then, they were used to investigate the role of LILRB4 after ischemic stroke using a transient middle cerebral artery occlusion (tMCAO) mouse model. Spatial transcriptomics analysis revealed increased LILRB4 expression in the ischemic hemisphere. Single-cell RNA sequencing (scRNA-seq) identified microglia-cluster3, an ischemia-associated microglia subcluster with elevated LILRB4 expression in the ischemic brain. Flow cytometry and immunofluorescence staining showed increased CD8+ T cell infiltration into the brain in LILRB4-KO-tMCAO mice. Behavioral tests, cortical perfusion maps, and infarct size measurements indicated that LILRB4-KO-tMCAO mice had more severe functional deficits and larger infarct sizes compared to Control-tMCAO and LILRB4-TG-tMCAO mice. T cell migration assays demonstrated that LILRB4-KD microglia promoted CD8+ T cell recruitment and activation in vitro, which was mitigated by CCL2 inhibition and recombinant arginase-1 addition. The scRNA-seq and spatial transcriptomics identified CCL2 was predominantly secreted from activated microglia/macrophage and increased CCL2 expression in LILRB4-KD microglia, suggesting a chemokine-mediated mechanism of LILRB4.ConclusionLILRB4 in microglia plays a crucial role in modulating the post-stroke immune response by regulating CD8+ T cell infiltration and activation. Knockout of LILRB4 exacerbates ischemic brain injury by promoting CD8+ T cell recruitment. Overexpression of LILRB4, conversely, offers neuroprotection. These findings highlight the therapeutic potential of targeting LILRB4 and its downstream pathways to mitigate immune-mediated damage in ischemic stroke.

Spatial Transcriptomics Analysis: Maternal Obesity Impairs Myogenic Cell Migration and Differentiation during Embryonic Limb Development.

Limb muscle is responsible for physical activities and myogenic cell migration during embryogenesis is indispensable for limb muscle formation. Maternal obesity (MO) impairs prenatal skeletal muscle development, but the effects of MO on myogenic cell migration remain to be examined. C57BL/6 mice embryos were collected at E13.5. The GeoMx DSP platform was used to customize five regions along myogenic cell migration routes (myotome, dorsal/ventral limb, limb stroma, limb tip), and data were analyzed by GeomxTools 3.6.0. A total of 2224 genes were down-regulated in the MO group. The GO enrichment analysis showed that MO inhibited migration-related biological processes. The signaling pathways guiding myogenic migration such as hepatocyte growth factor signaling, fibroblast growth factor signaling, Wnt signaling and GTPase signaling were down-regulated in the MO E13.5 limb tip. Correspondingly, the expression levels of genes involved in myogenic cell migration, such as Pax3, Gab1, Pxn, Tln2 and Arpc, were decreased in the MO group, especially in the dorsal and ventral sides of the limb. Additionally, myogenic differentiation-related genes were down-regulated in the MO limb. MO impedes myogenic cell migration and differentiation in the embryonic limb, providing an explanation for the impairment of fetal muscle development and offspring muscle function due to MO.

Re-analysis of single cell and spatial transcriptomics data reveals B cell landscape in gastric cancer microenvironment and its potential crosstalk with tumor cells for clinical prognosis

BackgroundAt present, immunotherapy has become a powerful treatment for advanced gastric cancer (AGC), but not all patients can benefit from it. According to the latest research, the impact of B cell subpopulations on the immune microenvironment of gastric cancer (GC) is unknown. Exploring whether the interaction between B cells and tumor cells in GC affects the effectiveness of immunotherapy has attracted our interest.MethodsThis study involved the re-analysis of single-cell RNA (scRNA) and spatial transcriptomics (ST) data from publicly available datasets. The focus was on investigating the subpopulations and differentiation trajectories of B cells in the gastric cancer (GC) tumor immune microenvironment (TIME). Spatial transcriptomics (ST) and multiple immunofluorescence (mIF) revealed a clear co-localization pattern between B cells and tumor cells. Multiple immunotherapy datasets were collected to identify unique immunotherapy biomarkers. The unique immunotherapeutic potential of targeting CCL28 was validated through a mouse gastric cancer model. In addition, flow cytometry revealed changes in the tumor immune microenvironment targeting CCL28.ResultsThe re-analysis of ST data from multiple cancer types revealed a co-localization pattern between B cells and tumor cells. A significant number of IgA plasma cells were identified in the GC TIME. Five different tumor-infiltrating B cell subpopulations and two unique B cell differentiation trajectories were characterized, along with seven GC-related states. By analyzing the communication between GC cells and B cells, it was further discovered that tumor cells can influence and recruit plasma cells through CCL28-CCR10 signaling. Additionally, there was a crosstalk between GC cells and B cells. Finally, we identified the LAMA/CD44 signaling axis as a potential prognostic marker for immunotherapy through a large amount of immunotherapy data. We also validated through various animal tumor models that targeting CCL28 can significantly promote CD8+T cell infiltration and function in the TME by regulating B cell and plasma cell functions, and has the ability to synergize immunotherapy.ConclusionThe co-localization and crosstalk between GC cells and B cells significantly affect the efficacy of immunotherapy, and inhibiting the CCL28-CCR10 signal axis is a potential immunotherapy target for GC. Meanwhile, LAMA/CD44 pair may be a potential adverse indicator for immunotherapy and tumor prognosis.

UQCRB and LBH are correlated with Gleason score progression in prostate cancer: Spatial transcriptomics and experimental validation

Prostate cancer (PCa) is a multifocal disease characterized by genomic and phenotypic heterogeneity within a single gland. In this study, Visium spatial transcriptomics (ST) analysis was applied to PCa tissues with different histological structures to infer the molecular events involved in Gleason score (GS) progression. The spots in tissue sections were classified into various groups using Principal Component Analysis (PCA) and Louvain clustering analysis based on transcriptome data. Anotation of the spots according to GS revealed notable similarities between transcriptomic profiles and histologically identifiable structures. The accuracy of macroscopic GS determination was bioinformatically verified through malignancy-related feature analysis, specifically inferred copy number variation (inferCNV), as well as developmental trajectory analyses, such as diffusion pseudotime (DPT) and partition-based graph abstraction (PAGA). Genes related to GS progression were identified from the differentially expressed genes (DEGs) through pairwise comparisons of groups along a GS gradient. The proteins encoded by the representative oncogenes UQCRB and LBH were found to be highly expressed in advanced-stage PCa tissues. Knockdown of their mRNAs significantly suppressed PCa cell proliferation and invasion. These findings were validated using The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) dataset, as well as through histological and cytological experiments. The results presented here establish a foundation for ST-based evaluation of GS progression and provide valuable insights into the GS progression-related genes UQCRB and LBH.

Eganelisib combined with immune checkpoint inhibitor therapy and chemotherapy in frontline metastatic triple-negative breast cancer triggers macrophage reprogramming, immune activation and extracellular matrix reorganization in the tumor microenvironment

BackgroundTriple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with a poor prognosis particularly in the metastatic setting. Treatments with anti-programmed cell death protein-1/programmed death-ligand 1 (PD-L1) immune...

STIE: Single-cell level deconvolution, convolution, and clustering in in situ capturing-based spatial transcriptomics

In in situ capturing-based spatial transcriptomics, spots of the same size and printed at fixed locations cannot precisely capture the randomly-located single cells, therefore inherently failing to profile transcriptome at the single-cell level. To this end, we present STIE, an Expectation Maximization algorithm that aligns the spatial transcriptome to its matched histology image-based nuclear morphology and recovers missing cells from ~70% gap area, thereby achieving the real single-cell level and whole-slide scale deconvolution, convolution, and clustering for both low- and high-resolution spots. STIE characterizes cell-type-specific gene expression and demonstrates outperforming concordance with true cell-type-specific transcriptomic signatures than the other spot- and subspot-level methods. Furthermore, STIE reveals the single-cell level insights, for instance, lower actual spot resolution than its reported spot size, unbiased evaluation of cell type colocalization, superior power of high-resolution spot in distinguishing nuanced cell types, and spatial cell-cell interactions at the single-cell level other than spot level.

Meningeal solitary fibrous tumor cell states phenocopy cerebral vascular development and homeostasis.

Meningeal solitary fibrous tumors (SFTs) are rare mesenchymal neoplasms that are associated with local recurrence and hematogenous metastasis. The cell states and spatial transcriptomic architecture underlying the unique clinical behavior of meningeal SFTs are unknown. Single-cell (n=4), spatial (n=8), and bulk RNA sequencing (n=22) was used to define the cell states and spatial transcriptomic architecture of meningeal SFTs across histological grades and in patient-matched pairs of primary/recurrent or intracranial/metastatic samples. Immunofluorescence, immunohistochemistry, and comparison of single-cell types to meningiomas, or to cerebral vascular development or homeostasis, were used for validation. Here we show meningeal SFTs are comprised of regionally distinct gene expression programs that resemble cerebral vascular development or homeostasis. Single-cell trajectory analysis and pseudotemporal ordering of single-cells suggest that meningeal SFT cell fate decisions are dynamic and interchangeable. Cell-cell communication analyses demonstrate receptor-ligand interactions throughout the meningeal SFT microenvironment, particularly between SFT cells, endothelia, and immature neurons. Direct comparison of single-cell transcriptomes from meningeal SFTs versus meningiomas shows that SFT cells are enriched in expression of endothelial markers while meningiomas cells are enriched in expression of mural cells markers. Meningeal SFT spatial transcriptomes show regionally distinct intratumor heterogeneity in cell states, gene expression programs, and cell-cell interactions across WHO histological grades and in patient-matched pairs of primary/recurrent or intracranial/metastatic samples. These results shed light on pathways underlying meningeal SFT biology in comparison to other central nervous system tumors and provide a framework for integrating single-cell, spatial, and bulk RNA sequencing data across human cancers and normal tissues.

A targetable type III immune response with increase of IL-17A expressing CD4+ T cells is associated with immunotherapy-induced toxicity in melanoma.

Immune checkpoint inhibitors are standard-of-care for the treatment of advanced melanoma, but their use is limited by immune-related adverse events. Proteomic analyses and multiplex cytokine and chemokine assays from serum at baseline and at the adverse event onset indicated aberrant T cell activity with differential expression of type I and III immune signatures. This was in line with the finding of an increase in the proportion of CD4+ T cells with IL-17A expression at the adverse event onset in the peripheral blood using flow cytometry. Multiplex immunohistochemistry and spatial transcriptomics on immunotherapy-induced skin rash and colitis showed an increase in the proportion of CD4+ T cells with IL-17A expression. Anti-IL-17A was administered in two patients with mild myocarditis, colitis and skin rash with resolution of the adverse events. This study highlights the potential role of type III CD4+ T cells in adverse event development and provides proof-of-principle evidence for a clinical trial using anti-IL-17A for treating adverse events.

Hypoxic Upregulation of IER2 Increases Paracrine GMFG Signaling of Endoplasmic Reticulum Stress-CAF to Promote Chordoma Progression via Targeting ITGB1.

Currently, the oncogenic mechanism of endoplasmic reticulum stress-CAF (ERS-CAF) subpopulation in chordoma remains unknown. Here, single-cell RNA sequencing, spatial transcriptomics, GeoMx Digital Spatial Profiler, data-independent acquisition proteomics, bulk RNA-seq, and multiplexed quantitative immunofluorescence are used to unveil the precise molecular mechanism of how ERS-CAF affected chordoma progression. Results show that hypoxic microenvironment reprograms CAFs into ERS-CAF subtype. Mechanistically, this occurrs via hypoxia-mediated transcriptional upregulation of IER2. Overexpression of IER2 in CAFs promotes chordoma progression, which can be impeded by IER2 knockdown or use of ERS inhibitors. IER2 also induces expression of ERS-CAF marker genes and results in production of a pro-tumorigenic paracrine GMFG signaling, which exert its biological function via directly binding to ITGB1 on tumor cells. ITGB1 inhibition attenuates tumor malignant progression, which can be partially reversed by exogenous GMFG intervention. Further analyses reveal a positive correlation between ITGB1high tumor cell counts and SPP1+ macrophage density, as well as the spatial proximity of these two cell types. Clinically, a significant correlation of high IER2/ITGB1 expression with tumor aggressive phenotype and poor patient survival is observed. Collectively, the findings suggest that ERS-CAF regulates SPP1+ macrophage to aggravate chordoma progression via the IER2/GMFG/ITGB1 axis, which may be targeted therapeutically in future.

Graph Fourier transform for spatial omics representation and analyses of complex organs

Spatial omics technologies decipher functional components of complex organs at cellular and subcellular resolutions. We introduce Spatial Graph Fourier Transform (SpaGFT) and apply graph signal processing to a wide range of spatial omics profiling platforms to generate their interpretable representations. This representation supports spatially variable gene identification and improves gene expression imputation, outperforming existing tools in analyzing human and mouse spatial transcriptomics data. SpaGFT can identify immunological regions for B cell maturation in human lymph nodes Visium data and characterize variations in secondary follicles using in-house human tonsil CODEX data. Furthermore, it can be integrated seamlessly into other machine learning frameworks, enhancing accuracy in spatial domain identification, cell type annotation, and subcellular feature inference by up to 40%. Notably, SpaGFT detects rare subcellular organelles, such as Cajal bodies and Set1/COMPASS complexes, in high-resolution spatial proteomics data. This approach provides an explainable graph representation method for exploring tissue biology and function.

Characteristics of blood–brain barrier heterogeneity between brain regions revealed by profiling vascular and perivascular cells

The blood–brain barrier (BBB) protects the brain and maintains neuronal homeostasis. BBB properties can vary between brain regions to support regional functions, yet how BBB heterogeneity occurs is poorly understood. Here, we used single-cell and spatial transcriptomics to compare the mouse median eminence, one of the circumventricular organs that has naturally leaky blood vessels, with the cortex. We identified hundreds of molecular differences in endothelial cells (ECs) and perivascular cells, including astrocytes, pericytes and fibroblasts. Using electron microscopy and an aqueous-based tissue-clearing method, we revealed distinct anatomical specializations and interaction patterns of ECs and perivascular cells in these regions. Finally, we identified candidate regionally enriched EC–perivascular cell ligand–receptor pairs. Our results indicate that both molecular specializations in ECs and unique EC–perivascular cell interactions contribute to BBB functional heterogeneity. This platform can be used to investigate BBB heterogeneity in other regions and may facilitate the development of central nervous system region-specific therapeutics.

An integrated single-cell reference atlas of the human endometrium

The complex and dynamic cellular composition of the human endometrium remains poorly understood. Previous endometrial single-cell atlases profiled few donors and lacked consensus in defining cell types. We introduce the Human Endometrial Cell Atlas (HECA), a high-resolution single-cell reference atlas (313,527 cells) combining published and new endometrial single-cell transcriptomics datasets of 63 women with and without endometriosis. HECA assigns consensus and identifies previously unreported cell types, mapped in situ using spatial transcriptomics and validated using a new independent single-nuclei dataset (312,246 nuclei, 63 donors). In the functionalis, we identify intricate stromal–epithelial cell coordination via transforming growth factor beta (TGFβ) signaling. In the basalis, we define signaling between fibroblasts and an epithelial population expressing progenitor markers. Integration of HECA with large-scale endometriosis genome-wide association study data pinpoints decidualized stromal cells and macrophages as most likely dysregulated in endometriosis. The HECA is a valuable resource for studying endometrial physiology and disorders, and for guiding microphysiological in vitro systems development.

Transcriptomics in the Study of Antiviral Innate Immunity.

Transcriptomics is an extremely important area of molecular biology and is a powerful tool for studying all RNA molecules in an organism. Conventional transcriptomic technologies include microarrays and RNA sequencing, and the rapid development of single-cell sequencing and spatial transcriptomics in recent years has provided an enormous scope for research in this field. This chapter describes the application, significance, and experimental procedures of a variety of transcriptomic technologies in antiviral natural immunity.

Comprehensive pan-cancer analysis reveals EPHB2 is a novel predictive biomarker for prognosis and immunotherapy response

PurposeRecent studies have increasingly linked Ephrin receptor B2 (EPHB2) to cancer progression. However, comprehensive investigations into the immunological roles and prognostic significance of EPHB2 across various cancers remain lacking.MethodsWe employed various databases and bioinformatics tools to investigate the impact of EPHB2 on prognosis, immune infiltration, genome instability, and response to immunotherapy. Validation of the correlation between EPHB2 expression and M2 macrophages included analyses using bulk and single-cell transcriptomic datasets, spatial transcriptomics, and multi-fluorescence staining. Moreover, we performed cMap web tool to screen for EPHB2-targeted compounds and assessed their potential through molecular docking and dynamics simulations. Additionally, in vitro validation using lung adenocarcinoma (LUAD) cell lines was conducted to confirm the bioinformatics predictions about EPHB2.ResultsEPHB2 dysregulation was observed across multiple cancer types, where it demonstrated significant diagnostic and prognostic value. Gene Set Enrichment Analysis (GSEA) indicated that EPHB2 is involved in enhancing cellular proliferation, invasiveness of cancer cells, and modulation of the anti-cancer immune response. Furthermore, it is emerged as a pan-cancer marker for M2 macrophage infiltration, supported by integrated analyses of transcriptomics and multiple fluorescence staining. In LUAD cells, knockdown of EPHB2 expression led to a decrease in both cell proliferation and migratory activity.ConclusionEPHB2 expression may serve as a pivotal indicator of M2 macrophage infiltration, offering vital insights into tumor dynamics and progression across various cancers, including lung adenocarcinoma, highlighting its significant prognostic and therapeutic potential for further exploration.

Spatially clustered type I interferon responses at injury borderzones

Sterile inflammation after myocardial infarction is classically credited to myeloid cells interacting with dead cell debris in the infarct zone1,2. Here we show that cardiomyocytes are the dominant initiators of a previously undescribed type I interferon response in the infarct borderzone. Using spatial transcriptomics analysis in mice and humans, we find that myocardial infarction induces colonies of interferon-induced cells (IFNICs) expressing interferon-stimulated genes decorating the borderzone, where cardiomyocytes experience mechanical stress, nuclear rupture and escape of chromosomal DNA. Cardiomyocyte-selective deletion of Irf3 abrogated IFNIC colonies, whereas mice lacking Irf3 in fibroblasts, macrophages, neutrophils or endothelial cells, Ccr2-deficient mice or plasmacytoid-dendritic-cell-depleted mice did not. Interferons blunted the protective matricellular programs and contractile function of borderzone fibroblasts, and increased vulnerability to pathological remodelling. In mice that died after myocardial infarction, IFNIC colonies were immediately adjacent to sites of ventricular rupture, while mice lacking IFNICs were protected from rupture and exhibited improved survival3. Together, these results reveal a pathological borderzone niche characterized by a cardiomyocyte-initiated innate immune response. We suggest that selective inhibition of IRF3 activation in non-immune cells could limit ischaemic cardiomyopathy while avoiding broad immunosuppression.