Браузер не даёт сохранять данные (например, приватный режим): закладки пропадут после закрытия вкладки.
Поиск статей PubMed
Ключевые слова, автор, журнал, годы — результаты из PubMed, аннотации с переводом на русский, закладки в браузере.
Найдено: 4 945
Страница 466 из 495-
Integrative genome-wide analysis unveils the genetic landscape of gallstone disease and highlights novel loci with therapeutic potential.
OBJECTIVE: Gallstone disease (GD) is a common gastrointestinal disorder with a significant genetic component. Despite known risk factors, the genetic basis of GD remains incompletely understood. We aimed to identify novel genetic loci associated with GD, explore their clinical implications and investigate their therapeutic potential. METHODS: We conducted a genome-wide association study from the UK Biobank followed by a meta-analysis, integrating summary statistics from the FinnGen R11, with further replication from Biobank Japan. Using systematic bioinformatic approaches, we performed gene prioritisation, colocalisation analysis, transcriptome-wide association study, Mendelian randomisations, cross-trait genetic correlations, phenome-wide association study, clinical investigations and gene-environment interactions by leveraging data from the FinnGen, Genotype-Tissue Expression project and Liver Cell Atlas single-cell transcriptomics data set. RESULTS: Our study highlighted novel susceptibility loci near candidate genes (ie, UGT1A4, FADS1/3) associated with GD, expanding the known genetic landscape. Functional annotation and colocalisation analysis implicated that the independent variants are involved in various hepatocyte functions, including bile secretion, cellular glucuronidation and cholesterol gallstone pathway. Mendelian randomisation established causal relationships between the level of unsaturated fatty acids and GD risk. We also demonstrated the implications of indirect bilirubin level in GD risk stratification and the protective effect of oily fish intake in genetically susceptible individuals. CONCLUSIONS: This study provides new insights into the genetic basis of GD and highlights the role of hepatocytes in GD pathogenesis. These findings have implications for the personalised prevention strategies and new therapeutic interventions in individuals predisposed to GD.
-
Pan-Cancer Analysis of a Depression-Related Gene Signature Identifies an Immunosuppressive Tumor Microenvironment and Links to Immunotherapy Response in Breast Cancer.
BACKGROUND: Depression has been increasingly associated with cancer progression and patient outcomes, yet its molecular and immunological correlates within tumors remain incompletely understood. This study aimed to investigate depression-associated gene signature across cancers and evaluate their relationship with tumor biology, immune microenvironment, and clinical outcomes, with a focus on breast cancer. METHODS: A depression-related gene signature comprising 382 genes was obtained from the Molecular Signatures Database and used to compute a DScore via single-sample gene set enrichment analysis (ssGSEA) across over 10,000 tumor samples from 33 cancer types in The Cancer Genome Atlas (TCGA). Tumor microenvironment features were assessed using ESTIMATE and CIBERSORT, and cell-type-specific patterns were evaluated using single-cell RNA sequencing. CACNA1H was validated using qPCR and IHC in breast cancer samples. RESULTS: DScore exhibited tissue-specific patterns across cancers and was elevated in several tumor types, including gastrointestinal, brain, renal, and endocrine malignancies. Higher DScore was associated with older age, advanced stage, and poorer survival across multiple malignancies, including breast, ovarian, uterine, and lung cancers, whereas inverse associations with survival were observed in selected brain, kidney, and endocrine cancers. Higher DScore was further associated with genomic instability, an immunosuppressive tumor microenvironment (TME), and poorer survival across multiple cancers, particularly in breast and ovarian cancers. In breast cancer, this phenotype was characterized by monocytic-lineage enrichment, increased M2 macrophages, and reduced CD8⁺ T-cell infiltration. Consistent with these findings, higher DScore was associated with reduced benefit from immune checkpoint therapy in breast and bladder cancers, with non-responders exhibiting higher DScore predominantly enriched in monocytic-lineage cells. CACNA1H was identified as a depression-related gene correlated with poor prognosis in breast cancer and was validated in independent cohorts. CONCLUSION: Depression-associated gene expression patterns are linked to tumor biology and immune features across cancers, with particularly strong relevance in breast cancer. These findings highlight the need for further research into how psychological, molecular, and immune factors interact in cancer progression and treatment response.
-
UPR-CEBPB-MIF Signaling Links to Macrophage Polarization and an Immunosuppressive Tumor Microenvironment in Clear Cell Renal Cell Carcinoma.
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) exhibits marked metabolic reprogramming, and the unfolded protein response (UPR) plays a crucial role in stress adaptation and immune regulation; however, its underlying mechanisms remain unclear. METHODS: Multi-omics data from The Cancer Genome Atlas (TCGA) program, Gene Expression Omnibus (GEO), and ArrayExpress were integrated, and UPR key genes were identified using an autoencoder combined with XGBoost. ConsensusClusterPlus and Weighted Gene Co-expression Network Analysis (WGCNA) were applied to determine the intersection genes of UPR-WGCNA-macrophage (UWMG). A prognostic model was then constructed using least absolute shrinkage and selection operator-Cox regression and validated across multiple cohorts. Single-cell transcriptome analysis was used to map UPR activity, trace myeloid differentiation paths, and examine CellChat-based communication patterns, aiming to clarify how UPR signaling connects to immune polarization. RESULTS: In the metabolic model, the UPR pathway showed the strongest contribution, and its activity was mainly observed in macrophages. From 17 UWMGs, a five-gene prognostic model (CEBPB, PLAUR, ARHGAP24, SNHG8, and ZBTB16) was developed and performed consistently across multiple independent cohorts. The high-risk group exhibited concurrent features of immune activation and suppression. Communication analysis revealed that tumor cells with high CEBPB expression exhibited enhanced MIF-CXCR4 signaling and were associated with macrophage M2-like polarization and an immunosuppressive microenvironment. CONCLUSIONS: The UPR-CEBPB-MIF signaling axis is associated with macrophage polarization and an immunosuppressive immune microenvironment in ccRCC. The proposed multi-omics model demonstrates stable prognostic value and provides potential targets for optimizing immunotherapy.
-
PLCH1 overexpression promotes breast cancer progression and predicts poor prognosis through the ERK1/2-EGR1 axis.
BACKGROUND: Phospholipase C η1 (PLCH1), a member of the phospholipase C superfamily, has been implicated in the development of multiple cancers. However, its specific role in breast cancer progression, its association with clinicopathological features, and its prognostic significance remain unclear. METHODS: PLCH1 expression was analyzed across multiple tumor types using the TNMplot database, which integrates RNA-seq, microarray, and normalized data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO), encompassing 40,442 tumor and 15,648 normal samples. Differential expression analysis was performed using boxplots and statistical tests to assess significance. DNA methylation and survival analyses were conducted using TCGA data, with Kaplan-Meier curves and Cox regression to evaluate prognostic value. Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, were performed on differentially expressed genes using the clusterProfiler package. Mutation analyses were conducted using mutation annotation format (MAF) files, and pathway activities were correlated with PLCH1 expression via single-sample GSEA (ssGSEA). Experimental validation included immunohistochemistry (IHC) on 100 breast invasive ductal carcinoma samples, real-time quantitative PCR (RT-qPCR), and Western blotting. PLCH1 knockdown functional studies assessed cell proliferation and signaling pathways. RESULTS: PLCH1 was significantly overexpressed in various cancers, including breast cancer, compared to normal tissues. PLCH1 expression was strongly correlated with the expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) in breast cancer tissues, further linking PLCH1 to poor prognosis and adverse patient outcomes. Functional studies revealed that PLCH1 was highly expressed in breast cancer cell lines, and PLCH1 knockdown significantly inhibited cell proliferation, induced cell cycle arrest, and reduced cyclin-dependent kinase 1 (CDK1) expression in BT-474 cells. Mechanistically, PLCH1 silencing downregulated early growth response 1 (EGR1) expression by suppressing the extracellular signal-regulated kinases 1 and 2 (ERK1/2) signaling pathway, impairing tumor cell proliferation. CONCLUSIONS: PLCH1 was overexpressed in breast cancer and was associated with worse patient outcomes. Its role in promoting cell proliferation via the ERK1/2-EGR1 axis highlighted PLCH1 as a potential therapeutic target for breast cancer. These findings offer new insights into the molecular mechanisms underlying breast cancer progression and suggest promising avenues for targeted therapy development.
-
Mechanistic study of glutamine metabolic reprogramming driving non-small cell lung cancer progression via the FGF17-FGFR4 axis mediating epithelial-mesenchymal transition.
INTRODUCTION: The reprogramming of glutamine metabolism holds a pivotal position in the energy provision and biosynthesis of tumors. However, the regulatory mechanism of this phenomenon in non-small cell lung cancer (NSCLC) is still not well-understood. NSCLC is a type of malignancy that has a high incidence and mortality rate globally. There is an urgent need to elucidate the role of glutamine metabolism in its pathological mechanism. This clarification may provide theoretical guidance for developing new therapeutic approaches. METHODS: Core targets of glutamine metabolism were screened by integrating single-cell transcriptomic and RNA sequencing data from public databases. Target expression was validated in clinical samples by immunohistochemistry (IHC) and Western blot (WB), and its association with clinical features was analyzed. Lentiviral gene silencing was employed to establish glutamine-deprived cell models and xenograft mouse models. To evaluate the effects of the target on cell proliferation, redox balance, and migratory/invasive behavior in cell culture and animal models, we utilized Transwell assays, colony formation assays, redox detection kits, and Seahorse metabolic flux analysis. Subsequently, WB and IHC served to elucidate the downstream pathways and potential synergistic effects of the drugs. RESULTS: Analysis of the single-cell atlas revealed a marked increase in epithelial (Epi) cell populations in the tumor milieu of NSCLC. By integrating weighted gene co-expression network analysis (WGCNA) with RNA sequencing, fibroblast growth factor 17 (FGF17) was pinpointed as a crucial regulatory factor. High FGF17 expression showed a strong association with poor prognosis in patient (p = 0.0078). Consistent clinical data further demonstrated that FGF17 upregulation was associated with higher TNM stages and the presence of lymph node metastasis. Functional and mechanistic analyses revealed that silencing FGF17 suppressed the FGFR4/MEK5/ERK5 signaling cascade, disturbed NRF2-dependent redox homeostasis, and consequently impaired epithelial-mesenchymal transition (EMT), leading to a marked reduction in cancer cell motility and invasiveness. In vivo, targeting FGF17 was shown to synergistically enhance cisplatin antitumor activity and reverse the EMT phenotype. CONCLUSION: As a critical driver of glutamine metabolic reprogramming, FGF17-activated under conditions of GLUL overexpression-stimulates the FGFR4/MEK5/ERK5/NRF2 signaling cascade to maintain redox homeostasis and promote invasion, thereby accelerating NSCLC progression. Targeted intervention of the pathway reverses malignant phenotypes and enhances chemosensitivity. These findings highlight FGF17 as a potential therapeutic target for NSCLC and provide new insights into tumor metabolism and EMT, thereby may paving the way for novel combination therapies.
-
Integrated multi-omics analysis reveals folate metabolism-related genes as prognostic markers and therapeutic targets in clear cell renal cell carcinoma.
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is an aggressive tumor with high metastatic potential and therapeutic resistance, yet the role of folate metabolism in its pathogenesis and immune evasion remains unclear. This study aims to develop and validate a folate metabolism-related gene (FMRG) scoring system to stratify patients by prognostic risk and immune phenotypes, and to explore the functional role of key FMRGs in ccRCC progression. METHODS: Using transcriptomic and clinical data from The Cancer Genome Atlas (TCGA), we developed a folate metabolism-related gene (FMRG) scoring system via integrative machine learning and validated it in an external cohort. We analyzed associations of the FMRG score with clinicopathological features, biological pathways, immune infiltration, therapeutic responsiveness, and drug sensitivity. Single-cell RNA sequencing and spatial transcriptomics mapped candidate gene expression, and in vitro experiments validated the functional role of NGF. RESULTS: A ten-gene prognostic model based on the FMRG score stratified ccRCC patients into groups with distinct clinical outcomes, immune profiles, and therapeutic responses. NGF was upregulated in ccRCC, with heterogeneous spatial expression. Functional assays showed that NGF enhances proliferation, migration, and invasion. CONCLUSIONS: This folate metabolism-based scoring framework facilitates prognostic stratification, tumor microenvironment characterization, and prediction of immunotherapy response in ccRCC. NGF is identified as a functional mediator of tumor progression, offering potential therapeutic targets and insights into metabolic-immune crosstalk.
-
High RSPO3 protein expression serves as an independent poor prognostic factor and promotes malignant progression in breast cancer.
OBJECTIVE: To elucidate the expression pattern, clinical prognostic significance, and distribution characteristics of R-spondin 3 (RSPO3) within the tumor microenvironment (TME) of breast cancer (BC), to observe its effects on the malignant biological behaviors of MCF-7 cells, and to explore the possible mechanisms underlying its function. METHODS: Integrated mRNA expression analysis was performed across multiple cohorts using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and validated by quantitative reverse transcription polymerase chain reaction (qRT PCR) in clinical samples. Immunohistochemistry (IHC) was used to detect RSPO3 protein expression in breast cancer tissue microarrays (TMAs), and the results were combined with survival data to assess prognostic value. Single‑cell transcriptomics data were interrogated to identify the primary cellular sources of RSPO3, followed by differential gene expression and pathway enrichment analyses in key subpopulations. Finally, in vitro functional assays were conducted to investigate the effects of RSPO3 on breast cancer cell proliferation, migration, and apoptosis. Specifically, a co‑culture system of human breast cancer‑associated fibroblasts (HBCFs) and MCF‑7 cells was employed to examine changes in RSPO3 expression and the proliferative and migratory capacities of breast cancer cells after co‑culture. The function of RSPO3 was verified by knocking down RSPO3 in the co‑culture system, and further validation was carried out through Western blotting, CHIR99021 activator rescue experiments, and tissue analysis. RESULTS: Compared to adjacent non-tumor tissues, RSPO3 mRNA expression was generally downregulated in BC tissues; however, RSPO3 protein levels were significantly higher in tumor tissues. High RSPO3 protein expression was an independent risk factor for reduced overall survival (OS). Single-cell analysis revealed that within the TME, RSPO3 was primarily expressed in fibroblasts, endothelial cells, and epithelial cells. Notably, among fibroblasts, RSPO3 expression was specifically enriched in the inflammatory cancer-associated fibroblast (iCAF) subpopulation. RSPO3⁺ iCAFs exhibited functional characteristics related to cell proliferation regulation, angiogenesis, Wnt signaling, and oxidative phosphorylation. In vitro experiments demonstrated that RSPO3 knockdown suppressed the proliferation, migration, and invasion of MCF-7 cells while promoting apoptosis.Furthermore, co-culture of HBCFs with MCF-7 cells significantly increased RSPO3 protein levels in MCF-7 cells, accompanied by markedly enhanced proliferation and migration abilities. Knockdown of RSPO3 significantly reversed these pro-tumorigenic effects. RSPO3 knockdown downregulated the expression of Axin2, Cyclin D1, and β-catenin. Treatment with the Wnt pathway activator CHIR99021 partially rescued the inhibition of invasion and migration induced by RSPO3 knockdown. Immunohistochemical staining of breast cancer tissues further confirmed the positive correlation between RSPO3 expression and β-catenin and Cyclin D1 expression. CONCLUSIONS: RSPO3 exhibited significant discrepancies between transcriptional and translational levels in breast cancer tissues. High RSPO3 protein expression indicated poor prognosis and served as an independent prognostic risk factor. Breast cancer-associated fibroblasts may promote tumor cell proliferation and migration by regulating RSPO3 expression and subsequently activating the Wnt/β-catenin pathway. RSPO3 represents a potential prognostic biomarker and therapeutic target.
-
High-Dimensional Single-Cell Multimodal Landscape of Human Carotid Atherosclerosis.
BACKGROUND: Atherosclerotic plaques are complex tissues composed of a heterogeneous mixture of cells. However, our understanding of the comprehensive transcriptional and phenotypic landscape of the cells within these lesions is limited. METHODS: To characterize the landscape of human carotid atherosclerosis in greater detail, we combined cellular indexing of transcriptomes and epitopes by sequencing and single-cell RNA sequencing to classify all cell types within lesions (n=21; 13 symptomatic) to achieve a comprehensive multimodal understanding of the cellular identities of atherosclerosis and their association with clinical pathophysiology. RESULTS: We identified 25 cell populations, each with a unique multiomic signature, including macrophages, T cells, NK (natural killer) cells, mast cells, B cells, plasma cells, neutrophils, dendritic cells, endothelial cells, fibroblasts, and smooth muscle cells (SMCs). Among the macrophages, we identified 2 proinflammatory subsets enriched in IL-1B (interleukin-1B) or C1Q expression, 2 TREM2-positive foam cells (1 expressing inflammatory genes), and subpopulations with a proliferative gene signature and SMC-specific gene signature with fibrotic pathways upregulated. Further characterization revealed various subsets of SMCs and fibroblasts, including SMC-derived foam cells. These foamy SMCs were localized in the deep intima of coronary atherosclerotic lesions. Utilizing cellular indexing of transcriptomes and epitopes by sequencing data, we developed a flow cytometry panel, using cell surface proteins CD29, CD142, and CD90, to isolate SMC-derived cells from lesions. Lastly, we observed reduced proportions of efferocytotic macrophages, classically activated endothelial cells, and contractile and modulated SMC-derived cells, while inflammatory SMCs were enriched in plaques of clinically symptomatic versus asymptomatic patients. CONCLUSIONS: Our multimodal atlas of cell populations within atherosclerosis provides novel insights into the diversity, phenotype, location, isolation, and clinical relevance of the unique cellular composition of human carotid atherosclerosis. These findings facilitate both the mapping of cardiovascular disease susceptibility loci to specific cell types and the identification of novel molecular and cellular therapeutic targets for the treatment of the disease.
-
Clinical translation of senescence-related pan-cancer multi-omics: tools for assessment and immunotherapy prediction.
Cellular senescence (CS) exerts dual roles in tumorigenesis, yet its pan-cancer molecular characteristics and clinical value remain unclear, hindering its translation to oncology and personalized therapy. To address the lack of specific and universal tools for senescence assessment and immunotherapy response prediction, this study systematically analyzed 1259 CS-related genes from the CellAge database across 31 cancer types by integrating multi-omics data, including bulk RNA-seq, single-cell/spatial transcriptomics, and CRISPR screening. We developed a rank-based algorithm SenScoreR (publicly available at https://gxhub.shinyapps.io/SenScoreR/ ) for senescence quantification, validated with 10 independent datasets, and constructed a machine learning-based predictive model CS.Sig for immunotherapy response. Results showed that tumors had significantly lower Rank-based Senescence Score (RSS) than normal tissues across 31 cancers (average diagnostic AUC = 0.895), with low RSS linked to poor survival; high RSS correlated with reduced genomic instability, enriched CD8⁺ T/NK cell/macrophage infiltration, upregulated PD-L1 expression, and elevated immune cytolytic activity. CS.Sig demonstrated robust performance in predicting ICI response (AUC = 0.716 across 10 cohorts), outperforming 13 existing signatures, while CRISPR screening identified 17 senescence-related targets (e.g., CEP55, PPP1CC) whose knockout enhanced anti-tumor immunity. Our findings clarify CS's role in maintaining tumor genomic stability and shaping immune microenvironments, and the developed SenScoreR, CS.Sig, and identified targets bridge basic CS research with clinical oncology, providing a translational resource and hypothesis basis for future experimental and clinical validation.
-
Single-cell transcriptome unveils mesenchymal cell diversity in endometriosis.
Mesenchymal cells constitute the primary structural support elements within endometriotic lesions, yet their pivotal roles in endometriotic pathogenesis remain largely uncharted. This study aimed to construct a single-cell atlas of endometriosis using samples from three ovarian tissues affected by endometriosis and three normal ovarian tissues. Through the utilization of scRNA-seq, we have unveiled six distinct mesenchymal subclusters in normal and endometriosis-afflicted ovaries, elucidating the diverse functions of mesenchymal populations in endometriosis. Our comprehensive analysis has revealed that mesenchymal cells predominantly engage in three key functions: ribosome-mediated protein synthesis and processing, cell adhesion facilitating intercellular support and communication, and a range of metabolic processes. Furthermore, our findings have identified several pivotal differentially expressed genes (e.g. C3, FN1, COL3A1, COL1A1, NRXN3), primarily associated with the complement and coagulation cascades, extracellular matrix (ECM) regulation, ECM receptor interactions, and cell adhesion molecules. In essence, our study provides a comprehensive transcriptomic dataset and novel insights into adhesive molecule and integrin networks within mesenchymal subclusters in endometriosis. This, in effect, has deepened the understanding of the pathomechanisms governing this condition.