Spatial Transcriptome Analysis Research Articles

Tissue-resident memory T cells in epicardial adipose tissue comprise transcriptionally distinct subsets that are modulated in atrial fibrillation

Atrial fibrillation (AF) is the most common sustained arrhythmia and carries an increased risk of stroke and heart failure. Here we investigated how the immune infiltrate of human epicardial adipose tissue (EAT), which directly overlies the myocardium, contributes to AF. Flow cytometry analysis revealed an enrichment of tissue-resident memory T (TRM) cells in patients with AF. Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-cell T cell receptor (TCR) sequencing identified two transcriptionally distinct CD8+ TRM cells that are modulated in AF. Spatial transcriptomic analysis of EAT and atrial tissue identified the border region between the tissues to be a region of intense inflammatory and fibrotic activity, and the addition of TRM populations to atrial cardiomyocytes demonstrated their ability to differentially alter calcium flux as well as activate inflammatory and apoptotic signaling pathways. This study identified EAT as a reservoir of TRM cells that can directly modulate vulnerability to cardiac arrhythmia.

Acute ocular hypertension in the living human eye: Model description and initial cellular responses to elevated intraocular pressure

This initial methods study presents the initial immunohistochemical and transcriptomic changes in the optic nerve head and retina from three research-consented brain-dead organ donors following prolonged and transient intraocular pressure (IOP) elevation. In this initial study, research-consented brain-dead organ donors were exposed to unilateral elevation of IOP for 7.5 h (Donor 1), 30 h (Donor 2), and 1 h (Donor 3) prior to organ procurement. Optic nerve tissue and retinal tissue was obtained following organ procurement for immunohistological and transcriptomic analysis.Optic nerve sections in Donor 1 exposed to 7.5-hours of unilateral sub-ischemic IOP elevation demonstrated higher levels of protein expression of the astrocytic marker, glial fibrillary acidic protein (GFAP), within the lamina cribrosa with greatest expression inferior temporally in the treated eye compared to control. Spatial transcriptomic analysis performed on optic nerve head tissues from Donor 2 exposed to 30 h of unilateral IOP elevation demonstrated differential transcription of mRNA across laminar and scleral regions. Immunohistochemistry of retinal sections from Donor 2 exhibited higher GFAP and IBA1 expression in the treated eye compared with control, but this was not observed in Donor 3, which was exposed to only 1-hour of IOP elevation. While there were no differences in GFAP protein expression in the retina following the 1-hour IOP elevation in Donor 3, there were higher levels of transcription of GFAP in the inner nuclear layer, and CD44 in the retinal ganglion cell layer, indicative of astrocytic and Müller glial reactivity as well as an early inflammatory response, respectively.We found that transcriptomic differences can be observed across treated and control eyes following unilateral elevation of IOP in brain dead organ donors. The continued development of this model affords the unique opportunity to define the acute mechanotranscriptomic response of the optic nerve head, evaluate the injury and repair mechanisms in the retina in response to IOP elevation, and enable correlation of in vivo imaging and functional testing with ex vivo cellular responses for the first time in the living human eye.

Spatiotemporal transcriptome atlas reveals gene regulatory patterns during the organogenesis of the rapid growing bamboo shoots.

Bamboo with its remarkable growth rate and economic significance, offers an ideal system to investigate the molecular basis of organogenesis in rapidly growing plants, particular in monocots, where gene regulatory networks governing the maintenance and differentiation of shoot apical and intercalary meristems remain a subject of controversy. We employed both spatial and single-nucleus transcriptome sequencing on 10× platform to precisely dissect the gene functions in various tissues and early developmental stages of bamboo shoots. Our comprehensive analysis reveals distinct cell trajectories during shoot development, uncovering critical genes and pathways involved in procambium differentiation, intercalary meristem formation, and vascular tissue development. Spatial and temporal expression patterns of key regulatory genes, particularly those related to hormone signaling and lipid metabolism, strongly support the hypothesis that intercalary meristem origin from surrounded parenchyma cells. Specific gene expressions in intercalary meristem exhibit regular and dispersed distribution pattern, offering clues for understanding the intricate molecular mechanisms that drive the rapid growth of bamboo shoots. The single-nucleus and spatial transcriptome analysis reveal a comprehensive landscape of gene activity, enhancing the understanding of the molecular architecture of organogenesis and providing valuable resources for future genomic and genetic studies relying on identities of specific cell types.

HIV infection is associated with compromised tumor microenvironment adaptive immune reactivity in Hodgkin lymphoma

AbstractThe impact of HIV infection on the tumor microenvironment (TME) of classic Hodgkin lymphoma (cHL), one of the most common comorbidities after HIV infection, is not well understood. Here, we have used multiplexed immunofluorescence and spatial transcriptomic analysis to dissect the impact of viral infections (Epstein-Barr virus [EBV] and HIV/EBV) on cHL TME. HIV−EBV+ cHL TME was characterized by higher cell densities of CD8high T cells coexpressing inhibitory receptors (PD-1 and TIGIT), macrophage subsets, and an in situ inflammatory molecular profile associated with increased expression of T-cell receptor (TCR) and B-cell receptor cell signaling pathways than HIV−EBV− cHL TME. Compared with HIV−EBV+, HIV+EBV+ cHL TME was characterized by significantly less CD8high T cells coexpressing PD-1 and TIGIT, a profile concomitant with significantly increased cell densities of CD155high neoplastic cells. Significant downregulation of in situ TCR signaling and upregulation of extracellular matrix reorganization pathways were found in HIV+EBV+ cHL TME, in line with an altered topological organization of CXCL13 and heparan sulfate, an extracellular matrix glycosaminoglycan. Our data reveal the complexity of the cellular and molecular composition of cHL TME in the presence of viral infections, with possible implications for combinatorial immunotherapies. Furthermore, the data suggest specific molecular targets and pathways for further investigation that could improve our understanding of possible mechanistic links between HIV and lymphomagenesis.

Molecular and cellular dynamics of the developing human neocortex at single-cell resolution.

The development of the human neocortex is a highly dynamic process and involves complex cellular trajectories controlled by cell-type-specific gene regulation1. Here, we collected paired single-nucleus chromatin accessibility and transcriptome data from 38 human neocortical samples encompassing both the prefrontal cortex and primary visual cortex. These samples span five main developmental stages, ranging from the first trimester to adolescence. In parallel, we performed spatial transcriptomic analysis on a subset of the samples to illustrate spatial organization and intercellular communication. This atlas enables us to catalog cell type-, age-, and area-specific gene regulatory networks underlying neural differentiation. Moreover, combining single-cell profiling, progenitor purification, and lineage-tracing experiments, we have untangled the complex lineage relationships among progenitor subtypes during the transition from neurogenesis to gliogenesis in the human neocortex. We identified a tripotential intermediate progenitor subtype, termed Tri-IPC, responsible for the local production of GABAergic neurons, oligodendrocyte precursor cells, and astrocytes. Remarkably, most glioblastoma cells resemble Tri-IPCs at the transcriptomic level, suggesting that cancer cells hijack developmental processes to enhance growth and heterogeneity. Furthermore, by integrating our atlas data with large-scale GWAS data, we created a disease-risk map highlighting enriched ASD risk in second-trimester intratelencephalic projection neurons. Our study sheds light on the gene regulatory landscape and cellular dynamics of the developing human neocortex.

Mutual exclusivity and co-occurrence patterns of immune checkpoints indicate NKG2A relates to anti-PD-1 resistance in gastric cancer

BackgroundAn increasing number of clinical studies have begun to explore combination strategies with immune checkpoint inhibitors, aiming to present new opportunities for overcoming anti-PD-1 treatment resistance in gastric cancer. Unfortunately, the exploration of certain immune checkpoint inhibitor combination strategies has yielded suboptimal results. Therefore, it is necessary to comprehensively analyze the expression patterns of immune checkpoints and identify optimal combination regimens of anti-PD-1 inhibitors with other immune checkpoint inhibitors.MethodsLeveraging single-cell RNA sequencing (scRNA-seq) and multivariate linear regression interaction models, we dissected the immune checkpoint expression characteristics of CD8+ T cells in gastric cancer and the immune checkpoint expression pattern (ICEP) mediating anti-PD-1 treatment resistance. Furthermore, we employed transcription factor analysis and CellOracle to explore the transcriptional regulatory mechanisms governing CD8+ T cell differentiation fates. Finally, we utilized Nichenet and spatial transcriptomic analysis to investigate the spatial expression patterns of immune checkpoints.ResultsInteraction analysis indicated that, among the known immune checkpoints, co-expression of NKG2A and PD-1 might exert a more profound inhibitory effect on the proliferative capacity of CD8+ T cells. The co-expression analysis revealed differential co-expression pattern of PD-1 and NKG2A, defined as ICEP1 (CD8+ T cells co-expressing PD-1, CTLA-4, TIGIT, LAG-3 or CD38) and ICEP2 (CD8+ T cells solely expressing NKG2A or co-expressing with other immune checkpoints), reflecting the co-occurrence pattern of PD-1 and the mutual exclusivity of NKG2A. Further, these two ICEP CD8+ T cell subsets represented distinct CD8+ T cell differentiation fates governed by MSC and RUNX3. Notably, ICEP2 CD8+ T cells were associated with anti-PD-1 therapy resistance in gastric cancer. This phenomenon may be attributed to the recruitment of LGMN+ macrophages mediated by the CXCL16-CXCR6 signaling pathway.ConclusionThis study unveiled two distinct ICEPs and the mutually exclusivity and co-occurrence characteristics of CD8+ T cells in gastric cancer. The ICEP2 CD8+ T cell subset, highly expressed in gastric cancer patients resistant to anti-PD-1 therapy, may be recruited by LGMN+ macrophages through CXCL16-CXCR6 axis. These findings provide evidence for NKG2A as a novel immunotherapeutic target in gastric cancer and offer new insights into combination strategies for immune checkpoint inhibitors in gastric cancer.Graphical

Spatial profiling of non-small cell lung cancer provides insights into tumorigenesis and immunotherapy response

Lung cancer is the second most common cancer worldwide and a leading cause of cancer-related deaths. Despite advances in targeted therapy and immunotherapy, the prognosis remains unfavorable, especially in metastatic cases. This study aims to identify molecular changes in non-small cell lung cancer (NSCLC) patients based on their response to treatment. Using tumor and matched immune cell rich peritumoral tissues, we perform a retrospective, comprehensive spatial transcriptomic analysis of a proven malignant NSCLC sample treated with immune checkpoint inhibitor (ICI). In addition to T cells, other immune cell types, such as B cells and macrophages, were also activated in responders to ICI treatment. In particular, B cells and B cell-mediated immunity pathways are consistently found to be activated. Analysis of the histologic subgroup (lung squamous cell carcinoma, LUSC; lung adenocarcinoma, LUAD) of NSCLC also confirms activation of B cell mediated immunity. Analysis of B cell subtypes shows that B cell subtypes were more activated in immune cell-rich tissues near tumor tissue. Furthermore, increased expression of B cell immunity-related genes is associated with better prognosis. These findings provide insight into predicting ICI treatment responses and identifying appropriate candidates for immunotherapy in NSCLC patients.

Insights into left-right asymmetric development of chicken ovary at the single-cell level

Avian ovaries develop asymmetrically apart from prey birds, with only the left ovary growing more towards functional organ. Here, we analyze over 135,000 cells from chick's left and right ovaries at six distinct embryonic developmental stages utilizing single-cell transcriptome sequencing. We delineate gene expression patterns across 15 cell types within these embryo ovaries, revealing side-specific development. The left ovaries exhibit cortex cells, zygotene germ cells, and transcriptional changes unique to the left side. Differential gene expression analysis further identifies specific markers and pathways active in these cell types, highlighting the asymmetry in ovarian development. A fine-scale analysis of the germ cell meiotic transcriptome reveals seven distinct clusters with gene expression patterns specific to various meiotic stages. The study also identifies signaling pathways and intercellular communications, particularly between pre-granulosa and germ cells. Spatial transcriptome analysis shows the asymmetry, demonstrating cortex cells exclusively in the left ovary, modulating neighboring cell types through putative secreted signaling molecules. Overall, this single-cell analysis provides insights into the molecular mechanisms of the asymmetric development of avian ovaries, particularly the significant role of cortex cells in the left ovary.

Myeloid-Specific Thrombospondin-1 Deficiency Exacerbates Aortic Rupture via Broad Suppression of Extracellular Matrix Proteins.

Rupture of abdominal aortic aneurysms (AAA) is associated with high mortality. However, the precise molecular and cellular drivers of AAA rupture remain elusive. Our prior study showed that global and myeloid-specific deletion of matricellular protein thrombospondin-1 (TSP1) protects mice from aneurysm formation primarily by inhibiting vascular inflammation. To investigate the cellular and molecular mechanisms that drive AAA rupture by testing how TSP1 deficiency in different cell populations affects the rupture event. We deleted TSP1 in endothelial cells and macrophages --- the major TSP1-expressing cells in aneurysmal tissues ---- by crossbreeding Thbs1 flox/flox mice with VE-cadherin Cre and Lyz2-cre mice, respectively. Aortic aneurysm and rupture were induced by angiotensin II in mice with hypercholesterolemia. Myeloid-specific Thbs1 knockout, but not endothelial-specific knockout, increased the rate of lethal aortic rupture by more than 2 folds. Combined analyses of single-cell RNA sequencing and histology showed a unique cellular and molecular signature of the rupture-prone aorta that was characterized by a broad suppression in inflammation and extracellular matrix production. Visium spatial transcriptomic analysis on human AAA tissues showed a correlation between low TSP1 expression and aortic dissection. TSP1 expression by myeloid cells negatively regulates aneurysm rupture, likely through promoting the matrix repair phenotypes of vascular smooth muscle cells thereby increasing the strength of the vascular wall.

Single-cell RNA sequencing and spatial transcriptome reveal potential molecular mechanisms of lung cancer brain metastasis

BackgroundLung cancer is a highly aggressive and prevalent disease worldwide. By the time it is first diagnosed, distant metastases have usually already occurred. Among them, the prognosis of patients with brain metastasis from lung cancer is very poor. Therefore, it is particularly important to identify the evolutionary status of tumor cells during lung cancer brain metastases and discover the underlying mechanisms of lung cancer brain metastases. MethodsIn this study, we analysed three types of data: single-cell RNA sequencing, bulk RNA sequencing, and spatial transcriptome. Firstly, we identified early metastatic epithelial cell clusters (EMEC) using CNV and trajectory analysis in scRNA-seq data. Secondly, we integrated scRNA-seq and spatial transcriptome data with the help of MIA (Multimodal intersection analysis) to explore the biological characteristics of EMEC. Finally, we used bulk RNA-seq data to validate the molecular characteristics of EMEC. ResultA total of 55,763 single cells were obtained and divided into 9 cell types. In brain metastasis, we found a significantly higher proportion of epithelial cells. In addition, we identified a specific subpopulation of epithelial cells, which was named as “early metastatic epithelial cell clusters (EMEC)”. It is enriched in oxidative phosphorylation, coagulation, complement. Moreover, we also found that EMEC underwent cellular communication with other immune cells through ligand-receptor pairs such as MIF-(CD74 + CXCR4) and MIF-(CD74 + CD44). Next, we validated that EMEC were associated with poor clinical prognosis using three independent external datasets. Finally, spatial transcriptome analysis revealed specificity in the spatial distribution of EMEC, which shifted from the peripheral regions to the central regions of the tumour as the depth of tumor invasion progressed. ConclusionThis study reveals the potential molecular mechanisms of lung cancer brain metastasis from both single-cell and spatial transcriptomic perspectives, providing biological insights and clinical reference value for detecting patients suffering from lung cancer brain metastasis.

Submandibular gland tissue RNAseq and spatial transcriptome analyses in IgG4-related disease.

To identify genes that could provide clues leading to the discovery of drugs to treat IgG4-related disease (IgG4-RD). Submandibular gland tissue bulk RNAseq analysis of 45 cases with a definite diagnosis of IgG4-RD was integrated with Visium spatial transcriptome analysis of 2 cases to identify pathogenic genes expressed in tertiary lymphoid tissues. Bulk RNAseq and pathway analyses showed upregulation of cell cycle and T cell-related signals in IgG4-RD. Spatial transcriptome analysis identified the cluster corresponding to germinal centers and the top 38 common genes that showed significant variations in expression compared with other clusters. The top 20 genes were extracted by comparing the bulk RNAseq data. Network analysis identified CDK1 as the ge most strongly associated of the top 20 genes. The CDK1 gene may be a regulator of the pathogenesis of IgG4-RD and provide clues for drug discovery.

Characterization of cuproptosis signature in clear cell renal cell carcinoma by single cell and spatial transcriptome analysis

Cuproptosis is a novel type to regulate cell death with copper-dependent manner, and has been reported to involve in the occurrence and development of various malignant tumors. However, the association between cuproptosis and the tumor microenvironment (TME) of clear cell renal cell carcinoma (ccRCC) remained unclear. To address this question, we integrated the single cell RNA sequencing (scRNA-seq) datasets of ccRCC across different stages, systematically examined the distinctive expression patterns of cuproptosis-related genes (CRGs) within the TME of ccRCC, and explored the crucial signatures using the spatial transcriptome sequencing (ST-seq) dataset. The cuproptosis activities reduced in cancer tissues along with the ccRCC development, and recovered after therapy. We identified HILPDA+ ccRCC1 subtype, characterized with hypoxia, as cuproptosis susceptible cells associated with a better prognosis. The main co-expression modules of HILPDA+ ccRCC1 subtype highlighted the role in anion transport, response to oxygen species and PD-L1-PD-1 pathway. Furthermore, the immunosuppressive cells might interact with HILPDA+ ccRCC1 subtype via HAVCR2-LGALS9, C3-C3AR1, HLA-A-CD8B and HLA-C-CD8A axises to shape the cuproptosis-related TME landscape. In summary, we anticipate that this study will offer valuable insights and potential strategies of cuproptosis for therapy of ccRCC.Graphical

Spatial omics technologies for understanding molecular status associated with cancer progression.

Cancer cells are generally exposed to numerous extrinsic stimulations in the tumor microenvironment. In this environment, cancer cells change their expression profiles to fight against circumstantial stresses, allowing their progression in the challenging tissue space. Technological advancements of spatial omics have had substantial influence on cancer genomics. This technical progress, especially that occurring in the spatial transcriptome, has been drastic and rapid. Here, we describe the latest spatial analytical technologies that have allowed omics feature characterization to retain their spatial and histopathological information in cancer tissues. Several spatial omics platforms have been launched, and the latest platforms finally attained single-cell level or even higher subcellular level resolution. We discuss several key papers elucidating the initial utility of the spatial analysis. In fact, spatial transcriptome analyses reveal comprehensive omics characteristics not only in cancer cells but also their surrounding cells, such as tumor infiltrating immune cells and cancer-associated fibroblasts. We also introduce several spatial omics platforms. We describe our own attempts to investigate molecular events associated with cancer progression. Furthermore, we discuss the next challenges in analyzing the multiomics status of cells, including their morphology and location. These novel technologies, in conjunction with spatial transcriptome analysis and, more importantly, with histopathology, will elucidate even novel key aspects of the intratumor heterogeneity of cancers. Such enhanced knowledge is expected to open a new path for overcoming therapeutic resistance and eventually to precisely stratify patients.

Discovering cancer stem-like molecule, nuclear factor I X, using spatial transcriptome in gastric cancer.

Gastric cancer (GC) is characterized by significant intratumoral heterogeneity, and stem cells are promising therapeutic targets. Despite advancements in spatial transcriptome analyses, unexplored targets for addressing cancer stemness remain unknown. This study aimed to identify Nuclear Factor IX (NFIX) as a critical regulator of cancer stemness in GC and evaluate its clinicopathological significance and function. Spatial transcriptome analysis of GC was conducted. The correlation between NFIX expression, clinicopathological factors, and prognosis was assessed using immunostaining in 127 GC cases. Functional analyses of cancer cell lines validated these findings. Spatial transcriptome analysis stratified GC tissues based on genetic profiles, identified CSC-like cells, and further refined the classification to identify and highlight the significance of NFIX, as validated by Monocle 3 and CytoTRACE analyses. Knockdown experiments in cancer cell lines have demonstrated the involvement of NFIX in cancer cell proliferation and kinase activity. This study underscores the role of spatial transcriptome analysis in refining GC tissue classification and identifying therapeutic targets, highlighting NFIX as a pivotal factor. NFIX expression is correlated with poor prognosis and drives GC progression, suggesting its potential as a novel therapeutic target for personalized GC therapies.

Spatial transcriptomics implicates impaired BMP signaling in NF1 fracture pseudarthrosis in murine and patient tissues.

The Neurofibromatosis Type 1 (NF1) RASopathy is associated with persistent fibrotic nonunions (pseudarthrosis) in human and mouse skeletal tissue. Here, we first performed spatial transcriptomics to define the molecular signatures across normal endochondral healing following fracture in mice. Within the control fracture callus, we observed spatially restricted activation of morphogenetic pathways, such as TGF-β, WNT, and BMP. To investigate the molecular mechanisms contributing to Nf1-deficient delayed fracture healing, we performed spatial transcriptomic analysis on a Postn-cre;Nf1flox/- (Nf1Postn) fracture callus. Transcriptional analyses, subsequently confirmed through p-SMAD1/5/8 immunohistochemistry, demonstrated a lack of BMP pathway induction in Nf1Postn mice. To further inform the human disease, we performed spatial transcriptomic analysis of fracture pseudarthrosis tissue from a NF1 patient. Analyses detected increased MAPK signaling at the fibrocartilaginous-osseus junction. Similar to the Nf1Postn fracture, BMP pathway activation was absent within the pseudarthrosis tissue. Our results demonstrate the feasibility to delineate the molecular and tissue-specific heterogeneity inherent in complex regenerative processes, such as fracture healing, and to reconstruct phase transitions representing endochondral bone formation in vivo. Furthermore, our results provide in situ molecular evidence of impaired BMP signaling underlying NF1 pseudarthrosis, potentially informing the clinical relevance of off-label BMP2 as a therapeutic intervention.

Spatiotemporal single-cell RNA sequencing reveals the role of steroid hormone pathway during chicken primordial follicle formation

The size of the initial primordial follicle pool in the ovary depends on primordial follicle formation, which determines the female reproductive lifespan. However, the molecular regulation of primordial follicle formation in chickens remains unclear. In this study, the left ovaries of chickens were collected at 2 d posthatch (dph), 5.5 dph, and 10.5 dph to examine the formation of primordial follicles. Single-cell mRNA sequencing (scRNA-seq) and spatial transcriptomic analysis were performed to explore the ovarian microenvironment and identify regulatory pathways involved in the formation of primordial follicles in chickens. Histomorphological analysis of chicken ovary tissues revealed the presence of germ cell cysts at 1 dph, which began to disintegrate at 2 dph. Primordial follicles appeared at 5.5 dph and continued to develop into larger-diameter follicles. scRNA-seq and spatial transcriptomic analysis revealed 24 cellular clusters involved in chicken primordial follicle formation. The metabolic pathway of steroid hormone synthesis was found in pregranulosa and pretheca cells. Histological analysis showed that chicken ovaries did not form primordial follicles after the inhibition of the steroid hormone synthesis pathway by simvastatin or tamoxifen. In addition, mRNA transcriptomic and bioinformatics analyses revealed that GREB1 was a downstream gene of the steroid hormone synthesis pathway during the formation of chicken primordial follicles. This study provides a valuable foundation for investigating primordial follicle formation in avian species and optimizing their reproductive performance.

Systematic comparison of sequencing-based spatial transcriptomic methods

Recent developments of sequencing-based spatial transcriptomics (sST) have catalyzed important advancements by facilitating transcriptome-scale spatial gene expression measurement. Despite this progress, efforts to comprehensively benchmark different platforms are currently lacking. The extant variability across technologies and datasets poses challenges in formulating standardized evaluation metrics. In this study, we established a collection of reference tissues and regions characterized by well-defined histological architectures, and used them to generate data to compare 11 sST methods. We highlighted molecular diffusion as a variable parameter across different methods and tissues, significantly affecting the effective resolutions. Furthermore, we observed that spatial transcriptomic data demonstrate unique attributes beyond merely adding a spatial axis to single-cell data, including an enhanced ability to capture patterned rare cell states along with specific markers, albeit being influenced by multiple factors including sequencing depth and resolution. Our study assists biologists in sST platform selection, and helps foster a consensus on evaluation standards and establish a framework for future benchmarking efforts that can be used as a gold standard for the development and benchmarking of computational tools for spatial transcriptomic analysis.

O-264 Profiling Tumor-Initiating Cells in Uterine Leiomyoma through Single-Cell Multi-omics

Abstract Study question What are the molecular and cellular features that contribute to the transformation of myometrial stem cells into tumor-initiating cells within uterine leiomyoma? Summary answer Transformative changes in differentiation and genetic processes, in a distinct subset of M/LM cells drives their progression into a tumorigenic state. What is known already Uterine leiomyomas (LM), which are benign smooth muscle-derived tumours of myometrium, impact approximately 75% of women, causing significant physical and psychological challenges and imposing substantial healthcare costs. The widespread consensus postulates a monoclonal origin for LM, implying their derivation from a dysregulated single multipotent stem cell that could give rise to tumor-initiating cells (TICs). While previous studies have shown cellular heterogeneity in both myometrium (M) and LM, the precise identity of the originating cells is unknown. Study design, size, duration Prospective, observational, and biomedical study conducted at Hospital La Fe (Valencia, Spain) for one year. Eight sample pairs of LM and M underwent single-nuclei RNAseq (snRNA-seq; n = 16) and single-cell proteomic (scP; n = 16) analyses, to generate a detailed transcriptomic and proteomic map decoupled from cell type, state, and spatial location. We further employed single-cell RNA velocity inference for differentiation trajectory [BR1] analysis of mesenchymal cells, followed by the identification of potential driver genes in LM tumorigenesis. Participants/materials, setting, methods Upon obtaining informed consent, we procured LM and M samples from eight patients aged 35-50 undergoing hysterectomies. Part of these samples were preserved in paraffin for spatial transcriptomics utilizing VISIUM (10x Genomics). The remaining tissues were dissociated into single-cell suspensions and underwent scRNA-seq and scP using Chromium Controller and Orbitrap Eclipse Tribid mass spectrometry, respectively. The analysis of the collected data was carried out using publicly accessible R/Python tools. Main results and the role of chance Analysis of snRNAseq (∼52,000 cells) revealed similar cellular compositions in M and LM, including endothelial, perivascular, smooth muscle cells (SMC), fibroblasts, and immune cells. Further trajectory analysis unveiled a subset of myometrial cells with potential as TICs, exhibiting reduced expression of hormone receptors like PGR. Analysis of these cells [BR1] suggested differentiation into two distinct cell types -fibroblasts and SMCs- with elevated hormone expression over pseudotime. Differential analysis between M and LM also showed a dysregulated transcriptomic profile in the TICs within the tumor, as evidenced by upregulation of RAD51B and HMGA2 and downregulation PGR among other genes. These genes are indicative markers, underscoring their significant roles in the tumorigenesis of LM by influencing hormone response and disrupting DNA repair mechanisms. Spatial transcriptomic analysis confirmed these findings and suggested that the distribution of TICs could be ubiquitous, since the expression of potential myometrial-stem markers, was markedly increased only on certain spots within the tissue across both LM and M. Lastly, scProt profiling (∼5,000 cells) also allowed the identification of putative TICs, which showed upregulation in LM of specific proteins involved in replication, transcription, and translation. Limitations, reasons for caution Our study sets the basis for TICs isolation in LM, yet functional validation studies need to be performed to address the clinical potential of our findings. Further studies including more patients, and addressing racial disparities will help to generalize these findings to a broader population. Wider implications of the findings Our findings indicate the presence of a particular subset of M/LM cells whose changes in differentiation path and genetic processes seem to drive the transformation of these cells into a tumorigenic state to develop LM. Targeting these markers might show promise for effectively treating these tumors. Trial registration number NCT04214457

Granulosa Cell-Layer Stiffening Prevents Escape of Mural Granulosa Cells from the Post-Ovulatory Follicle.

Ovulation is vital for successful reproduction. Following ovulation, cumulus cells and oocyte are released, while mural granulosa cells (mGCs) remain sequestered within the post-ovulatory follicle to form the corpus luteum. However, the mechanism underlying the confinement of mGCs has been a longstanding mystery. Here, in vitro and in vivo evidence is provided demonstrating that the stiffening of mGC-layer serves as an evolutionarily conserved mechanism that prevents mGCs from escaping the post-ovulatory follicles. The results from spatial transcriptome analysis and experiments reveal that focal adhesion assembly, triggered by the LH (hCG)-cAMP-PKA-CREB signaling cascade, is necessary for mGC-layer stiffening. Disrupting focal adhesion assembly through RNA interference results in stiffening failure, mGC escape, and the subsequent development of an abnormal corpus luteum characterized by decreased cell density or cavities. These findings introduce a novel concept of "mGC-layer stiffening", shedding light on the mechanism that prevents mGC escape from the post-ovulatory follicle.

ST-CellSeg: Cell segmentation for imaging-based spatial transcriptomics using multi-scale manifold learning.

Spatial transcriptomics has gained popularity over the past decade due to its ability to evaluate transcriptome data while preserving spatial information. Cell segmentation is a crucial step in spatial transcriptomic analysis, as it enables the avoidance of unpredictable tissue disentanglement steps. Although high-quality cell segmentation algorithms can aid in the extraction of valuable data, traditional methods are frequently non-spatial, do not account for spatial information efficiently, and perform poorly when confronted with the problem of spatial transcriptome cell segmentation with varying shapes. In this study, we propose ST-CellSeg, an image-based machine learning method for spatial transcriptomics that uses manifold for cell segmentation and is novel in its consideration of multi-scale information. We first construct a fully connected graph which acts as a spatial transcriptomic manifold. Using multi-scale data, we then determine the low-dimensional spatial probability distribution representation for cell segmentation. Using the adjusted Rand index (ARI), normalized mutual information (NMI), and Silhouette coefficient (SC) as model performance measures, the proposed algorithm significantly outperforms baseline models in selected datasets and is efficient in computational complexity.