Revealing novel biomarkers for oesophageal squamous cell carcinoma through integrated single-cell RNA sequencing analysis

Single-cell analysis of allergic diseases.

BackgroundAdipose-derived stem cells (ASCs) are obtained from a variety of sources in vivo where they present in large quantities. These cells are suitable for use in autologous transplantation and the construction of tissue-engineered adipose tissue. Studies have shown that ASCs differentiation is in a high degree of heterogeneity, yet the molecular basis including key regulators of differentiation remains to clarify.MethodsWe performed single-cell RNA sequencing and bioinformatics analysis on both undifferentiated (ASC-GM group) and adipogenically differentiated human ASCs (ASC-AD group, ASCs were cultured in adipogenic inducing medium for 1 week). And then, we verified the results of serum amyloid A1 (SAA1) with western blotting, immunofluorescence staining, oil red O staining. After these experiments, we down-regulated the expression of serum amyloid A1 (SAA1) gene to verify the adipogenic differentiation ability of ASCs.ResultsIn single-cell RNA sequence analyzing, we obtained 4415 cells in the ASC-GM group and 4634 cells in the ASC-AD group. The integrated sample cells could be divided into 11 subgroups (0–10 cluster). The cells in cluster 0, 2, 5 were came from ASC-GM group and the cells in cluster 1, 3, 7 came from ASC-AD group. The cells of cluster 4 and 6 came from both ASC-GM and ASC-AD groups. Fatty acid binding protein 4, fatty acid binding protein 5, complement factor D, fatty acid desaturase 1, and insulin like growth factor binding protein 5 were high expressed in category 1 and 7. Regulation of inflammatory response is the rank 1 biological processes. And cellular responses to external stimuli, negative regulation of defense response and acute inflammatory response are included in top 20 biological processes. Based on the MCODE results, we found that SAA1, C-C Motif Chemokine Ligand 5 (CCL5), and Annexin A1 (ANXA1) significantly highly expressed during adipogenic differentiation. Western blot and immunofluorescent staining results showed that SAA1 increased during adipogenesis. And the area of ORO positive staining in siSAA1 cells was significantly lower than in the siControl (negative control) cells.ConclusionsOur results also indicated that our adipogenic induction was successful, and there was great heterogeneity in the adipogenic differentiation of ASCs. SAA1 with the regulation of inflammatory response were involved in adipogenesis of ASCs based on single-cell RNA sequencing analysis. The data obtained will help to elucidate the intrinsic mechanism of heterogeneity in the differentiation process of stem cells, thus, guiding the regulation of self-renewal and differentiation of adult stem cells.

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.

Background and aims: Nonalcoholic steatohepatitis (NASH) has become one of the major causes of cirrhosis and liver failure. However, there are currently no approved medications for managing NASH. Our study was designed to assess the effects of ginkgetin on NASH and the involved mechanisms. Methods: We constructed a mouse model of NASH by high-fat diet for 24weeks. The effects of ginkgetin on NASH were evaluated by histological study, Western blot, and biochemical analysis. RNA Sequencing (RNA-Seq) analysis was used to investigate the alteration in gene expression and signaling pathways at bulk and single-cell levels. Results: Administration of ginkgetin resulted in a marked improvement in hepatic lipid accumulation, inflammation, and fibrosis in the NASH model. And these results were supported by bulk RNA-Seq analysis, in which the related signaling pathways and gene expression were markedly downregulated. Furthermore, single-cell RNA-Seq (scRNA-Seq) analysis revealed that the effects of ginkgetin on NASH were associated with the reprogramming of macrophages, hepatic stellate cells, and endothelial cells. Especially, ginkgetin induced a marked decrease in macrophages and a shift from pro-inflammatory to anti-inflammatory phenotype in NASH mice. And the NASH-associated macrophages (NAMs), which emerge during NASH, were also significantly downregulated by ginkgetin. Conclusion: Ginkgetin exhibits beneficial effects on improving NASH, supported by bulk and single-cell RNA-Seq. Our study may promote pharmacological therapy for NASH and raise the existent understanding of NASH.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a major respiratory disorder that is characterized by persistent airflow limitation and an abnormal inflammation response to noxious particles, such as cigarette smoke and environmental pollution. COPD is a leading cause of mortality, causing a significant economic and social burden in many countries worldwide. Umbelliferone, which is a coumarin derivative, has been shown to possess anti-inflammatory and antioxidant properties, which may be useful in alleviating COPD. METHODS: An integrative bioinformatics approach was adopted to analyze gene expression datasets from gene expression omnibus (GSE275503 for bulk RNA sequencing and GSE183974 for single-cell RNA sequencing). Differentially expressed genes (DEGs) were identified and overlapped with COPD-associated genes from GeneCards. Common genes were analyzed using the STRING database to construct a protein-protein interactions (PPI) network, and further processed in Cytoscape using the “cytoHubba” plug-in to identify the top 10 hub genes. Molecular docking of these genes, along with three key genes from single-cell analysis, was performed using AutoDock vina in SAMSON software. A molecular dynamic (MD) simulation study was carried out using Desmond and Schrodinger software. The MD simulations were performed to investigate the stability and dynamic behavior of the UMB with 6E3K and 1S9V over time 200 ns. RESULTS: From bulk and single-cell RNA sequencing analyses, 50 and 1053 DEGs were extracted, respectively, with the cut-off value of LogFC > 1 and [Formula: see text]-value < 0.05. A total number of 562 overlapping genes were identified between the DEGs and COPD-associated genes from GeneCards. The top 10 hub genes from the PPI network were ITGAM, CCL2, IFN-[Formula: see text], CCL5, FN1, IL-1B, BCL2, CDH1, IL-1A and CXCL8. Among these, molecular docking revealed the highest binding affinities for IFN-[Formula: see text] (PDB ID: 6E3K, −7.4 kcal/mol), ITGAM (PDB ID: 1NA5, −6.6 kcal/mol), IL-1B (PDB ID: 8C3U, −6.2 kcal/mol), FN1 (PDB ID: 3M7P, −6.1 kcal/mol) and BCL2 (PDB ID: 6YLD, −5.9 kcal/mol). Additionally, single-cell RNA analysis identified HLA-DQA2 (PDB ID: 1H15, −2.7 kcal/mol), HLA-DRB5 (PDB ID: 1S9V, −4.9 kcal/mol) and S100A9 (PDB ID: 6ZDY, −5.3 kcal/mol) as the top three genes. An MD simulation study evaluated protein-ligand stability, binding dynamics and conformational changes. Root mean square deviation (RMSD) and Root mean square fluctuation (RMSF) analyses identified key interacting residues involved in hydrogen bonding, hydrophobic interactions and water bridges. The 6E3K complex exhibited protein backbone RMSD of 5−7 Å, ligand RMSD of 2−5 Å and residue fluctuations <3 Å. The 1S9V complex showed protein RMSD of 2.85 Å, ligand RMSD of 1.95−2.30 Å and residue fluctuations around 1.25−3.25 Å. CONCLUSION: The top 10 Genes from the PPI network and the top 3 genes from the single-cell RNA analysis were associated with COPD-related pathways. Molecular docking with the UMB showed strong binding affinities, indicating its potential to inhibit these pathways and serve as a therapeutic option for COPD. The MD simulation confirmed stable binding, key interactions and structural flexibility.

Ischemic stroke (IS) is a fatal neurological disease that occurs when the blood flow to the brain is disrupted, leading to brain tissue damage and functional impairment. Cellular senescence, a vital characteristic of aging, is associated with a poor prognosis for IS. This study explores the potential role of cellular senescence in the pathological process following IS by analyzing transcriptome data from multiple datasets (GSE163654, GSE16561, GSE119121, and GSE174574). By using bioinformatics methods, we identified hub-senescence-related genes such as ANGPTL4, CCL3, CCL7, CXCL16, and TNF and verified them using quantitative reverse transcription polymerase chain reaction. Further analysis of single-cell RNA sequencing data suggests that MG4 microglial is highly correlated with cellular senescence in MCAO, and might play a crucial role in the pathological process after IS. Additionally, we identified retinoic acid as a potential drug for improving the prognosis of IS. This comprehensive investigation of cellular senescence in various brain tissues and peripheral blood cell types provides valuable insights into the underlying mechanisms of the pathology of IS and identifies potential therapeutic targets for improving patient outcomes.

Esophageal squamous cell carcinoma (ESCC) exhibits significant cellular heterogeneity, rendering it susceptible to developing radioresistance and recurring tumors. Single-cell RNA sequencing (scRNA-seq) is an advanced technique that allows for the exploration of distinct gene expression profiles in individual cells. To investigate cellular heterogeneity in ESCC, scRNA-seq analysis was performed on tumor tissues from ten ESCC patients, as well as adjacent non-malignant esophageal tissues. The cellular composition revealed 19 distinct cell clusters, further categorized into seven cell populations: 69.31% Fibroblast, 15.36% T cell, 5.30% Monocytes, 5.26% Endothelial cells, 2.68% plasma cell, 1.91% Epithelial cells, and 0.18% ambiguous. Notably, Fibroblast and Endothelial cells were more prevalent in non-malignant tissues, while the remaining cell types were enriched in tumor tissues. Differential gene expression analysis identified 49 genes with higher expression in tumor cells and 37 genes with lower expression. Gene Set Enrichment Analysis (GSEA) revealed the top three most relevant GO Biological Processes pathways: positive regulation of immune response, regulation of T cell activation, and positive regulation of cell migration. Furthermore, in post-treatment follow-up, four patients were observed to develop metastasis within one year. Comparative analysis between metastatic and non-metastatic patients unveiled 9 Differentially Expressed Genes (DEGs), including KRT6A and AKR1B10, which exhibited specific expression in Epithelial cells and were highly expressed in tumor tissues. Additionally, IGLC2, IGHG4, and IGHG1 demonstrated specific expression in plasma cells, with elevated expression in tumor tissues. These findings suggest that KRT6A, AKR1B10, IGLC2, IGHG4, and IGHG1 may serve as potential biomarkers for predicting post-chemotherapy metastasis in ESCC patients. Citation Format: Tzu-Hung Hsiao, Chih-Hung Lin, Ting-Shuan Wu, Li-Wen Lee, Chung-Ping Hsu. Characterizing Cellular Heterogeneity and Identifying Potential Biomarkers in Esophageal Squamous Cell Carcinoma (ESCC) Using Single-Cell RNA Sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5674.

BackgroundMitotic catastrophe (MC) is a well-recognized endogenous mechanism of tumor cell death, characterized as a delayed cell death process associated with aberrant mitosis. However, its prognostic significance in the context of intratumoral heterogeneity in esophageal squamous cell carcinoma (ESCC) remains largely unexplored.MethodsWe performed an in-depth analysis of single-cell RNA sequencing (scRNA-seq) data from ESCC obtained from the Gene Expression Omnibus (GEO) database. MC scores for individual cells were calculated using the AddModuleScore function, and T cell specific gene modules were identified via the high-dimensional weighted gene co-expression network analysis (hdWGCNA) framework. To further elucidate the developmental trajectories and intercellular interactions of T cells, pseudotime analysis and cell-cell communication inference were conducted. A prognostic risk model was then constructed using three machine learning algorithms combined with multivariate Cox regression analysis. Following risk stratification, we performed immune infiltration profiling, drug sensitivity analysis, and molecular docking to comprehensively assess the functional implications of the risk model in ESCC. Based on preliminary results from quantitative Real-time PCR (qRT-PCR) and Western blotting (WB), we selected the hub gene SLF2 for functional validation using wound healing, Cell Counting Kit-8 (CCK-8) assay, Transwell, and colony formation assays.ResultsBased on T cell mitotic catastrophe associated genes (MCAGs) and utilizing machine learning algorithms, we established a robust prognostic risk model for ESCC. The model demonstrated excellent stratification capability in predicting patient outcomes and effectively revealed the heterogeneity of the tumor immune microenvironment (TIME) and drug sensitivity. Furthermore, functional experiments confirmed that knockdown of the hub gene SLF2 significantly inhibited the migration, invasion, and proliferation of ESCC cells.ConclusionThe prognostic model based on MCAGs we developed serves as an effective tool for predicting outcomes in ESCC.T cell-specific MCAGs drive intratumoral heterogeneity in ESCC, serving as potential prognostic biomarkers and therapeutic targets.Supplementary InformationThe online version contains supplementary material available at 10.1186/s40246-025-00815-9.

Single-cell RNA sequencing analysis dissected the osteo-immunology microenvironment and revealed key regulators in osteoporosis

BackgroundHepatocellular carcinoma (HCC) is an aggressive liver cancer with poor prognosis. Deubiquitinating enzymes (DUBs) are critical regulators of tumor progression, yet the functional significance of DUBs in HCC remains poorly understood.MethodsHCC patient-derived organoids (PDOs), HCC cell lines and animal models were used to evaluate the anticancer responses of ubiquitin-specific protease (USP)2 inhibition. We analyzed the correlation of USP2 expression and immune cells infiltration using single-cell RNA sequencing and flow cytometry analysis. Mechanistically, we established an in vitro co-culture system and analyzed metabolic data to find out the bridge between tumor cell USP2 and macrophage in the microenvironment. Immunofluorescence, co-immunoprecipitation, CUT&RUN, ELISA, and mass spectrometry were conducted to explore the molecular pathway.ResultsWe found that the inhibitor (ML364) targeting USP2 shows effective anticancer responses against HCC PDOs. Targeting USP2 significantly inhibits lipid metabolism of HCC and induces cell ferroptosis. Single-cell RNA sequencing analysis and multiplex immunohistochemistry analysis indicated that high expression of USP2 in HCC was associated with the infiltration of M2 macrophage. Mechanistically, USP2 deubiquitinates and stabilizes peroxisome proliferator-activated receptor gamma (PPARγ) via removing the K48-linked ubiquitin chain at the K142 site. PPARγ promotes the transcription of fatty acid biosynthesis-related genes (ATP-citrate lyase, acetyl-CoA carboxylase and ACSS2) and de novo synthesis of fatty acids including oleic acid. HCC cell-derived oleic acid promotes M2 macrophage polarization by enhancing the fatty acid oxidation of macrophages. Polarized M2 macrophages further secrete interleukin-10, which created an IL-10/STAT3/USP2 positive-feedback loop to activate USP2 expression continuously.ConclusionOur data suggest that USP2, a key molecule mediating the interaction between HCC cells and tumor-associated macrophages, may be a promising therapeutic target for HCC.

Single-cell RNA sequencing reveals diverse intratumoral heterogeneities and gene signatures of two types of esophageal cancers

Proteomic and single-cell landscape reveals novel pathogenic mechanisms of HBV-infected intrahepatic cholangiocarcinoma

Background:Polymyalgia Rheumatica (PMR) is a common inflammatory disease in elderly persons whose pathogenesis is unclear [1-4].Objectives:We aimed to explore the pathogenetic features of PMR.Methods:We analyzed the cell subsets and their...

Idiopathic pulmonary arterial hypertension (IPAH) is a rare and severe cardiopulmonary disease with a challenging prognosis, and its underlying pathogenesis remains elusive. A comprehensive understanding of IPAH is crucial to unveil potential diagnostic markers and therapeutic targets. In this study, we investigated cellular heterogeneity and molecular pathology in IPAH using single-cell RNA sequencing (scRNA-seq) analysis. Our scRNA-seq results revealed significant alterations in three crucial signaling pathways in IPAH: the hypoxia pathway, TGF β pathway, and ROS pathway, primarily attributed to changes in gene expression within arterial endothelial cells. Moreover, through bulk RNA sequencing analysis, we identified differentially expressed genes (DEGs) enriched in GO and KEGG pathways, implicated in regulating cell adhesion and oxidative phosphorylation in IPAH lungs. Similarly, DEGs-enriched pathways in IPAH arterial endothelial cells were also identified. By integrating DEGs from three IPAH datasets and applying protein-protein interaction (PPI) analysis, we identified 12 candidate biomarkers. Subsequent validation in two additional PAH datasets led us to highlight five potential biomarkers (CTNNB1, MAPK3, ITGB1, HSP90AA1, and DDX5) with promising diagnostic significance for IPAH. Furthermore, real-time quantitative polymerase chain reaction (RT-qPCR) confirmed significant differences in the expression of these five genes in pulmonary arterial endothelial cells from PAH mice. In conclusion, our findings shed light on the pivotal role of arterial endothelial cells in the development of IPAH. Furthermore, the integration of single-cell and bulk RNA sequencing datasets allowed us to pinpoint novel candidate biomarkers for the diagnosis of IPAH. This work opens up new avenues for research and potential therapeutic interventions in IPAH management.

BackgroundCervical cancer ranks as the fourth most common malignancy among women worldwide, with approximately 604,000 new cases and 342,000 deaths annually. Despite advances in HPV vaccination and screening programs, significant challenges remain in diagnostic accuracy, therapeutic efficacy, and prognostic assessment. Traditional bulk RNA sequencing methods average gene expression data across entire tissue specimens, masking cellular diversity and spatial architectural patterns that influence tumor progression. Telomere maintenance mechanisms play crucial roles in cervical cancer development, with over 90% of cervical cancers exhibiting telomerase reactivation.Methods This study integrated single-cell RNA sequencing and spatial transcriptomics technologies to construct the first comprehensive spatial molecular atlas of cervical cancer. Single-cell RNA sequencing analysis utilized public datasets from the GEO database with systematic quality control through a multidimensional assessment framework. Spatial transcriptomics analysis employed the 10x Genomics Visium platform, successfully identifying 38 distinct cellular neighborhoods (N1-N38). Spatial expression patterns of 10 key genes were analyzed, including epithelial markers (MUC1, CDH1, KRT16), stromal markers (COL1A1, COMP, DCN), and immune markers (CD3G, FCGR1A). In vitro validation was performed using HeLa and SiHa cell lines.Results Multiple distinct cell subpopulations and 38 cellular neighborhoods with unique molecular characteristics were successfully identified. MKI67 demonstrated spatial heterogeneity with proliferative “hotspots”; COMP was primarily expressed in stromal regions and participated in tumor-stroma interactions; KRT16 exhibited patterns reflecting epithelial differentiation gradients. Different neighborhoods showed enrichment for various cell types, including immune hotspots, stromal-rich regions, and epithelial-dominant areas. Immunoglobulin-related genes (IGLC2, IGHG1, IGHG2, etc.) displayed unique spatial expression characteristics. Quantitative PCR validation confirmed differential expression patterns between cell lines.ConclusionsThis study established the first comprehensive spatial transcriptomic atlas of cervical cancer, revealing unprecedented insights into tumor microenvironment organization and cellular spatial relationships.