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Identification of a six-gene prognostic signature for bladder cancer associated macrophage.
As major components of the tumor microenvironment (TME), tumor-associated macrophages (TAMs) play an exceedingly complicated role in tumor progression and tumorigenesis. However, few studies have reported the specific TAM gene signature in bladder cancer. Herein, this study focused on developing a TAM-related prognostic model in bladder cancer patients based on The Cancer Genome Atlas (TCGA) data. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify key genes related to TAM (M2 macrophage). Gene ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis showed the functional categories of the key genes. Simultaneously, we used the Least Absolute Shrinkage and Selection Operator (LASSO) and univariate and multivariate Cox regressions to establish a TMA-related prognostic model containing six key genes: TBXAS1, GYPC, HPGDS, GAB3, ADORA3, and FOLR2. Subsequently, single-cell sequencing data downloaded from Gene Expression Omnibus (GEO) suggested that the six genes in the prognostic model were expressed in TAM specifically and may be involved in TAM polarization. In summary, our research uncovered six-TAM related genes that may have an effect on risk stratification in bladder cancer patients and could be regarded as potential TAM-related biomarkers.
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Spatially resolved transcriptomic analysis of the adult human prostate.
The prostate is an organ characterized by significant spatial heterogeneity. To better understand its intricate structure and cellular composition, we constructed a comprehensive single-cell atlas of the adult human prostate. Our high-resolution mapping effort identified 253,381 single cells and 34,876 nuclei sampled from 11 patients who underwent radical resection of bladder cancer, which were categorized into 126 unique subpopulations. This work revealed various new cell types in the human prostate and their specific spatial localization. Notably, we discovered four distinct acini, two of which were tightly associated with E-twenty-six transcription factor family (ETS)-fusion-negative prostate cancer. Through the integration of spatial, single-cell and bulk-seq analyses, we propose that two specific luminal cell types could serve as the common origins of prostate cancer. Additionally, our findings suggest that zone-specific fibroblasts may contribute to the observed heterogeneity among luminal cells. This atlas will serve as a valuable reference for studying prostate biology and diseases such as prostate cancer.
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TriLock-FISH enables in situ discrimination of influenza cRNA and mRNA for single-cell analysis of viral replication and transcription.
Influenza A virus produces three RNA species-viral RNA (vRNA), complementary RNA (cRNA), and messenger RNA (mRNA)-whose synthesis and trafficking are spatially compartmentalized. However, the high sequence similarity between cRNA and mRNA hinders their distinction in situ, limiting understanding of the spatial organization of the viral replication-transcription dynamics. Here, triple-lock fluorescence in situ hybridization (TriLock-FISH) was developed to distinguish vRNA, cRNA, and mRNA in situ with high specificity. TriLock-FISH enabled a genome-wide, time-resolved single-cell atlas of RNA abundance and localization, revealing marked cell-to-cell variation in RNA abundance but relatively conserved spatial organization. cRNA was found to be predominantly nuclear, with a small but reproducible cytoplasmic fraction. Application to infected mouse lung tissue demonstrated simultaneous spatial detection of all viral RNA species. This approach provides a highly specific framework for single-cell analysis of RNA virus replication and transcription.IMPORTANCEInfluenza virus relies on three closely related RNA molecules for replication and gene expression, yet distinguishing them inside infected cells has remained technically challenging. This limitation has hindered understanding of viral replication in space and time. We developed triple-lock fluorescence in situ hybridization, which enables simultaneous visualization of all three viral RNA species across all eight influenza genome segments in infected cells and tissues. Single-cell analysis revealed striking heterogeneity in viral RNA abundance across infected cells, whereas intracellular RNA localization patterns remained relatively conserved. Complementary RNA, a replication intermediate long thought to be strictly nuclear, was also detected at low levels in the cytoplasm. These findings provide new insight into influenza virus replication and establish a broadly applicable tool for studying RNA virus biology.
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Association analysis of FXYD5 with prognosis and immunological characteristics across pan-cancer.
BACKGROUND: The FXYD domain-containing ion transport regulator 5 (FXYD5) gene is a cancer promoter. However, evidence for an association between FXYD5 and various types of cancer is still lacking. Using multi-omics bioinformatics, our study aimed to reveal the expression distribution, prognostic value, immune infiltration correlation, and molecular functions of FXYD5. METHODS: Using pan-cancer multi-omics data (including The Cancer Genome Atlas, PrognoScan, Gene Expression Profiling Interactive Analysis, cBioPortal, Gene Expression Omnibus, TIMER and scTIME Portal), we assessed the differences in the expression and prognostic value of FXYD5 in malignant tumors. Furthermore, at the single-cell level, we analyze the expression distribution of FXYD5 across different cell types within the tumor microenvironment, and its relationship with the immune microenvironment. Finally, focusing on ovarian cancer, we conducted preliminary validation of the above findings using cell and molecular biology techniques. RESULTS: Our results indicated that FXYD5 was up-regulated in various tumor types and was positively associated with tumor progression. We also revealed that FXYD5 was ubiquitously expressed in microenvironmental cells at the single-cell level, and its upregulation was associated with enhanced immune infiltration, cancer-associated fibroblast infiltration, and dysfunction of tumor-infiltrating cytotoxic T lymphocyte. Additionally, its expression was positively correlated with immune checkpoint genes, DNA mismatch repair genes, MSI (microsatellite instability) and TMB (tumor mutational burden) across various cancers. Its higher expression in cytotoxic T lymphocytes attenuated its ability to predict patient survival with PD-L1 (programmed death-ligand 1) blockade therapy, and FXYD5 was found to be a potential regulator of tumor immune escape and resistance to cancer immunotherapies. Based on GSEA (gene set enrichment analysis) and experimental verification, FXYD5 activated TGF-β/SMAD signaling and drove EMT (epithelial-mesenchymal transition) to promote ovarian cancer progression. CONCLUSION: In summary, our study revealed that FXYD5-TGFβ axis may coregulate the interaction between tumors, CAFs (carcinoma-associated fibroblasts) and immune cells to reshape the tumor immune microenvironment and promote tumorigenesis and tumor progression. Thus, FXYD5 could be used as an immune-related biomarker for diagnosing and predicting the prognosis of multiple cancer types. Therefore, our findings suggest that targeting FXYD5 in TME (tumor microenvironment) may be a promising therapeutic strategy.
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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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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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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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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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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.