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Single-cell analysis of human non-small cell lung cancer lesions refines tumor classification and patient stratification.
Immunotherapy is a mainstay of non-small cell lung cancer (NSCLC) management. While tumor mutational burden (TMB) correlates with response to immunotherapy, little is known about the relationship between the baseline immune response and tumor genotype. Using single-cell RNA sequencing, we profiled 361,929 cells from 35 early-stage NSCLC lesions. We identified a cellular module consisting of PDCD1+CXCL13+ activated T cells, IgG+ plasma cells, and SPP1+ macrophages, referred to as the lung cancer activation module (LCAMhi). We confirmed LCAMhi enrichment in multiple NSCLC cohorts, and paired CITE-seq established an antibody panel to identify LCAMhi lesions. LCAM presence was found to be independent of overall immune cell content and correlated with TMB, cancer testis antigens, and TP53 mutations. High baseline LCAM scores correlated with enhanced NSCLC response to immunotherapy even in patients with above median TMB, suggesting that immune cell composition, while correlated with TMB, may be a nonredundant biomarker of response to immunotherapy.
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Elucidating the dynamic tumor microenvironment through deep transcriptomic analysis and therapeutic implication of MRE11 expression patterns in hepatocellular carcinoma.
AIM: This study aims to explore the dynamic tumor microenvironment of hepatocellular carcinoma (HCC) through deep transcriptomic analysis and to identify key regulatory genes, among which MRE11 was further validated for its immunomodulatory and prognostic significance. METHODS: We performed Summary-data-based Mendelian Randomization (SMR) analysis to identify genes causally associated with HCC and intersected these with DNA damage repair (DDR) genes, leading to the identification of MRE11. A comprehensive evaluation of MRE11 expression in HCC was conducted using transcriptomic data analysis. We collected data from 92 HCC patient samples and validated MRE11 expression differences in HCC tissues through qPCR, immunohistochemistry, and Western blotting. Publicly available single-cell RNA sequencing (scRNA-seq) data and spatial transcriptomics were utilized to explore MRE11's dynamic mechanisms in the tumor microenvironment (TME) of both primary and post-immunotherapy cases. We also screened for differentially expressed genes and constructed a robust HCC prognosis model using 101 machine-learning algorithms. RESULTS: Our results demonstrated that high MRE11 expression is strongly associated with poor prognosis in HCC. In the primary TME, MRE11 regulates immune responses, facilitating immune evasion. Single-cell analysis revealed significant tumor heterogeneity in MRE11 high-expression groups, particularly in macrophages and malignant cells, where MRE11 regulates immune evasion and tumor progression via the cGAS-STING pathway and HGF-MET axis. Under immunotherapy, high MRE11 expression facilitated epithelial-mesenchymal transition (EMT) and extensive remodeling of the TME. Furthermore, MRE11 dynamically enhanced macrophage regulation, exhibiting immunosuppressive and tumor-invasive features. Finally, our prognostic model exhibited strong predictive accuracy across multiple datasets. CONCLUSION: High MRE11 expression is crucial in regulating the immune microenvironment in HCC, fostering immune evasion and driving tumor progression. MRE11 emerges as a promising biomarker for HCC diagnosis and a potential target for personalized immunotherapy.
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Dexamethasone modulates immature neutrophils and interferon programming in severe COVID-19.
Although critical for host defense, innate immune cells are also pathologic drivers of acute respiratory distress syndrome (ARDS). Innate immune dynamics during Coronavirus Disease 2019 (COVID-19) ARDS, compared to ARDS from other respiratory pathogens, is unclear. Moreover, mechanisms underlying the beneficial effects of dexamethasone during severe COVID-19 remain elusive. Using single-cell RNA sequencing and plasma proteomics, we discovered that, compared to bacterial ARDS, COVID-19 was associated with expansion of distinct neutrophil states characterized by interferon (IFN) and prostaglandin signaling. Dexamethasone during severe COVID-19 affected circulating neutrophils, altered IFNactive neutrophils, downregulated interferon-stimulated genes and activated IL-1R2+ neutrophils. Dexamethasone also expanded immunosuppressive immature neutrophils and remodeled cellular interactions by changing neutrophils from information receivers into information providers. Male patients had higher proportions of IFNactive neutrophils and preferential steroid-induced immature neutrophil expansion, potentially affecting outcomes. Our single-cell atlas (see 'Data availability' section) defines COVID-19-enriched neutrophil states and molecular mechanisms of dexamethasone action to develop targeted immunotherapies for severe COVID-19.
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Thyroid hormone receptor α1: a novel regulator of thyroid cancer cell differentiation.
Thyroid hormone receptor α1 (TRα1) mediates the genomic actions of thyroid hormone (T3). The biology of TRα1 in growth and development has been well studied, but the functional role of TRα1 in cancers remains to be elucidated. Analysis of the human thyroid cancer database of The Cancer Genome Atlas (TCGA) showed that THRA gene expression is lost in highly dedifferentiated anaplastic thyroid cancer (ATC). We, therefore, explored the effects of TRα1 on the progression of ATC. We stably expressed TRα1 in two human ATC cell lines, THJ-11T (11T-TRα1 #2, #7, and #8) and THJ-16T (16T-TRα1 #3, #4, and #8) cells. We found that the expressed TRα1 inhibited ATC cell proliferation and induced apoptosis. TCGA data showed that THRA gene expression was best correlated with the paired box gene 8 (PAX8). Consistently, we found that the PAX8 expression was barely detectable in parental 11T and 16T cells. However, PAX8 gene expression was elevated in 11T- and 16T-TRα1-expressing cells at the mRNA and protein levels. Using various molecular analyses, we found that TRα1 directly regulated the expression of the PAX8 gene. Single-cell transcriptomic analyses (scRNA-seq) demonstrated that TRα1 functions as a transcription factor through multiple signaling pathways to suppress tumor growth. Importantly, scRNA-seq analysis showed that TRα1-induced PAX8, via its transcription program, shifts the cell landscape of ATC toward a differentiated state. The present studies suggest that TRα1 is a newly identified regulator of thyroid differentiation and could be considered as a potential therapeutic target to improve the outcome of ATC patients.
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Systems biology strategy and experimental validation to uncover the pharmacological mechanism of Xihuang Pill in treating non-small cell lung cancer.
BACKGROUND: Non-small cell lung cancer (NSCLC) accounts for almost 85% of lung cancer-related deaths worldwide. Xihuang Pill (XHP) is a representative anticancer Chinese patented medicine used to treat NSCLC in China. However, to date, a systematic analysis of XHP's antitumour effects and its impact on the immune microenvironment has not been performed. PURPOSE: Based on the systems biology strategy and experimental validation, the present study aimed to investigate the pharmacological mechanisms involved in treating NSCLC with XHP. METHODS: A subcutaneous tumour model was established to evaluate XHP's tumour-inhibitory effect in BALB/c nude mice. RNA sequencing (RNA-seq) and bioinformatics analysis were conducted to identify differentially expressed genes (DEGs) and signalling pathways related to XHP treatment. Network analysis based on network pharmacology and protein-to-protein networks was applied to identify the compounds and genes targeted by XHP. External data from the TCGA-NSCLC cohort were used to verify the clinical significance of XHP-targeted genes in NSCLC. The expression of survival-related candidate genes after XHP treatment was verified via qPCR. The protein expression of calcium voltage-gated channel subunit alpha 1C (CACNA1C) in different NSCLC cell lines was analysed in the Human Protein Atlas database (HPA) and DepMap Portal. Using the Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data (ESTIMATE) algorithm and the single-sample gene set enrichment analysis (ssGSEA) algorithm uncovered the role of CACNA1C in the NSCLC tumour microenvironment (TME). RESULTS: XHP (2 g/kg/d) significantly inhibited the growth of transplanted A549 tumours. RNA-seq identified a total of 529 DEGs (189 upregulated and 340 downregulated). In addition, 542 GO terms, 41 significant KEGG pathways, 9 upregulated hallmarks pathways, and 18 downregulated hallmark pathways were enriched. These GO terms and signalling pathways were closely related to cell proliferation, immunity, energy metabolism, and the inflammatory response of NSCLC. In addition, XHP's network pharmacology analysis identified 301 compounds and 1,432 target genes. A comprehensive strategic analysis identified CACNA1C as a promising gene by which XHP targets and regulates the TME of NSCLC, benefiting patient survival. CACNA1C expression was positively correlated with both the immune score and stromal score but negatively correlated with the tumour purity score. Additionally, CACNA1C expression was significantly correlated with the infiltration levels of 15 types of immune cells and the expression levels of 6 well-known checkpoint genes. CONCLUSIONS: Our results show that by regulating the pathways associated with cell proliferation and immunity, XHP can suppress cancer cell growth in NSCLC. Additionally, XHP may increase the expression of CACNA1C to suppress immune cell infiltration and regulate the expression of checkpoint-related genes, thereby improving the overall survival of NSCLC patients.
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Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris.
Here we present a compendium of single-cell transcriptomic data from the model organism Mus musculus that comprises more than 100,000 cells from 20 organs and tissues. These data represent a new resource for cell biology, reveal gene expression in poorly characterized cell populations and enable the direct and controlled comparison of gene expression in cell types that are shared between tissues, such as T lymphocytes and endothelial cells from different anatomical locations. Two distinct technical approaches were used for most organs: one approach, microfluidic droplet-based 3'-end counting, enabled the survey of thousands of cells at relatively low coverage, whereas the other, full-length transcript analysis based on fluorescence-activated cell sorting, enabled the characterization of cell types with high sensitivity and coverage. The cumulative data provide the foundation for an atlas of transcriptomic cell biology.
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Single-cell atlas reveals the key role of pro-inflammatory IREB2⁺ microglia subsets in the microenvironment of Alzheimer's disease.
Chronic neuroinflammation driven by activated microglia is a critical hallmark of Alzheimer's disease (AD) progression. Metabolic dysregulation, particularly iron metabolism, has been implicated in neurodegeneration, yet the role of iron-responsive element-binding protein 2 (IREB2) in AD-associated neuroinflammation remains poorly understood. We performed integrative analysis of single-cell RNA sequencing (scRNA-seq) data from AD brain tissues, using non-negative matrix factorization (NMF) and intercellular communication algorithms to map cellular landscapes. We identified microglial subpopulations and their inflammatory signaling. To experimentally validate the functional role of IREB2 in inflammatory responses, we conducted siRNA-mediated knockdown in the human neuroblastoma cell line SH-SY5Y, which serves as a neuronal model for assessing IREB2's effect on cytokine expression. Single-cell analysis revealed a distinct microglial subpopulation (IREB2⁺ MC C1) that is significantly expanded in AD. This subpopulation exhibits a hyper-inflammatory state, with enrichment of Toll-like receptor and IL-17 signaling pathways, and functions as a primary source of outgoing inflammatory signals (CCL3, CCL4). Furthermore, IREB2 knockdown in SH-SY5Y cells significantly suppressed the expression of key pro-inflammatory cytokines (IL6, IL-1β, and TNF-α), confirming that IREB2 positively regulates inflammation in neurons as well. IREB2 drives both microglial activation and neuronal inflammatory responses in AD, potentially via the NF-κB pathway. The IREB2⁺ microglial subpopulation represents a specific pathogenic entity that orchestrates the inflammatory microenvironment. Targeting IREB2 may therefore offer a dual-pronged therapeutic strategy to mitigate neuroinflammation and slow AD progression.
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Downregulation of the Protein C Signaling System Is Associated with COVID-19 Hypercoagulability-A Single-Cell Transcriptomics Analysis.
Because of the interface between coagulation and the immune response, it is expected that COVID-19-associated coagulopathy occurs via activated protein C signaling. The objective was to explore putative changes in the expression of the protein C signaling network in the liver, peripheral blood mononuclear cells, and nasal epithelium of patients with COVID-19. Single-cell RNA-sequencing data from patients with COVID-19 and healthy subjects were obtained from the COVID-19 Cell Atlas database. A functional protein-protein interaction network was constructed for the protein C gene. Patients with COVID-19 showed downregulation of protein C and components of the downstream protein C signaling cascade. The percentage of hepatocytes expressing protein C was lower. Part of the liver cell clusters expressing protein C presented increased expression of ACE2. In PBMC, there was increased ACE2, inflammatory, and pro-coagulation transcripts. In the nasal epithelium, PROC, ACE2, and PROS1 were expressed by the ciliated cell cluster, revealing co-expression of ACE-2 with transcripts encoding proteins belonging to the coagulation and immune system interface. Finally, there was upregulation of coagulation factor 3 transcript in the liver and PBMC. Protein C could play a mechanistic role in the hypercoagulability syndrome affecting patients with severe COVID-19.
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Single-Cell Analyses Offer Insights into the Different Remodeling Programs of Arteries and Veins.
Arteries and veins develop different types of occlusive diseases and respond differently to injury. The biological reasons for this discrepancy are not well understood, which is a limiting factor for the development of vein-targeted therapies. This study contrasts human peripheral arteries and veins at the single-cell level, with a focus on cell populations with remodeling potential. Upper arm arteries (brachial) and veins (basilic/cephalic) from 30 organ donors were compared using a combination of bulk and single-cell RNA sequencing, proteomics, flow cytometry, and histology. The cellular atlases of six arteries and veins demonstrated a 7.8× higher proportion of contractile smooth muscle cells (SMCs) in arteries and a trend toward more modulated SMCs. In contrast, veins showed a higher abundance of endothelial cells, pericytes, and macrophages, as well as an increasing trend in fibroblasts. Activated fibroblasts had similar proportions in both types of vessels but with significant differences in gene expression. Modulated SMCs and activated fibroblasts were characterized by the upregulation of MYH10, FN1, COL8A1, and ITGA10. Activated fibroblasts also expressed F2R, POSTN, and COMP and were confirmed by F2R/CD90 flow cytometry. Activated fibroblasts from veins were the top producers of collagens among all fibroblast populations from both types of vessels. Venous fibroblasts were also highly angiogenic, proinflammatory, and hyper-responders to reactive oxygen species. Differences in wall structure further explain the significant contribution of fibroblast populations to remodeling in veins. Fibroblasts are almost exclusively located outside the external elastic lamina in arteries, while widely distributed throughout the venous wall. In line with the above, ECM-targeted proteomics confirmed a higher abundance of fibrillar collagens in veins vs. more basement ECM components in arteries. The distinct cellular compositions and transcriptional programs of reparative populations in arteries and veins may explain differences in acute and chronic wall remodeling between vessels. This information may be relevant for the development of antistenotic therapies.
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Single-cell transcriptomic profiling reveals CD27+ cytotoxic T Cell heterogeneity and exhaustion dynamics in colorectal cancer tumor microenvironment.
BACKGROUND: CD27+ cytotoxic T cells play critical roles in anti-tumor immunity, yet their heterogeneity and functional states within the colorectal cancer (CRC) tumor microenvironment remain poorly characterized. Understanding the molecular mechanisms underlying T cell exhaustion is essential for developing effective immunotherapeutic strategies. METHODS: We performed comprehensive single-cell RNA sequencing analysis of CD27+ cytotoxic T cells from CRC tumor tissues and matched normal adjacent tissues using the GSE144735 dataset. Multiple dimensional reduction techniques, trajectory inference algorithms, and functional characterization approaches were employed to dissect cellular heterogeneity, differentiation trajectories, and exhaustion dynamics. In vitro co-culture experiments using HCT116 and RKO (MSI-H), HCT15 and SW480 (MSS) colorectal cancer cell lines with activated PBMCs were conducted to validate computational findings. RESULTS: UMAP and t-SNE analyses identified 11 distinct CD27+ T cell clusters with substantial phenotypic heterogeneity, including exhausted terminal, effector, and memory-like populations. Pseudotime trajectory analysis revealed progressive exhaustion pathways with three distinct differentiation fates. Exhausted CD27+ T cells exhibited significantly elevated expression of checkpoint molecules (PDCD1, LAG3, HAVCR2, CTLA4) and reduced cytotoxic capacity compared to effector populations. RNA velocity and PAGA connectivity analysis demonstrated that exhaustion represents a terminal differentiation state with limited plasticity. Gene regulatory network analysis identified key transcription factors governing effector-to-exhausted transitions. Notably, exhausted CD27+ T cells concentrated in tumor core regions, while effector populations distributed peripherally. Co-culture experiments confirmed that MSI-H cell lines (HCT116 and RKO) induced 2-3 times higher exhaustion marker expression compared to MSS cell lines (HCT15 and SW480). For MSI-H cells, PDCD1 showed 5.2-fold (HCT116) and 4.8-fold (RKO) upregulation, while LAG3 showed 4.8-fold (HCT116) and 4.2-fold (RKO) upregulation. In contrast, MSS cells showed lower induction: PDCD1 at 2.1-fold (SW480) and 1.9-fold (HCT15), LAG3 at 1.8-fold (SW480) and 1.6-fold (HCT15). Exploratory survival analysis (HR = 0.505, p = 0.673) did not reach statistical significance and is presented as hypothesis-generating only, highlighting the need for prospective validation in larger cohorts. PDCD1 and LAG3 were identified as prioritized immunotherapy targets based on their significant overexpression in exhausted T cell populations. CONCLUSION: This study provides a comprehensive single-cell atlas of CD27+ cytotoxic T cell heterogeneity in CRC, revealing exhaustion dynamics, regulatory networks, and spatial organization patterns. Our findings highlight the differential immunogenic capacity between MSI-H and MSS tumors and identify potential therapeutic targets for reversing T cell exhaustion in colorectal cancer.