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Integrative network toxicology and transcriptomic analyses identify DCP1B and HAS2 as key prognostic biomarkers in formaldehyde-associated Wilms tumor.
Background and objectivesWilms tumor, a common childhood malignancy, has been hypothesized to be associated with environmental factors such as formaldehyde exposure. As a potential endocrine disruptor with reported pro-proliferative effects, the molecular mechanism underlying the role of formaldehyde in Wilms tumor remains unclear. This study systematically investigated the mechanisms linking formaldehyde exposure to Wilms tumor using network toxicology and transcriptomic analysis.MethodsTranscriptomic data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases, whereas formaldehyde-related targets were predicted using the Search Tool for Interactions of Chemicals and Comparative Toxicogenomics databases. Candidate genes were screened through differential expression (|log2FC| > 2.5, p < 0.05) and weighted gene coexpression network analyses. Prognostic key genes were identified using univariate and Lasso-Cox regression, with nomogram construction and survival analysis. Single-cell RNA sequencing data (GSE223373) were further analyzed to characterize cellular heterogeneity and the cell-type-specific expression patterns of the identified key genes.ResultsSeventy-nine candidate genes associated with Wilms tumor were identified using multidimensional intersection analysis. These genes were significantly involved in pathways such as microRNAs in cancer and the cell cycle. Univariate Cox and Lasso-Cox regression analyses identified DCP1B and HAS2 as key genes closely associated with the prognosis of patients with Wilms tumor. Kaplan-Meier survival analysis demonstrated that higher expressions of DCP1B and HAS2 were significantly associated with better overall survival in these patients. The nomogram model constructed based on the two key genes demonstrated excellent calibration (area under the curve > 0.8) and clinical applicability. Network analysis identified NEAT1, the hsa-let-7 microRNA, and transcription factors such as PDX1 and E2F1 were as core regulatory nodes. Single-cell analysis demonstrated pronounced stromal expansion within Wilms tumor specimens and further revealed that DCP1B was preferentially enriched in tumor epithelial cells, whereas HAS2 exhibited a stromal-skewed distribution, predominantly within mesangial cells.ConclusionsDCP1B and HAS2 were identified as key prognostic genes for Wilms tumor. These findings suggest that formaldehyde exposure is associated with Wilms tumor pathogenesis through the potential involvement of cancer-associated microRNA pathways and cell cycle signaling, which could contribute to dysregulated cell proliferation and apoptosis.
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A pan-cancer analysis of the FAT1 in human tumors.
FAT atypical cadherin 1 (FAT1) is one of the most mutagenic genes in tumors, and several critical studies have revealed its role in tumors, although no pan-cancer studies are currently available. Therefore, we explored the potential oncogenic role of FAT1 in 33 tumors based on The Cancer Genome Atlas and Gene Expression Omibus datasets. We found that FAT1 was strongly expressed in most tumors and significantly correlated with their prognosis. Additionally, we analyzed the association of FAT1 with tumors from multiple perspectives, including single-cell sequencing, mutations, high tumor mutational burden, microsatellite instability, immune cell infiltration, and immune microenvironment. Our first pan-cancer study provided a relatively comprehensive understanding of the oncogenic role of FAT1 in tumors.
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Assessment of intra-tumoural colorectal cancer prognostic biomarkers using RNA in situ hybridisation.
Genome-wide expression studies using microarrays and RNAseq have increased our understanding of colorectal cancer development. Translating potential gene biomarkers from these studies for clinical utility has typically relied on PCR-based technology and immunohistochemistry. Results from these techniques are limited by tumour sample heterogeneity and the lack of correlation between mRNA transcript abundance and corresponding protein levels. The aim of this research was to investigate the clinical utility of the RNA in situ hybridisation technique, RNAscope®, for measuring intra-tumoural gene expression of potential prognostic markers in a colorectal cancer cohort. Two candidate gene markers (GFI1 and TNFRSF11A) assessed in this study were identified from a previous study led by the The Cancer Genome Atlas (TCGA) Network, and analysis was performed on 112 consecutively collected, archival FFPE colorectal cancer tumour samples. Consistent with the TCGA Network study, we found reduced GFI1 expression was associated with high-grade and left-sided tumours, and reduced TNFRSF11A expression was associated with metastasis and high nodal involvement. RNAscope® combined with image analysis also enabled quantification of GFI1 and TNFRSF11A mRNA expression levels at the single cell level, allowing cell-type determination. These data showed that reduced mRNA transcript abundance measured in patients with poorer prognosis occurred in carcinoma cells, and not lymphocytes, stromal cells or normal epithelial cells. To our knowledge, this is the first study to assess the intra-tumoural expression patterns of GFI1 and TNFRSF11A and to validate their microarray expression profiles using RNAscope. We also demonstrate the utility of RNAscope® technology to show that expression differences are derived from carcinoma cells rather than from cells located in the tumour microenvironment.
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Cross-tissue single-cell atlas reveals Id2 promotes sepsis-induced tissue damage by mediating macrophage metabolic reprogramming via Pkm2.
As important immune cells, macrophage polarization is directly related to tissue damage in sepsis, and the polarization of macrophages is associated with their metabolic patterns. Previous studies exploring macrophage function in sepsis mainly focused on specific tissues, lacking comprehensive comparisons between tissues. Herein, we performed single-cell RNA sequencing (scRNA-seq) to systematically profile macrophages derived from the brain, heart, intestine, lung, spleen, and peripheral blood mononuclear cells (PBMCs) under homeostatic and septic conditions. Under steady-state, we detected the markers of macrophages in different tissues, classified the macrophages into 10 functional subtypes and compared the differences in their distribution among tissues. In sepsis, we found that Pkm2 and Id2 played important roles in macrophage glycolysis. Mechanistically, Id2 mediated the metabolic reprogramming of macrophages by regulating the chromatin accessibility of Pkm2. Helichrysetin, an inhibitor of Id2, could significantly alleviate tissue damage and increase the survival of septic mice. In summary, our research depicted a cross-tissue macrophage landscape at the single-cell level that encompasses both homeostasis and sepsis. We also provided a new target and a potential drug for the treatment of sepsis by inhibiting macrophage metabolic reprogramming.
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Single-cell full-length transcriptome of human lung reveals genetic effects on isoform regulation beyond gene-level expression.
Genetic regulation of splicing uniquely contributes to trait-associated genome-wide association studies (GWAS) signals. However, quantitative trait loci (QTL) analysis using short-read sequencing of bulk tissues fails to capture full-length and cell-type-specific isoforms. Here, we present an isoform-level lung cell atlas from 129 never-smoking Korean women using single-cell long-read RNA-sequencing, identifying abundant unannotated and cell-type-specific isoforms. Isoform-level signatures of 37 lung cell types display a larger difference and therefore improve cell-type classification compared to gene-level expression. Notably, isoform-QTLs (isoQTLs) detect unannotated and/or cell-type-specific isoforms with independent genetic regulation from expression-QTL (eQTL), supported by enriched splicing functional elements. IsoQTLs nominate susceptibility isoforms from previously unexplained lung function and cancer GWAS loci, via eQTL-independent signals. We highlight a potentially functional novel variant of PPIL6 in multiciliated cells underlying lung cancer risk through alternative splicing. This isoform-level resource advances our understanding of cell-type-specific isoform regulation and its contribution to lung traits and diseases.
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Landscape of Epstein-Barr virus gene expression and perturbations in cancer.
Epstein-Barr virus (EBV) is the causative agent for multiple neoplastic diseases of epithelial and lymphocytic origin1-3. The heterogeneity of the viral elements expressed and the mechanisms by which these coding and non-coding genes maintain cancer cell properties in vivo remain elusive4,5. Here we conducted a multi-modal transcriptomic analysis of EBV-associated neoplasms and identified that the ubiquitously expressed RPMS1 non-coding RNAs support cancer cell properties by disruption of the interferon response. Our map of EBV expression shows a variable, but pervasive expression of BNLF2 discerned from the overlapping LMP1 RNA in bulk sequencing data. Using long-read single-molecule sequencing, we identified three new viral elements within the RPMS1 gene. Furthermore, single-cell sequencing datasets allowed for the separation of cancer cells and healthy cells from the same tissue biopsy and the characterization of a microenvironment containing interferon gamma excreted by EBV-stimulated T-lymphocytes. In comparison with healthy epithelium, EBV-transformed cancer cells exhibited increased proliferation and inhibited immune response induced by the RPMS1-encoded microRNAs. Our atlas of EBV expression shows that the EBV-transformed cancer cells express high levels of non-coding RNAs originating from RPMS1 and that the oncogenic properties are maintained by RPMS1 microRNAs. Through bioinformatic disentanglement of single cells from cancer tissues we identified a positive feedback loop where EBV-activated immune cells stimulate cancer cells to proliferate, which in turn undergo viral reactivation and trigger an immune response.
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Integration of human organoids single-cell transcriptomic profiles and human genetics repurposes critical cell type-specific drug targets for severe COVID-19.
Human organoids recapitulate the cell type diversity and function of their primary organs holding tremendous potentials for basic and translational research. Advances in single-cell RNA sequencing (scRNA-seq) technology and genome-wide association study (GWAS) have accelerated the biological and therapeutic interpretation of trait-relevant cell types or states. Here, we constructed a computational framework to integrate atlas-level organoid scRNA-seq data, GWAS summary statistics, expression quantitative trait loci, and gene-drug interaction data for distinguishing critical cell populations and drug targets relevant to coronavirus disease 2019 (COVID-19) severity. We found that 39 cell types across eight kinds of organoids were significantly associated with COVID-19 outcomes. Notably, subset of lung mesenchymal stem cells increased proximity with fibroblasts predisposed to repair COVID-19-damaged lung tissue. Brain endothelial cell subset exhibited significant associations with severe COVID-19, and this cell subset showed a notable increase in cell-to-cell interactions with other brain cell types, including microglia. We repurposed 33 druggable genes, including IFNAR2, TYK2, and VIPR2, and their interacting drugs for COVID-19 in a cell-type-specific manner. Overall, our results showcase that host genetic determinants have cellular-specific contribution to COVID-19 severity, and identification of cell type-specific drug targets may facilitate to develop effective therapeutics for treating severe COVID-19 and its complications.
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Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain.
Cytosine DNA methylation is essential in brain development and is implicated in various neurological disorders. Understanding DNA methylation diversity across the entire brain in a spatial context is fundamental for a complete molecular atlas of brain cell types and their gene regulatory landscapes. Here we used single-nucleus methylome sequencing (snmC-seq3) and multi-omic sequencing (snm3C-seq)1 technologies to generate 301,626 methylomes and 176,003 chromatin conformation-methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell taxonomy with 4,673 cell groups and 274 cross-modality-annotated subclasses. We identified 2.6 million differentially methylated regions across the genome that represent potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide spatial transcriptomics data validated the association of spatial epigenetic diversity with transcription and improved the anatomical mapping of our epigenetic datasets. Furthermore, chromatin conformation diversities occurred in important neuronal genes and were highly associated with DNA methylation and transcription changes. Brain-wide cell-type comparisons enabled the construction of regulatory networks that incorporate transcription factors, regulatory elements and their potential downstream gene targets. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a whole-brain SMART-seq2 dataset. Our study establishes a brain-wide, single-cell DNA methylome and 3D multi-omic atlas and provides a valuable resource for comprehending the cellular-spatial and regulatory genome diversity of the mouse brain.
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Fifteen hub genes associated with progression and prognosis of clear cell renal cell carcinoma identified by coexpression analysis.
Renal cell carcinoma (RCC) is the most common type of renal tumor, and the clear cell renal cell carcinoma (ccRCC) is the most frequent subtype. In this study, our aim is to identify potential biomarkers that could effectively predict the prognosis and progression of ccRCC. First, we used The Cancer Genome Atlas (TCGA) RNA-sequencing (RNA-seq) data of ccRCC to identify 2370 differentially expressed genes (DEGs). Second, the DEGs were used to construct a coexpression network by weighted gene coexpression network analysis (WGCNA). Moreover, we identified the yellow module, which was strongly related to the histologic grade and pathological stage of ccRCC. Then, the functional annotation of the yellow module and single-samples gene-set enrichment analysis of DEGs were performed and mainly enriched in cell cycle. Subsequently, 18 candidate hub genes were screened through WGCNA and protein-protein interaction (PPI) network analysis. After verification of TCGA's ccRCC data set, Gene Expression Omnibus (GEO) data set (GSE73731) and tissue validation, we finally identified 15 hub genes that can actually predict the progression of ccRCC. In addition, by using survival analysis, we found that patients of ccRCC with high expression of each hub gene were more likely to have poor prognosis than those with low expression. The receiver operating characteristic curve showed that each hub gene could effectively distinguish between localized and advanced ccRCC. In summary, our study indicates that 15 hub genes have great predictive value for the prognosis and progression of ccRCC, and may contribute to the exploration of the pathogenesis of ccRCC.
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CYB561 is a potential therapeutic target for breast cancer and is associated with immune cell infiltration.
BACKGROUND: Breast cancer (BC), a common malignant tumor originating from the terminal ductal lobular unit of the breast, poses a substantial health risk to women. Previous studies have associated cytochrome b561 (CYB561) with a poor prognosis in BC; however, its underlying mechanism of this association remains unclear. METHODS: We investigated the expression of CYB561 mRNA in BC using databases such as The Cancer Genome Atlas, Gene Expression Omnibus, Tumor-Normal-Metastatic plot, and Kaplan-Meier plotter databases. The prognostic value of CYB561 protein in BC was assessed in relation to its expression levels in tumor tissue samples from 158 patients with BC. The effect of CYB561 on BC progression was confirmed using in vivo and in vitro experiments. The biological functions and related signaling pathways of CYB561 in BC were explored using gene microarray, Innovative Pathway, Gene Ontology enrichment, and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. The correlation between CYB561 and the BC tumor immune microenvironment was evaluated using the CIBERSORT algorithm and single-cell analysis and further validated through immunohistochemistry of serial sections. RESULTS: Our study demonstrated that upregulation of CYB561 expression predicted poor prognosis in patients with BC and that CYB561 knockdown inhibited the proliferation, migration, and invasive ability of BC cells in vitro. CYB561 knockdown inhibited BC tumor formation in vivo.CYB561 was observed to modulate downstream tropomyosin 1 expression. Furthermore, CYB561 expression was associated with macrophage M2 polarization in the BC immune microenvironment. CONCLUSIONS: Elevated CYB561 expression suggests a poor prognosis for patients with BC and is associated with macrophage M2 polarization in the BC microenvironment. Therefore, CYB561 could potentially serve as a therapeutic target for BC treatment.