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Single-cell atlas reveals the key role of pro-inflammatory IREB2⁺ microglia subsets in the microenvironment of Alzheimer's disease.
Chronic neuroinflammation driven by activated microglia is a critical hallmark of Alzheimer's disease (AD) progression. Metabolic dysregulation, particularly iron metabolism, has been implicated in neurodegeneration, yet the role of iron-responsive element-binding protein 2 (IREB2) in AD-associated neuroinflammation remains poorly understood. We performed integrative analysis of single-cell RNA sequencing (scRNA-seq) data from AD brain tissues, using non-negative matrix factorization (NMF) and intercellular communication algorithms to map cellular landscapes. We identified microglial subpopulations and their inflammatory signaling. To experimentally validate the functional role of IREB2 in inflammatory responses, we conducted siRNA-mediated knockdown in the human neuroblastoma cell line SH-SY5Y, which serves as a neuronal model for assessing IREB2's effect on cytokine expression. Single-cell analysis revealed a distinct microglial subpopulation (IREB2⁺ MC C1) that is significantly expanded in AD. This subpopulation exhibits a hyper-inflammatory state, with enrichment of Toll-like receptor and IL-17 signaling pathways, and functions as a primary source of outgoing inflammatory signals (CCL3, CCL4). Furthermore, IREB2 knockdown in SH-SY5Y cells significantly suppressed the expression of key pro-inflammatory cytokines (IL6, IL-1β, and TNF-α), confirming that IREB2 positively regulates inflammation in neurons as well. IREB2 drives both microglial activation and neuronal inflammatory responses in AD, potentially via the NF-κB pathway. The IREB2⁺ microglial subpopulation represents a specific pathogenic entity that orchestrates the inflammatory microenvironment. Targeting IREB2 may therefore offer a dual-pronged therapeutic strategy to mitigate neuroinflammation and slow AD progression.
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Downregulation of the Protein C Signaling System Is Associated with COVID-19 Hypercoagulability-A Single-Cell Transcriptomics Analysis.
Because of the interface between coagulation and the immune response, it is expected that COVID-19-associated coagulopathy occurs via activated protein C signaling. The objective was to explore putative changes in the expression of the protein C signaling network in the liver, peripheral blood mononuclear cells, and nasal epithelium of patients with COVID-19. Single-cell RNA-sequencing data from patients with COVID-19 and healthy subjects were obtained from the COVID-19 Cell Atlas database. A functional protein-protein interaction network was constructed for the protein C gene. Patients with COVID-19 showed downregulation of protein C and components of the downstream protein C signaling cascade. The percentage of hepatocytes expressing protein C was lower. Part of the liver cell clusters expressing protein C presented increased expression of ACE2. In PBMC, there was increased ACE2, inflammatory, and pro-coagulation transcripts. In the nasal epithelium, PROC, ACE2, and PROS1 were expressed by the ciliated cell cluster, revealing co-expression of ACE-2 with transcripts encoding proteins belonging to the coagulation and immune system interface. Finally, there was upregulation of coagulation factor 3 transcript in the liver and PBMC. Protein C could play a mechanistic role in the hypercoagulability syndrome affecting patients with severe COVID-19.
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Single-Cell Analyses Offer Insights into the Different Remodeling Programs of Arteries and Veins.
Arteries and veins develop different types of occlusive diseases and respond differently to injury. The biological reasons for this discrepancy are not well understood, which is a limiting factor for the development of vein-targeted therapies. This study contrasts human peripheral arteries and veins at the single-cell level, with a focus on cell populations with remodeling potential. Upper arm arteries (brachial) and veins (basilic/cephalic) from 30 organ donors were compared using a combination of bulk and single-cell RNA sequencing, proteomics, flow cytometry, and histology. The cellular atlases of six arteries and veins demonstrated a 7.8× higher proportion of contractile smooth muscle cells (SMCs) in arteries and a trend toward more modulated SMCs. In contrast, veins showed a higher abundance of endothelial cells, pericytes, and macrophages, as well as an increasing trend in fibroblasts. Activated fibroblasts had similar proportions in both types of vessels but with significant differences in gene expression. Modulated SMCs and activated fibroblasts were characterized by the upregulation of MYH10, FN1, COL8A1, and ITGA10. Activated fibroblasts also expressed F2R, POSTN, and COMP and were confirmed by F2R/CD90 flow cytometry. Activated fibroblasts from veins were the top producers of collagens among all fibroblast populations from both types of vessels. Venous fibroblasts were also highly angiogenic, proinflammatory, and hyper-responders to reactive oxygen species. Differences in wall structure further explain the significant contribution of fibroblast populations to remodeling in veins. Fibroblasts are almost exclusively located outside the external elastic lamina in arteries, while widely distributed throughout the venous wall. In line with the above, ECM-targeted proteomics confirmed a higher abundance of fibrillar collagens in veins vs. more basement ECM components in arteries. The distinct cellular compositions and transcriptional programs of reparative populations in arteries and veins may explain differences in acute and chronic wall remodeling between vessels. This information may be relevant for the development of antistenotic therapies.
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Single-cell transcriptomic profiling reveals CD27+ cytotoxic T Cell heterogeneity and exhaustion dynamics in colorectal cancer tumor microenvironment.
BACKGROUND: CD27+ cytotoxic T cells play critical roles in anti-tumor immunity, yet their heterogeneity and functional states within the colorectal cancer (CRC) tumor microenvironment remain poorly characterized. Understanding the molecular mechanisms underlying T cell exhaustion is essential for developing effective immunotherapeutic strategies. METHODS: We performed comprehensive single-cell RNA sequencing analysis of CD27+ cytotoxic T cells from CRC tumor tissues and matched normal adjacent tissues using the GSE144735 dataset. Multiple dimensional reduction techniques, trajectory inference algorithms, and functional characterization approaches were employed to dissect cellular heterogeneity, differentiation trajectories, and exhaustion dynamics. In vitro co-culture experiments using HCT116 and RKO (MSI-H), HCT15 and SW480 (MSS) colorectal cancer cell lines with activated PBMCs were conducted to validate computational findings. RESULTS: UMAP and t-SNE analyses identified 11 distinct CD27+ T cell clusters with substantial phenotypic heterogeneity, including exhausted terminal, effector, and memory-like populations. Pseudotime trajectory analysis revealed progressive exhaustion pathways with three distinct differentiation fates. Exhausted CD27+ T cells exhibited significantly elevated expression of checkpoint molecules (PDCD1, LAG3, HAVCR2, CTLA4) and reduced cytotoxic capacity compared to effector populations. RNA velocity and PAGA connectivity analysis demonstrated that exhaustion represents a terminal differentiation state with limited plasticity. Gene regulatory network analysis identified key transcription factors governing effector-to-exhausted transitions. Notably, exhausted CD27+ T cells concentrated in tumor core regions, while effector populations distributed peripherally. Co-culture experiments confirmed that MSI-H cell lines (HCT116 and RKO) induced 2-3 times higher exhaustion marker expression compared to MSS cell lines (HCT15 and SW480). For MSI-H cells, PDCD1 showed 5.2-fold (HCT116) and 4.8-fold (RKO) upregulation, while LAG3 showed 4.8-fold (HCT116) and 4.2-fold (RKO) upregulation. In contrast, MSS cells showed lower induction: PDCD1 at 2.1-fold (SW480) and 1.9-fold (HCT15), LAG3 at 1.8-fold (SW480) and 1.6-fold (HCT15). Exploratory survival analysis (HR = 0.505, p = 0.673) did not reach statistical significance and is presented as hypothesis-generating only, highlighting the need for prospective validation in larger cohorts. PDCD1 and LAG3 were identified as prioritized immunotherapy targets based on their significant overexpression in exhausted T cell populations. CONCLUSION: This study provides a comprehensive single-cell atlas of CD27+ cytotoxic T cell heterogeneity in CRC, revealing exhaustion dynamics, regulatory networks, and spatial organization patterns. Our findings highlight the differential immunogenic capacity between MSI-H and MSS tumors and identify potential therapeutic targets for reversing T cell exhaustion in colorectal cancer.
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Transcriptomic and epigenetic dissection of spinal ependymoma (SP-EPN) identifies clinically relevant subtypes enriched for tumors with and without NF2 mutation.
Ependymomas encompass multiple clinically relevant tumor types based on localization and molecular profiles. Tumors of the methylation class "spinal ependymoma" (SP-EPN) represent the most common intramedullary neoplasms in children and adults. However, their developmental origin is ill-defined, molecular data are scarce, and the potential heterogeneity within SP-EPN remains unexplored. The only known recurrent genetic events in SP-EPN are loss of chromosome 22q and NF2 mutations, but neither types and frequency of these alterations nor their clinical relevance have been described in a large, epigenetically defined series. Transcriptomic (n = 72), epigenetic (n = 225), genetic (n = 134), and clinical data (n = 112) were integrated for a detailed molecular overview on SP-EPN. Additionally, we mapped SP-EPN transcriptomes to developmental atlases of the developing and adult spinal cord to uncover potential developmental origins of these tumors. The integration of transcriptomic ependymoma data with single-cell atlases of the spinal cord revealed that SP-EPN display the highest similarities to mature adult ependymal cells. Unsupervised hierarchical clustering of transcriptomic data together with integrated analysis of methylation profiles identified two molecular SP-EPN subtypes. Subtype A tumors primarily carried previously known germline or sporadic NF2 mutations together with 22q loss (bi-allelic NF2 loss), resulting in decreased NF2 expression. Furthermore, they more often presented as multilocular disease and demonstrated a significantly reduced progression-free survival as compared to SP-EP subtype B. In contrast, subtype B predominantly contained samples without NF2 mutation detected in sequencing together with 22q loss (monoallelic NF2 loss). These tumors showed regular NF2 expression but more extensive global copy number alterations. Based on integrated molecular profiling of a large multi-center cohort, we identified two distinct SP-EPN subtypes with important implications for genetic counseling, patient surveillance, and drug development priorities.
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Cisplatin resistance-related multi-omics differences and the establishment of machine learning models.
OBJECTIVES: Platinum-based chemotherapies are currently the first-line treatment of non-small cell lung cancer. This study will improve our understanding of the causes of resistance to cisplatin, especially in lung adenocarcinoma (LUAD) and provide a reference for therapeutic decisions in clinical practice. METHODS: Cancer Cell Line Encyclopedia (CCLE), The Cancer Genome Atlas (TCGA) and Zhongshan hospital affiliated to Fudan University (zs-cohort) were used to identify the multi-omics differences related to platinum chemotherapy. Cisplatin-resistant mRNA and miRNA models were constructed by Logistic regression, classification and regression tree and C4.5 decision tree classification algorithm with previous feature selection performed via least absolute shrinkage and selection operator (LASSO). qRT-PCR and western-blotting of A549 and H358 cells, as well as single-cell Seq data of tumor samples were applied to verify the tendency of certain genes. RESULTS: 661 cell lines were divided into three groups according to the IC50 value of cisplatin, and the top 1/3 (220) with a small IC50 value were defined as the sensitive group while the last 1/3 (220) were enrolled in the insensitive group. TP53 was the most common mutation in the insensitive group, in contrast to TTN in the sensitive group. 1348 mRNA, 80 miRNA, and 15 metabolites were differentially expressed between 2 groups (P < 0.05). According to the LASSO penalized logistic modeling, 6 of the 1348 mRNAs, FOXA2, BATF3, SIX1, HOXA1, ZBTB38, IRF5, were selected as the associated features with cisplatin resistance and for the contribution of predictive mRNA model (all of adjusted P-values < 0.001). Three of 6 (BATF3, IRF5, ZBTB38) genes were finally verified in cell level and patients in zs-cohort. CONCLUSIONS: Somatic mutations, mRNA expressions, miRNA expressions, metabolites and methylation were related to the resistance of cisplatin. The models we created could help in the prediction of the reaction and prognosis of patients given platinum-based chemotherapies.
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Single-cell analysis of innate spinal cord regeneration identifies intersecting modes of neuronal repair.
Adult zebrafish have an innate ability to recover from severe spinal cord injury. Here, we report a comprehensive single nuclear RNA sequencing atlas that spans 6 weeks of regeneration. We identify cooperative roles for adult neurogenesis and neuronal plasticity during spinal cord repair. Neurogenesis of glutamatergic and GABAergic neurons restores the excitatory/inhibitory balance after injury. In addition, a transient population of injury-responsive neurons (iNeurons) show elevated plasticity 1 week post-injury. We found iNeurons are injury-surviving neurons that acquire a neuroblast-like gene expression signature after injury. CRISPR/Cas9 mutagenesis showed iNeurons are required for functional recovery and employ vesicular trafficking as an essential mechanism that underlies neuronal plasticity. This study provides a comprehensive resource of the cells and mechanisms that direct spinal cord regeneration and establishes zebrafish as a model of plasticity-driven neural repair.
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Revealing the roles of TLR7, a nucleic acid sensor for COVID-19 in pan-cancer.
Recent studies suggested that cancer was a risk factor for coronavirus disease 2019 (COVID-19). Toll-like receptor 7 (TLR7), a severe acute respiratory syndrome 2 (SARS-CoV-2) virus's nucleic acid sensor, was discovered to be aberrantly expressed in many types of cancers. However, its expression pattern across cancers and association with COVID-19 (or its causing virus SARS-CoV-2) has not been systematically studied. In this study, we proposed a computational framework to comprehensively study the roles of TLR7 in COVID-19 and pan-cancers at genetic, gene expression, protein, epigenetic, and single-cell levels. We applied the computational framework in a few databases, including The Cancer Genome Atlas (TCGA), The Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), Human Protein Atlas (HPA), lung gene expression data of mice infected with SARS-CoV-2, and the like. As a result, TLR7 expression was found to be higher in the lung of mice infected with SARS-CoV-2 than that in the control group. The analysis in the Opentargets database also confirmed the association between TLR7 and COVID-19. There are also a few exciting findings in cancers. First, the most common type of TLR7 was "Missense" at the genomic level. Second, TLR7 mRNA expression was significantly up-regulated in 6 cancer types and down-regulated in 6 cancer types compared to normal tissues, further validated in the HPA database at the protein level. The genes significantly co-expressed with TLR7 were mainly enriched in the toll-like receptor signaling pathway, endolysosome, and signaling pattern recognition receptor activity. In addition, the abnormal TLR7 expression was associated with mismatch repair (MMR), microsatellite instability (MSI), and tumor mutational burden (TMB) in various cancers. Mined by the ESTIMATE algorithm, the expression of TLR7 was also closely linked to various immune infiltration patterns in pan-cancer, and TLR7 was mainly enriched in macrophages, as revealed by single-cell RNA sequencing. Third, abnormal expression of TLR7 could predict the survival of Brain Lower Grade Glioma (LGG), Lung adenocarcinoma (LUAD), Skin Cutaneous Melanoma (SKCM), Stomach adenocarcinoma (STAD), and Testicular Germ Cell Tumors (TGCT) patients, respectively. Finally, TLR7 expressions were very sensitive to a few targeted drugs, such as Alectinib and Imiquimod. In conclusion, TLR7 might be essential in the pathogenesis of COVID-19 and cancers.
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Prognostic Significance and Tumor Immune Microenvironment Heterogenicity of m5C RNA Methylation Regulators in Triple-Negative Breast Cancer.
PURPOSE: The m5C RNA methylation regulators are closely related to tumor proliferation, occurrence, and metastasis. This study aimed to investigate the gene expression, clinicopathological characteristics, and prognostic value of m5C regulators in triple-negative breast cancer (TNBC) and their correlation with the tumor immune microenvironment (TIM). METHODS: The TNBC data, Luminal BC data and HER2 positive BC data set were obtained from The Cancer Genome Atlas and Gene Expression Omnibus, and 11 m5C RNA methylation regulators were analyzed. Univariate Cox regression and the least absolute shrinkage and selection operator regression models were used to develop a prognostic risk signature. The UALCAN and cBioportal databases were used to analyze the gene characteristics and gene alteration frequency of prognosis-related m5C RNA methylation regulators. Gene set enrichment analysis was used to analyze cellular pathways enriched by prognostic factors. The Tumor Immune Single Cell Hub (TISCH) and Timer online databases were used to explore the relationship between prognosis-related genes and the TIM. RESULTS: Most of the 11 m5C RNA methylation regulators were differentially expressed in TNBC and normal samples. The prognostic risk signature showed good reliability and an independent prognostic value. Prognosis-related gene mutations were mainly amplified. Concurrently, the NOP2/Sun domain family member 2 (NSUN2) upregulation was closely related to spliceosome, RNA degradation, cell cycle signaling pathways, and RNA polymerase. Meanwhile, NSUN6 downregulation was related to extracellular matrix receptor interaction, metabolism, and cell adhesion. Analysis of the TISCH and Timer databases showed that prognosis-related genes affected the TIM, and the subtypes of immune-infiltrating cells differed between NSUN2 and NSUN6. CONCLUSION: Regulatory factors of m5C RNA methylation can predict the clinical prognostic risk of TNBC patients and affect tumor development and the TIM. Thus, they have the potential to be a novel prognostic marker of TNBC, providing clues for understanding the RNA epigenetic modification of TNBC.
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Identification of a seven-gene prognostic model for renal cell carcinoma associated with CD8+T lymphocyte cell.
CD8+ T lymphocytes are important elements of the tumor microenvironment, hence their involvement in the development and progression of tumors is complex. Data on the precise tumor-infiltrating lymphocytes gene signature in renal cell carcinoma (RCC) remain limited. Therefore, this study created a tumor-infiltrating lymphocytes-related predictive model for patients with RCC using data from The Cancer Genome Atlas. The most important genes associated with CD8 + T lymphocytes were identified using weighted gene co-expression network analysis. Functional categories of important genes were revealed using gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes signaling pathway analyses. A CD8 + T lymphocyte-related prognostic model with 7 important genes was simultaneously created using the least absolute shrinkage and selection operator, univariate and multivariate Cox regressions, and the 7 genes were expressed particularly in CD8 + T lymphocytes according to single-cell sequencing data obtained from the Gene Expression Omnibus. This study identified a seven-gene prognostic model associated with CD8 + T lymphocytes that may significantly influence risk stratification in patients with RCC. The genes included in the model are apolipoprotein B mRNA editing catalytic polypeptide 3G, CD3 gamma, eomesodermin, protein tyrosine phosphatase, non-receptor type 7, signal regulatory protein gamma, Fas ligand, and T-cell immunoreceptor with Ig and ITIM domains.