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Single-cell profiling reveals periosteal signatures of impaired periosteal cells proliferation in a drill-hole model of type 2 diabetes.
Type 2 diabetes mellitus (T2DM) is associated with an elevated fracture risk and impaired healing, but the periosteum's role in delayed repair remains unclear. In db/db mice, both trabecular and cortical bone mass were reduced, with single-cell RNA sequencing revealing downregulation of the Wnt pathway in osteogenic periosteal cells, which is critical for maintaining cortical bone. Transcriptomic analysis of periosteal cells from humans with T2DM further underscored the evolutionary conservation of osteogenic properties. A comprehensive atlas of periosteal cells under WT and T2DM conditions, pre- and post-fracture, identified induced fibrogenic cells as essential for fracture repair. Further analysis confirmed that induced fibrogenic cells contribute to both intramembranous and endochondral ossification. Importantly, we identified Fibrinogen-like Protein 2 (FGL2), expressed by fibro-adipogenic progenitors (FAPs) and periosteal cells, as a key factor hindering healing by suppressing periosteal proliferation through mitochondrial regulation via the mTORC1 pathway. These findings highlight the periosteal heterogeneity and dynamics involved in delayed fracture healing in T2DM.
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Widespread choroid plexus contamination in sampling and profiling of brain tissue.
The choroid plexus, a tissue responsible for producing cerebrospinal fluid, is found predominantly in the lateral and fourth ventricles of the brain. This highly vascularized and ciliated tissue is made up of specialized epithelial cells and capillary networks surrounded by connective tissue. Given the complex structure of the choroid plexus, this can potentially result in contamination during routine tissue dissection. Bulk and single-cell RNA sequencing studies, as well as genome-wide in situ hybridization experiments (Allen Brain Atlas), have identified several canonical markers of choroid plexus such as Ttr, Folr1, and Prlr. We used the Ttr gene as a marker to query the Gene Expression Omnibus database for transcriptome studies of brain tissue and identified at least some level of likely choroid contamination in numerous studies that could have potentially confounded data analysis and interpretation. We also analyzed transcriptomic datasets from human samples from Allen Brain Atlas and the Genotype-Tissue Expression (GTEx) database and found abundant choroid contamination, with regions in closer proximity to choroid more likely to be impacted such as hippocampus, cervical spinal cord, substantia nigra, hypothalamus, and amygdala. In addition, analysis of both the Allen Brain Atlas and GTEx datasets for differentially expressed genes between likely "high contamination" and "low contamination" groups revealed a clear enrichment of choroid plexus marker genes and gene ontology pathways characteristic of these ciliated choroid cells. Inclusion of these contaminated samples could result in biological misinterpretation or simply add to the statistical noise and mask true effects. We cannot assert that Ttr or other genes/proteins queried in targeted assays are artifacts from choroid contamination as some of these differentials may be due to true biological effects. However, for studies that have an unequal distribution of choroid contamination among groups, investigators may wish to remove contaminated samples from analyses or incorporate choroid marker gene expression into their statistical modeling. In addition, we suggest that a simple RT-qPCR or western blot for choroid markers would mitigate unintended choroid contamination for any experiment, but particularly for samples intended for more costly omic profiling. This study highlights an unexpected problem for neuroscientists, but it is also quite possible that unintended contamination of adjacent structures occurs during dissections for other tissues but has not been widely recognized.
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STHELAR, a multi-tissue dataset linking spatial transcriptomics and histology for cell type annotation.
Understanding the composition of the tumor microenvironment is critical for cancer research. Spatial transcriptomics profiles gene expressions in spatial context, revealing tissue architecture and cellular heterogeneity, but its cost and technical complexity limit adoption. To address this issue, we introduce a pipeline to build STHELAR, a large-scale dataset that integrates spatial transcriptomics with Hematoxylin and Eosin (H&E) whole-slide images for cell type annotation. The dataset comprises 31 human Xenium FFPE sections across 16 tissue types, for 22 cancerous and 9 non-cancerous patients. It contains over 11 million unique biological cells, each assigned to one of ten curated cell-type categories designed to accommodate a pan-cancer setting. Annotations were derived through Tangram-based alignment to single-cell reference atlases, followed by slide-specific clustering and differential expression analysis. Co-registered H&E images enabled the extraction of over 500,000 patches with segmentation and classification masks. Quality control steps assessed segmentation accuracy, filtered out low-confidence regions, and verified annotation integrity. STHELAR provides a reference resource for developing models to predict cell-type annotations directly from histological images.
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The Role of CD8A in the Immune Microenvironment of Breast Cancer.
BACKGROUND: Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer (BC), and it is often associated with a high tumor grade, a younger age at diagnosis, and a low survival rate. Conventional endocrine and anti-HER-2 therapies are usually ineffective against TNBC, creating treatment challenges and resulting in a poor prognosis. Hence, new targets and treatment strategies for TNBC are urgently required. METHODS: The GSE102818 dataset was used to identify differentially expressed genes (DEGs) between primary BC and metastatic BC lesions. The Cancer Genome Atlas and the cBioPortal platform were employed to explore mutations in candidate genes. Utilizing the Tumor IMmune Estimation Resource (TIMER), the relationship between the expression of candidate genes and immune cell infiltration was assessed. Additionally, the cell-specific expression of the candidate genes was examined in the immune microenvironment of primary BC and metastatic BC lesions using the single-cell RNA sequencing (scRNA-seq) datasets GSE118389 and GSE202695. Finally, the protein expression of the candidate genes in clinical TNBC samples was evaluated. RESULTS: CD8A was identified as a hub gene in the DEG network and was found to be down-regulated in metastatic BC lesions. CD8A expression was highly correlated with the infiltration of CD8+ T cells, and elevated CD8A expression was correlated with improved survival. Interestingly, scRNA-seq data revealed that CD8A was down-regulated in CD8+ T cells in the immune microenvironment of metastatic BC lesions. Finally, the evaluation of clinical samples confirmed the down-regulation of CD8A in the immune microenvironment of BC lung metastases. CONCLUSIONS: In patients with metastatic TNBC, high levels of CD8A (especially in the immune microenvironment) are associated with a good prognosis.
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Classification of Estrogen Receptor-Positive Breast Cancer Based on Immunogenomic Profiling and Validation at Single-Cell Resolution.
Background: The aim of this paper was to identify an immunotherapy-sensitive subtype for estrogen receptor-positive breast cancer (ER+ BC) patients by exploring the relationship between cancer genetic programs and antitumor immunity via multidimensional genome-scale analyses. Methods: Multidimensional ER+ BC high-throughput data (raw count data) including gene expression profiles, copy number variation (CNV) data, single-nucleotide polymorphism mutation data, and relevant clinical information were downloaded from The Cancer Genome Atlas to explore an immune subtype sensitive to immunotherapy using the Consensus Cluster Plus algorithm based on multidimensional genome-scale analyses. One ArrayExpress dataset and eight Gene Expression Omnibus (GEO) datasets (GEO-meta dataset) as well as the Molecular Taxonomy of Breast Cancer International Consortium dataset were used as validation sets to confirm the findings regarding the immune profiles, mutational features, and survival outcomes of the three identified immune subtypes. Moreover, the development trajectory of ER+ BC patients from the single-cell resolution level was also explored. Results: Through comprehensive bioinformatics analysis, three immune subtypes of ER+ BC (C1, C2, and C3, designated the immune suppressive, activation, and neutral subtypes, respectively) were identified. C2 was associated with up-regulated immune cell signatures and immune checkpoint genes. Additionally, five tumor-related pathways (transforming growth factor, epithelial-mesenchymal transition, extracellular matrix, interferon-γ, and WNT signaling) tended to be more activated in C2 than in C1 and C3. Moreover, C2 was associated with a lower tumor mutation burden, a decreased neoantigen load, and fewer CNVs. Drug sensitivity analysis further showed that C2 may be more sensitive to immunosuppressive agents. Conclusion: C2 (the immune activation subtype) may be sensitive to immunotherapy, which provides new insights into effective treatment approaches for ER+ BC.
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Single-Nucleus Phosphatome Rewiring and Phosphoproteomics Reveal PFKFB2 as an LRRK2-Linked Metabolic Node in Human Parkinsonian Substantia Nigra.
Aberrant signaling by leucine-rich repeat kinase 2 (LRRK2) drives Parkinson's disease (PD) biology, linking Rab phosphorylation to endolysosomal dysfunction. However, how LRRK2-linked trafficking intersects with metabolic remodeling within vulnerable human substantia nigra cell states remains poorly defined. Here, phosphatome-wide systems analysis, single-nucleus transcriptomics, structural modeling, and independent phosphoproteomic evidence were integrated to identify the glycolytic regulator PFKFB2 as a phosphorylation-associated metabolic node. Sample-level pseudobulk profiling of a human substantia nigra single-nucleus RNA-seq data set revealed distributed phosphatome remodeling across the PD spectrum, prioritizing PFKFB2 as a transcriptionally reduced, dynamically rewired systems hub. Full-atlas analysis across 390,360 nuclei showed that this tissue-level decrease resolved into disease-stage-specific cellular redistribution: PFKFB2 was reduced across oligodendrocyte-lineage and neuronal compartments in PD, whereas Parkinson's disease dementia (PDD) showed microglial induction alongside astrocytic and neuronal loss. Stratification by PFKFB2 expression revealed marked transcriptional polarity: PFKFB2-positive cellular states were enriched for LRRK2-Rab trafficking and lysosomal programs, whereas PFKFB2-negative states retained mitochondrial/OXPHOS signatures; paired donor-pseudobulk analysis confirmed that the principal PFKFB2-associated PDD microglial program was reproducible across donors. Structurally, AlphaFold-guided peptide docking identified the flexible C-terminal regulatory tail of PFKFB2 as a kinase-accessible region, prioritizing the conserved Ser483 locus as the strongest LRRK2-compatible structural candidate. Independent phosphoproteomic interrogation of human and mouse LRRK2 perturbation data sets supported the orthologous PFKFB2/Pfkfb2 Ser483/Ser486 region as an LRRK2-responsive phosphosite candidate, exhibiting inhibitor-sensitive reduction and inhibitor-resistant retention under A2016T LRRK2 conditions. Together, these findings position the PFKFB2 signaling axis as a cell-state-resolved metabolic interface linking LRRK2-Rab trafficking with the mitochondrial-endolysosomal disease architecture of the Parkinsonian substantia nigra.
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Empagliflozin and liraglutide ameliorate HFpEF in mice via augmenting the Erbb4 signaling pathway.
Heart failure with preserved ejection fraction (HFpEF) is closely associated with metabolic derangement. Sodium glucose cotransporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) exert anti-HFpEF effects, but the underlying mechanisms remain unclear. In this study, we explored the anti-HFpEF effects of empagliflozin and liraglutide and the underlying molecular mechanisms in a mouse model of HFpEF. This model was established by high-fat diet (HFD) feeding plus Nω-nitro-L-arginine methyl ester (L-NAME) treatment. The mice were treated with empagliflozin (20 mg·kg-1·d-1, i.g.) or liraglutide (0.3 mg·kg-1·d-1, i.p.) or their combination for 4 weeks. At the end of the experimental protocol, cardiac function was measured using ultrasound, then mice were euthanized and heart, liver, and kidney tissues were collected. Nuclei were isolated from frozen mouse ventricular tissue for single-nucleus RNA-sequencing (snRNA-seq). We showed that administration of empagliflozin or liraglutide alone or in combination significantly improved diastolic function, ameliorated cardiomyocyte hypertrophy and cardiac fibrosis, as well as exercise tolerance but no synergism was observed in the combination group. Furthermore, empagliflozin and/or liraglutide lowered body weight, improved glucose metabolism, lowered blood pressure, and improved liver and kidney function. After the withdrawal of empagliflozin or liraglutide for 1 week, these beneficial effects tended to diminish. The snRNA-seq analysis revealed a subcluster of myocytes, in which Erbb4 expression was down-regulated under HFpEF conditions, and restored by empagliflozin or liraglutide. Pseudo-time trajectory analysis and cell-to-cell communication studies confirmed that the Erbb4 pathway was a prominent pathway essential for both drug actions. In the HFpEF mouse model, both empagliflozin and liraglutide reversed Erbb4 down-regulation. In rat h9c2 cells, we showed that palmitic acid- or high glucose-induced changes in PKCα and/or ERK1/2 phosphorylation at least in part through Erbb4. Collectively, the single-cell atlas reveals the anti-HFpEF mechanism of empagliflozin and liraglutide, suggesting that Erbb4 pathway represents a new therapeutic target for HFpEF. Effects and mechanisms of action of empagliflozin and liraglutide in HFpEF mice. HFpEF was induced with a high-fat diet and L-NAME for 15 weeks, and treatment with empagliflozin and liraglutide improved the HFpEF phenotype. Single nucleus RNA sequencing (snRNA-seq) was used to reveal the underlying mechanism of action of empagliflozin and liraglutide.
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A bioinformatic analysis found low expression and clinical significance of ATF4 in breast cancer.
BACKGROUND: Activating Transcription Factor 4 (ATF4) expression exhibits differential patterns across different types of tumors. Besides, the pathogenesis of breast cancer is complex, and the exact relationship between ATF4 and ATF4 remains uncertain. METHODS: The analysis of ATF4 expression was conducted by utilizing The Cancer Genome Atlas (TCGA) pan-cancer data, while the gene expression profile of breast cancer was checked by the comprehensive database-Gene Expression Omnibus database. In order to gain a more comprehensive understanding of the specific cell types that exhibit ATF4 expression within the microenvironment of breast cancer, we conducted a single-cell analysis of ATF4 using two distinct datasets of human breast cancer (GSE114717 and GSE11088, respectively). The spatial distribution of ATF4 within a tissue was demonstrated based on datasets obtained from the Human Protein Atlas (HPA) and SpatialDB. The clinical prognostic significance of ATF4 was assessed by analyzing clinical survival data obtained from TCGA, GSE4830, and GSE25055 datasets. We used the R package clusterProfiler to carry out an enrichment analysis of ATF4. We assessed how ATF4 impacts the growth and movement of breast cancer cell lines. We manipulated ATF4 levels using plasmid transfection techniques. RESULTS: The expression of ATF4 was found to be suboptimal and demonstrated a significant correlation with enhanced disease-specific survival (p = 0.012) and overall survival (p = 0.032) in breast cancer as well as other malignancies. We conducted an analysis to investigate the interaction between the infiltration level of immune cells and the expression of ATF4, using samples obtained from TCGA with known immune cell infiltration scores. Furthermore, a notable positive correlation exists between the elevated expression of ATF4 and immune-related genomes, specifically those associated with chemokine as well as immunity. Subsequent examination revealed a notable augmentation in the cytodifferentiation of T cells into regulatory T (Treg) cells within tissues exhibiting elevated levels of ATF4 expression. ATF4 exhibits notable upregulation in the MDA-MB-231 cell, thereby exerting a substantial impact on cell proliferation and migration upon its knockdown. Conversely, the overexpression of ATF4 in the MCF7 Luminal A breast cancer cell line can also modulate cellular function. CONCLUSIONS: Our study suggests that ATF4 helps T cells differentiate into Treg cells in breast cancer. ATF4 can represent a clinically useful biomarker to predict the overall survival rate, especially in patients with different subtypes of breast cancer. Provide certain guidance value for the development of targeted drugs or inhibitors targeting ATF4.
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Histone Methyltransferase SETD1B Maintains Cancer Stem Cell Niche by Regulating the Crosstalk between CD24 and Surface Adhesion Molecules in Hepatocellular Carcinoma.
Purpose: Hepatocellular carcinoma (HCC) is a highly aggressive malignancy with a dismal prognosis that is largely attributed to the capacity of liver cancer stem cells (LCSCs) to self-renew in response to conventional therapies. Therefore, it is crucial to develop new therapeutic strategies that target LCSCs to improve the clinical outcomes of patients with HCC. Experimental Design: We surveyed and analyzed publicly available single-cell TCGA (the cancer genome atlas), single-cell (scRNA-seq) and spatial RNA-sequencing databases from HCC patient specimens for genes uniquely expressed in LCSCs. We generated and characterized LCSCs from patient-derived HCC cell lines and used them as tools to uncover the previously unknown molecular mechanisms associated with the stemness of LCSCs. We selectively screened a bank of natural compounds to identify drugs that can specifically target LCSCs for HCC treatment and documented their effects both in vitro and in vivo. Results: TCGA analyses showed that SETD1B expression was aberrantly elevated in HCC, correlating with poor prognosis and a distinct molecular signature of stemness. We demonstrated that SETD1B, driven by MAZ, enhances stem characteristics by promoting anchorage-independence, cellular adhesion, tumor sphere formation, and growth via the surface glycoprotein CD24. We identified triptolide (Trip), which serves as a potent suppressor of LCSC stemness by targeting SETD1B for degradation, thereby dramatically attenuating HCC progression in vitro and in vivo. Conclusions: These findings establish the MAZ/SETD1B/CD24 signaling cascade as a critical regulatory mechanism of LCSC stemness and highlight Trip as a potential therapeutic agent for HCC.
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Developmental and cellular vulnerabilities underlie genetic architecture of schizophrenia.
Schizophrenia (SZ) is a highly heritable neuropsychiatric condition with complex polygenic architecture. Elucidating the cellular and developmental substrates vulnerable to the genetic risk is essential for understanding the underlying neurobiological mechanisms. Here, we integrated genome-wide association study (GWAS) and whole-exome sequencing (WES) data with a developmental multi-omics atlas of the human cortex (including 5 cortical regions), comprising about 3 million single-nucleus RNA sequencing (snRNA-Seq) and single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-Seq) profiles across 8 neurodevelopmental processes, to map cell-type-specific enrichment of SZ genetic risk. Our enrichment analyses revealed that both common and rare genetic liabilities converged on broad excitatory and inhibitory neuronal classes. Across different statistical frameworks, we identified genetic enrichment within intratelencephalic (IT) projection neurons and layer 6b excitatory neurons (Ex-L6b) networks across multiple cortical regions. Stage-resolved developmental mapping in the frontal cortex showed that genetic liabilities, particularly the rare variants, are predominantly concentrated within early developmental processes, namely neurogenesis and neuronal migration. Differential expression analysis in postmortem frontal cortex snRNA-Seq datasets cross-validated the cellular substrates of the genetic liabilities. Collectively, our findings establish a high-resolution cellular and temporal framework of SZ susceptibility, implicating mature associative IT microcircuits, deep-layer thalamocortical-regulating networks, and early developmental specification windows as primary points of genetic convergence in SZ.