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Landscape of Cell Communication in Human Dental Pulp.
The cellular atlas of the stroma is not well understood. Here, the cell populations in human dental pulp through single-cell RNA sequencing are profiled. Dental pulp stem cells, pulp cells, T cells, macrophages, endothelial cells, and glial cells are identified in human dental pulp. These cells support each other through sending growth signals. Based on the appearance of ligand-receptor pairs between two cell populations, pulp cells have the greatest communication with other cell types, while T cells have the least communication. In addition, T cells expressing TLR1, TLR2, and TLR4, and endothelial cells expressing TLR4, monitor bacterial invasion. These findings provide the census of normal dental pulp.
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Single-cell mapping reveals several immune subsets associated with liver metastasis of pancreatic ductal adenocarcinoma.
BACKGROUND: Identifying a metastasis-correlated immune cell composition within the tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) will help to develop promising and innovative therapeutic strategies. However, the dynamics of immune cell lineages in the TME of advanced PDAC remains elusive. METHODS: Twenty-six samples from 11 patients (including 11 primary tumor tissues, 10 blood, and 5 lymph nodes) with different stages were used to develop a multiscale immune profile. High-dimensional single-cell analysis with mass cytometry was performed to search for metastasis-correlated immune changes in the microenvironment. The findings were further validated by published single-cell RNA sequencing (scRNA-seq) data and multiplex fluorescent immunohistochemistry. FINDINGS: High-dimensional single-cell profiling revealed that the three immune-relevant sites formed a distinct immune atlas. Interestingly, the PDAC microenvironment with the potential for metastatic spread to the liver was characterized by a decreased proportion of CD103+PD-1+CD39+ T cells with cytotoxic and exhausted functional status and an increased proportion of CD73+ macrophages. Analysis of scRNA-seq data of PDAC further confirmed the identified subsets and revealed strong potential interactions via various ligand-receptor pairs between the identified T subsets and the macrophages. Moreover, stratified patients with different immune compositions correlated with clinical outcomes of PDAC. CONCLUSIONS: Our study uncovered metastasis-correlated immune changes, suggesting that ecosystem-based patient classification in PDAC will facilitate the identification of candidates likely to benefit from immunotherapy. FUNDING: This work was supported by the National Key Research and Development Program of China, the Shanghai International Science and Technology Collaboration Program, the Shanghai Sailing Program, and the Key Laboratory of diagnosis and treatment of severe hepato-pancreatic diseases of Zhejiang Province.
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Single-cell analysis revealed a diagnostic model of hepatocellular carcinoma based on cancer stem cell-related gene.
BACKGROUND: Cancer stem cells (CSCs) play a pivotal role in hepatocellular carcinoma (HCC) pathogenesis, driving tumor initiation, progression, metastasis, and therapeutic resistance. This study aimed to establish a reliable CSC-based signature for HCC through single-cell analysis. METHODS: The study integrates single-cell RNA sequencing (scRNA-seq) data with the Dynamic Data Retrieval Tree (DDRTree) algorithm to identify and characterize CSCs in HCC. A prognostic stemness-associated gene signature was constructed using the Cancer Genome Atlas-Liver hepatocellular carcinoma (TCGA-LIHC) cohort as the training set and validated across two independent HCC datasets (GSE14520-GPL571 and GSE14520-GPL3921). Genes with significant prognostic relevance to CSC biology were prioritized for signature inclusion. The efficacy of model was assessed via survival analysis (Kaplan-Meier) and predictive accuracy evaluation [time-dependent receiver operating characteristic (ROC) curves], demonstrating robust stratification of high- versus low-risk HCC patients and strong prognostic discrimination. RESULTS: A total of 17 CSC-related signatures in HCC were identified by copy number variation (CNV) pattern. Then, we constructed 4-CSCs-related gene predictive model by multivariate Cox regression. The model robustly stratified patients into high- and low-risk cohorts, with high-risk individuals exhibiting markedly reduced overall survival (OS). Kaplan-Meier analysis confirmed significant survival disparity between groups (P<0.001), while time-dependent ROC curves validated the model high predictive accuracy. This prognostic signature may guide the development of personalized therapeutic strategies for HCC. CONCLUSIONS: The prognostic model consisted of 4-CSC-related genes had a prognostic predictive value, providing a new perspective for precision immuno-oncology studies.
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Multi-omic analysis of gallbladder cancer identifies distinct tumor microenvironments associated with disease progression.
Gallbladder carcinoma (GBC) is the most aggressive biliary tract cancer and is associated with a high mortality rate. Treatment of GBC faces therapeutic challenges owing to the elusive nature of in situ drivers within the local tumor microenvironment that drive its progression. Here, we created a single-cell atlas of 1,117,245 cells and a mutational landscape from 102 patients, which unveiled spatial-temporal characterizations of cellular constitutions, spatial interplays and molecular functions, and generalized five local ecosystems stratifying clinical outcomes. An integrated epithelial program, AI-EPI, combined with spatial transcriptome analysis, revealed the concurrent localization of a highly malignant tumor subtype (GM16) and AREG+ T cell, B cell, dendritic cell and macrophage subtypes within the pro-metastatic niche of primary adenocarcinomas. In vitro and in vivo experiments suggest that in addition to promoting metastasis, AREG facilitates CXCL5 expression in tumor cells through EGFR-pERK-EGR1 signaling, leading to increased neutrophil infiltration and impeding the effectiveness of immunotherapy. Our study provides a spatial-temporal landscape of the GBC microenvironment and sheds light on potential strategies for preventing immunotherapy resistance.
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CKS2 Mediates Hepatocellular Carcinoma Recurrence After Hepatic Ischemia-Reperfusion Injury Related to M2 Macrophages.
PURPOSE: Hepatocellular carcinoma (HCC) recurrence remains a significant burden on global healthcare. Hepatic ischemia-reperfusion injury (HIRI) is a common complication in liver surgery and may be a contributing factor to HCC recurrence. Nevertheless, the potential mechanism underlying HIRI-induced HCC recurrence has not been fully elucidated. Herein, by combining bioinformatics approaches and basic experimental research, CKS2 was preliminarily identified as a crucial factor involved in HIRI-induced HCC recurrence potentially by modulating M2 macrophages. METHODS: Through performing Weighted Gene Co-Expression Network Analysis (WGCNA), differential gene expression analysis, and screening for genes associated with disease-free survival (DFS) on large-scale genomics projects including The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), the pivotal role of CKS2 in HIRI-induced HCC recurrence was determined. The clinical significance, single-cell analysis, immune cell infiltration correlation, functional enrichment, mutation landscape, and drug sensitivity of CKS2 in HCC were further characterized. Finally, CKS2 expression and function were validated through experimental techniques such as flow cytometry, immunohistochemistry, Western blot assay and quantitative real-time PCR (qRT-PCR). RESULTS: The expression of CKS2 was significantly upregulated in HIRI and HCC tissues and was closely associated with adverse clinical outcomes in HCC patients. There was a positive correlation between CKS2 expression and tumor stemness characteristics. Additionally, high CKS2 expression was strongly linked to M2 macrophage infiltration in HCC tissues. And drug sensitivity analysis indicated that HCC patients with high CKS2 expression were prone to develop drug resistance, complicating clinical anti-tumor treatment. Ultimately, the expression pattern of CKS2 and its correlation with M2 macrophages in HCC were confirmed through experimental validation. CONCLUSION: CKS2 was identified as a key factor in HIRI-induced HCC recurrence and was critically associated with M2 macrophage infiltration abundance, providing novel insights and a direction for future research.
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Identifying genes associated with Sorafenib resistance in hepatocellular carcinoma to develop risk model.
BACKGROUND: Hepatocellular carcinoma (HCC) poses a considerable global health challenge, notably due to the resistance to sorafenib therapy, which significantly impedes effective treatment strategies. This study aimed to identify potential resistance-associated genes and develop a robust prognostic model to predict patient outcomes. METHODS: We utilized transcriptomic data from the gene expression omnibus (GEO) database, focusing on sorafenib-resistant Huh7 and MHCC97H cell lines (GSE94550 and GSE176151), and integrated expression, mutation, and clinical data from the cancer genome atlas (TCGA) and international cancer genome consortium (ICGC) databases. Single-cell RNA sequencing data (GSE149614) were processed with the Seurat and Harmony R packages for quality control and integration. Differential gene expression analysis, consensus clustering, and principal component analysis were performed to identify significant genes and stratify patients based on prognostic outcomes. RESULTS: The analysis revealed 305 potential resistance-associated genes, with a seven-gene (ANAPC13, NCAPD2, KIF2C, CDK5RAP2, MANBA, PPAT, and LPCAT1) risk model demonstrating significant prognostic capability, indicated by area under curve values of 0.824, 0.746, and 0.717 for 1, 3, and 5-year survival predictions, respectively. Notably, immune cell infiltration analyses highlighted significant correlations between risk scores and specific immune cell types, suggesting potential therapeutic targets. Drug sensitivity analysis further identified various compounds with lower IC50 values in high-risk groups. To facilitate clinical application, a nomogram plot was designed. CONCLUSION: This study provides a comprehensive framework for understanding sorafenib resistance in HCC, alongside a validated prognostic model that holds potential for clinical application.
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Single-cell transcriptomic atlas of enteroendocrine cells along the murine gastrointestinal tract.
BACKGROUND: Enteroendocrine cells (EECs) produce over 20 gut hormones which contribute to intestinal physiology, nutrient metabolism and the regulation of food intake. The objective of this study was to generate a comprehensive transcriptomic map of mouse EECs from the stomach to the rectum. METHODS: EECs were purified by flow-cytometry from the stomach, upper small intestine, lower small intestine, caecum and large intestine of NeuroD1-Cre mice, and analysed by single cell RNA sequencing. Regional datasets were analysed bioinformatically and combined into a large cluster map. Findings were validated by L-cell calcium imaging and measurements of CCK secretion in vitro. RESULTS: 20,006 EECs across the full gastrointestinal tract could be subdivided based on their full transcriptome into 10 major clusters, each exhibiting a different pattern of gut hormone expression. EECs from the stomach were largely distinct from those found more distally, even when expressing the same hormone. Cell clustering was also observed when performed only using genes related to GPCR cell signalling, revealing GPCRs predominating in different EEC populations. Mc4r was expressed in 55% of Cck-expressing cells in the upper small intestine, where MC4R agonism was found to stimulate CCK release in primary cultures. Many individual EECs expressed more than one hormone as well as machinery for activation by multiple nutrients, which was supported by the finding that the majority of L-cells exhibited calcium responses to multiple stimuli. CONCLUSIONS: This comprehensive transcriptomic map of mouse EECs reveals patterns of GPCR and hormone co-expression that should be helpful in predicting the effects of nutritional and pharmacological stimuli on EECs from different regions of the gut. The finding that MC4R agonism stimulates CCK secretion adds to our understanding of the melanocortin system.
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Identification of Immune Cell Infiltration and Immune-Related Genes in the Tumor Microenvironment of Glioblastomas.
Glioblastoma (GBM) is one of the most prevalent malignant brain tumors with poor prognosis. Increasing evidence has revealed that infiltrating immune cells and other stromal components in the tumor microenvironment (TME) are associated with prognosis of GBM. The aim of the present study was to identify immune cells and immune-related genes extracted from TME in GBM. RNA-sequencing and clinical data of GBM were downloaded from The Cancer Genome Atlas (TCGA). Four survival-related immune cells were identified via Kaplan-Meier survival analysis and immune-related differentially expressed genes (DEGs) screened. Functional enrichment and protein-protein interaction (PPI) networks for the genes were constructed. In addition, we identified 24 hub genes and the expressions of 6 of the genes were significantly associated with prognosis of GBM. Finally, the genes were validated in single-cell sequencing studies of GBM, and the immune cells validated in an independent GBM cohort from the Chinese Glioma Genome Atlas (CGGA). Overall, 24 immune-related genes infiltrating the tumor microenvironment were identified in the present study, which could serve as novel biomarkers and immune therapeutic targets.
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Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases.
BACKGROUND: Pro-inflammatory fibroblasts are critical for pathogenesis in rheumatoid arthritis, inflammatory bowel disease, interstitial lung disease, and Sjögren's syndrome and represent a novel therapeutic target for chronic inflammatory disease. However, the heterogeneity of fibroblast phenotypes, exacerbated by the lack of a common cross-tissue taxonomy, has limited our understanding of which pathways are shared by multiple diseases. METHODS: We profiled fibroblasts derived from inflamed and non-inflamed synovium, intestine, lungs, and salivary glands from affected individuals with single-cell RNA sequencing. We integrated all fibroblasts into a multi-tissue atlas to characterize shared and tissue-specific phenotypes. FINDINGS: Two shared clusters, CXCL10+CCL19+ immune-interacting and SPARC+COL3A1+ vascular-interacting fibroblasts, were expanded in all inflamed tissues and mapped to dermal analogs in a public atopic dermatitis atlas. We confirmed these human pro-inflammatory fibroblasts in animal models of lung, joint, and intestinal inflammation. CONCLUSIONS: This work represents a thorough investigation into fibroblasts across organ systems, individual donors, and disease states that reveals shared pathogenic activation states across four chronic inflammatory diseases. FUNDING: Grant from F. Hoffmann-La Roche (Roche) AG.
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Identifying transposable element expression dynamics and heterogeneity during development at the single-cell level with a processing pipeline scTE.
Transposable elements (TEs) make up a majority of a typical eukaryote's genome, and contribute to cell heterogeneity in unclear ways. Single-cell sequencing technologies are powerful tools to explore cells, however analysis is typically gene-centric and TE expression has not been addressed. Here, we develop a single-cell TE processing pipeline, scTE, and report the expression of TEs in single cells in a range of biological contexts. Specific TE types are expressed in subpopulations of embryonic stem cells and are dynamically regulated during pluripotency reprogramming, differentiation, and embryogenesis. Unexpectedly, TEs are expressed in somatic cells, including human disease-specific TEs that are undetectable in bulk analyses. Finally, we apply scTE to single-cell ATAC-seq data, and demonstrate that scTE can discriminate cell type using chromatin accessibly of TEs alone. Overall, our results classify the dynamic patterns of TEs in single cells and their contributions to cell heterogeneity.