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Placenta accreta spectrum disorder at single-cell resolution: a loss of boundary limits in the decidua and endothelium.
BACKGROUND: Placenta accreta spectrum disorders are associated with severe maternal morbidity and mortality. Placenta accreta spectrum disorders involve excessive adherence of the placenta preventing separation at birth. Traditionally, this condition has been attributed to excessive trophoblast invasion; however, an alternative view is a fundamental defect in decidual biology. OBJECTIVE: This study aimed to gain insights into the understanding of placenta accreta spectrum disorder by using single-cell and spatially resolved transcriptomics to characterize cellular heterogeneity at the maternal-fetal interface in placenta accreta spectrum disorders. STUDY DESIGN: To assess cellular heterogeneity and the function of cell types, single-cell RNA sequencing and spatially resolved transcriptomics were used. A total of 12 placentas were included, 6 placentas with placenta accreta spectrum disorder and 6 controls. For each placenta with placenta accreta spectrum disorder, multiple biopsies were taken at the following sites: placenta accreta spectrum adherent and nonadherent sites in the same placenta. Of note, 2 platforms were used to generate libraries: the 10× Chromium and NanoString GeoMX Digital Spatial Profiler for single-cell and spatially resolved transcriptomes, respectively. Differential gene expression analysis was performed using a suite of bioinformatic tools (Seurat and GeoMxTools R packages). Correction for multiple testing was performed using Clipper. In situ hybridization was performed with RNAscope, and immunohistochemistry was used to assess protein expression. RESULTS: In creating a placenta accreta cell atlas, there were dramatic difference in the transcriptional profile by site of biopsy between placenta accreta spectrum and controls. Most of the differences were noted at the site of adherence; however, differences existed within the placenta between the adherent and nonadherent site of the same placenta in placenta accreta. Among all cell types, the endothelial-stromal populations exhibited the greatest difference in gene expression, driven by changes in collagen genes, namely collagen type III alpha 1 chain (COL3A1), growth factors, epidermal growth factor-like protein 6 (EGFL6), and hepatocyte growth factor (HGF), and angiogenesis-related genes, namely delta-like noncanonical Notch ligand 1 (DLK1) and platelet endothelial cell adhesion molecule-1 (PECAM1). Intraplacental tropism (adherent versus non-adherent sites in the same placenta) was driven by differences in endothelial-stromal cells with notable differences in bone morphogenic protein 5 (BMP5) and osteopontin (SPP1) in the adherent vs nonadherent site of placenta accreta spectrum. CONCLUSION: Placenta accreta spectrum disorders were characterized at single-cell resolution to gain insight into the pathophysiology of the disease. An atlas of the placenta at single cell resolution in accreta allows for understanding in the biology of the intimate maternal and fetal interaction. The contributions of stromal and endothelial cells were demonstrated through alterations in the extracellular matrix, growth factors, and angiogenesis. Transcriptional and protein changes in the stroma of placenta accreta spectrum shift the etiologic explanation away from "invasive trophoblast" to "loss of boundary limits" in the decidua. Gene targets identified in this study may be used to refine diagnostic assays in early pregnancy, track disease progression over time, and inform therapeutic discoveries.
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Effects of HOX family regulator-mediated modification patterns and immunity characteristics on tumor-associated cell type in endometrial cancer.
Endometrial cancer (UCEC) is one of three major malignant tumors in women. The HOX gene regulates tumor development. However, the potential roles of HOX in the expression mechanism of multiple cell types and in the development and progression of tumor microenvironment (TME) cell infiltration in UCEC remain unknown. In this study, we utilized both the The Cancer Genome Atlas (TCGA) database and International Cancer Genome Consortium (ICGC) database to analyze transcriptome data of 529 patients with UCEC based on 39 HOX genes, combing clinical information, we discovered HOX gene were a pivotal factor in the development and progression of UCEC and in the formation of TME diversity and complexity. Here, a new scoring system was developed to quantify individual HOX patterns in UCEC. Our study found that patients in the low HOX score group had abundant anti-tumor immune cell infiltration, good tumor differentiation, and better prognoses. In contrast, a high HOX score was associated with blockade of immune checkpoints, which enhances the response to immunotherapy. The Real-Time quantitative PCR (RT-qPCR) and Immunohistochemistry (IHC) exhibited a higher expression of the HOX gene in the tumor patients. We revealed that the significant upregulation of the HOX gene in the epithelial cells can activate signaling pathway associated with tumour invasion and metastasis through single-cell RNA sequencing (scRNA-seq), such as nucleotide metabolic proce and so on. Finally, a risk prognostic model established by the positive relationship between HOX scores and cancer-associated fibroblasts (CAFs) can predict the prognosis of individual patients by scRNA-seq and transcriptome data sets. In sum, HOX gene may serve as a potential biomarker for the diagnosis and prediction of UCEC and to develop more effective therapeutic strategies.
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Temporal analysis of enhancers during mouse cerebellar development reveals dynamic and novel regulatory functions.
We have identified active enhancers in the mouse cerebellum at embryonic and postnatal stages which provides a view of novel enhancers active during cerebellar development. The majority of cerebellar enhancers have dynamic activity between embryonic and postnatal development. Cerebellar enhancers were enriched for neural transcription factor binding sites with temporally specific expression. Putative gene targets displayed spatially restricted expression patterns, indicating cell-type specific expression regulation. Functional analysis of target genes indicated that enhancers regulate processes spanning several developmental epochs such as specification, differentiation and maturation. We use these analyses to discover one novel regulator and one novel marker of cerebellar development: Bhlhe22 and Pax3, respectively. We identified an enrichment of de novo mutations and variants associated with autism spectrum disorder in cerebellar enhancers. Furthermore, by comparing our data with relevant brain development ENCODE histone profiles and cerebellar single-cell datasets we have been able to generalize and expand on the presented analyses, respectively. We have made the results of our analyses available online in the Developing Mouse Cerebellum Enhancer Atlas, where our dataset can be efficiently queried, curated and exported by the scientific community to facilitate future research efforts. Our study provides a valuable resource for studying the dynamics of gene expression regulation by enhancers in the developing cerebellum and delivers a rich dataset of novel gene-enhancer associations providing a basis for future in-depth studies in the cerebellum.
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Single-cell analysis reveals crosstalk between TREM1-positive myeloid cells and cancer-associated fibroblasts in colorectal cancer progression.
BACKGROUND: The limited efficacy of immunotherapy in colorectal cancer (CRC) underscores the need to better define immunosuppressive mechanisms within the tumor microenvironment (TME). We applied single-cell RNA sequencing (scRNA-seq) to characterize stromal-immune interactions shaping the CRC TME. METHODS: Paired tumor and adjacent normal mucosa samples from eight patients with CRC were analyzed by scRNA-seq. Integrated bioinformatic approaches, including trajectory inference, transcriptional regulon analysis, and cell-cell communication modeling, were used to define cellular differentiation and intercellular signaling. Key findings were validated using The Cancer Genome Atlas datasets, multiplex immunofluorescence staining, and in vitro functional assays. RESULTS: Trajectory analysis demonstrated a progressive increase in triggering receptor expressed on myeloid cells 1 (TREM1) expression during tumor-associated myeloid differentiation. TREM1-positive myeloid cells exhibited enriched M2-like signatures and were preferentially associated with consensus molecular subtype 4 tumors, characterized by stromal activation and poor clinical outcomes. Stromal profiling identified an α-smooth muscle actin (ACTA2)-positive population associated with CRC progression. Spatial analyses revealed close localization of TREM1-positive myeloid cells and ACTA2-positive cancer-associated fibroblasts (CAFs) in tumor tissues. Mechanistically, integrated bioinformatic analyses indicated that TREM1-positive myeloid cells engage CAFs primarily through secreted phosphoprotein 1 (SPP1) signaling, while CAFs reinforce immunosuppressive myeloid phenotypes via TGF-β-associated extracellular matrix pathways. Functional assays showed that TREM1 inhibition reduced SPP1 expression and attenuated M2 macrophage polarization. CONCLUSIONS: These findings identify a bidirectional interaction between TREM1-positive myeloid cells and CAFs that contributes to a profibrotic and immunosuppressive CRC microenvironment, highlighting the TREM1-SPP1 axis as a pathway of potential translational relevance.
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Aged brain multi-omic integration captures immunometabolic and sex variation.
Resolving the molecular basis for heterogeneous ageing in the human brain requires integrating its diverse molecular layers. Here we applied a tensor-decomposition framework to jointly analyse single-nucleus RNA-seq, DNA methylation, H3K9ac histone acetylation and proteomic data from 276 post-mortem human cortices. The analysis uncovered two dominant, multi-omic themes. First, we identified an immunometabolic axis characterised by microglial activation, suppression of PI3K-Akt-mTOR signalling and epigenetic signatures that suggest repurposing of developmental transcription factors such as BARHL1. Second, we decomposed the effect of sex into a multi-omic program linked to cellular plasticity: although driven by canonical sex-chromosome genes, this axis was epigenetically enriched for pathways regulating stem-cell pluripotency and exhibited a female-biased shift toward precursor-like states in the oligodendrocyte lineage. Together, these findings deliver a high-resolution atlas of glial ageing and demonstrate that broad risk factors manifest as complex, cell-specific vulnerabilities; an insight critical for the development of targeted therapeutic strategies.
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Early microglial priming in Alzheimer's disease revealed by ME-seq.
Epigenetic modifications, particularly DNA methylation, change dynamically with aging and are implicated in Alzheimer's Disease (AD), yet how methylation interfaces with transcriptional and chromatin regulation at single-cell resolution remains poorly understood. Progress has been limited by a lack of scalable technologies capable of jointly profiling these regulatory layers. Here, we present ME-seq, a highly scalable technologies capable of simultaneously profiling DNA methylation, gene expression, and chromatin accessibility, while achieving a 100-fold reduction in cost. We generated over 400,000 single-nucleus trimodal profiles from the aging and AD mouse brain across ages, producing the first such atlas of neurodegeneration. We found AD progression triggers pronounced, disease-specific shifts in cellular composition, characterized by accelerated epigenetic aging and the expansion of disease-associated microglia (DAM). Integrative analyses, including aging clocks, revealed that DNA methylation acts as an early priming layer preceding transcriptional activation with IRF1 identified as a methylation-sensitive transcription factor serving as a gatekeeper for DAM activation. Our results establish ME-seq as a transformative tool for large-scale epigenomic dissection, revealing DNA methylation as a primary coordinator of cell-state transitions in the aging brain.
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Gene regulatory programs of cognitive resilience and pathogenesis in Alzheimer's disease.
INTRODUCTION: Cognitive resilience in Alzheimer's disease (AD), wherein individuals maintain cognition despite substantial neuropathology, implies protective regulatory programs that remain poorly characterized. METHODS: We constructed a cell-type-resolved gene regulatory network atlas from 1.7 million nuclei across 687 individuals spanning 26 cell types in the dorsolateral prefrontal cortex, classified as Control, Resilient, or AD dementia. RESULTS: Analysis of 223 transcription factor regulons reveals a three-state regulatory framework: homeostatic erosion of IRF8/STAT1 interferon programs (State I), compensatory NF-κB suppression via BCL6 that distinguishes resilient from demented individuals (State II), and pathogenic FLI1/IKZF1 network expansion driving vascular-immune remodeling (State III). NF-κB emerges as the central hub, with BCL6-mediated repression and FLI1/RELA-driven activation constituting opposing molecular switches. DISCUSSION: Replicated across independent cohorts, these findings model resilience as an active regulatory state and nominate stage-specific therapeutic strategies: restoring homeostatic programs, prolonging compensatory suppression, and constraining inflammatory escalation.
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Exploring the Prognostic Significance and Immunotherapeutic Potential of Single-Cell Sequencing-Identified Long Noncoding RNA (LncRNA) in Patients With Non-small Cell Lung Cancer.
BACKGROUND: Single-cell RNA sequencing technology can provide insight into lung cancer. The purpose of this study was to analyze the relationship between long noncoding RNA (lncRNA) discovered by RNA sequencing and immunotherapy in patients with non-small cell lung cancer (NSCLC). METHODS: In this study, we utilized data from The Cancer Genome Atlas (TCGA) to extract gene expression data and prognostic information from patients with NSCLC. We employed univariate, least absolute shrinkage and selection operator (LASSO), multivariate Cox regression analyses to construct risk models, and Kaplan-Meier (KM) analysis to compare survival differences between high- and low-risk groups. To evaluate the accuracy of our risk model predictions, we utilized a nomogram, calibration curve, correlation index curve (C-index), and receiver operating characteristic (ROC). Additionally, we conducted Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to investigate the differential expression of lncRNA genes. We also used the tumor immune dysfunction and exclusivity (TIDE) algorithm and the R package "pRRophetic" to analyze the tumor microenvironment. Finally, we utilized stem cell indices based on mRNA expression-based stemness index (mRNAsi) expression to better assess patient prognosis. RESULTS: Our analysis identified a set of 28 lncRNAs with prognostic risk profiles in patients with lung adenocarcinoma. Notably, patients in the low-risk group exhibited significantly better overall survival (OS) compared to those in the high-risk group. Kaplan-Meier (KM) survival curves revealed that these prognostic risk markers accurately predicted survival outcomes in non-small cell lung cancer (NSCLC) patients. MerCK18 and myeloid-derived suppressor cells (MDSC) were strongly associated with immune escape and immunotherapy in high- and low-risk subgroups. In our investigation of potential chemotherapeutic agents for the treatment of NSCLC, we screened a total of 60 agents and found that PPM1D was more effective in the low-risk group. However, we did not observe a strong correlation between the stem cell index mRNAsi and OS. CONCLUSION: Our study highlights the close association between lncRNAs and prognostic risk profiles and the prognosis of patients with non-small cell lung cancer, offering a promising avenue for the clinical implementation of immunotherapy.
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Single-cell multiomics reveals disrupted glial gene regulatory programs in Alzheimer's disease via interpretable machine learning.
Recent development of single-cell technology across multiple omics platforms has provided new ways to obtain holistic views of cells to study disease pathobiology. Alzheimer's disease (AD) is the most common form of dementia worldwide, yet the detailed understanding of its cellular and molecular mechanisms remains limited. In this study, we analyzed paired single-cell transcriptomic (scRNA-seq) and chromatin accessibility (scATAC-seq) data from the Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD) Consortium to investigate the molecular mechanisms of AD at a cell-subpopulation-specific resolution focusing on glial cells. We benchmarked various multi-omics integration methods using diverse metrics and built an analytic workflow that enabled effective batch correction and cross-modality alignment, creating a unified cell state space. Through integrative analysis of 26 human brain samples, we uncovered AD-associated gene expression and pathway changes in glial subpopulations and highlighted important transcriptomic and epigenomic signatures via functional inference and interpretable machine learning paradigms, discovering the profound involvement of the Solute Carrier proteins (SLC) family genes in multiple glial cell types. We also identified glial cell-specific regulatory programs mediated by key transcription factors such as JUN and FOSL2 in astrocytes, the Zinc Finger (ZNF) family genes in microglia, and the SOX family of transcription factors in oligodendrocytes. Our study provides a comprehensive workflow and a high-resolution view of how glial regulatory programs are disrupted in AD. Our findings offer novel insights into disease-related changes in gene regulation and suggest potential targets for further research and therapy.
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Single-nucleus sequencing and spatial metabolomics analysis reveal the regulatory mechanism of ginkgolic acid biosynthesis in the episperm of Ginkgo biloba.
Ginkgo biloba is a singular and relict gymnosperm indigenous to China. Its distinctive fleshy episperm is rich in unique metabolites, ginkgolic acids, which protect the developing seed from biotic stresses. The unique nature of the tissue and its metabolites has made it highly challenging to elucidate the molecular and cellular mechanisms governing ginkgolic acid biosynthesis and regulation. In this study, we performed the mass spectrometry imaging of G. biloba seed, revealing that ginkgolic acids primarily accumulate in the secretory cavities of the episperm. We constructed a single-cell expression atlas of the G. biloba episperm and identified seven cellular types: meristem cells, subepidermal cells, lignified cells, trancheid cells, parenchymal cells, secretory cavity cells, and epidermis cells. Based on the analysis of upregulated gene expression in secretory cavity cells, pseudotime analysis of cell differentiation, and gene expression trajectory analysis, we precisely identified the key enzyme-encoding genes highly associated with ginkgolic acid biosynthesis. This approach elucidated the cellular and molecular mechanisms underlying secretory cell differentiation, secretory cavity formation, and ginkgolic acid biosynthesis and accumulation in response to exogenous jasmonic acid induction. By constructing a molecular interaction network, it was determined that the GbWRKY35, encoded by Gb_25334, is the core transcription factor. We further identified the signaling proteins that interact with GbWRKY35, confirming its central positive regulatory role in ginkgolic acid biosynthesis. As a core transcription factor, GbWRKY35 regulates ginkgolic acid biosynthesis through stimulating the expression of GbAAE16. This study provides the first spatially resolved investigation into the molecular and cellular regulatory mechanisms of ginkgolic acid biosynthesis in the episperm under jasmonic acid induction.