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PubMed2025

GeneFEAST: the pivotal, gene-centric step in functional enrichment analysis interpretation.

SUMMARY: GeneFEAST, implemented in Python, is a gene-centric functional enrichment analysis summarization and visualization tool that can be applied to large functional enrichment analysis (FEA) results arising from upstream FEA pipelines. It produces a systematic, navigable HTML report, making it easy to identify sets of genes putatively driving multiple enrichments and to explore gene-level quantitative data first used to identify input genes. Further, GeneFEAST can juxtapose FEA results from multiple studies, making it possible to highlight patterns of gene expression amongst genes that are differentially expressed in at least one of multiple conditions, and which give rise to shared enrichments under those conditions. Thus, GeneFEAST offers a novel, effective way to address the complexities of linking up many overlapping FEA results to their underlying genes and data, advancing gene-centric hypotheses, and providing pivotal information for downstream validation experiments. AVAILABILITY AND IMPLEMENTATION: GeneFEAST GitHub repository: https://github.com/avigailtaylor/GeneFEAST; Zenodo record: 10.5281/zenodo.14753734; Python Package Index: https://pypi.org/project/genefeast; Docker container: ghcr.io/avigailtaylor/genefeast.

Software↗
PubMed2025

Identification and validation of prognostic genes associated with mitochondrial nuclear genes in gastric cancer.

Mitochondrial-related nuclear genes (MNGs) have shown great importance in cancer diagnosis and prognosis, but their role in gastric cancer (GC) remains unclear. GC-related transcriptome data from the gene expression omnibus and cancer genome atlas databases were analyzed to identify differentially expressed MNGs. A prognostic risk model was constructed through univariate Cox and least absolute shrinkage and selection operator regression, validated by Kaplan-Meier (K-M) survival curve and receiver operating characteristic curve. This was followed by immune infiltration analysis, independent prognostic analysis, functional enrichment analysis, drug sensitivity analysis, drug prediction, molecular docking and construction of regulatory networks. Three prognostic genes (ATP8A2, COX15 and TARS2) were identified. The expression of TARS2 and COX15 was positively correlated with CNV, while ATP8A2 was unaffected. The risk model and nomogram, integrating risk score and clinicopathological factors, exhibited excellent predictive performance. A significant correlation was observed between prognostic genes and differential immune cells, such as T cells, B cells, and NK cells. BMS-754807, Gefitinib, JQ1, Lapatinib, and Sapitinib exhibited significant differences in sensitivity between the high-risk group and the low-risk group. The results of molecular docking showed TP8A2 has stable binding ability with cytosine, COX15 with indomethacin, and TARS2 with bisacodyl. RT-qPCR revealed downregulation of ATP8A2 and upregulation of COX15 and TARS2 in GC samples. MNGs, including ATP8A2, COX15, and TARS2, demonstrated significant associations with immune infiltration, CNV, and prognostic outcomes of GC.

Humans↗
PubMed2026

Kynurenine metabolism-related gene signature for prognostic stratification in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a major global health burden with high mortality rates and limited therapeutic options. The identification of reliable biomarkers for early diagnosis and prognosis prediction is urgently needed. Kynurenine metabolism, a critical pathway in immune regulation and tumor progression, has been implicated in various cancers. However, its prognostic value in HCC has not been fully elucidated. This study aimed to develop a prognostic risk model based on kynurenine metabolism-related genes (KMRGs) for HCC patients. METHODS: Transcriptomic and clinical data of HCC patients were retrieved from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. A prognostic risk model was established using least absolute shrinkage and selection operator (LASSO) and Cox regression analyses. Survival analysis and functional enrichment analysis were conducted to validate the predictive performance of the model and to investigate the underlying mechanisms. ALDH8A1 was ultimately identified as a target gene based on survival analysis, and its impact on tumor cell migration was assessed using the HCC cell line. RESULTS: A prognostic model based on seven KMRGs was established. The high-risk group exhibited significantly worse overall survival compared to the low-risk group. Functional enrichment analysis in high-risk patients highlighted significant enrichment in core biological processes, including spliceosome assembly and ribonucleoprotein complex biogenesis. Furthermore, a nomogram integrating the risk score and clinical pathological features was developed, demonstrating moderate predictive performance for HCC prognosis. CONCLUSIONS: This study successfully constructed a prognostic risk model based on seven KMRGs, providing a valuable tool for predicting clinical outcomes in HCC patients. These findings highlight the potential role of kynurenine metabolism in HCC progression and offer new insights for future therapeutic strategies.

ALDH8A1↗
PubMed2026

The association of cardiovascular health with new-onset pulmonary hypertension and the mediating role of proteomic signatures.

BACKGROUND: The cardiovascular health (CVH) metrics have been reported to play an important role in the development of noncommunicable chronic diseases, yet its link to pulmonary hypertension (PH) risk and the underlying biological mechanisms remain unclear. This study aimed to investigate the association of CVH with PH risk and elucidate the mediating role of plasma proteomic signatures. METHODS: A total of 279 220 participants without PH at enrollment of the UK Biobank were included. Cox regression was used to quantify the association between CVH and incident PH. Proteome-wide association analysis, mediation analysis, and functional enrichment analysis were conducted to identify protein mediators. Key hub proteins were further validated at the transcriptional level through quantitative polymerase chain reaction (qPCR) in an animal model of PH, as well as at the protein level, and by macrophage-specific knockdown of interleukin (IL)-6 and CCL4 to evaluate its impact on rat pulmonary artery smooth muscle cell (PASMC) migration and proliferation. RESULTS: Over a median 13.2-year follow-up, 1325 PH cases occurred. Compared to the lowest CVH, participants with moderate and high CVH had 59% [hazard ratio (HR): 0.41; 95% confidence interval (CI): 0.33-0.49] and 82% (HR: 0.18; 95% CI: 0.14-0.23) lower risk, respectively. Proteomic analyses revealed that this association was significantly mediated by a distinct plasma protein signature. Pathway enrichment analysis indicates that proteins are significantly enriched in inflammatory/immune pathways, and key hub proteins were identified as participating in the central mechanism pathway. In the lung tissue of PH rat models, the mRNA and protein expression levels of IL-6 and C-C motif chemokine ligand 4 (CCL4) were significantly elevated. Furthermore, functional assays demonstrated that knockdown of IL-6 or CCL4 in macrophages significantly attenuated the migration and proliferation of rat PASMCs in vitro. CONCLUSION: High CVH level, defined by Life's Essential 8 (LE8), is significantly linked to a reduced risk of developing PH. This protective effect is primarily mediated by a proteomic signature, revealing the role of signaling pathways such as cytokine-cytokine receptor interaction in the prevention of PH.

Hypertension, Pulmonary↗
PubMed2026

Identification and genetic validation of potential therapeutic targets for pulmonary hypertension through multi-omics causal inference.

Pulmonary hypertension (PH) underscores the urgent need for novel therapeutic targets. This study aimed to employ a proteome-wide Mendelian randomization (MR) approach to systematically identify circulating proteins causally associated with PH, thereby providing genetically validated candidate targets for drug development. We adopted a 2-sample MR design, integrating large-scale plasma proteomic quantitative trait loci (pQTL) data (encompassing 4148 proteins) and summary statistics from a large-scale PH genome-wide association study (2047 cases, 8301 controls). Candidate targets were screened through a multilayered analytical pipeline comprising proteomic MR, transcriptomic MR, and summary-data-based Mendelian randomization. The ultimately identified MR-Identified Causal Candidate Targets (MR-ICTs) underwent rigorous Bayesian colocalization analysis, followed by biological characterization through functional enrichment analysis, single-cell transcriptomics, and phenome-wide association studies. Through robust genetic causal inference, this study provides that circulating proteins such as LYZ, GREM2, NID1, and PF4V1 play causal roles in PH pathogenesis. These findings offer a set of rigorously genetically validated, high-priority therapeutic targets for developing novel PH treatments, specifically addressing key pathological mechanisms such as innate immunity, BMP signaling pathway dysregulation, and platelet activation. Our multi-dimensional analysis ultimately identified 6 MR-ICTs causally associated with PH. Notably, the causal associations for lysozyme C (LYZ), gremlin-2 (GREM2), nidogen-1 (NID1), and platelet factor 4 variant 1 (PF4V1) were stringently validated by Bayesian colocalization analysis (posterior probability for hypothesis 4 [PPH4], indicating a shared causal variant, > 0.99). Functional enrichment analysis revealed significant involvement of these targets in immune response and TGF-β signaling pathways. Single-cell analysis further elucidated their cell-type-specific expression, with LYZ predominantly expressed in monocytes and PF4V1 almost exclusively in platelets.

Hypertension, Pulmonary↗
PubMed2026

DeeDeeExperiment: building an infrastructure for integrating and managing omics data analysis results in R/Bioconductor.

SUMMARY: Modern omics experiments now involve multiple conditions and complex designs, producing an increasingly large set of differential expression and functional enrichment analysis results. However, no standardized data structure exists to store and contextualize these results together with their metadata, leaving researchers with an unmanageable and potentially non-reproducible collection of results that are difficult to navigate and/or share. Here we introduce DeeDeeExperiment, a new S4 class for managing and storing omics data analysis results, implemented within the Bioconductor ecosystem, which promotes interoperability, reproducibility and good documentation. This class extends the widely used SingleCellExperiment object by introducing dedicated slots for Differential Expression (DEA) and Functional Enrichment Analysis (FEA) results, allowing users to organize, store, and retrieve information on multiple contrasts and associated metadata within a single data object, ultimately streamlining the management and interpretation of many omics datasets. AVAILABILITY AND IMPLEMENTATION: DeeDeeExperiment is available on Bioconductor under the MIT license (https://bioconductor.org/packages/DeeDeeExperiment), with its development version also available on Github (https://github.com/imbeimainz/DeeDeeExperiment).

Software↗
PubMed2024

Expression profile of long noncoding RNAs and comprehensive analysis of lncRNA-cisTF-DGE regulation in condyloma acuminatum.

OBJECTIVE: To identify differentially expressed long noncoding RNAs (lncRNAs) in condyloma acuminatum (CA) and to explore their probable regulatory mechanisms by establishing coexpression networks. METHODS: High-throughput RNA sequencing was performed to assess genome-wide lncRNA expression in CA and paired adjacent mucosal tissue. The expression of candidate lncRNAs and their target genes in larger CA specimens was validated using real-time quantitative reverse transcriptase polymerase chain reaction (RT‒qPCR). Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used for the functional enrichment analysis of these candidate lncRNAs and differential mRNAs. The coexpressed mRNAs of the candidate lncRNAs, calculated by Pearson's correlation coefficient, were also analysed using GO and KEGG analysis. In addition, the interactions among differentially expressed lncRNAs (DElncRNAs)-cis-regulatory transcription factors (cisTFs)-differentially expressed genes (DEGs) were analysed and their network was constructed. RESULTS: A total of 546 lncRNAs and 2553 mRNAs were found to be differentially expressed in CA compared to the paired control. Functional enrichment analysis revealed that the DEGs coexpressed with DElncRNAs were enriched in the terms of cell adhesion and keratinocyte differentiation, and the pathways of ECM-receptor interaction, local adhesion, PI3K/AKT and TGF-ß signaling. We further constructed the network among DElncRNAs-cisTFs-DEGs and found that these 95 DEGs were mainly enriched in GO terms of epithelial development, regulation of transcription or gene expression. Furthermore, the expression of 3 pairs of DElncRNAs and cisTFs, EVX1-AS and HOXA13, HOXA11-AS and EVX1, and DLX6-AS and DLX5, was validated with a larger number of specimens using RT‒qPCR. CONCLUSION: CA has a specific lncRNA profile, and the differentially expressed lncRNAs play regulatory roles in mRNA expression through cis-acting TFs, which provides insight into their regulatory networks. It will be useful to understand the pathogenesis of CA to provide new directions for the prevention, clinical treatment and efficacy evaluation of CA.

RNA, Long Noncoding↗
PubMed2026

Multi-omics Approaches to CCAAT/Enhancer-Binding Protein Beta in Oral Squamous Cell Carcinoma: Crosstalk Between Tumor Cells and Tumor-Associated Macrophages Driving Disease Progression.

BACKGROUND: CCAAT/Enhancer-Binding Protein Beta (CEBPB) is an important transcription factor that regulates tumor progression. However, the mechanism by which CEBPB regulates the progression of Oral Squamous Cell Carcinoma (OSCC) remains incompletely understood. Tumor progression depends on complex intercellular interactions within the tumor microenvironment. The purpose of this study was to investigate the role and epigenetic regulatory mechanisms of CEBPB in interactions between OSCC cells and tumor-infiltrating immune cells. METHODS: Bulk RNA-seq, ChIP-seq, and scRNA-seq data were obtained from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. The HOMER algorithm was employed to identify enhancers and predict the CEBPB-binding motif. Cell cluster analysis, functional enrichment, and intercellular interaction analysis were performed using the "Seurat" R package. H3K27ac enrichment at GAS6 enhancers was validated by ChIP-qPCR. Metastatic OSCC cells with CEBPB knockdown or GAS6 overexpression were established and co-cultured with THP-1 cells. IL-10 and IL-6 secretion from co-cultured THP-1 cells was detected via ELISA. Chemotaxis of OSCC cells toward THP-1 cells was assessed through a Transwell assay. RESULTS: CEBPB was upregulated in OSCC and correlated with poor prognosis. By integrating H3K27ac ChIP-seq and bulk RNA-seq data, 131 CEBPB-regulated enhancer-controlled genes were identified in lymph node metastatic OSCC cells. scRNA-seq analysis revealed eight major cell clusters in primary foci and lymph node metastases, including T/NK cells, malignant epithelial cells, B/plasma cells, macrophages, fibroblasts, dendritic cells, endothelial cells, and mast cells, with the malignant epithelial cells stratified into distinct sub-clusters. CEBPB expression was elevated in malignant epithelial cells of lymph node metastases compared to primary foci. Furthermore, 15 pairs of enhanced ligand-receptor interactions were identified in lymph node metastases relative to primary foci. GAS6 was a CEBPB-regulated enhancer-controlled gene, primarily mediating interactions between malignant cells and macrophages. CEBPB knockdown in metastatic OSCC cells significantly impaired their chemotaxis toward cocultured THP-1 cells, and downregulated IL-10/IL-6 secretion and CD206 expression in cocultured THP-1 cells. Conversely, GAS6 overexpression reversed these inhibitory effects. CONCLUSION: CEBPB activated GAS6 transcription in metastatic OSCC cells. The CEBPB/ GAS6 axis in metastatic OSCC cells enhanced their chemotaxis toward macrophages and promoted the M2 polarization of macrophages, thereby facilitating the establishment of an immunosuppressive microenvironment.

Humans↗
PubMed2025

Comprehensive identification and analysis of clusters of tandemly duplicated genes reveal their contributions to adaptive evolution of green plants.

Tandem gene duplication occurred more frequently compared with the episodic whole-genome duplication (WGD), providing a continuous supply of genetic material for evolutionary innovation and adaptation to changing environments. The rising roles of clusters of tandemly duplicated genes (CTDGs) in the evolution of phenotypic diversity have been unraveled in mammals. However, the content and biological roles of CTDGs remain largely unknown in plants. Here, we comprehensively identified CTDGs in 220 published plant genomes representing major lineages of green plants. The number of CTDGs showed great variation across taxa, ranging from 0 to 6028. The size of CTDGs varied from 2 to 47 genes, with small clusters containing two members predominating. Interestingly, significant expansion of CTDGs was found in early-diverging land plants and is closely associated with the evolution of key traits (e.g., ABA response, plant cuticle, UV-B resistance) required for plants to conquer terrestrial environments. Functional enrichment analysis revealed conserved and specialized functional profiles among different sizes of CTDGs in both Arabidopsis thaliana and the bryophyte Physcomitrium patens. Small CTDGs were enriched in fundamental stress responses, including protein modification, signal transduction, and responses to diverse stress stimuli, while large CTDGs were enriched in more sophisticated processes such as plant hormone biosynthesis and signaling, plant-microbe interactions, and reproductive processes. Expression pattern analyses of CTDGs under different stress conditions in A. thaliana and P. patens revealed that the highest number of CTDGs showed differential expression under drought stress, suggesting important roles of CTDGs in the evolution of desiccation tolerance in early land plants. The results of this study provide new additions to our knowledge about the abundance of CTDGs across green plants and reveal their important contributions to enable plants to overcome stressful environments on land.

Gene Duplication↗
PubMed2025

Inflammatory pathways and immune dysregulation in pediatric postoperative septic shock: A study integrating transcriptomics, machine learning and molecular docking.

This study elucidates the molecular and immune regulatory mechanisms of pediatric postoperative septic shock. Transcriptomic data were obtained from the Gene Expression Omnibus database. Differentially expressed genes were identified using the limma package, and gene co-expression modules were constructed using Weighted Gene Co-expression Network Analysis. Functional enrichment was performed via gene set enrichment analysis, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses. Immune cell infiltration was assessed using ESTIMATE and CIBERSORT. Mendelian randomization was applied to explore causal relationships between gene expression and septic shock. Feature genes were selected using machine learning algorithms, and a diagnostic nomogram model was constructed. Finally, molecular docking analysis was performed to screen and evaluate the binding affinity of traditional Chinese medicine monomers to core target proteins. A total of 1331 differentially expressed genes were identified, and the turquoise module was strongly correlated with septic shock. Enrichment analysis revealed significant activation of IL-6/JAK/STAT3, TNF-α/NF-κB, and PI3K/Akt/mTOR pathways. Immune infiltration analysis indicated suppressed immune scores and imbalances in neutrophils, macrophages, T cells, and B cells. Mendelian randomization confirmed causal associations for 6 genes, including PIM3. The predictive model based on feature genes demonstrated high diagnostic performance. Molecular docking suggested that quercetin and astramembrannin I could stably bind PIM3. This study systematically identified core genes, dysregulated immune pathways, and candidate small-molecule interventions in pediatric septic shock, providing novel insights for early diagnosis and targeted therapy.

Humans↗
PubMed2026

Identification of mitochondrial energy metabolism-related candidate genes UQCR10 and NDUFA6 in pediatric tetralogy of fallot: an exploratory bioinformatics study.

BACKGROUND: Tetralogy of Fallot (TOF) is one of the most common cyanotic congenital heart diseases in infants and young children. Its molecular basis remains incompletely understood. This study aimed to identify mitochondrial energy metabolism-related candidate genes associated with pediatric TOF using public heart tissue transcriptomic datasets from the GEO database. METHODS: Datasets GSE146218 and GSE217772 were downloaded and merged, followed by batch-effect correction. Differential expression analysis was performed to identify differentially expressed genes (DEGs). Functional enrichment analysis, weighted gene co-expression network analysis (WGCNA), and protein-protein interaction (PPI) network analysis were used to prioritize candidate genes. The Comparative Toxicogenomics Database (CTD) was used as an exploratory literature-based tool to summarize gene-disease associations. RESULTS: A total of 960 DEGs were identified. Functional enrichment analyses showed that these genes were mainly enriched in mitochondrial energy metabolism-related pathways, including oxidative phosphorylation and the mitochondrial respiratory chain. WGCNA and PPI network analyses further prioritized UQCR10 and NDUFA6 as candidate genes, and both genes showed increased expression in TOF heart tissue samples. CTD analysis suggested literature-based associations between these genes and cardiovascular or developmental disease-related terms. CONCLUSION: This exploratory bioinformatics study identified UQCR10 and NDUFA6 as mitochondrial energy metabolism-related candidate genes upregulated in pediatric TOF heart tissue. These findings suggest that mitochondrial respiratory chain-related transcriptional alterations may be involved in TOF-associated myocardial remodeling or stress responses. Further experimental and clinical validation is required to confirm their biological relevance.

Humans↗
PubMed2026

ScRNA-seq analysis reveals the effects of nitrite stress on the endocrine system of the eyestalk in Litopenaeus vannamei.

Nitrite is a harmful substance generated in Litopenaeus vannamei farming systems, largely originating from the inadequate breakdown of surplus feed and shrimp feces. Its accumulation in the water can affect the growth and physiological functions of shrimp, damage the immune system, and even cause mass mortality, thus becoming a key environmental factor restricting the green development of the industry. Under nitrite stress, the eyestalk, as an important neuroendocrine regulatory center in crustaceans, participates in the stress adaptation of the organism and exerts a protective effect by regulating energy metabolism and immune function. However, the molecular regulatory mechanism of the eyestalk in response to nitrite stress remains unclear. In this study, single-cell RNA sequencing (scRNA-seq) technology was used to analyze the heterogeneity of eyestalk cells in L. vannamei under nitrite stress. A total of 18, 394 high-quality cells were obtained, and six major cell subpopulations, including Neurosecretory cell, Motor neuron, Sensory neuron, Interneuron, Neurogliocyte, and Support cell, were identified. Differential expression analysis identified 839 differentially expressed genes, and different cell types showed distinct specific responses to nitrite stress. Functional enrichment analysis indicated that pathways such as glycolysis, oxidative phosphorylation, ribosome function, and endoplasmic reticulum protein processing were significantly activated, while signal transduction and DNA repair-related pathways were inhibited. Further analysis revealed that nitrite stress could induce mitochondrial function changes and trigger oxidative stress, thereby affecting the neuroendocrine system function of the eyestalk. This study provided insights into transcriptomic responses of the eyestalk to nitrite stress at the single-cell level, laying a theoretical foundation for the management of aquaculture environments.

Animals↗
PubMed2026

Transcriptomic analysis identifies novel ferroptosis-related biomarkers and therapeutic targets in pulmonary arterial hypertension.

BACKGROUND: Ferroptosis plays a significant role in pulmonary arterial hypertension (PAH), although its underlying mechanisms and key pathogenic genes remain unclear. METHODS: Transcriptomic data from human PAH and control lung tissue were obtained from the Gene Expression Omnibus (GEO) database, whereas ferroptosis-related genes (FRGs) were sourced from the MsigDb and FerrDb databases. Differentially expressed FRGs (DE-FRGs) were identified through the intersection of FRGs with differentially expressed genes (DEGs). Functional enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Key hub genes were identified through Least Absolute Shrinkage and Selection Operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and weighted correlation network analysis (WGCNA). Gene set enrichment analysis (GSEA) was conducted to explore the functional roles and associated pathways of hub genes. The relationship between hub genes and immune infiltration was investigated. Expression levels of potential biomarkers were validated via Quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) in two PAH animal models (monocrotaline-induced and Sugen5416 plus hypoxia-induced PAH). Finally, molecular docking was employed to screen potential therapeutic compounds. RESULTS: A total of 133 DE-FRGs were identified, with KEGG and GO analyses highlighting their involvement in intracellular iron homeostasis and ferroptosis. Hub genes, notably FZD7 and NFE2, were identified using LASSO, SVM-RFE, and WGCNA. Immune infiltration analysis suggested that monocytes and neutrophils play key roles in PAH pathogenesis. Validation in PAH animal models showed significant upregulation of Fzd7 and downregulation of Nfe2 in lung tissues of both MCT- and SuHx-induced PAH models. Molecular docking identified tetrachlorodibenzodioxin (TCDD) has good binding affinity. CONCLUSION: In summary, we investigated two ferroptosis-related biomarkers, FZD7 and NFE2, in PAH using transcriptomics, offering new insights into molecular mechanisms and potential targeted therapies for the disease.

Ferroptosis↗
PubMed2026

Transcriptomic and network analyses identify epigenetic regulators of drug-tolerant persister (DTP) subsets in EGFR-mutant HCC827 non-small cell lung cancer.

BACKGROUND: The clinical efficacy of osimertinib, a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI), in EGFR-mutant non-small cell lung cancer (NSCLC) is limited by the inevitable acquired resistance. Drug-tolerant persister (DTP) cells, which survive initial therapy, are considered a key reservoir for this resistance. Understanding the molecular characteristics of DTPs is essential for developing strategies to prevent relapse. OBJECTIVE: This study aimed to characterize the transcriptomic landscape of osimertinib-tolerant DTP cells and identify key epigenetic regulators associated with the DTP phenotype in EGFR-mutant HCC827 NSCLC cells through integrated transcriptomic and network analyses. METHODS: We established an in vitro model of osimertinib tolerance using an EGFR-mutant (exon 19 deletion) HCC827 NSCLC cell line. Parental HCC827 cells and DTP subsets were subjected to transcriptomic analysis by RNA sequencing (RNA-seq). Differentially expressed genes were identified, followed by bioinformatics analyses, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein-protein interaction (PPI) network analyses to identify key biological processes driving the DTP phenotype. Key findings were validated using quantitative real-time PCR (qPCR). RESULTS: Osimertinib treatment induced a morphologically distinct DTP population. Transcriptomic profiling revealed a marked shift in gene expression compared to parental cells. Functional enrichment analysis showed significant upregulation of epigenetic pathways. PPI network analysis identified a core module of eight hub genes, including histone deacetylases (HDAC5, HDAC9), sirtuins (SIRT1, SIRT2), and histone acetyltransferase (KAT2B). qPCR confirmed increased expression of HDAC5, HDAC9, and SIRT1. CONCLUSION: Epigenetic reprogramming accompanies the transition to an osimertinib-tolerant state in EGFR-mutant HCC827 cells. Targeting HDACs and sirtuins may represent a promising strategy to eliminate DTP subpopulations and delay or prevent acquired resistance.

Drug-tolerant persister↗
PubMed2025

Identification of novel cytoskeleton protein involved in spermatogenic cells and sertoli cells of non-obstructive azoospermia based on microarray and bioinformatics analysis.

BACKGROUND: During mammalian spermatogenesis, the cytoskeleton system plays a significant role in morphological changes. Male infertility such as non-obstructive azoospermia (NOA) might be explained by studies of the cytoskeletal system during spermatogenesis. METHODS: The cytoskeleton, scaffold, and actin-binding genes were analyzed by microarray and bioinformatics (771 spermatogenic cellsgenes and 774 Sertoli cell genes). To validate these findings, we cross-referenced our results with data from a single-cell genomics database. RESULTS: In the microarray analyses of three human cases with different NOA spermatogenic cells, the expression of TBL3, MAGEA8, KRTAP3-2, KRT35, VCAN, MYO19, FBLN2, SH3RF1, ACTR3B, STRC, THBS4, and CTNND2 were upregulated, while expression of NTN1, ITGA1, GJB1, CAPZA1, SEPTIN8, and GOLGA6L6 were downregulated. There was an increase in KIRREL3, TTLL9, GJA1, ASB1, and RGPD5 expression in the Sertoli cells of three human cases with NOA, whereas expression of DES, EPB41L2, KCTD13, KLHL8, TRIOBP, ECM2, DVL3, ARMC10, KIF23, SNX4, KLHL12, PACSIN2, ANLN, WDR90, STMN1, CYTSA, and LTBP3 were downregulated. A combined analysis of Gene Ontology (GO) and STRING, were used to predict proteins' molecular interactions and then to recognize master pathways. Functional enrichment analysis showed that the biological process (BP) mitotic cytokinesis, cytoskeleton-dependent cytokinesis, and positive regulation of cell-substrate adhesion were significantly associated with differentially expressed genes (DEGs) in spermatogenic cells. Moleculare function (MF) of DEGs that were up/down regulated, it was found that tubulin bindings, gap junction channels, and tripeptide transmembrane transport were more significant in our analysis. An analysis of GO enrichment findings of Sertoli cells showed BP and MF to be common DEGs. Cell-cell junction assembly, cell-matrix adhesion, and regulation of SNARE complex assembly were significantly correlated with common DEGs for BP. In the study of MF, U3 snoRNA binding, and cadherin binding were significantly associated with common DEGs. CONCLUSION: Our analysis, leveraging single-cell data, substantiated our findings, demonstrating significant alterations in gene expression patterns.

Male↗
PubMed2024

Relationship between inflammation/immunity and epilepsy: A multi-omics mendelian randomization study integrating GWAS, eQTL, and mQTL data.

OBJECTIVES: Increasing evidence suggests that activated innate/adaptive immunity induces an inflammatory response, thereby participating in epileptogenesis. However, the biological explanation of inflammation/immunity as a potential cause for epilepsy remains largely unknown. This research aimed to determine the causal effects of inflammation/immune-related genes in epilepsy based on multi-omics mendelian randomization (MR). METHODS: We employed summary-data-based MR (SMR) approach to combine GWAS for epilepsy (12,891 cases and 312,803 control) with gene expression quantitative trait loci (cis-eQTL, 31,684 participants) and DNA methylation QTL (cis-mQTL, 1,980 participants) data. Five additional MR methods were then used for sensitivity analyses to confirm the reliability of causal associations. In addition, enrichment analysis of key genes was conducted to provide insight into the biological functions of epilepsy risk variants. RESULTS: A total of 386 inflammation/immune-related genes were selected for further analyses. Primary SMR analysis indicated that 37 DNA methylation sites and six genes regulated by them had potential causal relationship with epilepsy. MR analysis further refined the results, identifying three genes that had a causal effect on epilepsy. Notably, VEGFA (OR: 0.925; 95 % CI: 0.862-0.994) expression was negatively correlated with epilepsy risk, whereas IL16 (OR: 1.076; 95 % CI: 1.028-1.126) and HLA-DPA1 (OR: 1.041; 95 % CI: 1.009-1.074) expressions were positively associated with epilepsy risk. Functional enrichment analysis revealed that the identified genes were involved in GO-BP terms related to VEGF activation signaling and chemotaxis regulation. CONCLUSION: This analysis confirms the causal role of inflammation/immunity in epilepsy, and the identified candidate genes provide clues for drug development in clinical practice.

Humans↗
PubMed2026

Identification of a novel human gut microbes and microbial metabolites related genes signature for prognostic implication in head and neck squamous carcinomas.

BACKGROUND: The gut microbiota acts as a critical driver influencing the pathogenesis, therapeutic response, and clinical outcomes across various cancer types. This study aimed to investigate the prognostic value of human gut microbes and microbial metabolites related genes (HGMMMRGs) in head and neck squamous cell carcinoma (HNSCC). METHODS: We constructed a prognostic risk model comprising 19 core HGMMMRGs using LASSO penalized regression and a multivariate Cox proportional hazards model. The predictive performance of the model was evaluated through Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, nomograms, and concordance index. In addition, functional enrichment analysis was performed on the differentially expressed risk genes. Furthermore, the relationship between the immune microenvironment of HNSCC and the risk diagnostic model was examined. Western blot analysis was used to assess the expression levels of IL10 in both HNSCC tissues and adjacent normal tissues. Finally, the correlation between IL10 and the gut microbiota was explored. RESULTS: This study developed a risk score model integrating 19 HGMMMRG genes, which can serve as a tool to guide prognosis and immune microenvironment assessment in HNSCC patients. Survival analysis showed that patients in the high-risk group had significantly worse outcomes (P&#x2009;<&#x2009;0.05). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed significant enrichment of differentially expressed genes (DRLs) and immune-related pathways. Western blot analysis further confirmed that IL10 was highly expressed in HNSCC, and the abundance of Faecalibacterium prausnitzii and Enterococcus durans colonies was correlated with IL10 expression. CONCLUSION: We developed a prognostic model for HGMMMRGs that can be effectively used to predict OS in patients with HNSCC. Second, Faecalibacterium prausnitzii and Enterococcus durans can influence the prognosis of patients with HNSCC by mediating the expression IL10 and thereby affecting the prognosis of HNSCC patients. Thus, human gut microbes and microbial metabolite-related genes may be another promising strategy for the treatment of patients with HNSCC.

HNSCC↗
PubMed2026

Decreased expression of Kr&#xfc;ppel-like factor 4 is associated with colorectal cancer progression.

Kr&#xfc;ppel-like factor 4 (KLF4), a key transcription factor,plays an important role in cell proliferation, differentiation, and apoptosis. Here, we explored the prognostic value of KLF4 and its role in colorectal cancer (CRC) progression. We analyzed transcriptomic data and clinical information related to CRC from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. database. Immunohistochemistry was performed to evaluate KLF4 expression in CRC tissue samples. Additionally, we examined the relationship between clinicopathological factors and patient prognosis using Cox proportional hazards model analysis. Lentiviral transfection was used to create KLF4 knockdown HCT-116 cells. Analysis of the TCGA database and two GEO datasets (GSE21510 and GSE117606) revealed that KLF4 was expressed at low levels in CRC. Furthermore, reduced KLF4 levels correlated with lymph node metastasis, distant metastasis, and advanced TNM staging. ROC curve analysis indicated that KLF4 can effectively differentiate cancerous tissue from normal tissue. Functional enrichment analysis identified KLF4 as significantly linked to the glycoprotein metabolic pathway. Our detection of KLF4 expression in CRC tissue samples confirmed its decreased levels and their association with poorer patient survival. However, KLF4 was not identified as an independent prognostic factor. In vitro, KLF4 knockdown promoted HCT-116 cell migration and invasion and downregulated the mRNA expression of glycoprotein synthesis- and glycosylation-related genes. Conversely, KLF4 re-expression markedly reversed these effects. Our findings suggested that low KLF4 expression served as a predictor factor for disease progression in CRC patients. Furthermore, reduced KLF4 levels enhance the migration and invasion of CRC cells, which may be related to impaired glycoprotein metabolism.

Colorectal cancer↗