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Integrated transcriptomic analysis systematically reveals the heterogeneity and molecular characterization of cancer-associated fibroblasts in osteosarcoma.
BACKGROUND: Osteosarcoma (OS), with a peak incidence during the adolescent growth spurt, is correlated with poor prognosis for its high malignancy. The tumor microenvironment (TME) is highly complicated, with frequent interactions between tumor and stromal cells. The cancer-associated fibroblasts (CAFs) in the TME have been considered to actively involve in the progression, metastasis, and drug resistance of OS. This study aimed to characterize cellular heterogeneity and molecular characterization in CAFs subtypes and explore the potential targeting therapeutic strategies to improve the prognosis of OS patients. METHODS: The single-cell atlas of human OS tumor lesions were constructed from the GEO database. Then significant marker genes and potential biological functions for each CAFs subtype were identified and explored using the Seurat R package. Next, by performing the survival analyses and constructing the risk scores for CAFs subtypes, we aimed to identify and characterize the prognostic values of specific marker genes and different CAFs subtypes. Furthermore, we explored the therapeutic targets and innovative drugs targeting different CAFs subtypes based on the GDSC database. Finally, prognoses related CAFs subtypes were further validated through immunohistochemistry (IHC) on clinical OS specimens. RESULTS: Overall, nine main cell clusters and five subtypes of CAFs were identified. The differentially expressed marker genes for each CAFs clusters were then identified. Moreover, through Gene Ontology (GO) enrichment analysis, we defined the CAFs_2 (upregulated CXCL14 and C3), which was closely related to leukocyte migration and chemotaxis, as inflammatory CAFs (iCAFs). Likewise, we defined the CAFs_4 (upregulated CD74, HLA-DRA and HLA-DRB1), which was closely related to antigen process and presentation, as antigen-presenting CAFs (apCAFs). Furthermore, Kaplan-Meier analyses showed that CAFs_2 and CAFs_4 were correlated with poor clinical prognosis of OS patients. Meanwhile, therapeutic drugs targeting CAFs_2 and CAFs_4, such as 17-AAG/Docetaxel/Bleomycin and PHA-793887/NG-25/KIN001-102, were also explored, respectively. Finally, IHC assay confirmed the abundant CAFs_2 and CAFs_4 subtypes infiltration in the OS microenvironment compared with adjacent tissues. CONCLUSION: Our study revealed the diversity, complexity, and heterogeneity of CAFs in OS, and complemented the single-cell atlas in OS TME.
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Single-cell RNA sequencing reveals different chondrocyte states in femoral cartilage between osteoarthritis and healthy individuals.
BACKGROUND: Cartilage injury is the main pathological manifestation of osteoarthritis (OA). Healthy chondrocyte is a prerequisite for cartilage regeneration and repair. Differences between healthy and OA chondrocyte types and the role these types play in cartilage regeneration and OA progression are unclear. METHOD: This study conducted single-cell RNA sequencing (scRNA-seq) on the cartilage from normal distal femur of the knee (NC group) and OA femur (OA group) cartilage, the chondrocyte atlas was constructed, and the differences of cell subtypes between the two groups were compared. Pseudo-time and RNA velocity analysis were both performed to verify the possible differentiation sequence of cell subtypes. GO and KEGG pathway enrichment analysis were used to explore the potential functional characteristics of each cell subtype, and to predict the functional changes during cell differentiation. Differences in transcriptional regulation in subtypes were explored by single-cell regulatory network inference and clustering (SCENIC). The distribution of each cell subtype in cartilage tissue was identified by immunohistochemical staining (IHC). RESULT: A total of 75,104 cells were included, they were divided into 19 clusters and annotated as 11 chondrocyte subtypes, including two new chondrocyte subtypes: METRNL+ and PRG4+ subtype. METRNL+ is in an early stage during chondrocyte differentiation, and RegC-B is in an intermediate state before chondrocyte dedifferentiation. With cell differentiation, cell subtypes shift from genetic expression to extracellular matrix adhesion and collagen remodeling, and signal pathways shift from HIF-1 to Hippo. The 11 subtypes were finally classified as intrinsic chondrocytes, effector chondrocytes, abnormally differentiated chondrocytes and dedifferentiated chondrocytes. IHC was used to verify the presence and distribution of each chondrocyte subtype. CONCLUSION: This study screened two new chondrocyte subtypes, and a novel classification of each subtype was proposed. METRNL+ subtype is in an early stage during chondrocyte differentiation, and its transcriptomic characteristics and specific pathways provide a foundation for cartilage regeneration. EC-B, PRG4+ RegC-B, and FC are typical subtypes in the OA group, and the HippO-Taz pathway enriched by these cell subtypes may play a role in cartilage repair and OA progression. RegC-B is in the intermediate state before chondrocyte dedifferentiation, and its transcriptomic characteristics may provide a theoretical basis for intervening chondrocyte dedifferentiation.
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[Single-cell transcriptome analysis reveals development atlas of mouse molar pulp cells].
Objective: Single-cell RNA sequencing (scRNA-seq) was used to analyze the developing mouse molars, in order to construct a spatiotemporal development atlas of pulp cells, and further to reveal the developmental process and regulatory mechanism of tooth development. Methods: Ten mandibular first molars from C57BL/6 mice in postnatal day (PN) 0 and 3 were respectively dissected and digested to obtain single-cell suspensions. scRNA-seq was performed on 10× Genomics platform. PN 7 mouse molar scRNA-seq data were obtained from our previous study. PN 0, 3, and 7 scRNA-seq data were integrated for following analysis. The initial quality control, mapping and single cell expression matrix construction were performed by Cell Ranger. Quality control, standardization, dimensional reduction and cluster analysis were performed by using Seurat. Monocle was used to generate the pseudotime trajectory. Scillus was used to perform gene ontology analysis. In order to detect the spatiotemporal change of different population of pulp cells, the marker genes of each cluster were demonstrated by RNAscope in situ hybridization. Results: There were twenty-six cell clusters within mouse molars, which were identified as eight different cell types, including dental pulp cells, dental follicle cells, epithelial cells, immune cells, endothelial cells, perivascular cells, glial cells and erythrocytes. We further re-clustered and analyzed dental pulp cells. Cluster 0 were mature pulp cells, which located at the upper portion of crown. The main functions of cluster 0 were osteogenesis and extracellular structure organization. Cluster 1 were apical papilla cells, which located at the apical part of roots, whose main functions were extracellular structure organization and organ development. Cluster 2 were cycling cells, which were actively proliferated, resided in the lower portion of the crown. Cluster 3 and 4 were preodontoblasts and odontoblasts, respectively. Their functions were closely related to biomineralization. The proportion of mature pulp cells increased with the development process, while the proportion of cycling cells and odontoblast lineage decreased. According to the expression pattern of marker genes of each cluster, we constructed a cell atlas of dental pulp. Pseudotime trajectory analysis found there were two development trajectories within dental pulp. They both started from SPARC related modular calcium binding 2 (Smoc2)+ dental papilla cells, then went through DNA topoisomerase Ⅱ alpha (Top2a)+ cycling cells, and finally divided into coxsackie virus and adenovirus receptor (Cxadr)+ mature pulp cells or dentin sialophosphoprotein (Dspp)+ odontoblasts two lineages. Conclusions: scRNA-seq could fully discover the intercellular heterogeneity of cells on transcriptome level, which provides a powerful tool to study the process and regulatory mechanism of organ development.
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Cross-species single-nucleus analysis reveals the potential role of whole-genome duplication in the evolution of maize flower development.
BACKGROUND: The evolution and development of flowers are biologically essential and of broad interest. Maize and sorghum have similar morphologies and phylogeny while harboring different inflorescence architecture. The difference in flower architecture between these two species is likely due to spatiotemporal gene expression regulation, and they are a good model for researching the evolution of flower development. RESULTS: In this study, we generated single nucleus and spatial RNA-seq data for maize ear, tassel, and sorghum inflorescence. By combining single nucleus and spatial transcriptome, we can track the spatial expression of single nucleus cluster marker genes and map single nucleus clusters to spatial positions. This ability provides great power to annotate the single nucleus clusters. Combining the cell cluster resolved transcriptome comparison with genome alignment, our analysis suggested that maize ear and tassel inflorescence diversity is associated with the maize-specific whole genome duplication. Taking sorghum as the outgroup, it is likely that the loss of gene expression profiling contributes to the inflorescence diversity between tassel and ear, resulting in the unisexual flower architecture of maize. The sequence of highly expressed genes in the tassel is more conserved than the highly expressed genes in the ear. CONCLUSION: This study provides a high-resolution atlas of gene activity during inflorescence development and helps to unravel the potential evolution associated with the differentiation of the ear and tassel in maize.
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Single-cell profiling reveals a reduced epithelial defense system, decreased immune responses and the immune regulatory roles of different fibroblast subpopulations in chronic atrophic gastritis.
PURPOSE: To identify key cellular changes and molecular events in atrophic mucosa, we aimed to elucidate the molecular mechanisms driving the occurrence of chronic atrophic gastritis (CAG). METHODS: We used single-cell RNA sequencing (scRNA-seq) to characterize changes in the epithelial state and tissue microenvironment associated with CAG. The molecular changes were identified by comparing differentially expressed genes (DEGs) between the two mucosa states. Gene Ontology (GO) pathway enrichment analysis was used to explore the potential functional changes in each cell subtype in atrophic mucosa. Gene set score analysis was conducted to compare the functional roles of different fibroblast subtypes and functional changes in cell subtypes between the CAG and control groups. Metabolic analysis was performed to compare the metabolic activity of C1Q+ macrophages under different conditions. NichNet analysis was used to analyze the regulatory relationships between CCL11+APOE+ fibroblasts and C1Q+ macrophages and between CCL11+APOE+ fibroblasts and CD8+ effector T cells. Transcription factor (TF) analysis was performed to determine the transcription status of different T-cell subtypes in atrophic and normal mucosa. RESULTS: We generated a single-cell transcriptomic atlas from 3 CAG biopsy samples and paired adjacent normal tissues. Our analysis revealed that chief cells and parietal cells exhibited a loss of detoxification ability and that surface mucous cells displayed a reduced antimicrobial defense ability in CAG lesions. The mucous neck cells in CAG lesions showed upregulation of genes related to cell cycle transition, which may lead to aberrant DNA replication. Additionally, cells with the T exhaustion phenotype infiltrated under CAG condition. C1Q+ macrophages exhibited reduced phagocytosis, downregulated expression of pattern recognition receptors and decreased metabolic activity. NichNet analysis revealed that a subpopulation of CXCL11+APOE+ fibroblasts regulated the inflammatory response in the pathogenesis of atrophic gastritis. APSN+CXCL11+APOE+ fibroblasts were found to be associated with gastric cancer (GC) development. CONCLUSIONS: The main goal of this study was to comprehensively elucidate the cellular changes in CAG lesions. We observed an immune decline in the mucosal microenvironment during the development of CAG, including a reduced immune response of C1Q+ macrophages, reduced cytotoxicity of T cells, and increased infiltration of exhausted T cells. Specifically, we demonstrated that different epithelial subtypes aberrantly express genes related to susceptibility to external bacterial infection and aberrant cell cycle progression. Our study provides new insights into the functions of epithelial changes and immune alterations during the development of CAG.
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Single-cell analysis of UNC13D-mediated immune and dedifferentiation heterogeneity in acute myeloid leukemia and development of a prognostic model.
BACKGROUND: Acute myeloid leukemia (AML) is a highly heterogeneous hematologic malignancy, with its pathogenesis closely associated with cellular states at various stages of differentiation. Existing clinical prognostic models often fail to account for this heterogeneity and lack integration of key molecular pathways. This study aimed to characterize AML differentiation-associated heterogeneity at the single-cell level, investigate the role of UNC13D in immune and dedifferentiation states, and develop a prognostic model integrating these features. METHODS: This study combined single-cell RNA sequencing data (GSE178910) with bulk RNA-sequencing (RNA-seq) datasets [The Cancer Genome Atlas-Acute Myeloid Leukemia (TCGA-LAML) and Oregon Health & Science University (OHSU)]. Seurat and Harmony were used for batch correction and unsupervised clustering, followed by cell state annotation using AddModuleScore-based scoring of lineage-specific gene sets. UNC13D expression was assessed to infer its association with differentiation stage and pathway activity. Prognostic genes within the MYC proto-oncogene signaling pathway were identified using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression. An eight-gene risk model was then constructed and validated across two cohorts. RESULTS: We identified eleven AML cellular subpopulations, grouped into five functional differentiation states. UNC13D was predominantly expressed in common myeloid progenitor-like (CMP-like) cells and correlated with multiple oncogenic and immune-related pathways. The resulting eight-gene prognostic model (PRDX4, KPNB1, DEK, ABCE1, ODC1, GLO1, MCM5, CCNA2) demonstrated good predictive performance in both the training and validation cohorts, with stable 1- and 3-year area under the curve (AUC) values. Differential pathway enrichment revealed marked biological divergence between high- and low-risk groups, including immune signaling and cell cycle regulation. CONCLUSIONS: Our study delineates the differentiation landscape of AML and identifies UNC13D as a potential biomarker of cellular plasticity and immune modulation. The constructed model provides a reliable prognostic tool and offers novel insights for AML stratification and precision therapy development.
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Multimodal integration of neuroimaging, transcriptomics and single-cell analysis reveals molecular correlates linking osteoporosis to brain abnormalities.
BACKGROUND: Osteoporosis (OP) and cognitive decline are highly prevalent comorbidities; however, the molecular mechanisms linking them remain unclear. We adopted a multimodal integrative strategy combining neuroimaging, transcriptomics, single-cell analysis, and in vivo validation to elucidate potential mechanisms. METHODS: Fifty-six patients and fifty-three healthy controls underwent resting-state functional MRI (fMRI) to assess regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF). Transcriptomic data from the Allen Human Brain Atlas (AHBA), single-nucleus RNA sequencing (snRNA-seq) of the human hippocampus, and validation using ovariectomized (OVX) mouse models were integrated. RESULTS: fMRI revealed significant ALFF/ReHo alterations in the hippocampus, prefrontal cortex, and posterior cingulate cortex of OP patients, with the left hippocampal ALFF mediating the association between bone mineral density (BMD) and Montreal Cognitive Assessment (MoCA) scores. Spatial correlation analyses have linked these brain functional changes to neurotransmitter receptors (5-HT1a, D1, GABAa, etc.) and genes enriched in synaptic function, neurogenesis, and dopaminergic signaling. snRNA-seq identified the caudal hippocampus as a key region, with astrocytes enriched in OP-associated Gene Program 5 (involving NR4A3 and KCNIP1) and functional pathways such as glutamatergic synapses and calcium signaling. OVX mice showed bone loss, spatial learning/memory impairment, hippocampal astrocyte abnormalities, and upregulation of GFAP, RGS7, and RGS6 proteins. CONCLUSION: Our multimodal study establishes a molecular framework for the bone-brain axis, highlighting astrocytes and synaptic signaling as potential targets for the dual protection of bone and brain health.
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Integrated analysis of single-cell and bulk RNA-sequencing identifies a signature based on T-cell marker genes to predict prognosis and therapeutic response in lung squamous cell carcinoma.
Cancer immunotherapy is an increasingly successful strategy for treating patients with advanced or conventionally drug-resistant cancers. T cells have been proved to play important roles in anti-tumor and tumor microenvironment shaping, while these roles have not been explained in lung squamous cell carcinoma (LUSC). In this study, we first performed a comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data from the gene expression omnibus (GEO) database to identify 72 T-cell marker genes. Subsequently, we constructed a 5-gene prognostic signature in the training cohort based on the T-cell marker genes from the cancer genome atlas (TCGA) database, which was further validated in the testing cohort and GEO cohort. The areas under the receiver operating characteristic curve at 1-, 3-, and 5-years were 0.614, 0.713 and 0.702 in the training cohort, 0.669, 0.603 and 0.645 in the testing cohort, 0.661, 0.628 and 0.590 in the GEO cohort, respectively. Furthermore, we created a highly reliable nomogram to facilitate clinical application. Gene set enrichment analysis showed that immune-related pathways were mainly enriched in the high-risk group. Tumor immune microenvironment indicated that high-risk group exhibited higher immune score, stromal score, and immune cell infiltration levels. Moreover, genes of the immune checkpoints and human leukocyte antigen family were all overexpressed in high-risk group. Drug sensitivity revealed that low-risk group was sensitive to 8 chemotherapeutic drugs and high-risk group to 4 chemotherapeutic drugs. In short, our study reveals a novel prognostic signature based on T-cell marker genes, which provides a new target and theoretical support for LUSC patients.
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A novel prognostic model based on epithelial cell progression genes identifies OAS1 as a suppressor of bladder cancer aggressiveness.
BACKGROUND: Bladder cancer (BLCA) is a highly heterogeneous malignancy with an unpredictable prognosis. Tumour progression is closely linked to the complex tumour microenvironment (TME), particularly the role of epithelial cells. This study aims to identify key epithelial cell-derived signature genes driving tumour progression, construct a reliable prognostic model, and further explore the biological functions of a pivotal gene, OAS1, in BLCA. METHODS: Single-cell RNA sequencing (scRNA-seq) data from public cohorts were analyzed to identify epithelial cell subpopulations and delineate their malignant progression trajectory. Genes significantly associated with this progression were identified through pseudotime analysis. Bulk RNA-seq and clinical data from The Cancer Genome Atlas (TCGA) BLCA cohort were utilized for least absolute shrinkage and selection operator (LASSO) Cox regression to build a prognostic risk model. The model's predictive efficacy was validated in an independent Gene Expression Omnibus (GEO) cohort. Furthermore, in vitro experiments including CCK-8, transwell, and wound healing assays were conducted to investigate the impact of OAS1 on the proliferation, migration, and invasion capabilities of BLCA cells. RESULTS: scRNA-seq analysis revealed a distinct epithelial cell subpopulation with high tumor-suppressive activity. A four-gene signature associated with tumor progression was successfully constructed into a prognostic model. Patients in the high-risk group exhibited significantly poorer overall survival in both the TCGA and validation cohorts. Multivariate Cox analysis confirmed the model as an independent prognostic factor. The risk score was significantly correlated with immune infiltration patterns and response to immunotherapy. Among the signature genes, OAS1 was identified as a critical factor. In vitro functional experiments demonstrated that knockdown of OAS1 markedly promoted the proliferation, migration, and invasion of BLCA cells. CONCLUSION: We established a novel prognostic model for BLCA based on epithelial cell tumor progression-associated genes, which serves as a robust predictor for patient outcomes and immunotherapeutic responsiveness. Our findings further highlight OAS1 as a key gene that suppresses the aggressive phenotypes of BLCA cells, suggesting it is a potential therapeutic target. This study provides valuable insights for precise prognosis and treatment stratification of BLCA patients.
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Single-cell analysis reveals the implication of vascular endothelial cell-intrinsic ANGPT2 in human intracranial aneurysm.
AIMS: While previous single-cell RNA sequencing (scRNA-seq) studies have attempted to dissect intracranial aneurysm (IA), the primary molecular mechanism for IA pathogenesis remains unknown. Here, we uncovered the alterations of cellular compositions, especially the transcriptome changes of vascular endothelial cells (ECs), in human IA. METHODS AND RESULTS: We performed scRNA-seq to compare the cell atlas of sporadic IA and the control artery. The transcriptomes of 43 462 cells were profiled for further analysis. In general, IA had increased immune cells (T/NK cells, B cells, myeloid cells, mast cells, neutrophils) and fewer vascular cells (ECs, vascular smooth muscle cells, and fibroblasts). Based on the obtained high-quantity and high-quality EC data, we found genes associated with angiogenesis in ECs from IA patients. By EC-specific expression of candidate genes in vivo, we observed the involvement of angpt2a in causing cerebral vascular abnormality. Furthermore, an IA zebrafish model mimicking the main features of human IA was generated through targeting pdgfrb gene, and knockdown of angpt2a alleviated the vascular dilation in the IA zebrafish model. CONCLUSION: By performing a landscape view of the single-cell transcriptomes of IA and the control artery, we contribute to a deeper understanding of the cellular composition and the molecular changes of ECs in IA. The implication of angiogenic regulator ANGPT2 in IA formation and progression, provides a novel potential therapeutical target for IA interventions.