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Integrative Single-Cell and Spatial Transcriptomics Reveal Organelle Stress-Associated Heterogeneity and Immune Microenvironment Remodeling in Lung Adenocarcinoma.
BACKGROUND: Lung adenocarcinoma (LUAD) exhibits marked heterogeneity. Organelle stress-adaptive programs that tumor cells develop under hypoxia, nutrient limitation, and proteostasis pressure may drive functional reprogramming of tumor biology, remodel the immune microenvironment, and ultimately influence the benefits of immunotherapy. Therefore, it is necessary to systematically characterize the coordinated changes across organelle stress-related pathways in LUAD, establish a subtyping and prognostic stratification framework, and identify key molecules as well as potential cell-cell communication axes. METHODS: Transcriptomic profiles and clinical follow-up data from The Cancer Genome Atlas LUAD (TCGA-LUAD) cohort and public cohorts were collected. Pathway activities were quantified using organelle stress-related gene sets, and core stress programs associated with overall survival (OS) and progression-free survival (PFS) were screened by Cox regression and Kaplan-Meier analyses. Nonnegative matrix factorization (NMF) was used for unsupervised subtyping and stability evaluation. Functional enrichment, genomic features, and immune landscapes were compared between subtypes, and potential benefit from immune checkpoint blockade (ICB) was inferred using tumor immune dysfunction and exclusion (TIDE) and immunophenoscore (IPS). Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) were integrated to characterize malignant cell states, spatial niches, and cell-cell communication networks. In LUAD cell lines, the candidate gene was silenced by small interfering RNA (siRNA), and phenotypic assays were performed to validate its effects. RESULTS: The organelle stress activity-based system robustly classified LUAD into two biologically distinct subtypes (the mitochondrial-ribosome biogenesis, MRB, subtype and the lysosomal catabolism, LC, subtype), which showed systematic differences in prognosis and functional programs. The MRB subtype exhibited enhanced stress and metabolic adaptation accompanied by immune exclusion features, whereas the LC subtype showed a relatively immune-active tumor microenvironment. Immunotherapy-related analyses suggested divergent trends in potential ICB benefit between the two subtypes. Multiscale evidence highlighted SLC16A14 (MCT14) as a key node linking stress heterogeneity to malignant progression. At the single-cell level, SLC16A14 was mainly expressed in malignant cells, and communication analyses suggested that CALCR-related signaling may mediate tumor-endothelial interactions and contribute to an immune-excluded microenvironment. In vitro, SLC16A14 silencing suppressed tumor cell proliferation, invasion, and migration, supporting its role as a key molecule connecting stress adaptation and tumor progression. CONCLUSION: We established an organelle stress program-based subtyping and prognostic framework for LUAD, revealed the coupling between stress adaptation and TME remodeling, and proposed SLC16A14 and its associated communication network as potential intervention targets, providing multiomics evidence for interpreting LUAD heterogeneity and for stratifying immunotherapy and combination strategies.
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Multi-omics analysis reveals key genes associated with clear cell renal cell carcinoma.
BACKGROUND: The most common type of kidney cancer is ccRCC (Clear Cell Renal Cell Carcinoma). Existing research has shown that when kidney cancer progresses from T2 to T3 or T4 stage, the treatment options and prognosis significantly differ. The aim of this study is to identify prognosis-related genes in ccRCC using single-cell data and Mendelian randomization analysis. METHODS: Single-cell RNA sequencing (scRNA-seq) data from six ccRCC patients (GSE156632) were analyzed in R. After quality control and normalization, cells were embedded, clustered, and annotated to define major cell types. Cell-cell signaling networks were inferred using CellChat. Stage-related co-expression programs were identified using high-dimensional weighted gene co-expression network analysis (hdWGCNA), and modules enriched in advanced disease were prioritized. To connect expression patterns with germline variation, we obtained expression quantitative trait loci (eQTL) summary statistics from the UK Biobank and performed two-sample Mendelian randomization using the ukb-b-1316 exposure dataset. For clinical validation, bulk RNA-seq and survival data from The Cancer Genome Atlas (TCGA) were incorporated, and candidate genes were evaluated using univariable Cox proportional hazards models. RESULTS: hdWGCNA identified three modules, from which we selected 150 genes. eQTL combined with Mendelian randomization analysis revealed a potential causal relationship between RBP5, PRDX2, GTSF1, BSG, and COX14 and tumorigenesis. Further TCGA data analysis indicated that PRDX2 might serve as a protective factor in ccRCC, consistent with the Mendelian randomization results. Furthermore, its expression exhibited a gradual decline with tumor stage progression. Kaplan-Meier(KM) curves demonstrated better prognosis for patients with high PRDX2 expression. Cell communication analysis revealed more frequent communication between cells with reduced PRDX2 expression and vascular endothelial cells. Moreover, the experiments demonstrate that the migration and proliferation abilities of ccRCC cells are enhanced after knocking down PRDX2. CONCLUSION: These results suggest that PRDX2 may play a role in the progression of ccRCC and could potentially serve as a prognostic factor and therapeutic target for ccRCC.
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Integrated single-cell and spatial transcriptomics reveal divergent immunological and stromal programs in peritoneal versus ovarian endometriosis.
BACKGROUND: Endometriosis encompasses heterogeneous lesions, primarily peritoneal and ovarian subtypes, with distinct immunological and fibrotic features. The subtype-specific roles of the immune microenvironment in pathogenesis remain unclear. Integrated analysis combining high-resolution cellular atlases with spatial context is needed to decipher these mechanisms. METHODS: We performed an integrative analysis of published single-cell RNA sequencing (n = 81,676 cells) from control endometrium (Ctrl), eutopic endometrium (EuE), peritoneal endometriosis (EcP), and ovarian endometriosis (EcO), and spatial transcriptomic (n = 60 segments) data from Ecp and match EuE. Analytical pipelines include cellular atlas construction, differential expression, spatial co-expression, and cell-cell communication inference. RESULTS: Our single-cell atlas revealed fundamentally distinct cellular ecosystems. EcP was enriched for CCL19 + perivascular cells (6.4-fold vs. control) and immune-active niches, whereas EcO exhibited pronounced smooth muscle differentiation and NNMT upregulation. Spatial analysis compartmentalized these programs, with the CCL19-CCR7 chemokine axis localized to stromal niches in EcP strongly correlated (ρ = 0.872). In contrast, EcO showed enhanced smooth muscle gene expression (MYH11, log₂FC = 3.87). Cell-cell communication networks diverged, with EcP dominated by chemokine and TGF-β signaling, and EcO dominated by smooth muscle and PDGF pathways. Therapeutic target analysis revealed subtype-specific patterns: immune checkpoints (CTLA4 and PDCD1) were upregulated in EcP, whereas MMP9 was dramatically downregulated in EcO. CONCLUSION: EcP and EcO exhibit fundamentally divergent programs. We propose to conceptualize these as an ‘immune-hot’, chemokine-driven inflammatory niche (EcP) versus an ‘immune-cold’, fibromuscular survival niche (EcO). These findings underscore that lesion-specific immune-stromal crosstalk may dictates pathogenesis and suggest a potential paradigm shift toward immunologically-informed, subtype-specific precision therapeutics, which warrant further experimental validation.
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Peripheral blood transcriptomes and a single-cell atlas suggest a monocyte-associated immune recovery-failure axis in STEMI.
BACKGROUND: Patients with ST-segment elevation myocardial infarction (STEMI) continue to show substantial inflammatory heterogeneity after reperfusion therapy, and recovery trajectories may differ markedly across patients. Compared with traditional diagnostic models, characterizing the dynamic immune trajectory from acute inflammation toward recovery may better identify programs associated with impaired resolution. This study aimed to construct an immune recovery-failure framework that is transferable across cohorts and anchored by single-cell data. METHODS: We integrated six public GEO peripheral-blood bulk transcriptome cohorts and one public single-cell RNA-seq dataset. An acute-to-recovery immune axis was constructed from directionally concordant longitudinal and cross-sectional contrasts, and a recovery-failure phenotype was defined in the discovery longitudinal cohort from paired transcriptomic features. An 18-gene monocyte-associated module was then derived using bulk recovery-failure associations, monocyte specificity, monocyte-state differences, and pseudotime information. External cohorts were used to evaluate temporal transfer and baseline-to-follow-up associations rather than definitive clinical prediction, and the single-cell dataset was used for donor-aware cell-type anchoring and exploratory state-level interpretation. RESULTS: Among 81 STEMI patients who met the longitudinal definition criteria, unsupervised stratification classified 35 as recovery-failure patients and 46 as recovery-sufficient patients. We constructed an 18-gene monocyte-associated recovery-failure module. The module distinguished the two transcriptomically defined groups in the discovery cohort and declined from the acute phase toward recovery in external longitudinal cohorts. Baseline module burden was associated with later composition-adjusted inflammatory burden, but this was interpreted as a baseline-to-follow-up association rather than clinical event prediction. At the single-cell level, donor-aggregated lesion-associated shifts were largest in monocytes, and the module decreased along the acute-high-to-recovery-biased monocyte pseudotime direction. In 1,000 matched random monocyte-gene modules, the observed module showed a higher aggregate recovery statistic than nearly all random signatures. CONCLUSIONS: We propose a STEMI immune recovery-failure framework derived from public peripheral-blood transcriptomes, evaluated across independent longitudinal datasets, and linked to monocyte state variation in a public single-cell context. The framework is does not evidence of a causal mechanism or a validated hard-endpoint prediction model; rather, it provides a reproducible transcriptomic description of impaired inflammatory resolution that should be tested prospectively and experimentally.
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Single-nucleus multiomic profiling of the aging mouse substantia nigra reveals conserved gene alterations linked to Parkinson's disease.
Parkinson's disease (PD) is a prevalent neurodegenerative disorder predominantly affecting individuals over 60. Its motor symptoms stem from the deterioration of dopaminergic neurons within the substantia nigra. Despite aging being a significant risk factor, the specific mechanisms linking aging and PD pathology remain unclear. Leveraging advancements in single-cell genomics, this study utilizes single-nucleus multiome sequencing to capture transcriptomic and epigenetic profiles from 40,125 cells across the lifespan of the mouse substantia nigra. Our analysis pinpoints age-associated changes at a cell type-specific level, revealing a subset of genes that increasingly express with age and are enriched in PD-related pathways, notably in oligodendrocytes at late aging stages. Integration with five public PD single-cell RNA-seq data sets highlights 85 genes consistently differentially expressed with aging and PD. Key genes such as Hsp90aa1 and Hsp90ab1 are upregulated at late aging stages in oligodendrocytes, microglia, and glutamatergic neurons. Additionally, Apoe in microglia and genes related to protein folding in oligodendrocytes are upregulated at late aging stages, whereas genes involved in myelination are downregulated at early aging stages in oligodendrocyte. Our multiomic atlas underscores the substantial regulatory network changes during aging that may predispose to PD, providing valuable insights for furthering understanding of PD pathogenesis and potential therapeutic targets.
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scRNA-Seq: First Atlas and Cellular Landscape of Lacrimal Sac: Implications in Primary Acquired Nasolacrimal Duct Obstruction Pathogenesis.
PURPOSE: The aim of this study was to describe the transcriptional changes of individual cellular components in the lacrimal sac in patients with primary acquired nasolacrimal duct obstruction (PANDO) and attempt to construct the first lacrimal sac cellular atlas to elucidate the potential mechanisms that may drive the disease pathogenesis. METHODS: Lacrimal sac samples were obtained intra-operatively during the endoscopic dacryocystorhinostomy (EnDCR) procedure from five patients. Single-cell RNA sequencing was performed to analyze each individual cell population including epithelial and immune cells during the early inflammatory and late inflammatory phases of the disease. RESULTS: Eleven cell types were identified among 25,791 cells. T cells and B cells were the cell populations with the greatest variation in cell numbers between the two phases and were involved in immune response and epithelium migration-related pathways. The present study showed that epithelial cells highly expressed the genes of senescence-associated secretory phenotype (SASP) and were involved in influencing the inflammation, neutrophil chemotaxis, and migration during the late inflammatory stage. Enhanced activity of CXCLs-CXCRs between the epithelial cells and neutrophils was noted by the cell-cell communication analysis and is suspected to play a role in inflammation by recruiting more neutrophils. CONCLUSIONS: The study presents a comprehensive single-cell landscape of the lacrimal sac cells in different phases of PANDO. The contribution of T cells, B cells, and epithelial cells to the inflammatory response, and construction of the intercellular signaling networks between the cells within the lacrimal sac has further enhanced the present understanding of the PANDO pathogenesis.
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Single cell transcriptomic atlas reveals macrophage polarization dynamics and intercellular communication networks in gingival tissue of periodontitis patients undergoing orthodontic treatment.
BACKGROUND: Periodontitis combined with orthodontic treatment creates a complex inflammatory and biomechanical microenvironment in gingival tissue, where macrophages play pivotal roles in tissue remodeling and immune regulation. However, the heterogeneity of macrophage subtypes and their polarization dynamics in this clinical context remain poorly understood. METHODS: We performed single-cell RNA sequencing (scRNA-seq) on gingival tissue samples from periodontitis patients undergoing orthodontic treatment. Using integrated bioinformatics approaches including dimensionality reduction, pseudotime trajectory analysis, RNA velocity, cell-cell communication inference, and functional enrichment analysis, we comprehensively characterized macrophage subtypes, their polarization states, and intercellular signaling networks. RESULTS: We identified 11 distinct cell populations with significant macrophage heterogeneity, including M1-like pro-inflammatory and M2-like tissue-remodeling subtypes along with intermediate transitional states. Trajectory analysis revealed dynamic polarization pathways with multiple branching points, demonstrating remarkable phenotypic plasticity. Macrophages served as central communication hubs, engaging in extensive crosstalk with fibroblasts, epithelial cells, endothelial cells, and lymphocytes through cytokine, growth factor, chemokine, and extracellular matrix signaling pathways. Transcription factor analysis identified NF-κB, STAT1, and IRF family members driving M1 polarization, while PPARγ, C/EBPβ, and KLF4 promoted M2 phenotypes. Telomere maintenance gene profiling revealed differential cellular aging patterns across subtypes, with pro-inflammatory macrophages showing stress-induced senescence signatures. Functional enrichment demonstrated that macrophages integrate inflammatory responses with mechanotransduction pathways, responding to both periodontal pathogens and orthodontic mechanical forces. CONCLUSIONS: This single-cell transcriptomic atlas provides unprecedented insights into macrophage heterogeneity and functional specialization in periodontitis patients undergoing orthodontic treatment.
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Single-cell atlas of Exopalaemon carinicauda gills provides insights into pillar cell-mediated responses to low-salinity stress in crustaceans.
Low-salinity stress exerts strong constraints on ion homeostasis in crustaceans cultivated in coastal environments. Gills function as central osmoregulatory organs in crustaceans, coordinating transepithelial ion flux and acid-base balance; however, the cellular mechanisms governing gill adaptation to reduced salinity remain poorly understood. Here, integrated ultrastructural characterization and single-cell RNA sequencing (scRNA-seq) were applied to define cellular responses to low-salinity exposure in Exopalaemon carinicauda gills. Low salinity induced pronounced morphological remodeling in pillar cells. Single-cell transcriptomic profiling resolved 11 transcriptionally distinct populations, including two ionocyte lineages represented by pillar cells and septal cells. Comparative analyses demonstrated a marked expansion of pillar cell subcluster 3 under low-salinity stress, accompanied by enrichment of differentially expressed genes (DEGs) in ion transport pathways, notably hydrogen ion transport. Weighted gene co-expression network analysis identified coordinated up-regulation of hub genes associated with pH regulation within pillar cells. Pseudotime reconstruction further indicated that gill adaptation to low-salinity stress proceeds through a defined differentiation trajectory (cell fate 1) originating from pillar cells. Core stress-responsive genes in pillar cells, including V(H +)-ATPases and cytoplasmic carbonic anhydrase, were predominantly associated with acid-base regulation. Collectively, these results delineate gill cellular heterogeneity and identify pillar cell-mediated regulatory mechanisms that underpin crustacean physiological adaptation to low-salinity environments.
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Multiomics Reveals IL-17 Drives Epithelial Keratinization and Proliferation via EHF in Odontogenic Keratocysts.
This study aims to investigate epithelial cell (EpC) heterogeneity in odontogenic keratocysts (OKCs) and the molecular mechanisms driving their characteristic keratinization and rapid proliferation. We integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics to profile OKC EpCs, validating findings via immunostaining and comparative analysis with normal oral mucosa. The regulatory roles of interleukin-17 (IL-17) and the transcription factor EHF were functionally assessed in vitro using human oral keratinocytes. Multi-omics mapping identified a distinct epithelial subpopulation (EpC2) characterized by robust keratinization, elevated keratin 13 (KRT13), and upregulated IL-17 signaling. Clinical OKC tissues exhibited significant upregulation and spatial co-localization of IL-17 and KRT13. In vitro, IL-17 robustly promoted cellular proliferation and KRT13 expression. Regulon analysis pinpointed EHF as the core transcription factor driving EpC2. EHF knockdown suppressed proliferation and downregulated KRT13, while overexpression amplified these processes. Crucially, IL-17 stimulation failed to rescue KRT13 expression in EHF-depleted cells, suggesting EHF as a critical downstream mediator. We present a comprehensive single-cell and spatial transcriptomic atlas of the OKC epithelium. The IL-17/EHF signaling axis appears to be a fundamental driver of OKC pathogenesis, promoting pathological hyperkeratinization and cellular proliferation. Targeting this axis presents a promising therapeutic strategy to manage OKC growth and prevent recurrence.
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[Types of Preeclampsia According to Placental Single Cell RNA Sequencing, Type 1 and Type 2 Levels - Insights and Clinical Implications].
INTRODUCTION: Preeclampsia, one of the Great Obstetrical Syndromes, remains a major contributor to maternal and fetal morbidity worldwide. Its clinical heterogeneity, classically reflected in "early" versus "late" presentations, underscores the need for biologically grounded sub-classifications to guide diagnosis and management. OBJECTIVES: To characterize the cellular and molecular mechanisms underlying preeclampsia subtypes using advanced single-cell and single-nuclei transcriptomic approaches, and to evaluate their alignment with a proposed integrated model distinguishing Type I (placental dysfunction) from Type II (maternal cardiovascular maladaptation) preeclampsia. METHODS: We performed single-cell and single-nuclei RNA sequencing on approximately 90,000 placental cells, encompassing 46 distinct cell populations, including trophoblast, lymphoid, myeloid, stromal, and endothelial lineages. Comparative transcriptomic analyses were conducted between early-onset and late-onset preeclampsia and control pregnancies. RESULTS: Profound cellular dysregulation was identified in early-onset preeclampsia across multiple placental cell types, consistent with widespread placental dysfunction, angiogenic imbalance, inflammatory response and apoptosis. In contrast, late-onset preeclampsia exhibited comparatively subtle transcriptional changes, suggestive of a distinct pathophysiological process driven by maternal cardiovascular maladaptation, placental aging, cellular senescence and oxidative stress. These findings support the classification of preeclampsia into Type I (placental-dominant, early-onset) and Type II (maternal-dominant, late-onset) forms, each characterized by specific risk factors, biomarkers, and therapeutic targets. CONCLUSIONS: This placental molecular atlas integrates single-cell and single-nuclei transcriptomic data with clinical phenotypes, providing mechanistic support for the Type I and Type II preeclampsia framework. These insights inform the development of targeted interventions, including RNA-based therapies to modulate placental angiogenic pathways in early-onset disease, and maternal cardiovascular optimization strategies in late-onset disease.