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Impact of per- and polyfluoroalkyl substances on diabetic kidney disease.
PURPOSE: This study aims to elucidate the mechanistic role of Per- and Polyfluoroalkyl Substances (PFAS) in the pathogenesis and progression of diabetic kidney disease (DKD). METHODS: This study systematically evaluated the toxicity profiles of PFAS compounds utilizing PubChem, ProTox 3.0, and ChEMBL databases. Potential PFAS-related targets were predicted through SwissTargetPrediction and SuperPred platforms. Gene targets associated with DKD were compiled from the GeneCards and OMIM databases. Intersection analysis of PFAS and DKD-related targets was performed to identify candidate genes. A protein-protein interaction network was constructed using STRING to delineate hub targets. Functional enrichment analyses were subsequently conducted via DAVID to elucidate underlying biological processes and pathways. Validation of hub targets encompassed immunohistochemical staining, single-cell expression profiling, subcellular localization assays, and gene expression analyses using external datasets from the Human Protein Atlas (HPA) and Gene Expression Omnibus (GEO). Furthermore, correlations between immune cell infiltration and gene set enrichment analysis (GSEA) were performed to investigate potential mechanistic links. Finally, molecular docking simulations of PFAS compounds with hub proteins were executed using Discovery Studio and CDOCKER to predict binding interactions. RESULTS: A total of 424 PFAS-associated targets were identified, alongside 9,999 potential toxic targets related to DKD. KEGG pathway enrichment analysis revealed that PFAS toxicity in DKD is implicated in critical signaling pathways, including nitrogen metabolism, peroxisome proliferator-activated receptor (PPAR) signaling, endocrine resistance, insulin resistance, and AMP-activated protein kinase (AMPK) signaling. Hub targets identified comprised MMP9, BCL2, CYP3A43, ACE, HNF4A, HSP90AA1, AGTR1, MMP2, AGTR2, and HMGCR. GSEA further indicated that these hub targets may contribute to immune-mediated renal injury. Molecular docking simulations substantiated strong binding affinities between PFAS compounds and the identified hub proteins, supporting their potential mechanistic involvement. CONCLUSION: This study provides a theoretical framework for elucidating the toxic targets and underlying mechanisms through which PFAS contribute to the pathogenesis of DKD.
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Exploring the role of EBV in multiple sclerosis pathogenesis through EBV interactome.
BACKGROUND: Epstein-Barr virus (EBV) is a known risk factor for multiple sclerosis (MS), even though the underlying molecular mechanisms are unclear and engage multiple immune pathways. Furthermore, the ultimate role of EBV in MS pathogenesis is still elusive. In contrast, Cytomegalovirus (CMV) has been identified as a protective factor for MS. OBJECTIVES: This study aims to identify MS-associated genes that overlap with EBV interactome and to examine their expression in immune and glial cell subtypes. METHODS: We used P-HIPSTer, GWAS, and the Human Protein Atlas (HPA) to derive data on the EBV interactome, MS-associated genes and single-cell gene expression in immune and glial cells. The geneOverlap and dplyr R packages identified overlapping genes. A similar analysis was done for CMV and Adenovirus as negative control. Metascape and GTEx analyzed biological pathways and brain-level gene expression; transcriptomic analysis was performed on glial cells and peripheral blood in MS and controls. All the analyses performed in this study were generated using publicly available data sets. RESULTS: We identified a "core" group of 21 genes shared across EBV interactome, MS genes, and immune and glial cells (p<0.001). Pathway analysis revealed expected associations, such as immune system activation, and unforeseen results, like the prolactin signaling pathway. BCL2 in astrocytes, MINK1 in microglia were significantly upregulated while AHI1 was downregulated in MS compared to controls. CONCLUSIONS: Our findings offer novel insights into EBV and CMV interaction with immune and glial cells in MS, that may shed light on mechanisms involved in disease pathophysiology.
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Construction and validation of transcription‑factor‑based prognostic signature for TACE non‑response and characterization of tumor microenvironment infiltration in hepatocellular carcinoma.
Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Despite continuous development of treatment methods, overall survival rate of liver cancer is low. Transcatheter arterial chemoembolization (TACE) is a first-choice treatment for advanced liver cancer. Although it is generally effective, a number of patients do not benefit from it. Therefore, the present study was conducted to assess the response of patients following TACE. RNA-sequencing data and corresponding clinical information were extracted from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. Models were constructed using weighted gene co-expression network analysis and least absolute shrinkage and selection operator-Cox regression analysis based on TCGA-LIHC and GSE104580 cohorts. The receiver operating characteristic curve was used for evaluation. Immunoassay, half-maximal inhibitory concentration analysis of risk groups, genomic enrichment analysis and nomogram construction were also performed. The predictive models were validated at the single-cell level using single-cell databases. Finally, the present study examined the expression of TACE refractoriness-related TFs (TRTs) in TACE-resistant and non-resistant cell lines in vitro. A risk categorization approach was created based on screening of four TRTs. The patients were split into high- and low-risk groups. There were significant variations in immune cell infiltration, medication sensitivity and overall survival (OS) between patients in the high-risk and low-risk groups. Multivariate Cox regression analysis showed that the risk score was an independent prognostic factor for OS. In the single-cell gene set, risk score was a good indicator of tumor microenvironment (TME). Reverse transcription-quantitative PCR revealed that three high-risk TRTs were upregulated in TACE-resistant cells. Prognosis and TME status of liver cancer patients following TACE could be assessed using a predictive model based on transcription factor correlation. This predictive model provided a reliable and simplified method to guide the clinical treatment of HCC.
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Single-cell atlas of hepatitis C virus inoculated tree shrew liver reveals immune activation, metabolic reprogramming, and persistent inflammation.
BACKGROUND: Hepatitis C virus (HCV) remains a major global health challenge, largely due to the absence of robust animal models that recapitulate this disease, hindering mechanistic studies and vaccine development. This study employed tree shrews to determine the molecular profiles of distinct liver cell populations following HCV infection. METHODS: Tree shrews received intrahepatic injections of the HCV JFH1 strain and were analysed at two timepoints: 1 week post-inoculation (acute) and 111 weeks post-inoculation (long-term). Viral load was assessed up to 30 weeks. Liver pathology was assessed via haematoxylin and eosin (H&E) staining. Single-cell transcriptomic profiling was performed on liver tissues, while tree shrew primary hepatocytes and ITH6 hepatic cells, as well as human Huh7 cells, were used to characterise cellular changes following HCV infection. FINDINGS: Sixteen major cell types were identified in 157,298 liver cells across HCV-inoculated and control tree shrews. Acute inoculation triggered widespread induction of interferon-stimulated genes (ISGs) across all cell types, including the periportal ISGhigh hepatocyte subcluster, and concurrent reduction in metabolic gene expression in hepatocytes in vivo. Impaired glucose metabolism, as confirmed in HCV-exposed ITH6 cells, likely contributed to this metabolic shift. Erythroblasts were exclusively detected during acute inoculation and exhibited enhanced intercellular communication signatures. Among neutrophils, three distinct subclusters were identified, one of which displayed elevated expression of neutrophil extracellular trap (NET) markers and enhanced NET formation in inoculated livers. INTERPRETATION: This study provides a comprehensive single-cell transcriptomic landscape of HCV-inoculated tree shrew livers. These findings underscore the use of the tree shrew model for advancing mechanistic understanding of HCV pathogenesis, as well as its relevance for therapeutic and vaccine development. FUNDING: This work was supported by grants from National Natural Science Foundation of China (U1902215, U25A20646), National Key Research and Development Plan Program (2022YFF0710900), Key Project of the CAS "Light of West China" Program (xbzg-zdsys-202302), and Yunnan Province (202305AH340006, 202001AS070023).
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[Exploring the Role of PCDHGB4 in the Occurrence of Lung Squamous Cell Carcinoma Based on Bioinformatics Analysis].
BACKGROUND: Lung squamous cell carcinoma (LUSC) is a subtypes of non-small cell lung cancer (NSCLC). It has been reported that members of the protocadherin γ family can regulate tumor cell growth by inhibiting the Wnt signaling pathway. Protocadherin-gamma subfamily B4 (PCDHGB4) as a family member in LUSC was rarely reported. The aim of this study was to investigate the role and potential prognostic value of PCDHGB4 in the development of LUSC using bioinformatics methods. METHODS: The Cancer Genome Atlas (TCGA), cBioPortal and UALCAN databases were used to analyze the expression, prognosis, clinicopathological features, immune cell infiltration, immune regulatory genes, immune checkpoint inhibitors (ICIs), and methyltransferases of PCDHGB4 in LUSC. At the single cell level, we analyzed the clustering results of cell subtypes and the expression of PCDHGB4 in different immune cell subpopulations. In addition, we compared the promoter methylation levels of PCDHGB4 in LUSC tissues and normal tissues and performed protein-protein interaction and mutation analysis. Finally, enrichment analysis was performed based on the differentially expressed genes. RESULTS: Bioinformatics analysis results showed that the expression level of PCDHGB4 in LUSC tissues was lower than that in normal tissues. Survival analysis showed that increased PCDHGB4 expression was associated with poor prognosis. Single-cell sequencing analysis showed that PCDHGB4 was expressed in T cells, monocytes or macrophages, and dendritic cells. It was further found that PCDHGB4 played an important role in tumor immunity and confirmed that PCDHGB4 was associated with immune checkpoints, immune regulatory genes, and methyltransferases. Besides, enrichment analysis revealed that PCDHGB4 was involved in multiple cancer-related pathways. CONCLUSIONS: The expression of PCDHGB4 was low in LUSC. PCDHGB4 was related to the poor prognosis of patients, and PCDHGB4 was closely related to the infiltration and pathway of tumor immune cells. PCDHGB4 may be a potential prognostic marker and a new target for immunotherapy in LUSC.
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Single-cell landscape of human adipose tissue reveals THBS1 as a potential driver of fibro-inflammation in metabolic disease.
The cellular complexity of adipose tissue plays a critical role in the pathogenesis of metabolic disease; however, mechanisms underlying adipose dysfunction remain poorly understood. Here, we constructed a single-nucleus and bulk transcriptomic atlas of human visceral adipose tissues from an ethnically homogeneous cohort with defined metabolic states: lean with normal glucose tolerance, obesity, and obesity with type 2 diabetes. Single-nucleus RNA sequencing (snRNA-seq) revealed a fibro-inflammatory subpopulation of adipose stem cells and adipocytes characterized by high THBS1 expression, which were enriched in individuals with obesity and obesity with type 2 diabetes compared to lean controls. Through complementary in vitro (human primary ASCs, THP-1 macrophages, and Matrigel-captured mature adipocytes), ex vivo (mouse and human visceral adipose tissue explants), and in vivo (gain-of-function and antibody-mediated neutralization) experiments, we demonstrated that THBS1 promoted adipose fibrosis and inflammation via macrophage-mediated TGFβ activation, impairing adipogenesis and adipocyte function. Inhibition of THBS1 attenuated fibro-inflammatory features in metabolically dysfunctional adipose tissues. Moreover, THBS1 levels in plasma and adipocytes correlated with metabolic traits, including BMI and HbA1c. Collectively, our study provides a cellular atlas of human visceral adipose tissues across metabolic disease states and identifies THBS1 as a key pathogenic driver and potential therapeutic target.
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Mapping the Single-Cell Differentiation Landscape of Osteosarcoma.
PURPOSE: The genetic intratumoral heterogeneity observed in human osteosarcomas poses challenges for drug development and the study of cell fate, plasticity, and differentiation, which are processes linked to tumor grade, cell metastasis, and survival. EXPERIMENTAL DESIGN: To pinpoint errors in osteosarcoma differentiation, we transcriptionally profiled 31,527 cells from a tissue-engineered model that directs mesenchymal stem cells toward adipogenic and osteoblastic fates. Incorporating preexisting chondrocyte data, we applied trajectory analysis and non-negative matrix factorization to generate the first human mesenchymal differentiation atlas. RESULTS: This "roadmap" served as a reference to delineate the cellular composition of morphologically complex osteosarcoma tumors and quantify each cell's lineage commitment. Projecting a bulk RNA-sequencing osteosarcoma dataset onto this roadmap unveiled a correlation between a stem-like transcriptomic phenotype and poorer survival outcomes. CONCLUSIONS: Our study quantifies osteosarcoma differentiation and lineage, a prerequisite to better understanding lineage-specific differentiation bottlenecks that might someday be targeted therapeutically.
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Identification of the novel therapeutic target gene SLC12A9, which determines the prognosis of patients with colorectal cancer.
BACKGROUND: Feasible therapeutic targets need to be identified to overcome tumor heterogeneity and ameliorate therapeutic resistance. We explored the identification of oncogenes on Ch.7q, which is amplified ubiquitously in colorectal cancer (CRC). In this study, we focused on SLC12A9, which encodes a channel protein that regulates ion concentration inside and outside of the cell. MATERIALS AND METHODS: Expression and survival analyses of SLC12A9 were performed using reverse transcription quantitative polymerase chain reaction, The Cancer Genome Atlas dataset, and immunohistochemistry. A gene set enrichment analysis (GSEA) was performed to elucidate the correlation between SLC12A9 and gene sets associated with tumor progression. Subsequently, an in vitro proliferation assay was performed using SLC12A9-knockdown CRC cells. RESULTS: SLC12A9 was highly expressed in tumor cells, and its high expression was associated with a poor prognosis. The GSEA revealed an association with mTORC1 signaling. In the colony formation assay, SLC12A9 knockdown by siRNA suppressed the proliferative capacity of CRC cells. Public single-cell RNA sequencing data have revealed that SLC12A9 is derived from malignant epithelial cells in CRC tissues. CONCLUSION: Our results suggest that abundant SLC12A9 expression is associated with a poor prognosis due to the devastating growth of CRC cells, in part via the mTORC1 signaling pathway.
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Pan-cancer analysis: predictive role of TAP1 in cancer prognosis and response to immunotherapy.
BACKGROUND: Transporter associated with antigen processing 1 (TAP1) is a molecule involved in processing and presentation of major histocompatibility complex class I restricted antigens, including tumor-associated antigens. TAP1 participates in tumor immunity, and is aberrantly expressed in multiple cancer types; METHODS: Transcriptome profiles were obtained from The Cancer Genome Atlas and Genotype-Tissue Expression databases. Genetic alterations, protein distribution, and interaction information for TAP1 were downloaded from cBioPortal, Human Protein Atlas and Compartmentalized Protein-Protein Interaction, respectively. Single-cell analyses of TAP1 across cancers were conducted via the Tumor Immune Single-cell Hub website. Gene set enrichment analysis was employed to investigate TAP1-associated functional mechanisms and processes. Immune cell infiltration was explored using Tumor Immune Estimation Resource 2.0. Pan-cancer correlations between TAP1 expression and immunotherapy biomarkers were explored using the Spearman's correlation test. Associations with immunotherapy responses were also investigated using clinicopathological and prognostic information from cohorts of patients with cancer receiving immune checkpoint inhibitors. RESULTS: TAP1 expression was elevated in most cancer types and exhibited distinct prognostic value. Immune cells expressed more TAP1 than malignant cells within most tumors. TAP1 expression was significantly correlated with immune-related pathways, T-lymphocyte infiltration, and immunotherapeutic biomarkers. Clinical cohort validation revealed a significant correlation with immune therapeutic effects and verified the prognostic role of TAP1 in immunotherapy. Western blot assay indicated that TAP1 is upregulated in glioblastoma compared with adjacent normal brain tissues. CONCLUSION: TAP1 is a robust tumor prognostic biomarker and a novel predictor of clinical prognosis and immunotherapeutic responses in various cancer types.
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An Eight-Gene Metabolic Prognostic Signature in Head and Neck Squamous Cell Carcinoma: Cross-Cohort Evaluation, Single-Cell Analysis, and Preliminary Functional Evaluation of PYGL and G6PD.
BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is the most prevalent pathological subtype of head and neck malignancies. Although metabolic reprogramming contributes to malignant progression and adaptation within the tumor microenvironment in HNSCC, its biological and prognostic implications remain incompletely understood. OBJECTIVE: To develop and evaluate a metabolism-related prognostic score for head and neck squamous cell carcinoma (HNSCC) across multiple cohorts, identify its cellular sources at single-cell resolution, and perform preliminary in vitro functional evaluation of PYGL and G6PD. METHODS: Metabolism-related differentially expressed genes were screened in The Cancer Genome Atlas Head and Neck Squamous Cell Carcinoma cohort (TCGA-HNSC). A total of 506 patients with survival data were divided into a training set (n = 355) and an internal test set (n = 151) at a 7:3 ratio. Training-only repeated nested cross-validation benchmarked 126 algorithmic configurations. Survival-SVM had the highest mean out-of-fold C-index, whereas an eight-gene LASSO + StepCox model was retained for interpretability and cross-cohort transportability. External cohort evaluation of overall survival (OS) was performed in GSE65858 (n = 270), while GSE117973 (n = 77), which used disease-specific survival (DSS), was treated as an exploratory cohort. By integrating 54,163 single cells from the GSE150321 and GSE172577 datasets, analyses, including inferCNV, 12 predefined metabolic modules, CellChat, and scTenifoldKnk, were conducted to investigate the cellular origins of the risk score and candidate regulatory networks; additionally, PYGL- and G6PD-targeting siRNAs were evaluated for their effects on target protein expression and wound closure in vitro. RESULTS: We developed a metabolic prognostic model that included HPRT1, ADA, PYGL, P4HA1, LDHA, G6PD, NT5E, and FTH1. The concordance indices (C-indices) were 0.638 in the TCGA training set, 0.651 in the internal test set, and 0.604 in GSE65858. In a complete-case clinical cohort of 473 TCGA patients, a model combining the risk score with age, sex, and T, N, and M categories achieved C-indices of 0.693 in TCGA and 0.677 in GSE65858. The corresponding 3-year areas under the receiver operating characteristic curve (AUCs) were 0.735 and 0.700. Single-cell analysis showed that the eight genes were distributed across malignant epithelial, proliferating, immune, endothelial, and stromal populations. The 16,240 copy number variation-high (CNV-high) epithelial cells had higher eight-gene scores and higher transcriptional scores for glycogen metabolism, the pentose phosphate pathway, glycolysis, and redox-related programs. Small interfering RNA (siRNA)-mediated silencing of G6PD or PYGL reduced relative wound closure at 12 h in TU686 and SCC25 cells. CONCLUSION: The eight-gene metabolic score provided moderate and cohort-dependent prognostic discrimination in the TCGA internal test set and GSE65858. Its bulk transcriptomic signal arose from several cell populations. Silencing PYGL or G6PD reduced target protein expression and wound closure. These findings provide preliminary in vitro evidence linking both genes to a migratory phenotype in HNSCC.