Integrative multi-omics and mendelian randomization reveal the critical role of pyroptosis in prognosis and therapy of lung squamous cell carcinomas

Single-cell transcriptomics combined with Mendelian randomization reveals the pivotal role of WDR83OS in clear cell renal cell carcinoma: An observational and bioinformatic study.

This study aimed to comprehensively investigate the molecular mechanisms of clear cell renal cell carcinoma (ccRCC), identify key cellular subpopulations and genes, develop an effective diagnostic model, and screen potential targeted therapies for ccRCC. We analyzed single-cell transcriptomic sequencing data to identify the major cellular subpopulations in ccRCC. High-dimensional weighted gene co-expression network analysis and multiple machine learning algorithms were used to identify key genes and develop a diagnostic model. Two-sample Mendelian randomization analysis was performed to assess causality. Molecular docking was used to identify a candidate therapeutic agent. Data processing was conducted using R and Python. The proportion of endothelial cells was significantly higher in ccRCC (P < .001). High-dimensional weighted gene co-expression network analysis showed that the pink module was closely associated with endothelial cells. Univariate logistic regression and Least Absolute Shrinkage and Selection Operator identified 11 key genes: WDR83OS, TMA7, PFDN5, DSTN, PHPT1, HMGN3, TMSB10, RPL27A, RPL23A, RPL15, and RPL27. Based on these genes, a diagnostic model for ccRCC was developed using multiple machine learning algorithms and achieved an area under the receiver operating characteristic curve of 0.960. In addition, 2-sample Mendelian randomization analysis supported a causal association between WDR83OS and ccRCC (inverse-variance weighted: odds ratio = 1.160, P = .033). Molecular docking indicated that oxyphenbutazone had a high binding affinity for WDR83OS, with a binding energy of -7.124 kcal/mol. By integrating multiple bioinformatic approaches, this study identified key cellular populations and genes in ccRCC, developed a reliable diagnostic model, and highlighted WDR83OS as a potentially important therapeutic target.

Integrated Multi-Omics and Single-Cell Analyses Identify PCDHGB4 as a Prognostic Biomarker and Oncogenic Regulator in Pan-Squamous Cell Carcinoma

A multi-omics integrative analyses reveals CYBB-mediated apoptotic and immune dysregulation as a key target of berberine in diffuse large B-cell lymphoma

This integrative study identifies berberine-related genes with potential causal relevance to DLBCL and prioritizes CYBB as a functionally relevant target linked to apoptosis, immune regulation, and prognosis, highlighting the potential involvement of berberine–CYBB axis underlying berberine activity in DLBCL.

Study on the potential role of KIF23 in doxorubicin-induced cardiomyopathy through multi-omics integration and AI-based screening.

OBJECTIVE Doxorubicin-induced cardiomyopathy (DIC) is a common and severe cardiotoxic effect of doxorubicin (DOX)-based chemotherapy. This study aimed to identify core genes associated with DIC and investigate their immunoregulatory mechanisms. METHODS Core genes were identified based on GEO datasets by integrating differential expression analysis, WGCNA, and machine learning algorithms. Functional enrichment analysis, immune infiltration analysis, and single-cell RNA sequencing analysis were subsequently performed. In addition, AI-based drug screening, molecular docking, molecular dynamics simulation, and Western blot validation were conducted. RESULTS KIF23 was identified as the core gene. Functional analysis of DIC-related genes indicated that they were mainly involved in chromatin remodeling, cell cycle regulation, and energy metabolism. Immune infiltration analysis revealed significant enrichment of macrophages, dendritic cells, and regulatory T cells in the DIC group, and KIF23 expression was negatively correlated with multiple immune cell infiltrations. Single-cell analysis showed that KIF23 was predominantly enriched in macrophage populations. AI-based drug screening identified BRD-K40329609 as a potential therapeutic candidate. Molecular docking and 100 ns molecular dynamics simulations suggested a potential binding affinity between DOX and KIF23. In vitro experiments further demonstrated that DOX significantly downregulated KIF23 expression in cardiomyocytes. CONCLUSION This study identified KIF23 as a core gene associated with DIC and suggested that it may be involved in immune microenvironment remodeling and macrophage-related pathological processes, providing new insights into the molecular mechanisms of DIC and potential therapeutic targets.

Integrated single-cell transcriptomics, Mendelian randomization, and machine learning identify CEBPZ as an immune-related biomarker in oral lichen planus.

BACKGROUND Oral lichen planus (OLP) is a chronic, immune-mediated oral mucosal disease with complex pathophysiology and potential for malignant transformation. Understanding its molecular basis is critical for the development of precise diagnostic and therapeutic strategies. OBJECTIVES We aimed to identify key immune-related biomarkers and characterize cellular dynamics in OLP, with a particular focus on the role of CEBPZ in disease pathogenesis. MATERIAL AND METHODS We analyzed single-cell RNA sequencing (scRNA-seq) data from OLP lamina propria samples (GSE211630) to identify disease-specific T-cell subpopulations using high-dimensional weighted gene co-expression network analysis (hdWGCNA) for oxidative stress-related gene modules.-data-based Mendelian randomization (SMR) integrated FinnGen genome-wide association study (GWAS; 342,499 Europeans) data with Genotype-Tissue Expression (GTEx) expression quantitative trait loci (eQTL) data to identify causal genes. Machine learning (ML) models (least absolute shrinkage and selection operator (LASSO) and convolutional neural network (CNN)) were developed using bulk RNA-seq datasets (GSE52130 and GSE38616) for diagnostic purposes. RESULTS We identified OLP-specific T-cell populations (clusters 0, 3, 5, 7, 13, and 15) with enhanced migration inhibition factor (MIF) pathway signaling toward B cells and monocytes. Two oxidative stress-associated modules contained hub genes, including CEBPZ. Summary-data-based Mendelian randomization analysis identified 231 OLP-associated genes, with CEBPZ uniquely intersecting LASSO-selected markers (odds ratio (OR) = 1.057, 95% confidence interval (95% CI) = 1.013-1.102, p = 0.010). Machine learning models achieved area under the curve (AUC) values ranging from 0.653 to 0.745, with the CNN model reaching a validation accuracy of 0.735. CEBPZ showed elevated expression in OLP T cells and correlated with enhanced MIF-(CD74+CXCR4) signaling. CONCLUSIONS This integrative approach identifies CEBPZ as a pivotal biomarker linking genetic susceptibility, oxidative stress, and immune dysregulation in OLP. Our diagnostic models offer promising tools for OLP management.

Integrated analyses of single-cell transcriptome and mendelian randomization reveal the role of lymphatic endothelial CD74 in the progression of atherosclerosis.

Background Lymphatic dysfunction plays a critical role in the development of atherosclerotic plaques, and targeting lymphatic regulation offers promising strategies for preventing and treating atherosclerosis (AS). This study aims to identify key genes influencing AS in lymphatic endothelial cells (LECs) followed by validation, and to explore potential intervention targets for AS treatment. Methods Single-cell data from the GEO database and Mendelian randomization was employed to identify genes in LECs that may either exacerbate or protect against AS. AS mouse models were established, followed by the assessment of key gene expression in lymphatic vessels within the plaque adventitia. In vitro, LECs were manipulated by silencing or overexpressing key genes to investigate the signaling pathways and mechanisms through which genes influence lymphangiogenesis. Results Human carotid plaque data via the GEO database revealed that LEC-specific genes are closely associated with vasculogenesis, cell migration, and inflammatory responses during AS. Mendelian randomization analysis identified CD74 as a promoter of AS progression. In vivo experiments revealed a significant upregulation of CD74 expression during AS. Correlation analysis of CD74 in LECs with inflammatory genes from the GEO database, along with the in vitro construction of CD74 silencing and overexpression models in LECs, revealed the critical role of CD74 in the inflammatory response in AS. Gene correlation analysis and experimental validation revealed that CD74 promotes LEC pyroptosis through the NLRP3/SYK pathway. Additionally, in vitro results demonstrated that CD74 impairs lymphangiogenesis by inducing pyroptosis. Conclusions This study has identified the key gene CD74 in LECs that influence the progression of AS. Moreover, during AS, CD74 mediates NLRP3/SYK-dependent LEC pyroptosis, thereby inhibiting lymphangiogenesis and exacerbating the inflammatory response. These findings provide a novel molecular mechanism by which CD74 disrupts lymphatic function and accelerates AS progression, offering potential avenues for intervention in AS.