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Significance of CD47 and Its Association With Tumor Immune Microenvironment Heterogeneity in Ovarian Cancer.
BACKGROUND: It was reported that tumor heterogeneity and the surrounding tumor microenvironment (TME) in ovarian cancer affects immunotherapy efficacy and patient outcomes. And the TME of ovarian cancer is intrinsically heterogeneous. CD47 plays vital roles in cell functional behavior and immune homeostasis relating to cancer prognosis. But how it affects TME and its contribution to heterogeneity in ovarian cancer has not been fully illustrated. Therefore, we aimed to identify a prognostic biomarker which may help explain tumor immune microenvironment heterogeneity of ovarian cancer. METHODS: Cancer single-cell state atlas (CancerSEA) was used to evaluate functional role of CD47. Several bioinformatics database including Oncomine, Gene Expression Profiling Interaction Analysis (GEPIA), Tumor Immune Estimation Resource (TIMER), The Human Protein Atlas (HPA), Ualcan and Kaplan-Meier plotter (KM plotter) were applied to illustrate correlation of CD47 with ovarian cancer prognosis and immune infiltration. Tumor Immune Single-cell Hub (TISCH) single cell database was employed to evaluate correlation of CD47 with tumor microenvironment. GeneMANIA was implemented to identify regulation networks of CD47. Differentially expressed genes (DEGs) between CD47 high and low expression groups were analyzed with R package DESeq2. Kyoto encyclopedia of genes and genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) were utilized to explore how CD47 affect the immune related cell signaling pathway. RESULTS: CD47 expression was upregulated and connected to worse OS and PFS in ovarian cancer. Close relation was found between CD47 expression level and immune infiltration in ovarian cancer, especially with Treg cells, Monocytes, Macrophages and T cell exhaustion (P<0.05). The CD47 expression level was relatively low in plasma cells, dendritic cells and Mono/Macro cells of OV_GSE115007, in myofibroblasts, fibroblasts and endothelial cells of OV_GSE118828, compared to malignant cells of OV_GSE118828 dataset. The cell components and distribution in primary and metastatic ovarian cancer are quite distinct, which may lead to TME heterogeneity of ovarian cancer. CONCLUSION: Our results indicated that CD47 is closely correlated to ovarian cancer immune microenvironment and might induce ovarian cancer heterogeneity. Therefore, CD47 may be used as a candidate prognostic biomarker and provide us with new insights into potential immunotherapy in ovarian cancer patients.
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Fibroblasts positive for meflin have anti-fibrotic properties in pulmonary fibrosis.
The prognosis of elderly individuals with idiopathic pulmonary fibrosis (IPF) remains poor. Fibroblastic foci, in which aggregates of proliferating fibroblasts and myofibroblasts are involved, are the pathological hallmark lesions in IPF to represent focal areas of active fibrogenesis. Fibroblast heterogeneity in fibrotic lesions hampers the discovery of the pathogenesis of pulmonary fibrosis. Therefore, to determine the pathogenesis of IPF, identification of functional fibroblasts is warranted. The aim of this study was to determine the role of fibroblasts positive for meflin, identified as a potential marker for mesenchymal stromal cells, during the development of pulmonary fibrosis.We characterised meflin-positive cells in a single-cell atlas established by single-cell RNA sequencing (scRNA-seq)-based profiling of 243 472 cells from 32 IPF lungs and 29 normal lung samples. We determined the role of fibroblasts positive for meflin using bleomycin (BLM)-induced pulmonary fibrosis.scRNA-seq combined with in situ RNA hybridisation identified proliferating fibroblasts positive for meflin in fibroblastic foci, not dense fibrosis, of fibrotic lungs in IPF patients. A BLM-induced lung fibrosis model for meflin-deficient mice showed that fibroblasts positive for meflin had anti-fibrotic properties to prevent pulmonary fibrosis. Although transforming growth factor-β-induced fibrogenesis and cell senescence with the senescence-associated secretory phenotype were exacerbated in fibroblasts via the repression or lack of meflin, these were inhibited in meflin-deficient fibroblasts with meflin reconstitution.These findings provide evidence to show the biological importance of meflin expression on fibroblasts and myofibroblasts in the active fibrotic region of pulmonary fibrosis.
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PRKCB Mediates Ferroptosis-Immune Crosstalk in Acute Lung Injury: Insights from Integrated Single-Cell Transcriptomics.
BACKGROUND: Acute respiratory distress syndrome (ARDS), previously classified under the broader category of acute lung injury (ALI), a life-threatening condition characterized by uncontrolled inflammation, remains a major challenge in critical care medicine. Ferroptosis, an iron-dependent cell death driven by lipid peroxidation, is implicated in ALI pathogenesis, yet its cell-specific landscape and interplay with the immune microenvironment remain poorly defined. METHODS: We integrated single-cell and bulk transcriptomic data from public databases (12 samples, 50,316 high-quality cells). Cell populations were annotated, and ferroptosis propensity was scored using the FerrDb gene set. Cell-cell communication, transcriptional regulation, and pseudotime trajectory analyses were performed. Key predictions were validated in an LPS-induced alveolar epithelial cell (MLE-12) model using the PRKCB inhibitor Enzastaurin and the ferroptosis inhibitor Ferrostatin-1. RESULTS: We constructed a cellular atlas of ALI, noting a significant shift toward immune cell infiltration (macrophages/neutrophils >80%). Ferroptosis driver scores were significantly elevated in ALI, particularly within epithelial and myeloid cells, but not fibroblasts. CellChat analysis revealed a remodeled communication network centered on myeloid cells, with enhanced interactions involving ferroptosis-high-risk cells. Pseudotime analysis of epithelial cells illustrated a continuous transition toward a ferroptotic state, accompanied by stage-specific gene expression. Multi-algorithm integration identified Protein Kinase C Beta (PRKCB) as a core regulatory gene. In vitro validation confirmed that PRKCB inhibition attenuated LPS-induced cell death, lipid peroxidation, and dysregulation of key ferroptosis markers (GPX4, SLC7A11, ACSL4). CONCLUSION: Our study provides the first single-cell resolution map of ferroptosis heterogeneity in ALI, uncovering a PRKCB-mediated positive feedback loop between ferroptosis and immune dysregulation. These findings identify PRKCB as a potential therapeutic target to disrupt this pathogenic crosstalk.
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Disturbed Flow Induces Reprogramming of Endothelial Cells to Immune-like and Foam Cells under Hypercholesterolemia during Atherogenesis.
BACKGROUND: Atherosclerosis occurs preferentially in the arteries exposed to disturbed flow (d-flow), while the stable flow (s-flow) regions are protected even under hypercholesterolemic conditions. We recently showed that d-flow alone initiates flow-induced reprogramming of endothelial cells (FIRE), including the novel concept of partial endothelial-to-immune-cell-like transition (partial EndIT), but was not validated using a genetic lineage-tracing model. Here, we tested and validated the two-hit hypothesis that d-flow is an initial instigator of partial FIRE but requires hypercholesterolemia to induce a full-blown FIRE and atherosclerotic plaque development. METHODS: Mice were treated with adeno-associated virus expressing proprotein convertase subtilisin/kexin type 9 and a Western diet to induce hypercholesterolemia and/or partial carotid ligation (PCL) surgery to expose the left common carotid artery (LCA) to d-flow. Single-cell RNA sequencing (scRNA-seq) analysis was performed using cells obtained from the intima and leftover LCAs and the control right common carotid arteries at 2 and 4 weeks post-PCL. Comprehensive immunohistochemical staining was performed on EC-specific confetti mice treated with PCL and hypercholesterolemic conditions at 4 weeks post-PCL to validate endothelial reprogramming. RESULTS: Atherosclerotic plaques developed by d-flow under hypercholesterolemia at 2 and 4 weeks post-PCL, but not by d-flow or hypercholesterolemia alone, as expected. The scRNA-seq results of 98,553 single cells from 95 mice revealed 25 cell clusters; 5 EC, 3 vascular smooth muscle cell (SMC), 5 macrophage (MΦ), and additional fibroblast, T cell, natural killer cell, dendritic cell, neutrophil, and B cell clusters. Our scRNA-seq analyses showed that d-flow under hypercholesterolemia transitioned healthy ECs to full immune-like (EndIT) and, more surprisingly, foam cells (EndFT), in addition to inflammatory and mesenchymal cells (EndMT). Further, EC-derived foam cells shared remarkably similar transcriptomic profiles with foam cells derived from SMCs and MΦs. Comprehensive lineage-tracing studies using immunohistochemical staining of canonical protein and lipid markers in the EC-specific confetti mice clearly demonstrated direct evidence supporting the novel FIRE hypothesis, including EndIT and EndFT, when d-flow was combined with hypercholesterolemia. Further, reanalysis of the publicly available human carotid plaque scRNA-seq and Perturb-seq datasets supported the FIRE hypothesis and a potential mechanistic link between the genes and FIRE. CONCLUSION: We provide evidence supporting the two-hit hypothesis: ECs in d-flow regions, such as the branching points, are partially reprogrammed, while hypercholesterolemia alone has minimal endothelial reprogramming effects. Under hypercholesterolemia, d-flow fully reprograms arterial ECs, including the novel EndIT and EndFT, in addition to inflammation and EndMT, during atherogenesis. This single-cell atlas provides a crucial roadmap for developing novel mechanistic understanding and therapeutics targeting flow-sensitive genes, proteins, and pathways of atherosclerosis.
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Comprehensive Pan-Cancer Analysis of KIF18A as a Marker for Prognosis and Immunity.
KIF18A belongs to the Kinesin family, which participates in the occurrence and progression of tumors. However, few pan-cancer analyses have been performed on KIF18A to date. We used multiple public databases such as TIMER, The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Human Protein Atlas (HPA) to explore KIF18A mRNA expression in 33 tumors. We performed immunohistochemistry on liver cancer and pancreatic cancer tissues and corresponding normal tissues to examine the expression of KIF18A protein. Univariate Cox regression and Kaplan-Meier survival analysis were applied to detect the effect of KIF18A on overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) of patients with these tumors. Subsequently, we explored KIF18A gene alterations in different tumor tissues using cBioPortal. The relationship between KIF18A and clinical characteristics, tumor microenvironment (TME), immune regulatory genes, immune checkpoints, tumor mutational burden (TMB), microsatellite instability (MSI), mismatch repairs (MMRs), DNA methylation, RNA methylation, and drug sensitivity was applied for further study using the R language. Gene Set Enrichment Analysis (GSEA) was utilized to explore the molecular mechanism of KIF18A. Bioinformatic analysis and immunohistochemical experiments confirmed that KIF18A was up-regulated in 27 tumors and was correlated with the T stage, N stage, pathological stage, histological grade, and Ki-67 index in many cancers. The overexpression of KIF18A had poor OS, DSS, and PFI in adrenocortical carcinoma (ACC), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), brain lower-grade glioma (LGG), liver cancer (LIHC), lung adenocarcinoma (LUAD), and pancreatic cancer (PAAD). Univariate and multivariate regression analysis confirmed KIF18A as an independent prognostic factor for LIHC and PAAD. The mutation frequency of KIF18A is the highest in endometrial cancer. KIF18A expression levels were positively associated with immunocyte infiltration, immune regulatory genes, immune checkpoints, TMB, MSI, MMRs, DNA methylation, RNA methylation, and drug sensitivity in certain cancers. In addition, we discovered that KIF18A participated in the cell cycle at the single-cell level and GSEA analysis for most cancers. These findings suggested that KIF18A could be regarded as a latent prognostic marker and a new target for cancer immunological therapy.
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The cycling and aging mouse female reproductive tract at single-cell resolution.
The female reproductive tract (FRT) undergoes extensive remodeling during reproductive cycling. This recurrent remodeling and how it shapes organ-specific aging remains poorly explored. Using single-cell and spatial transcriptomics, we systematically characterized morphological and gene expression changes occurring in ovary, oviduct, uterus, cervix, and vagina at each phase of the mouse estrous cycle, during decidualization, and into aging. These analyses reveal that fibroblasts play central-and highly organ-specific-roles in FRT remodeling by orchestrating extracellular matrix (ECM) reorganization and inflammation. Our results suggest a model wherein recurrent FRT remodeling over reproductive lifespan drives the gradual, age-related development of fibrosis and chronic inflammation. This hypothesis was directly tested using chemical ablation of cycling, which reduced fibrotic accumulation during aging. Our atlas provides extensive detail into how estrus, pregnancy, and aging shape the organs of the female reproductive tract and reveals the unexpected cost of the recurrent remodeling required for reproduction.
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Biomarkers associated with cell-in-cell structure in kidney renal clear cell carcinoma based on transcriptome sequencing.
BACKGROUND: Kidney renal clear cell carcinoma (KIRC), the main histological subtype of renal cell carcinoma, has a high incidence globally. Cell-in-cell structures (CICs), as a cellular biological phenomenon, play pivotal roles in cell competition, immune evasion and tumor progression in the context of KIRC. METHODS: Data for this study were sourced from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) were identified using the limma package. Enrichment analyses were performed using the clusterProfiler package. Support vector machine-recursive feature elimination (SVM-RFE) and Least Absolute Shrinkage and Selection Operator (LASSO) regression, implemented via the caret and glmnet packages in R, were used to select biomarkers. The accuracy of these biomarkers was verified by using the receiver operating characteristic (ROC) curve as well as in vitro experiments (CCK-8 assay, wound healing assay, Transwell assay, and quantitative real-time PCR). The CIBERSORT algorithm was applied to explore the association between immune infiltration and the biomarkers. Further analysis explored the association between these biomarkers and clinicopathological characteristics of KIRC. For single-cell data, the Seurat package is used to read the sample data, and the SCTransform function is employed for normalization. RESULTS: This study identified 1,256 DEGs which enriched in T-cell immune system regulation processes. Five hub genes (CDKN2A, VIM, TGFB1, CTSS, and CDC20) were biomarkers with area under the curve (AUC) values > 0.8, indicating high predictive performance. In vitro validation experiments demonstrated that the expressions of all five biomarkers in KIRC cells were elevated, and the knockdown of CTSS could inhibit the migration and invasion of KIRC cells. Immune infiltration analysis showed higher proportions of T-cells and macrophages in tumor tissues. CDKN2A and CDC20 expressions correlated significantly with stage and grade, while TGFB1, CDKN2A, and CDC20 were highly expressed in proliferative tumor cells. CONCLUSION: This study provides new biomarkers for KIRC, offering valuable insights into its developmental mechanisms for the research of CIC in this disease.
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Integrating bulk and single-cell RNA sequencing reveals cellular heterogeneity and immune infiltration in hepatocellular carcinoma.
Efficacy of immunotherapy in hepatocellular carcinoma (HCC) is blocked by its high degree of inter- and intra-tumor heterogeneity and immunosuppressive tumor microenvironment. However, the correlation between tumor heterogeneity and immunosuppressive microenvironment in HCC has not been well addressed. Here, we endeavored to dissect inter- and intra-tumor heterogeneity in HCC and uncover how they contribute to the immunosuppressive microenvironment. We performed consensus molecular subtyping with non-negative matrix factorization (NMF) clustering to stratify the inter-heterogeneity profile of HCC tumors. We grouped HCC tumors from the Cancer Genome Atlas (TCGA) patients into three subtypes (S1, S2 and S3), where S1 was characterized as a 'hot tumor' profile with high expression level of T cell genes and rate of immune scores. S2 was characterized as a 'cold tumor' profile with the highest tumor purity score, and S3 as an 'immunosuppressed tumor' profile with the poorest prognosis and a high expression level of immunosuppressive genes such as cytotoxic T-lymphocyte-associated protein-4, TIGIT, and PDCD1. Moreover, we combined weighted gene co-expression network analysis and single-cell regulatory network inference and clustering (SCENIC) in the single-cell dataset of the S3-like subtype (CS3) and identified a transcription factor, BATF, which could upregulate immunosuppressive genes. Finally, we identified a cell interaction network in which a myeloid-derived suppressor cell-like macrophage subtype could promote the formation of immunosuppressive T-cells.
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Machine learning combined with single-cell analysis reveals predictive capacity and immunotherapy response of T cell exhaustion-associated lncRNAs in uterine corpus endometrial carcinoma.
BACKGROUND: The exhaustion of T-cells is a primary factor contributing to immune dysfunction in cancer. Long non-coding RNAs (lncRNAs) play a significant role in the advancement, survival, and treatment of Uterine Corpus Endometrial Carcinoma (UCEC). Nevertheless, there has been no investigation into the involvement of lncRNAs associated with T-cell exhaustion (TEXLs) in UCEC. The goal of this work is to establish predictive models for TEXLs in UCEC and study their related immune features. METHODS: Using transcriptome and single-cell sequencing data from The Cancer Genome Atlas and Gene Expression Omnibus databases, we employed co-expression analysis and univariate Cox regression to identify prognostic-associated TEXLs (pTEXLs). The prognostic model was developed using the Least Absolute Contraction and Selection Operator. The immunotherapy characteristics of the prognostic model risk score were studied. Then molecular subgroups were identified through non-negative Matrix Factorization based on pTEXLs. The identification of co-expressed genes was done using a weighted correlation network analysis. Subsequently, a diagnostic model for UCEC was created. In-depth investigations, both in vitro and in vivo, were carried out to elucidate the molecular mechanism of the key gene within the diagnostic model. RESULTS: Receiver operating characteristic curve, calibration curve, and decision curve analysis proved the validity of the predictive models established according to pTEXLs. The subgroup with lower risk scores in the prognostic model has better responses to blocking immune checkpoint therapy. Single-cell analysis suggests that the expression level of MIEN1 is relatively high in immune cells among diagnostic genes. Furthermore, the targeted suppression of MIEN1 via sh-MIEN1 diminishes the proliferative, migratory, and invasive capacities of UCEC cells, potentially associated with CD8+ T cell exhaustion. CONCLUSIONS: The association between TEXLs and UCEC was methodically elucidated by our investigation. A stable pTEXLs risk prediction model and a diagnosis model for UCEC were also established.
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Developmental and sexual dimorphic atlas of the prenatal mouse external genitalia at the single-cell level.
Birth defects of the external genitalia are among the most common in the world. Proper formation of the external genitalia requires a highly orchestrated process that involves special cell populations and sexually dimorphic hormone signaling. It is clear what the end result of the sexually dimorphic development is (a penis in the male versus clitoris in the female); however, the cell populations involved in the process remain poorly defined. Here, we used single-cell messenger RNA sequencing in mouse embryos to uncover the dynamic changes in cell populations in the external genitalia during the critical morphogenetic window. We found that overall, male and female external genitalia are largely composed of the same core cellular components. At the bipotential stage of development (embryonic day or E14.5), few differences in cell populational composition exist between male and female. Although similar in cell population composition, genetic differences in key sexual differentiation developmental pathways arise between males and females by the early (E16.5) and late (E18.5) differentiation stages. These differences include discrete cell populations with distinct responsiveness to androgen and estrogen. By late sexual differentiation (E18.5), unique cell populations in both male and female genitalia become apparent and are enriched with androgen- and estrogen-responsive genes, respectively. These data provide insights into the morphogenesis of the external genitalia that could be used to understand diseases associated with defects in the external genitalia.