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Epigenetic inactivation of COL4A4 orchestrates JAK2/STAT3-driven progression and microenvironment reprogramming in renal cell carcinoma.
BACKGROUND: Renal cell carcinoma (RCC) is a common urinary malignancy that lacks reliable early biomarkers. Although epigenetic silencing of tumor suppressor genes mediated by DNA methylation is common in RCC, the specific role and regulation of the basement membrane component COL4A4 remain unclear. METHODS: Bulk and single-cell RNA sequencing (scRNA-seq), DNA methylation analysis, The Cancer Genome Atlas data and in-house clinical RCC cohorts were integrated to characterize COL4A4 expression, epigenetic regulation, clinical significance, and associations with tumor microenvironment (TME) features. The biological functions of COL4A4 were evaluated using in vitro functional assays and in vivo xenograft models. Mechanistic studies included 5-Aza demethylation treatment and JAK2/STAT3 pathway inhibition. RESULTS: COL4A4 was downregulated in RCC, and its downregulation is associated with promoter hypermethylation, serving as an independent prognostic factor. Functionally, COL4A4 inhibited RCC cell proliferation, migration, and invasion in vitro, and suppressed tumor growth in vivo. Mechanistically, COL4A4 negatively modulated the JAK2/STAT3 signaling pathway. scRNA-seq revealed that COL4A4 was predominantly enriched in epithelial cells. Low COL4A4 expression is associated with altered extracellular matrix-receptor interactions and an immunosuppressive TME. CONCLUSIONS: COL4A4 acts as a methylation-silenced RCC tumor suppressor that negatively modulates JAK2/STAT3 signaling and correlates with TME features, representing a potential epigenetic therapeutic target.
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A Single-Cell Transcriptome Profiling of Triptolide-Induced Nephrotoxicity in Mice.
Triptolide (TP), an active component isolated from the traditional Chinese herb Tripterygium wilfordii Hook F (TWHF), shows great promise for treating inflammation-related diseases. However, its potential nephrotoxic effects remain concerning. The mechanism underlying TP-induced nephrotoxicity is inadequately elucidated, particularly at single-cell resolution. Hence, single-cell RNA sequencing (scRNA-seq) of kidney tissues from control and TP-treated mice is performed to generate a thorough description of the renal cell atlas upon TP treatment. Heterogeneous responses of nephron epithelial cells are observed after TP exposure, attributing differential susceptibility of cell subtypes to excessive reactive oxygen species and increased inflammatory responses. Moreover, TP disrupts vascular function by activating endothelial cell immunity and damaging fibroblasts. Severe immune cell damage and the activation of pro-inflammatory Macro_C1 cells are also observed with TP treatment. Additionally, ligand-receptor crosstalk analysis reveals that the SPP1 (osteopontin) signaling pathway targeting Macro_C1 cells is triggered by TP treatment, which may promote the infiltration of Macro_C1 cells to exacerbate renal toxicity. Overall, this study provides comprehensive information on the transcriptomic profiles and cellular composition of TP-associated nephrotoxicity at single-cell resolution, which can strengthen the understanding of the pathogenesis of TP-induced nephrotoxicity and provide valuable clues for the discovery of new therapeutic targets to ameliorate TP-associated nephrotoxicity.
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KeyPathwayMineR: De Novo Pathway Enrichment in the R Ecosystem.
De novo pathway enrichment is a systems biology approach in which OMICS data are projected onto a molecular interaction network to identify subnetworks representing condition-specific functional modules and molecular pathways. Compared to classical pathway enrichment analysis methods, de novo pathway enrichment is not limited to predefined lists of pathways from (curated) databases and thus particularly suited for discovering novel disease mechanisms. While several tools have been proposed for pathway enrichment, the integration of de novo pathway enrichment in end-to-end OMICS analysis workflows in the R programming language is currently limited to a single tool. To close this gap, we have implemented an R package KeyPathwayMineR (KPM-R). The package extends the features and usability of existing versions of KeyPathwayMiner by leveraging the power, flexibility and versatility of R and by providing various novel functionalities for performing data preparation, visualization, and comparison. In addition, thanks to its interoperability with a plethora of existing R packages in e.g., Bioconductor, CRAN, and GitHub, KPM-R allows carrying out the initial preparation of the datasets and to meaningfully interpret the extracted subnetworks. To demonstrate the package's potential, KPM-R was applied to bulk RNA-Seq data of nasopharyngeal swabs from SARS-CoV-2 infected individuals, and on single cell RNA-Seq data of aging mice tissue from the Tabula Muris Senis atlas.
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Etiology-based Molecular Characterization of Hepatocellular Carcinoma Reveals SQLE's Contribution to Immunosuppressive Microenvironment.
BACKGROUND: Hepatocellular carcinoma (HCC) is a kind of fatal cancer with a variety of risk factors. However, a pan-etiology molecular characterization of HCC has not been explored. OBJECTIVE: The objective of this study is to explore etiology-specific features of HCC and improve our understanding of tumorigenesis, thereby revealing potential therapeutic targets. METHODS: RNA-seq, genetic alteration, copy number alteration, and clinicopathological data of The Cancer Genome Atlas -Liver Hepatocellular Carcinoma cohort were downloaded and explored. Immune-related features and single-cell and spatial transcriptomic data were adopted and analyzed. RESULTS: Etiology-based analyses revealed that HCC with different etiologies showed different clinical features, including gender composition, ethnic composition, clinical stage distribution, and survival. In addition, distinct genetic alterations, copy number alterations, and tumor microenvironment were observed in HCC patients with different etiologies. Significantly enhanced expression of squalene epoxidase (SQLE) was observed in viral hepatitis-related HCC and was associated with poor tumor grade and overall survival. Correlation analysis revealed a negative relationship between SQLE expression and anti-tumor immunity. Single-cell and spatial transcriptomics demonstrated that SQLE contributed to reduced T cell and NK cell infiltration while increasing macrophage and monocyte infiltration. CONCLUSION: The current study demonstrated that HCC has etiology-specific clinical features, genetic alteration, copy number alteration, and tumor microenvironment. Overexpression of SQLE in viral hepatitis-related HCC correlate with poor clinical outcome and may contribute to reduce T cell and NK cell infiltration while increased macrophage and monocyte infiltration, which lead to immunosuppressive microenvironment and can be an actionable target.
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Integrative Multi-Omics and Machine Learning Reveal Senescent Fibroblast-Associated ADAMTS2 as a Critical Indicator of Intestinal Inflammation in IBD.
Although cellular senescence contributes to tissue dysfunction in inflammatory bowel disease (IBD), the heterogeneity of senescence at the single-cell resolution remains poorly defined. In this study, we systematically characterized the senescence landscape within the IBD microenvironment, with particular emphasis on fibroblast subpopulations and their systemic consequences. Single-cell RNA sequencing (scRNA-seq) dataset was applied to profile senescence-associated feature heterogeneity. Fibroblasts were classified into high-senescence (HS-Fibro) and low-senescence (LS-Fibro) groups according to senescence scores. HS-Fibro-specific gene signatures were identified and functionally annotated. Intercellular communication networks were constructed using CellChat to delineate the HS-Fibro interactome atlas, with emphasis on identifying cellular targets responsive to senescence-associated secretory phenotype (SASP) signals. Integrated microarray datasets were employed to elucidate the systemic impact of HS-Fibro in IBD. Through the integration of differential expression analysis, Weighted Gene Co-expression Network Analysis (WGCNA), and an ensemble of 113 machine learning algorithms, seven hub genes implicated in IBD progression were systematically identified and prioritized. In the IBD microenvironment, fibroblasts exhibited enhanced senescence activity. HS-Fibro displayed potent pro-inflammatory properties and enhanced communicative capacity. IBD patients with high HS-Fibro infiltration showed sustained immune-inflammatory activity. Systematic bioinformatic analysis and immunohistochemistry validation identified ADAMTS2 as a robust diagnostic indicator for IBD, with substantially elevated expression in patients relative to controls. The human colon fibroblast cell line CCD-18Co was treated with H2O2 to establish a cellular senescence model, demonstrating marked upregulation of ADAMTS2, SASP markers, and fibrosis-related genes. Moreover, siRNA-mediated knockdown of ADAMTS2 resulted in obvious attenuation of these SASP and fibrosis-associated genes.
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The prognostic significance of KLRB1 and its further association with immune cells in breast cancer.
BACKGROUND: Killer cell lectin-like receptor B1 (KLRB1) is an important member of the natural killer cell gene family. This study explored the potential value of KLRB1 as a breast cancer (BC) biomarker and its close association with the tumor immune microenvironment during the development of BC. METHODS: We examined the differential expression of KLRB1 in pan-cancer. Clinical and RNA-Seq data from BC samples were evaluated in The Cancer Genome Atlas (TCGA) and validated in Gene Expression Omnibus (GEO) datasets and by immunohistochemistry (IHC) staining. The relationship between KLRB1 and clinical parameters was explored through Chi-square tests. The diagnostic value of KLRB1 was evaluated using a receiver operating characteristic (ROC) curve. Survival analysis was tested by Kaplan-Meier curves to demonstrate the relationship between KLRB1 and survival. Univariable and multivariate cox regression analyses were carried out as well. The analysis of immune infiltration level and gene set enrichment analysis (GSEA) were conducted to examine KLRB1's mechanism during the progression of BC. We used the Tumor Immune Estimation Resource (TIMER), the Cancer Single-cell Expression Map (CancerSCEM) database, the Tumor Immune Single-cell Hub (TISCH) database, and the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) method to explore KLRB1's association with immune infiltration level and different quantitative distribution of immune cells. The relevant signaling pathways in BC associated with KLRB1 were identified using GSEA. RESULTS: The expression of KLRB1 was downregulated across the majority of cancers including BC. The lower KLRB1 expression group exhibited shorter relapse free survival (RFS) and overall survival (OS). IHC staining showed that KLRB1 staining was weaker in breast tumor tissues than in paratumors. Additionally, GSEA identified several pathway items distinctly enriched in BC. KLRB1 expression level was also positively related to the infiltrating number of immune cells in BC. Moreover, the CancerSCEM and TISCH databases as well as the CIBERSORT method demonstrated the close relationship between KLRB1 and immune cells, particularly macrophages. CONCLUSION: Low KLRB1 expression was considered an independent prognostic biomarker and played an important role in the tumor immune microenvironment of BC patients.
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Systems mapping of intra-donor, cross-tissue T cell clonal expansion and tissue adaptation in the gut-liver-blood axis.
The human gut-liver axis is a critical immunological interface, yet factors that shape T cell adaptation and clonal expansion across tissues remain unclear. We performed integrated single-cell RNA and T cell receptor sequencing on T cells from matched colon epithelium, lamina propria, liver, and blood of the same donors, enabling clonal tracking and tissue-specific transcriptional profiling without inter-individual confounders. Colonic intraepithelial lymphocytes were largely clonally distinct from lamina propria T cells. Tissue-resident T cells in colon vs. liver displayed marked transcriptional divergence, with colonic lamina propria tissue-resident memory T cells (TRMs) enriched for interferon-stimulated genes (e.g., ISG15 and IFITM3). Ligand-receptor analysis implicated liver-derived factors, including fibrinogen gamma chain, in shaping colon TRM states. Across tissues, highly expanded clones of the same cell type shared a core upregulated gene set, suggesting common determinants of clonal success. These data provide a same-donor single-cell atlas of T cell diversity and adaptation across the human gut-liver-blood axis.
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Temporal transcriptomic dynamics in developing macaque neocortex.
Despite intense research on mice, the transcriptional regulation of neocortical neurogenesis remains limited in humans and non-human primates. Cortical development in rhesus macaque is known to recapitulate multiple facets of cortical development in humans, including the complex composition of neural stem cells and the thicker supragranular layer. To characterize temporal shifts in transcriptomic programming responsible for differentiation from stem cells to neurons, we sampled parietal lobes of rhesus macaque at E40, E50, E70, E80, and E90, spanning the full period of prenatal neurogenesis. Single-cell RNA sequencing produced a transcriptomic atlas of developing parietal lobe in rhesus macaque neocortex. Identification of distinct cell types and neural stem cells emerging in different developmental stages revealed a terminally bifurcating trajectory from stem cells to neurons. Notably, deep-layer neurons appear in the early stages of neurogenesis, while upper-layer neurons appear later. While these different lineages show overlap in their differentiation program, cell fates are determined post-mitotically. Trajectories analysis from ventricular radial glia (vRGs) to outer radial glia (oRGs) revealed dynamic gene expression profiles and identified differential activation of BMP, FGF, and WNT signaling pathways between vRGs and oRGs. These results provide a comprehensive overview of the temporal patterns of gene expression leading to different fates of radial glial progenitors during neocortex layer formation.
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Prognostic biomarkers related to PANoptosis in esophageal cancer and their immune microenvironment: multi-omics analysis and therapeutic significance.
INTRODUCTION: Esophageal squamous cell carcinoma (ESCA) is one of the most common cancers worldwide. PANoptosis is an inflammatory programmed cell death pathway event regulated by the PANoptosome complex. Currently, there is limited research on the PANoptosis-related genes (PORGs) in ESCA. We aim to explore the prognostic biomarkers of PANoptosis in ESCA and their underlying mechanisms through comprehensive bioinformatics analysis. METHODS: In this study, we analyzed transcriptome and single-cell RNA sequencing (scRNA-seq) data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Weighted gene co-expression network analysis (WGCNA) and differential expression analysis were used to identify PANoptosis-related differentially expressed genes (POR-DEGs) in esophageal cancer. Hub genes were screened by univariate and multivariate Cox regression combined with machine learning models to construct diagnostic and prognostic models. The potential mechanisms of hub genes in esophageal cancer were preliminarily explored through gene immune infiltration and functional enrichment analysis. The differences and driving factors between high- and low-risk subgroups, as well as the regulation of PANoptosis by hub genes related to macrophages, were further revealed by immune assessment, drug sensitivity analysis, single-cell analysis, and molecular docking. Finally, the accuracy of model genes was verified by immunohistochemistry in clinical samples. RESULTS: Firstly, 74 PANoptosis-related differentially expressed genes (POR-DEGs) were identified for further analysis. Among the 74 genes, CCT6A, GMNN, and HSPB6 were identified as hub genes, and the constructed diagnostic and prognostic models were valuable. The high-risk subgroup showed poor prognosis, immune exhaustion, significant activation of pDC-LILRA4 cells, poor response to immunotherapy, and moderate sensitivity to chemotherapy. Further exploration of the immune regulatory mechanism of prognostic biomarkers revealed that the three hub genes, CCT6A, GMNN, and HSPB6, were closely related to the ESCA immune microenvironment. The CCT6A targeted by the traditional Chinese medicine component quercetin may inhibit PANoptosis by promoting the differentiation of Mono-CD14 cells into TAM-SPP1 macrophages. DISCUSSION: We constructed prognostic and diagnostic models using PANoptosis-related prognostic biomarkers, analyzed the differences and treatments between high-risk and low-risk groups, and revealed a new mechanism by which CCT6A may inhibit PANoptosis by promoting TAM-SPP1 differentiation, providing new targets and biomarkers for ESCA treatment.
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Expression of OLR1 gene on tumor-associated macrophages of head and neck squamous cell carcinoma, and its correlation with clinical outcome.
Head and neck squamous cell carcinoma (HNSCC) is one of the most heavily immune infiltrated human tumors, having distinct immune subtypes associated with different molecular characteristics and clinical outcomes. The tumor microenvironment (TME) of HNSCC which was dominated by tumor-associated macrophages (TAMs) had a relatively inferior prognosis. High levels of oxidized low-density lipoprotein receptor 1 (OLR1) expression are associated with more aggressive and metastatic characteristics in multiple cancers. However, the link between the OLR1 expression and immunosuppression of TME, and the molecular mechanisms which govern intratumoral TAMs behavior are unclear. Here, we performed the transcriptional analysis based on a single-cell RNA-sequencing (scRNA-seq) dataset of HNSCC, and found that the OLR1 expression was specifically enriched on the TAMs. Evaluation of protein expression within histologic sections of primary HNSCC patient samples showed a co-expression pattern of OLR1 and CD68 on macrophages. A total of 498 tumor samples of HNSCC patients from The Cancer Genome Atlas (TCGA) database were also analyzed. Remarkably, OLR1 expression was dramatically higher in HNSCC tissues than that in adjacent normal tissues, and the patients with high levels of OLR1 expression had significantly unfavorable overall survival (Hazard Ratio = 1.724, log-rank P-value = 0.0066) when compared to patients harboring low expression levels of OLR1. In summary, we reported that the specific expression of OLR1 on the TAMs was significantly correlated with poor survival outcomes, revealing that OLR1 could serve as a potential prognosis marker and promising target for immunotherapy in HNSCC.