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Osteostaticytes: A novel osteoclast subset couples bone resorption and bone formation.
BACKGROUND: Osteomyelitis (OM) is an inflammatory condition of bone characterized by cortical bone devascularization and necrosis. Dysregulation of bone remodelling is triggered by OM. Bone remodelling is precisely coordinated by bone resorption and formation via a reversal phase. However, the cellular and molecular mechanisms underlying bone remodelling failure after osteomyelitis remain elusive. METHODS: To elucidate the cellular and molecular mechanism underlying bone healing after osteomyelitis, we employed single-cell RNA sequencing (scRNA-seq) to depict the atlas of human cortical bone in normal, infected and reconstructed states. Dimensionality reduction by t-stochastic neighbourhood embedding (t-SNE) and graph-based clustering were applied to analyse the detailed clusters of osteoclast lineages. After trajectory analysis of osteoclast lineages over pseudotime, real-time PCR and immunofluorescence (IF) staining were applied to identify marker gene expression of various osteoclast lineages in the osteoclast induction model and human bone sections, respectively. The potential function and communication of osteoclasts were analysed via gene set enrichment analysis (GSEA) and CellChat. The chemotactic ability of mesenchymal stem cells (MSCs) and osteoclast lineage cells in various differentiation states was determined by transwell assays and coculture assays. The effects of various osteoclast lineages on the osteogenic differentiation potential of MSCs were also determined by using this coculture system. A normal mouse tibia fracture model and an osteomyelitis-related tibia fracture model were generated via injection of luciferase-labelled Staphylococcus aureus to verify the relationships between a novel osteoclast lineage and MSCs. Then, the infection was detected by a bioluminescence imaging system. Finally, immunofluorescence staining was used to detect the expression of markers of MSCs and novel osteoclast lineages in different remodelling phases in normal and infected bone remodelling models. RESULTS: In this study, we constructed a cell atlas encompassing normal, infected, and reconstructed cortical bone. Then, we identified a novel subset at the earlier stage of the osteoclast lineage that exhibited increased expression of IDO1, CCL3, and CCL4. These IDO1highCCL3highCCL4high cells, termed osteostaticytes (OSCs), were further regarded as the reservoir of osteoclasts in the reversal phase. Notably, OSCs exhibited the highest chemotactic activity, surpassing other lineage subsets. We also discovered that cells at the earlier stage of the osteoclast lineage play a significant role in recruiting mesenchymal stem cells (MSCs). Finally, the data revealed that OSCs might be positively related to the occurrence of bone MSCs and the contribution of bone remodelling. CONCLUSION: Collectively, our findings revealed a novel stage (OSC) within the osteoclast lineage, potentially representing elusive bone reversal cells due to its increased chemotactic ability towards MSCs and potential contribution to bone remodelling. This study provides valuable insights into the intricate mechanisms of the reversal phase during bone remodelling and unveils potential therapeutic strategies for diseases associated with bone uncoupling. TRANSLATIONAL POTENTIAL OF THIS ARTICLE: This study identified a new subset, referred to as IDO1(plus symbol) CCL3(plus symbol) CCL4(plus symbol) osteostaticytes which displayed the highest chemotactic activity among all osteoclast lineages and may serve as reversal cells in bone remodelling. These findings offer new insights and insights for understanding bone reversal-related diseases and may serve as novel therapeutic targets for conditions such as osteomyelitis and delayed bone healing.
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Multi-omics analysis and experiments validate the tumor-suppressive role of mitochondrial lipid metabolism gene ACSM5 in lung adenocarcinoma and its impact on the immune microenvironment.
BACKGROUND: Lung adenocarcinoma (LUAD) is the most prevalent subtype of non-small cell lung cancer, characterized by high incidence and poor prognosis. Mitochondrial lipid metabolism (MTLM) contributes to tumor proliferation and drug resistance by regulating lipid breakdown and energy supply and is strongly linked to prognosis in multiple cancers. Nevertheless, its impact on LUAD has yet to be clarified. METHODS: MTLM-associated genes were extracted from the MitoCarta 3.0 database and relevant publications. A four-gene prognostic model was formulated using Cox regression analysis, with individual gene contributions clarified through Shapley Additive Explanations (SHAP) analysis. The model was verified using The Cancer Genome Atlas and Gene Expression Omnibus datasets, and a nomogram incorporating clinical features was developed. Immunomicroenvironment characteristics and drug sensitivity were evaluated, leading to the identification of potential therapeutic agents. A competing endogenous RNAs (ceRNA) and transcription factor (TF) regulatory network was constructed for the core genes. Drug components targeting these core genes were identified through reverse pharmacology and molecular docking. Single-cell RNA sequencing (scRNA-seq) was carried out to analyze the expression of core genes across cellular subpopulations. Finally, the core gene ACSM5 was investigated for its prognostic value and immune regulatory role in LUAD, with its function further validated through clonogenic assays and Transwell experiments. RESULTS: A MTLM-related prognostic model incorporating ACSL4, ACSS3, CHPT1, and ACSM5 was established, with ACSM5 contributing most significantly to the model’s prediction. Patients in the high-risk group had notably shorter survival than those in the low-risk group, and the risk score was identified as an independent prognostic factor. The nomogram, combining clinical features and risk scores, showed an AUC value of 0.712. Notable differences were detected between distinct risk groups in terms of immune microenvironment and drug sensitivity. The ceRNA network and TF regulatory network revealed upstream and downstream targets of the core genes. Reverse pharmacological analysis identified drugs and components affecting the CYP27A1 gene. Molecular docking results showed strong binding between CHPT1 and 3-methylcholanthrene and aztreonam. ScRNA-seq revealed the expression patterns of core genes at the single-cell level. High ACSM5 expression in LUAD was positively linked to prognosis, and ACSM5 was determined to be an independent prognostic factor for LUAD. Experimental results demonstrated that ACSM5 inhibits LUAD cell proliferation, invasion, and migration. CONCLUSION: The MTLM-based four-gene prognostic model developed in this study effectively predicts LUAD patient outcomes, with ACSM5 serving as the core prognostic gene. This model provides new theoretical support for personalized treatment and precise prognosis assessment in LUAD.
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Construction of a ferroptosis-related prognostic signature and identification of SRSF9 as a key biomarker in lung adenocarcinoma.
BACKGROUND: Ferroptosis is a distinct form of regulated cell death characterized by iron-dependent lipid peroxidation, which plays crucial roles in tumor biology and therapeutic response. However, the prognostic significance of ferroptosis-related genes (FRGs) in lung adenocarcinoma (LUAD) remains incompletely understood. This study aimed to construct and validate a ferroptosis-related prognostic model for LUAD by integrating single-cell and bulk transcriptomic data. METHODS: Single-cell RNA sequencing (scRNA-seq) data from GSE127465 were integrated with bulk transcriptomic data from The Cancer Genome Atlas lung adenocarcinoma cohort (TCGA-LUAD). FRGs were identified through single-cell gene set scoring with the AUCell algorithm and differential expression analysis. A least absolute shrinkage and selection operator (LASSO)-Cox regression model was constructed and externally validated using the GSE72094 and GSE68465 cohorts. Associations between the model, genomic features, and the tumor immune microenvironment were systematically analyzed. The functional role of SRSF9 was verified through in vitro experiments. RESULTS: A total of 93 candidate genes significantly associated with ferroptosis activity were identified, and an 8-gene prognostic signature (PEBP1, TXN, TIMP1, SRSF9, CFL1, OTUB1, FURIN, and PTPN6) was constructed. The signature demonstrated robust prognostic performance across validation cohorts, with time-dependent area under the curve (AUC) values ranging from 0.65 to 0.74. High-risk patients exhibited elevated tumor mutation burden (TMB) and distinct immune infiltration patterns. Consensus clustering analysis classified patients into two ferroptosis-related molecular subtypes with significantly different prognoses. Functional experiments demonstrated that SRSF9 knockdown inhibited LUAD cell proliferation, migration, and invasion. Moreover, SRSF9 knockdown downregulated glutathione peroxidase 4 (GPX4) and SLC7A11, increased lipid peroxidation and malondialdehyde (MDA) levels, and the resulting cell viability loss was rescued by ferrostatin-1, indicating that SRSF9 knockdown induces ferroptosis in LUAD cells. CONCLUSIONS: The ferroptosis-related prognostic signature established in this study may facilitate risk stratification in LUAD patients. SRSF9 may regulate ferroptosis-related pathways through modulation of GPX4 and SLC7A11, and functional experiments further confirmed that SRSF9 knockdown induces ferroptosis in LUAD cells, highlighting SRSF9 as a candidate therapeutic target that warrants further investigation.
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Single-Cell Atlas Reveals Tumorigenic Profiles and Immune Dynamics of Adrenal Incidentalomas.
Adrenal incidentalomas (AIs) are commonly detected endocrine lesions, identified during imaging for unrelated conditions. These lesions exhibit considerable heterogeneity and diverse clinical outcomes. This study employed single-cell RNA sequencing to investigate tumorigenic characteristics of AIs, including non-functional adrenocortical adenomas, Conn's syndrome, and pheochromocytomas. Through integrating public datasets, 302 696 cells are analyzed. Three adrenocortical cell subtypes exhibit gene expression patterns linked to tumorigenesis. Clusterin emerges as a potential biomarker for adrenocortical adenomas. Adrenocortical tumor cells show dysregulated hormone secretion and transcription factor steroidogenic factor 1 (SF1) is significantly upregulated, distinguishing cortical from medullary tumors. In pheochromocytomas, a MYCN proto-oncogene (MYCN)-positive cluster correlates with poorer survival. Immune microenvironment analysis reveals specific immune subtypes and roles in tumor progression. Specifically, myeloid cells may regulate benign tumors, while lymphoid cells, such as CD8-positive (CD8+) T cells, appear to promote immune activation and infiltration in malignant tumors. Overall, this study enhances the understanding of adrenal adenoma heterogeneity, revealing crucial transcriptional profiles, immune interactions, and clinically relevant candidate biomarkers.
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Single-Cell View of Tumor Microenvironment Gradients in Pleural Mesothelioma.
Immunotherapies have shown great promise in pleural mesothelioma (PM), yet most patients still do not achieve significant clinical response, highlighting the importance of improving the understanding of the tumor microenvironment (TME). Here, we utilized high-throughput, single-cell RNA sequencing (scRNA-seq) to de novo identify 54 expression programs and construct a comprehensive cellular catalog of the PM TME. We found four cancer-intrinsic programs associated with poor disease outcome and a novel fetal-like, endothelial cell population that likely responds to VEGF signaling and promotes angiogenesis. Across cellular compartments, we observe substantial difference in the TME associated with a cancer-intrinsic sarcomatoid signature, including enrichment in fetal-like endothelial cells, CXCL9+ macrophages, and cytotoxic, exhausted, and regulatory T cells, which we validated using imaging and bulk deconvolution analyses on independent cohorts. Finally, we show, both computationally and experimentally, that NKG2A:HLA-E interaction between NK and tumor cells represents an important new therapeutic axis in PM, especially for epithelioid cases. Significance: This manuscript presents the first single-cell RNA sequencing atlas of PM tumor microenvironment. Findings of translational relevance, validated experimentally and using independent bulk cohorts, include identification of gene programs predictive of survival, a fetal-like endothelial cell population, and NKG2A blockade as a promising new immunotherapeutic intervention in PM.
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Prognostic significance of key immune cell functional alterations in clear cell renal cell carcinoma.
BACKGROUND: While immune cells are pivotal in clear cell renal cell carcinoma (ccRCC), functional alterations of specific subsets and their prognostic implications remain unclear. We aimed to identify key immune cells, characterize their functional states, and develop a prognostic model by integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq) data. METHODS: scRNA-seq dataset GSE210038 was analyzed to annotate tumor-infiltrating immune cells. Key immune cells were identified from deconvolved The Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) and Gene Expression Omnibus Series (GSE)105261 datasets using support vector machine-recursive feature elimination (SVM-RFE), least absolute shrinkage and selection operator (LASSO), and random forest (RF) algorithms. Immune Response Enrichment Analysis (IREA) delineated polarization states of key immune cells in response to cytokines. Cellular communication was profiled via CellChat. Prognostic genes associated with key immune cells were screened by univariate Cox and LASSO regression. A risk score (RS) model was constructed and validated in TCGA-KIRC (training, n=511) and E-MTAB-1980 (validation, n=101) cohorts. Receiver operating characteristic (ROC) curves evaluated overall survival (OS) prediction efficacy. Nomograms and drug sensitivity analyses were performed. RESULTS: Seven immune cell types infiltrated ccRCC. CD8+ T and natural killer (NK) cells were identified as the key immune cells. IREA revealed T8-c polarization in CD8+ T cells [enriched for interferon (IFN)-α1/interleukin (IL)-36α] and NK-f polarization in NK cells (enriched for IL-18/IL-2). CellChat analysis showed amplified protease activated receptors (PARs) signaling from key immune cells to cancer-associated fibroblasts, but attenuated Annexin A1 (ANXA1)-formyl peptide receptor 1 (FPR1) signaling to macrophages. Ten immune-cell-associated prognostic genes (PTTG1, CLEC2D, PLIN2, LRBA, ABCB1, MIR155HG, ADAM8, P2RY8, SORL1, CD82) were used to build the RS model. The model stratified patients into high/low-risk groups with distinct OS (log-rank P<0.001). The area under the curves (AUCs) for 1-/3-/5-year OS were 0.751/0.734/0.747 (training) and 0.742/0.740/0.778 (validation). The nomogram [incorporating RS and metastatic stage (M stage)] showed robust calibration. Drug sensitivity analysis revealed low-risk patients responded better to tyrosine kinase inhibitors, while high-risk patients were sensitive to a B-cell lymphoma-2 inhibitor. CONCLUSIONS: CD8+ T and NK cells exhibit functional polarization and altered cellular communication indicative of augmented anti-tumor immunity in ccRCC. The immune-cell-derived 10-gene signature provides a reliable prognostic tool and guides personalized therapy.
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Single-cell sequencing in diabetic retinopathy: progress and prospects.
Diabetic retinopathy is a major ocular complication of diabetes, characterized by progressive retinal microvascular damage and significant visual impairment in working-age adults. Traditional bulk RNA sequencing offers overall gene expression profiles but does not account for cellular heterogeneity. Single-cell RNA sequencing overcomes this limitation by providing transcriptomic data at the individual cell level and distinguishing novel cell subtypes, developmental trajectories, and intercellular communications. Researchers can use single-cell sequencing to draw retinal cell atlases and identify the transcriptomic features of retinal cells, enhancing our understanding of the pathogenesis and pathological changes in diabetic retinopathy. Additionally, single-cell sequencing is widely employed to analyze retinal organoids and single extracellular vesicles. Single-cell multi-omics sequencing integrates omics information, whereas stereo-sequencing analyzes gene expression and spatiotemporal data simultaneously. This review discusses the protocols of single-cell sequencing for obtaining single cells from retina and accurate sequencing data. It highlights the applications and advancements of single-cell sequencing in the study of normal retinas and the pathological changes associated with diabetic retinopathy. This underscores the potential of these technologies to deepen our understanding of the pathogenesis of diabetic retinopathy that may lead to the introduction of new therapeutic strategies.
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Prognosis and therapeutic benefits prediction based on NK cell marker genes through single-cell RNA-seq with integrated bulk RNA-seq analysis for hepatocellular carcinoma.
Tumor-infiltrating immune cells greatly participate in regulating tumorigenesis and metastasis of hepatocellular carcinoma (HCC). Natural killer cell, as an important role of innate immunity, plays an indispensable role in antitumor immunity and regulate tumor development. In this study, we firstly identified 251 NK cell marker genes of HCC based on single-cell RNA sequencing data. Subsequently, an NK cell marker genes-related prognostic signature (NKPS) was developed in the cancer genome atlas (TCGA) cohort for risk stratification and prognosis prediction. The predictive value of the NKPS in prognosis was well validated in different clinical subgroups and three external datasets (ICGC-LIHC cohort, GSE14520 cohort and Guilin cohort). Moreover, multivariate analysis revealed the independent prognostic value of NKPS for OS in HCC. Further functional analysis indicated the NKPS was associated with basic cellular processes, that may contribute to the development and progression of HCC. Thereafter, immune characteristics as well as the therapeutic benefits in NKPS risk score-defined subgroups were analyzed. Patients with low-risk score exhibited immune-active status, manifested as higher immune scores, more infiltration of CD8+ T cells and macrophage M1, and higher T-cell receptor (TCR) richness and diversity. Remarkably, the NKPS was negatively correlated with immunotherapy response-related signatures. In addition, the low-risk group exhibited significantly improved therapeutic benefits, either from immunotherapy or traditional chemotherapy and target therapy. Overall, the NKPS showed an excellent predictive value for prognosis and therapeutic responses for HCC, which might also provide novel insights into better HCC management strategies.
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Cell type atlas and lineage tree of a whole complex animal by single-cell transcriptomics.
Flatworms of the species Schmidtea mediterranea are immortal-adult animals contain a large pool of pluripotent stem cells that continuously differentiate into all adult cell types. Therefore, single-cell transcriptome profiling of adult animals should reveal mature and progenitor cells. By combining perturbation experiments, gene expression analysis, a computational method that predicts future cell states from transcriptional changes, and a lineage reconstruction method, we placed all major cell types onto a single lineage tree that connects all cells to a single stem cell compartment. We characterized gene expression changes during differentiation and discovered cell types important for regeneration. Our results demonstrate the importance of single-cell transcriptome analysis for mapping and reconstructing fundamental processes of developmental and regenerative biology at high resolution.
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Increased IL4I1 expression predicts poor survival and modulates the immune microenvironment in acute myeloid leukemia.
BACKGROUND: The immunometabolic enzyme Interleukin-4-induced-1 (IL4I1) is implicated in cancer pathogenesis, yet its specific function and clinical relevance in acute myeloid leukemia (AML) remain unclear. METHODS: Comparative analysis of IL4I1 mRNA levels between AML patients and normal controls was performed using the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. The Kaplan–Meier survival analysis was conducted to evaluate the prognostic value of IL4I1. Functional insights were derived from analyses of differentially expressed genes (DEGs), Gene Set Enrichment Analysis (GSEA), and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Immune infiltration was evaluated using the ssGSEA, ESTIMATE, quanTIseq and single-cell RNA sequencing (scRNA-seq) analysis. Finally, in vitro and in vivo functional experiments were perfromed to explore the impact of IL4I1 on AML progression and immunoregulation. RESULTS: IL4I1 expression was significantly elevated in AML compared to normal controls (p = 0.0004) and associated with poorer overall survival (p = 0.003). Bioinformatic analysis revealed that IL4I1 was linked to immune-related pathways—including humoral immune response, leukocyte interactions, and chemokine signaling—and to cellular amino acid metabolism. Its expression correlated with immune cell infiltration and checkpoint molecule expression. Experimentally, IL4I1 promoted leukemia cell proliferation in vitro and in vivo (p < 0.05). Furthermore, silencing IL4I1 suppressed M2 macrophage polarization and reduced secretion of inflammatory factors (p < 0.05). CONCLUSIONS: IL4I1 may serve as a potential biomarker for poor prognosis and an attractive target for immune-based therapeutic interventions in AML.