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Expression of PDZ domain-containing proteins is correlated with prognosis and immune infiltration in hepatocellular carcinoma.
BACKGROUND: Hepatocellular carcinoma (HCC)-a predominant type of primary liver cancer-poses a significant global health threat with high incidence and mortality rates. Despite advances in treatment modalities, including surgery, chemotherapy, and immunotherapy, HCC exhibits high relapse rates and low long-term survival, necessitating the identification of novel prognostic markers and treatment targets. This study aims to develop a prognostic model centered on the PDZ domain by identifying key PDZ proteins associated with HCC through bioinformatics analysis of large-scale public datasets, in order to improve prognosis prediction and inform therapeutic strategies. METHODS: Differentially expressed PDZ proteins (DEPs) in HCC were identified through RNA sequencing (RNA-seq) analysis from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. Cox regression and random survival forest (RSF) modeling were employed to construct a prognostic model and evaluate the prognostic potential of DEPs. Subsequently, the correlation of DEP-related risk scores with immune cell infiltration and genetic variations was analyzed separately. Quantitative polymerase chain reaction (qPCR) was conducted to validate the expression of key DEPs in HCC tissues. RESULTS: A prognostic model for HCC constructed using nine key DEPs demonstrated reliable predictive performance across 1-, 3-, and 5-year survival rates. DEP-related risk scores were significantly associated with immune cell infiltration, with high-risk groups exhibiting an increase in pro-tumor immune cells and a decrease in anti-tumor immune cells. Genetic variations, including single nucleotide polymorphisms (SNPs) and copy number variations (CNVs), also differed between high- and low-risk groups. qPCR validation confirmed that the expression of SNX27, DLG5, PARD3, and RHPN1 was significantly upregulated in HCC tissues. CONCLUSIONS: PDZ proteins may serve as prognostic markers and therapeutic targets in HCC. DEP-related risk scores offer insights into immune infiltration patterns and treatment responsiveness, providing a foundation for future HCC research and development of precision medicine.
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Multi-omics and network toxicology prioritize ADAMTS13 as a candidate gene computationally linked to TDCPP targets in hepatocellular carcinoma.
BACKGROUND: Tris(1,3-dichloro-2-propyl) phosphate (TDCPP), a widely used organophosphate flame retardant, has been increasingly recognized as a potential environmental risk factor for human cancers. However, its potential association with hepatocellular carcinoma (HCC) and the underlying molecular mechanisms remain largely unclear. METHODS: An integrative network toxicology and multi-omics approach was employed to explore the potential computational link between TDCPP‑related targets and HCC transcriptomic changes. TDCPP-associated targets were collected from public databases and intersected with differentially expressed genes from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network analysis (WGCNA) and machine learning algorithms were applied to identify candidate genes. Functional enrichment, immune infiltration, single-cell RNA sequencing, and molecular docking analyses were subsequently performed. RESULTS: A total of six candidate genes were identified, among which ADAMTS13 exhibited strong discriminative performance in the predictive models. Functional analyses suggested that these genes may be involved in pathways related to extracellular matrix organization, immune regulation, and tumor microenvironment remodeling. Immune infiltration and single-cell analyses indicated a potential association between ADAMTS13 expression and tumor microenvironment characteristics. Molecular docking analysis further suggested a potential interaction between TDCPP and ADAMTS13 at the structural level. CONCLUSIONS: These findings suggest a computational association between TDCPP-related targets and HCC transcriptomic changes, with ADAMTS13 emerging as a computationally prioritized candidate gene for further experimental investigation. This study provides a hypothesis-generating framework for understanding possible molecular links between environmental contaminants and hepatocarcinogenesis, but does not establish causality or confirm actual TDCPP exposure in the analyzed patient cohorts.
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Vimentin promotes glioma progression and maintains glioma cell resistance to oxidative phosphorylation inhibition.
PURPOSE: Glioma has been demonstrated as one of the most malignant intracranial tumors and currently there is no effective treatment. Based on our previous RNA-sequencing data for oxidative phosphorylation (OXPHOS)-inhibition resistant and OXPHOS-inhibition sensitive cancer cells, we found that vimentin (VIM) is highly expressed in the OXPHOS-inhibition resistant cancer cells, especially in glioma cancer cells. Further study of VIM in the literature indicates that it plays important roles in cancer progression, immunotherapy suppression, cancer stemness and drug resistance. However, its role in glioma remains elusive. This study aims to decipher the role of VIM in glioma, especially its role in OXPHOS-inhibition sensitivity, which may provide a promising therapeutic target for glioma treatment. METHODS: The expression of VIM in glioma and the normal tissue has been obtained from The Cancer Genome Atlas (TCGA) database, and further validated in Human Protein Atlas (HPA) and Chinese Glioma Genome Atlas (CGGA). And the single-cell sequencing data was obtained from TISCH2. The immune infiltration was calculated via Tumor Immune Estimation Resource (TIMER), Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data (ESTIMATE) and ssGSEA, and the Immunophenoscore (IPS) was calculated via R package. The differentiated expressed genes were analyzed including GO/KEGG and Gene Set Enrichment Analysis (GSEA) between the VIM-high and -low groups. The methylation of VIM was checked at the EWAS and Methsurv. The correlation between VIM expression and cancer stemness was obtained from SangerBox. We also employed DepMap data and verified the role of VIM by knocking down it in VIM-high glioma cell and over-expressing it in VIM-low glioma cells to check the cell viability. RESULTS: Vim is highly expressed in the glioma patients compared to normal samples and its high expression negatively correlates with patients' survival. The DNA methylation in VIM promoters in glioma patients is lower than that in the normal samples. High VIM expression positively correlates with the immune infiltration and tumor progression. Furthermore, Vim is expressed high in the OXPHOS-inhibition glioma cancer cells and low in the OXPHOS-inhibition sensitive ones and its expression maintains the OXPHOS-inhibition resistance. CONCLUSIONS: In conclusion, we comprehensively deciphered the role of VIM in the progression of glioma and its clinical outcomes. Thus provide new insights into targeting VIM in glioma cancer immunotherapy in combination with the current treatment.
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Integrative analysis of the bladder cancer from a cell cycle NCAM1 perspective at both single cell and bulk resolution.
INTRODUCTION: Bladder cancer (BLCA) is a prevalent and deadly form of urinary cancer, and there is a need for effective therapies, particularly for muscle-invasive bladder cancer (MIBC). Cell cycle inhibitors show promise in restoring control of the cell cycle in BLCA cells, but their clinical prognosis evaluation is limited. METHODS: Transcriptome and scRNA-seq data were collected from the Cancer Genome Atlas Program (TCGA)-BLCA and GSE190888 cohort, respectively. R software and the Seurat package were used for data analysis, including cell quality control, dimensionality reduction, and identification of differentially expressed genes. Genes related to the cell cycle were obtained from the genecards website, and a protein-protein interaction network analysis was performed using cytoscape software. Functional enrichment analysis, immune infiltration analysis, drug sensitivity analysis, and molecular docking were conducted using various tools and packages. BLCA cell lines were cultured and transfected for in vitro experimental assays, including RT-qPCR analysis, and CCK-8 cell viability assays. RESULTS: We identified 32 genes as independent risk or protective factors for BLCA prediction. Functional enrichment analysis revealed their involvement in cell cycle regulation, apoptosis, and various signaling pathways. Using these genes, we developed a nomogram for predicting BLCA survival, which displayed high prognosis stratification efficacy in BLCA patients. Four cell cycle associated key genes identified, including NCAM1, HBB, CKD6, and CTLA4. We also identified the main cell types in BLCA patients and investigated the functional differences between epithelial cells based on their expression levels of key genes. Furthermore, we observed a high positive correlative relationship between the infiltration of cancer-associated fibroblasts and the risk score value. Finally, we conducted in vitro experiments to demonstrate the suppressive role of NCAM1 in BLCA cell proliferation. CONCLUSION: These findings suggest that cell cycle associated genes could serve as potential biomarkers for predicting BLCA prognosis and may represent therapeutic targets for the development of more effective therapies. Hopefully, these findings provide valuable insights into the molecular mechanisms and potential therapeutic targets in BLCA from the perspective of cell cycle. Moreover, NCAM1 was a novel cell proliferation suppressor in the BLCA carcinogenesis.
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Childhood-onset lupus nephritis is characterized by complex interactions between kidney stroma and infiltrating immune cells.
Children with systemic lupus erythematosus (SLE) are at increased risk of developing kidney disease, termed childhood-onset lupus nephritis (cLN). Single-cell transcriptomics of dissociated kidney tissue has advanced our understanding of LN pathogenesis, but loss of spatial resolution prevents interrogation of in situ cellular interactions. Using a technical advance in spatial transcriptomics, we generated a spatially resolved, single-cell resolution atlas of kidney tissue from eight patients with cLN and four control individuals. Annotated cells were assigned to 30 reference cell types, including major kidney subsets and infiltrating immune cells. Analysis of spatial distribution demonstrated that individual immune lineages localized to specific regions in cLN kidneys, including myeloid cells that trafficked to inflamed glomeruli and B cells that clustered within tubulointerstitial immune hotspots. Gene expression varied as a function of tissue location, demonstrating how incorporation of spatial data can provide new insights into the immunopathogenesis of SLE. Alterations in immune phenotypes were accompanied by parallel changes in gene expression by resident kidney stromal cells. However, there was little correlation between histologic scoring of cLN disease activity and glomerular cell transcriptional signatures at the level of individual glomeruli. Last, we identified modules of spatially correlated gene expression with predicted roles in induction of inflammation and the development of tubulointerstitial fibrosis. Single-cell spatial transcriptomics allowed insights into the molecular heterogeneity of cLN, paving the way toward more targeted and personalized treatment approaches.
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Increased Smoothened signaling promotes kidney fibrosis through inhibiting autophagy in fibroblasts.
INTRODUCTION: Kidney fibrosis progressively induces kidney function loss, leading to kidney failure. Myofibroblast transition from fibroblast is significantly involved in the development of kidney fibrosis. Previous studies revealed that sonic hedgehog (Shh), the upstream ligand of Smoothened (Smo) receptor signaling, contributes to kidney fibrosis. However, the role of Smo in fibroblast activation remains unclear. METHODS: Here, fibroblast-specific Smo and β-catenin knockout mice were generated, primary kidney fibroblasts were isolated and cultured. Single-nucleus (snRNA-seq) plus bulk RNA sequencing were performed. Autophagy capacities, including autophagy flux, autophagy vacuoles, and autophagy-related gene expression, were assessed. RESULTS: From snRNA-seq data of the human atlas combined with bulk RNA sequencing of primary mouse kidney fibroblasts, we discovered Smo was upregulated in kidney fibroblasts in chronic kidney disease (ureteral obstruction, ischemia/reperfusion, Adriamycin nephrosis and 5/6th nephrectomy models). This was accompanied by substantially diminished autophagic capacity. Shh stimulation or ectopic Smo deactivated autophagy, exaggerated myofibroblast proliferation and activation in the fibroblasts. These effects were further enhanced in autophagosome protein ATG5 knockout fibroblasts. Moreover, Smo, through the β-arrestin 1/Src/β-catenin pathway, induced the transcription of mammalian target of rapamycin. This mediated autophagy suppression in fibroblasts, leading to myofibroblast activation and kidney fibrosis. Fibroblast-specific knockout of Smo or β-catenin greatly preserves autophagy capacity and ameliorates kidney fibrosis. Notably, NVP-LDE225, a specific Smo antagonist, effectively restored fibroblast autophagy and retarded kidney fibrotic lesion formation. CONCLUSIONS: Our study defines a prominent mechanism of myofibroblast activation and supplies a potential avenue for targeting fibroblast Smo to treat chronic kidney disease.
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Investigating the prognostic value of constructing disulfidptosis-related gene models for lung adenocarcinoma patients.
OBJECTIVE: Disulfidptosis is a novel mode of cell death, a programmed mode of intracellular disulfide accumulation due to solute carrier family 7 member 11 (SLC7A11)-mediated abnormalities in the cell membrane cystine transport system. Numerous studies have confirmed the prominent role played by SLC7A11 in tumors, but the involvement of SLC7A11 as an important mediator of disulfidptosis in the death process of lung adenocarcinoma cells remains unclear. MATERIALS AND METHODS: We obtained 4,107 SLC7A11-related genes and analyzed them using a total of 1,040 lung adenocarcinoma transcriptome sequencing data from The Cancer Genome Atlas (TCGA) cohort and GEO (Gene Expression Omnibus) cohort and 991 relevant clinical data. First, we screened for differential genes and identified molecular subtypes for assessing characteristic differences between lung adenocarcinoma subtypes under the influence of SLC7A11-associated genes. Then, risk score models were constructed to assess the prognosis, immune infiltration, tumor microenvironment, and drug treatment effects in lung adenocarcinoma patients. Finally, we also analyzed the distribution of cell types and expression of characteristic genes within the tumor using a single-cell database. In addition, relevant drug sensitivities were predicted. RESULTS: We screened 956 genes with significant differences and identified 2 molecular subtypes and found significant differences in their prognosis and that subtype B had a significantly better survival prognosis than subtype A. In addition, we found that pathways associated with cell proliferation division and DNA repair were enriched in the high-risk type A samples. Finally, we constructed a robust risk-scoring system, and our risk analysis revealed a general reduction of various immune cell components and tumor stromal components in the immune microenvironment of high-risk lung adenocarcinoma and a distinct immune infiltration pattern of immune cells, which was associated with a lower survival rate. CONCLUSIONS: Our comprehensive analysis of SLC7A11-related genes suggests that disulfidptosis has a potential value in the tumor microenvironment, immunity, clinical outcome, and prognosis of lung adenocarcinoma. These findings may increase our understanding of disulfidptosis as a novel cell death paradigm and provide ideas for assessing the prognosis of lung adenocarcinoma and developing new diagnostic and therapeutic strategies.
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Prognosis of colorectal cancer, prognostic index of immunogenic cell death associated genes in response to immunotherapy, and potential therapeutic effects of ferroptosis inducers.
INTRODUCTION: This study leverages bioinformatics and medical big data to integrate datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), providing a comprehensive overview of immunogenic cell death (ICD)-related gene expression in colorectal cancer (CRC). The research aims to elucidate the molecular pathways and gene networks associated with ICD in CRC, with a focus on the therapeutic potential of cell death inducers, including ferroptosis agents, and their implications for precision medicine. METHODS: We conducted differential expression analysis and utilized advanced bioinformatic techniques to analyze ICD-related gene expression in CRC tissues. Unsupervised consensus clustering was applied to categorize CRC patients into distinct ICD-associated subtypes, followed by an in-depth immune microenvironment analysis and single-cell RNA sequencing to investigate immune responses and cell infiltration patterns. Experimental validation was performed to assess the impact of cell death inducers on ICD gene expression and their interaction with ferroptosis inducers in combination with other clinical drugs. RESULTS: Distinct ICD gene expression profiles were identified in CRC tissues, revealing molecular pathways and intricate gene networks. Unsupervised consensus clustering refined the CRC cohort into unique ICD-associated subtypes, each characterized by distinct clinical and immunological features. Immune microenvironment analysis and single-cell RNA sequencing revealed significant variations in immune responses and cell infiltration patterns across these subtypes. Experimental validation confirmed that cell death inducers directly affect ICD gene expression, highlighting their therapeutic potential. Additionally, combinatorial therapies with ferroptosis inducers and clinical drugs were shown to influence drug sensitivity and resistance in CRC. DISCUSSION: Our findings underscore the importance of ICD-related genes in CRC prognosis and therapeutic targeting. The study provides actionable insights into the efficacy of cell death-inducing therapies, particularly ferroptosis inducers, and their regulatory mechanisms in CRC. These discoveries support the development of precision medicine strategies targeting ICD genes and offer valuable guidance for translating these therapies into clinical practice, with the potential to enhance CRC treatment outcomes and patient survival.
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Integrative mapping of human CD8+ T cells in inflammation and cancer.
CD8+ T cells exhibit remarkable phenotypic diversity in inflammation and cancer. However, a comprehensive understanding of their clonal landscape and dynamics remains elusive. Here we introduce scAtlasVAE, a deep-learning-based model for the integration of large-scale single-cell RNA sequencing data and cross-atlas comparisons. scAtlasVAE has enabled us to construct an extensive human CD8+ T cell atlas, comprising 1,151,678 cells from 961 samples across 68 studies and 42 disease conditions, with paired T cell receptor information. Through incorporating information in T cell receptor clonal expansion and sharing, we have successfully established connections between distinct cell subtypes and shed light on their phenotypic and functional transitions. Notably, our approach characterizes three distinct exhausted T cell subtypes and reveals diverse transcriptome and clonal sharing patterns in autoimmune and immune-related adverse event inflammation. Furthermore, scAtlasVAE facilitates the automatic annotation of CD8+ T cell subtypes in query single-cell RNA sequencing datasets, enabling unbiased and scalable analyses. In conclusion, our work presents a comprehensive single-cell reference and computational framework for CD8+ T cell research.
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Single-cell atlas of hepatic cellular plasticity and immune niche reprogramming in liver cirrhosis.
BACKGROUND: Cirrhosis is a severe liver disease characterized by inflammation, fibrosis, and immune dysregulation. This study exploits publicly available single-cell sequencing datasets to decipher disease-relevant specific immune cell subtypes, their gene expression profiles and altered transcription factor activity in cirrhosis, aiming to understand their roles in disease onset and progression. METHODS: To investigate the dynamic changes and underlying mechanisms of immune cells in cirrhosis, we employed a comprehensive bioinformatics approach integrating several advanced tools and analytical methods. Single-cell RNA sequencing data were processed and analyzed using Seurat for cell clustering and annotation. Monocle was used for pseudotime trajectory analysis to explore cellular differentiation pathways. CellChat enabled the assessment of cell‒cell communication networks among immune populations. Additionally, we conducted single-cell regulatory network inference to identify key transcriptional regulators. Immune response enrichment analysis (IREA) was performed to evaluate immune-related functional pathways, providing deeper insights into the immune landscape and disease progression in cirrhosis. RESULTS: We analyzed 35,017 cells, identifying 21 clusters and 12 major immune cell types. Macrophages, CD4+ T cells, and NK cells showed notable shifts in proportion in cirrhosis, suggesting key roles in disease progression. Pseudotime analysis revealed core macrophage and CD4+ T-cell subpopulations linked to cirrhosis. Functional analysis showed enrichment of IFN-α, IFN-β, and IL-1β in cirrhotic immune cells, primarily regulated by ETS2 and THRA. Fibroblast-mediated intercellular communication was enhanced, especially via increased macrophage migration inhibitory factor (MIF) signaling with B cells, indicating potential therapeutic targets in cytokine pathways and transcriptional regulation. CONCLUSION: The analysis revealed three key axes influencing disease-related immune regulation: TNF-α/ETS2-driven polarization of macrophages toward a Mac-d phenotype, IL-1α/β/THRA-associated polarization of CD4+ T cells toward a T4-c phenotype, and enhancement of the fibroblast-to-B-cell MIF signaling axis. This network offers valuable insights and potential therapeutic targets for advancing cirrhosis research and clinical treatment.