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DCX knockout ferret reveals a neurogenic mechanism in cortical development.
Lissencephaly is a rare brain malformation for which our understanding remains limited due to the absence of suitable animal models that accurately represent human phenotypes. Here, we establish doublecortin (DCX) knockout ferrets as a model that faithfully replicates key features of the disorder. We reveal the critical roles of DCX in neural progenitor cell proliferation and radial glial fiber extension, processes essential for normal cortical development. Utilizing single-nucleus RNA sequencing (snRNA-seq) and spatial transcriptomics, we provide a detailed atlas of the lissencephalic cortex, illustrating disrupted neuronal lamination and the specific interactions between inhibitory and excitatory neurons. These findings enhance our understanding of the cellular and molecular mechanisms underlying lissencephaly and highlight the potential of DCX knockout ferrets as a valuable tool for neurodevelopmental research, offering insights into both the pathology of lissencephaly and the general principles of brain development.
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Single-cell atlas of photoaged skin reveals JAK-STAT blockade as a strategy to reverse dermal remodeling.
INTRODUCTION: Chronic ultraviolet (UV) exposure superimposes inflammatory and matrix-degenerative insults on intrinsic aging to produce cutaneous photoaging, yet the cell-type-resolved circuits and druggable nodes driving this process remain poorly defined. METHODS: Chronic We established a chronic UVA+UVB-induced mouse model of photoaging and performed single-cell RNA sequencing of control, UV-exposed, and UV + ruxolitinib-treated dorsal skin to map photoaging and therapeutic response at cellular resolution. RESULTS: Chronic Across 14 major lineages, UV exposure preserved overall cellular composition but induced a coordinated transcriptional network shift, marked by activation of JAK-STAT/IRF/AP-1-driven inflammatory and oxidative-stress programs and suppression of developmental, DNA-repair, and differentiation modules. Fibroblast reclustering resolved eight states and identified a papillary-to-reticular transitional continuum with the highest transcriptional burden, integrating senescence-associated secretory phenotype and extracellular-matrix disassembly signatures and skewing pseudotime toward late, terminal states. Topical JAK1/2 inhibition with ruxolitinib attenuated clinical and histological photoaging phenotypes, restored collagen and elastic fiber architecture, and rebalanced fibroblast trajectories by suppressing inflammatory/stress pathways while reactivating basement-membrane, extracellular-matrix, adhesion, and wound-healing programs. Cross-lineage analysis further revealed reversal of conserved stress-metabolic axes, including Hmox1, Gpx3, Ucp2, and Nr4a2, restoration of structural-matrix programs involving Dcn, Gsn, and Nup210l, normalization of aging regulators such as Cdkn1a and Trp53, and re-establishment of dermal-epidermal crosstalk through collagen IV-syndecan and fibronectin/laminin-CD44/αvβ1 signaling. DISCUSSION: Chronic These findings identify transitional fibroblasts as central executors of UV-driven dermal remodeling and support JAK1/2 inhibition as a network-level strategy to restore dermal-epidermal homeostasis in photoaged skin.
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Insights into the heterogeneity of the tumor microenvironment in lung adenocarcinoma and squamous carcinoma through single-cell transcriptomic analysis: Implications for distinct immunotherapy outcomes.
BACKGROUND: Immune checkpoint blockade has emerged as a key strategy to the therapy landscape of non-small cell lung cancer (NSCLC). However, notable differences in immunotherapeutic outcomes exist between the two primary NSCLC subtypes: lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). This disparity may stem from the tumor immune microenvironment's heterogeneity at the transcriptome level. METHODS: By integrative analysis of transcriptomic characterization of 38 NSCLC patients by single-cell RNA sequencing, the present study revealed a distinct tumor microenvironment (TME) between LUAD and LUSC, with relevant results further confirmed in bulk transcriptomic and multiplex immunofluorescence (mIF) validation cohort of neoadjuvant immunotherapy patients. RESULTS: LUAD exhibited a more active immune microenvironment compared to LUSC. This included highly expression of HLA I/II in cancer cells, reinforced antigen presentation potential of dendritic cells and enhanced cytotoxic activity observed in T/NK cells. In LUSC, cancer cells highly expressed genes belonging to the aldo-keto reductases, glutathione S-transferases and aldehyde dehydrogenase family, negatively correlating with immunotherapy outcomes in the validation cohort of our center. Further analysis revealed elevated infiltrated cancer-associated fibroblasts (CAFs) in LUSC, which was corroborated in The Cancer Genome Atlas cohort. Corresponding increased infiltration of ADH1B+ CAFs in major pathologic response (MPR) patients and the higher presence of FAP+ CAFs in non-MPR patients were demonstrated by multiplex mIF. Moreover, upregulating immunosuppressive extracellular matrix remodeling was identified in LUSC. CONCLUSIONS: These comprehensive analyses advance the understanding of the differences in TME between LUAD and LUSC, offering insights for patient selection and developing subtype-specific treatment strategies.
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Identification and Validation of T-Cell Exhaustion Signature for Predicting Prognosis and Immune Response in Pancreatic Cancer by Integrated Analysis of Single-Cell and Bulk RNA Sequencing Data.
PURPOSE: Pancreatic cancer (PACA) is one of the most fatal malignancies worldwide. Immunotherapy is largely ineffective in patients with PACA. T-cell exhaustion contributes to immunotherapy resistance. We investigated the prognostic potential of T-cell exhaustion-related genes (TEXGs). METHODS: A single-cell RNA (scRNA) sequencing dataset from Tumor Immune Single-Cell Hub (TISCH) and bulk sequencing datasets from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were used to screen differentially expressed TEXGs. Kaplan-Meier survival, LASSO regression, and univariate/multivariate Cox regression analyses were performed to construct a TEXG risk model. This model was used to predict the prognosis, tumor immune microenvironment, and immunotherapy response. The PACA cohorts from the ICGC and GSE71729 datasets were used to validate the risk model. Pan-cancer expression of SPOCK2 was determined using the TISCH database. RESULTS: A six-gene (SPOCK2, MT1X, LIPH, RARRES3, EMP1, and MEG3) risk model was constructed. Patients with low risk had prolonged survival times in both the training (TCGA-PAAD, n = 178) and validation (ICGC-PACA-CA, ICGC-PAAD-US, and GSE71729, n = 412) datasets. Multivariate Cox regression analysis demonstrated that the risk score was an independent prognostic variable for PACA. High-risk patients correlated with their immunosuppressive status. Immunohistochemical staining confirmed the changes in TEXGs in clinical samples. Moreover, pan-cancer scRNA sequencing datasets from TISCH analysis indicated that SPOCK2 may be a novel marker of exhausted CD8+ T-cells. CONCLUSION: We established and validated a T-cell exhaustion-related prognostic signature for patients with PACA. Moreover, our study suggests that SPOCK2 is a novel marker of exhausted CD8+ T cells.
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Single-nucleus RNA sequencing decodes abnormal cell-collagen communication in a sheep endometrial fibrosis model.
Endometrial fibrosis in sheep reduces reproductive performance with elusive therapeutic targets. The fibrotic endometrium is a complex ecosystem with heterogeneous cells and their interactions. The molecular characterization of key cells and the mechanisms of these interactions are unclear. To uncover the key molecular features of sheep endometrial fibrosis tissue, we used single-nucleus RNA sequencing to profile the transcriptional characterization of sheep endometrial cells from both normal and fibrotic tissues, aiming to clarify the mechanisms of fibrosis development. Histomorphological analysis revealed significant collagen deposition in fibrotic endometrial tissue. The transcription atlas of sheep endometrial cells was created, identifying eight main endometrial cell types. Key findings include the abnormal expression of collagen-related genes in fibrotic cells and the identification of endothelial cells and fibroblasts as major contributors to fibrogenesis with aberrant receptor-ligand interactions involving collagen-related genes. Fibroblasts had a tendency to differentiate into myofibroblasts in fibroblast-mediated fibrosis progression. In vitro experiments demonstrated the role of fibroblasts in fibroblast activation through the PERK/eIF2α/CHOP stress pathway. Additionally, fibrosis disturbs the immune microenvironment. This study highlights that high collagen gene expression in injured endometrial cells leads to abnormal tissue repair and fibrosis, offering valuable insights for understanding endometrial fibrosis at the single-cell level.
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Pan-cancer analysis identifies migrasome-related genes as a potential immunotherapeutic target: A bulk omics research and single cell sequencing validation.
INTRODUCTION: The migrasome is a newly discovered organelle that resembles extracellular vesicles in structure. However, the function of the migrasome in tumors, particularly in relation to tumor immunity and tumor microenvironment, is unclear. METHODS: Gene expression data, copy number variation raw data, and methylation data of 33 cancer types were downloaded from The Cancer Genome Atlas database. Immunohistochemistry (IHC) based on 114 case of colorectal cancer was used to validate the expression of the migrasome hub-gene. We analyzed the expression, prognosis, genetic variation, and drug sensitivity profiles of migrasome-related genes (MRGs) in pan-cancer datasets. A migrasome score was constructed based on gene set enrichment analysis, and the correlation of migrasomes with the tumor microenvironment was assessed. The CancerSEA was used to perform a single-cell level functional analysis of the migrasome. Additionally, we also analyzed the correlation between migrasomes and tumor mutational burden (TMB), microsatellite instability (MSI), and tumor immune dysfunction and exclusion scores. Single-cell transcriptome sequencing (scRNA-seq) data was used to assess the activation state of migrasomes in the tumor microenvironment. RESULTS: PIGK expression was significantly up-regulated in 22 of 33 tumors, and high expression of migrasome was estimated to have contributed to poor prognosis. Missense mutations are the most common type of mutation in MRGs. We identified piperlongumine as a potential drug targeting migrasomes. The migrasome score was significantly and positively correlated with the tumor immunity score and the stroma score. In most tumors, the abundance of macrophages in the tumor microenvironment was significantly and positively correlated with the migrasome score. Additionally, the migrasome scores were significantly correlated with the immune checkpoint genes in pan-cancer as well as immune checkpoint therapy-related markers including TMB and MSI. According to scRNA-seq analysis, migrasome differed significantly among cells of the tumor microenvironment. IHC confirmed low expression of ITGA5 and PIGK in colorectal cancer. DISCUSSION: We performed the first pan-cancer analysis of migrasomes and discovered that they play an important role in tumor development and immune escape. Our study provides new insights into the role of migrasomes in tumor prognosis and immunotherapy.
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Kidney Single-Cell Atlas Reveals Myeloid Heterogeneity in Progression and Regression of Kidney Disease.
BACKGROUND: Little is known about the roles of myeloid cell subsets in kidney injury and in the limited ability of the organ to repair itself. Characterizing these cells based only on surface markers using flow cytometry might not provide a full phenotypic picture. Defining these cells at the single-cell, transcriptomic level could reveal myeloid heterogeneity in the progression and regression of kidney disease. METHODS: Integrated droplet- and plate-based single-cell RNA sequencing were used in the murine, reversible, unilateral ureteric obstruction model to dissect the transcriptomic landscape at the single-cell level during renal injury and the resolution of fibrosis. Paired blood exchange tracked the fate of monocytes recruited to the injured kidney. RESULTS: A single-cell atlas of the kidney generated using transcriptomics revealed marked changes in the proportion and gene expression of renal cell types during injury and repair. Conventional flow cytometry markers would not have identified the 12 myeloid cell subsets. Monocytes recruited to the kidney early after injury rapidly adopt a proinflammatory, profibrotic phenotype that expresses Arg1, before transitioning to become Ccr2+ macrophages that accumulate in late injury. Conversely, a novel Mmp12+ macrophage subset acts during repair. CONCLUSIONS: Complementary technologies identified novel myeloid subtypes, based on transcriptomics in single cells, that represent therapeutic targets to inhibit progression or promote regression of kidney disease.
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The transcriptional landscape of developing human trisomy 21 lungs.
RATIONALE: Trisomy 21 (T21), resulting in Down syndrome (DS), is the most prevalent chromosomal abnormality worldwide. While pulmonary disease is a major cause of morbidity and mortality in DS, the ontogeny of pulmonary complications remains poorly understood. We recently demonstrated that T21 lung anomalies, including airway branching and vascular lymphatic -abnormalities, are initiated in utero. Here, we aimed to describe molecular changes at the single-cell level in prenatal T21 lungs. METHODS: Single-cell RNA sequencing was used to generate transcriptomic profiles of individual human lung cells in tissue obtained from T21 (n = 5) and non-T21 (n = 4) prenatal lungs. Clustering of cells, marker identification, uniform manifold approximation and projection representation, and differential expression analysis were performed in Seurat. Cell type annotation and pathway analysis were annotated using ToppFun and a human fetal lung cell atlas. Spatial differences in cellular phenotypes were validated using immunofluorescence staining and fluorescent in situ hybridization. RESULTS: Our results detail changes in gene expression at the time of initiation of histopathological abnormalities in T21 prenatal lungs. Notably, we identify precocious differentiation of epithelial cells, widespread induction of key extracellular matrix molecules in mesenchymal cells, and hyperactivation of IFN signaling in endothelial cells. CONCLUSIONS: This single-cell dataset of T21 lungs greatly expands our understanding of antecedents to pulmonary complications and should facilitate efforts to mitigate respiratory disease in DS.
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Development and validation of a leukemia prognostic model through single-cell RNA sequencing and machine learning approaches.
BACKGROUND: Leukemia prognosis varies significantly among patients, highlighting the need for accurate prediction tools. Emerging evidence suggests that the immune microenvironment plays a crucial role in leukemia progression and treatment response. METHODS: We analyzed RNA expression profiles and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, supplemented by single-cell RNA sequencing datasets. Differential gene expression analysis was performed using stringent criteria (logFC > 1, FDR < 0.05) to identify leukemia-associated genes. Ten distinct machine learning algorithms, including Lasso, CoxBoost, and ensemble methods, were implemented for prognostic model development with cross-platform validation. Single-cell analysis employed Seurat for quality control and cell type annotation, while CellChat algorithm mapped intercellular communication networks. Experimental validation was conducted using quantitative RT-PCR analysis of key immune markers (TLR2, TLR4, CCR7, IL18) in U937 and K562 leukemia cell lines compared to normal peripheral blood mononuclear cells. RESULTS: The machine learning-derived prognostic model demonstrated exceptional predictive performance with area under the curve values of 0.874, 0.891, and 0.925 for 1-, 2-, and 3-year survival endpoints, respectively. Six critical immune regulatory genes (TLR2, TLR4, CCR7, IL18, TIRAP, FOXP3) were identified as both differentially expressed and prognostically significant, with IL18 showing the highest discriminative capacity (AUC = 0.983). RT-PCR validation confirmed significant upregulation of all tested genes in leukemia cell lines: TLR2 (3.8-fold in U937, 2.2-fold in K562), TLR4 (3.4-fold in U937, 1.8-fold in K562), CCR7 (4.1-fold in U937, 2.7-fold in K562), and IL18 (5.2-fold in U937, 3.6-fold in K562) compared to normal controls (all p < 0.05). Single-cell analysis revealed substantial cellular heterogeneity with cell type-specific expression patterns and complex intercellular communication networks involving B cells, T cells, natural killer cells, and dendritic cells. CONCLUSION: This study provides a reliable prognostic tool for leukemia and offers insights into the critical role of the immune microenvironment in leukemia pathogenesis. Our findings may guide the development of personalized immunotherapy strategies for leukemia patients.
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Cleavage Stimulation Factor Subunit 2: Function Across Cancers and Potential Target for Chemotherapeutic Drugs.
The cleavage stimulation factor subunit complex is involved in the cleavage and polyadenylation of 3'-end pre-mRNAs that regulate mRNA formation and processing. However, cleavage stimulation factor subunit 2 (CSTF2) was found to play a more critical regulatory role across cancers. General cancer data sets from The Cancer Genome Atlas and Genotype-Tissue Expression project were thus downloaded for differential analysis, and the possible functions and mechanisms of CSTF2 in general cancer were analyzed using the Compartments database, cBioPortal database, Tumor Immune Single-cell Hub database, and Comparative Toxigenomics database using gene set enrichment analysis and R software. The results showed that CSTF2 could affect DNA repair and methylation in tumor cells. In addition, CSTF2 was associated with multiple tumor immune infiltrates in a wide range of cancers, and its high expression was associated with multiple immune checkpoints; therefore, it could serve as a potential target for many drug molecules. We also proved that CSTF2 promotes oral cell proliferation and migration. The high diagnostic efficacy of CSTF2 suggested that this gene may act as a new biomarker and personalized therapeutic target for a variety of tumors.