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PubMed2025

Identification of multicohort-based predictive signature for NMIBC recurrence reveals SDCBP as a novel oncogene in bladder cancer.

BACKGROUND: Despite surgical and intravesical chemotherapy interventions, non-muscle invasive bladder cancer (NMIBC) poses a high risk of recurrence, which significantly impacts patient survival. Traditional clinical characteristics alone are inadequate for accurately assessing the risk of NMIBC recurrence, necessitating the development of novel predictive tools. METHODS: We analyzed microarray data of NMIBC samples obtained from the ArrayExpress and GEO databases. LASSO regression was utilized to develop the predictive signature. We combined gene signature and clinicopathological factors to construct a clinical nomogram for estimating NMIBC recurrence in a local cohort. Finally. the biological functions and potential mechanisms of SDCBP in bladder cancer were investigated experimentally in vitro and in vivo. RESULTS: An 8-gene signature was developed, and its efficiency for predicting NMIBC recurrence was evaluated using Kaplan-Meier and time-dependent ROC curves in both training and validation datasets. Immunohistochemical testing revealed elevated levels of ACTN4 and SDCBP in recurrent NMIBC tissues. We integrated the two proteins with clinical factors to develop a nomogram model, which showed superior accuracy compared to individual parameters. Gene Set Variation Analysis and Gene Set Enrichment Analysis unveiled SDCBP exerted cancer-promoting biological processes, such as angiogenesis, EMT, metastasis and proliferation. Experimental procedures demonstrated that silencing SDCBP attenuated cell growth, glucose metabolism and extracellular acidification rate, accompanied by decreased expression of p-AKT, p-ERK1/2, LDHA and Vimentin. CONCLUSIONS: The established 8-gene signature holds promise as a tool for predicting NMIBC recurrence, while targeting SDCBP may represent a potential strategy for delaying disease relapse.

Urinary Bladder Neoplasms↗

PubMed2025

Verification of biological markers of subacute cutaneous lupus erythematosus via TMT labelling proteomics combined with transcriptome data.

OBJECTIVE: This study aimed to investigate biological markers in subacute cutaneous lupus erythematosus (SCLE). METHODS: The tandem mass tag (TMT)-labelling proteomics method was used to explore differentially expressed proteins between SCLE lesions and normal skin tissues. The differences in transcriptomic data between SCLE tissues and normal skin tissues were analysed from the GEO database (GSE81071, GSE109248 and GSE112943). The differences in transcriptomic data from peripheral blood mononuclear cells (PBMCs) of patients with systemic lupus erythematosus (SLE) and normal controls were analysed (GSE81622 and GSE154851). The 35 healthy controls, 30 SCLE patients, 35 SLE patients and 30 lupus nephritis (LN) patients were diagnosed and enrolled. The serum expression levels of IFI44 and EPSTI1 were detected. Data were presented as the mean ± standard deviation or frequency and were analysed using Student's t-test, Chi-square test and one-way ANOVA between the groups. Receiver operating characteristic (ROC) curves were used to analyse the clinical efficacy of IFI44 and EPSTI1 in distinguishing SCLE from SLE. RESULTS: In a comparative analysis of SCLE lesions and normal skin tissues, proteomics studies identified 376 proteins that exhibited significant differential expression. In GO and KEGG analyses, the enriched terms mainly included the interferon-gamma-mediated signalling pathway (p < .001), immune receptor activity (p < .001) and cell adhesion molecules (p < .001). The top 10 hub genes were screened in SCLE as follows: CD8A, CXCL10, IFI44, CD7, CCL5, TLR4, EPSTI1, ISG15, KLRD1 and SELL using Cytoscape (3.10.1) software. The 15 common proteins/genes between proteomics and three datasets results were found, including CXCL10, OAS1, DDX60L, CFB, IFI6, HERC6, IFI44L, GBP1, EPSTI1, OAS2, CXCL11, TYMP, IFI44, ISG15 and IFIT3. The 61 differentially expressed genes in GSE81622 and the top 100 differentially expressed genes in GSE154851, alongside the 15 identified genes described above through Venn diagram analysis. Four common genes, IFI44L, IFI44, EPSTI1 and OAS1, were identified. Two common genes, IFI44 and EPSTI1, were found in hub genes from the proteomics results. The serum levels of IFI44 and EPSTI1 in LN were significantly higher than those in SLE patients (p < .05). ROC curve analysis demonstrated that serum levels of IFI44 and EPSTI1 could differentiate SCLE from SLE with an area under the curve (AUC) of 0.898 and 0.847, respectively. CONCLUSIONS: The IFI44 and EPSTI1 proved to be closely involved in the progression from SCLE to SLE, and can represent new candidate diagnostic molecular markers of occurrence and progression of SCLE.

Humans↗

PubMed2025

Development and validation of a novel risk stratification signature derived from migrasome and tumor microenvironment-related genes for molecular subtyping and improving clinical outcomes in head and neck squamous cell carcinoma.

BACKGROUND: The tumor microenvironment (TME) and migrasomes released by tumor cells significantly influence carcinogenesis and immune evasion. However, our understanding of the prognostic and therapeutic implications of migrasome and tumor microenvironment-related genes (mtmRGs) in head and neck squamous cell carcinoma (HNSCC) remains limited. METHODS: We explored the relationship between mtmRGs and HNSCC prognosis by utilizing The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Subsequently, we developed an innovative prognostic signature, and assessed its prognostic significance using the Kaplan-Meier method, time-dependent receiver operating characteristic (ROC), and Cox regression analyses. To explore the underlying mechanisms, we conducted gene set variation analysis (GSVA), gene set enrichment analysis (GESA), and immune infiltration analysis. A nomogram was developed to estimate the overall survival (OS) rates for HNSCC patients. Lastly, we chose P4HA1, which was part of the signature, for additional experimental validation in vitro and in vivo. RESULTS: The mtmRGs signature effectively classifies HNSCC patients into two distinct risk subgroups, with the high-risk cohort demonstrating significantly poorer OS. The risk score serves as an independent prognostic factor for HNSCC patients; those with lower risk scores are more likely to exhibit favorable responses to immunotherapy, particularly with CTLA4 inhibitors. Furthermore, a lower risk score is significantly correlated with the sensitivity of HNSCC patients to cyclophosphamide, gemcitabine, and axitinib. CONCLUSION: This study presents an innovative gene signature associated with mtmRGs, which may be utilized both for predicting survival and directing personalized chemotherapy and immunotherapy regiments for patients with HNSCC.

Humans↗

PubMed2025

ANXA3 hypomethylation as a prognostic biomarker in hepatitis B virus-related acute-on-chronic liver failure.

BACKGROUND: Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is associated with a poor prognosis. This research aimed to characterize the expression pattern and clinical value of Annexin A3 (ANXA3) in HBV-ACLF patients. METHODS: First of all, ACLF-related datasets were downloaded from the Gene Expression Omnibus (GEO) database to carry out bioinformatics analyses. RT-qPCR, ELISA, and Methylight were used to measure ANXA3 gene expression and promoter methylation levels. A validation cohort was leveraged to further validate the results. RESULTS: Transcriptome analysis showed that ANXA3 was among the most differentially expressed genes when comparing dead patients with HBV-ACLF to those with survivors. The mRNA and serum levels of ANXA3 were elevated, and methylation levels were decreased in HBV-ACLF patients. The PMR value of ANXA3 in patients with HBV-ACLF was negatively correlated with inflammation-related cytokines IL-6, TNF-α, and IL-1β, as well as quantitative clinical parameters AST, TBIL, PT, INR, NEUT%, and MELD score, and positively correlated with PTA (all p < 0.05). In HBV-ACLF patients, ANXA3 was considered to be an independent influence factor for the 90-day mortality. It was also found that ANXA3, especially hypomethylation, was associated with 28- and 90-day overall survival in patients with HBV-ACLF based on receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and Kaplan-Meier curves. CONCLUSIONS: ANXA3 hypomethylation has a prominent predictive value for short-term mortality in patients with HBV-ACLF and may serve as a promising biomarker of HBV-ACLF prognosis.

Humans↗

PubMed2026

Integrated bioinformatics analysis reveals cross-talking hub genes and therapeutic agents between sepsis and acute myocardial infarction.

BACKGROUND: Sepsis and acute myocardial infarction (AMI) are two significant diseases that may share overlapping etiological mechanisms. This study aims to systematically identify core genes common to both conditions and to explore their potential as therapeutic targets and drug candidates through an integrative analysis of clinical data and bioinformatics. METHODS: The AMI dataset was obtained from the GEO database, and RNA sequencing data were collected from blood samples of patients with sepsis at our hospital. Common genes were identified using differential expression gene analysis (DEG) and weighted gene co-expression network analysis (WGCNA). Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were performed. A protein-protein interaction (PPI) network was constructed, and hub genes were identified using the MCC/Degree algorithm. Diagnostic value was assessed via receiver operating characteristic curve analysis. Immune infiltration patterns, single-cell sequencing data, and molecular docking simulations were employed to evaluate immune relevance and identify potential therapeutic compounds. RESULTS: A total of 417 genes were identified between sepsis and AMI, with enrichment analysis revealing significant involvement in inflammatory responses. Three hub genes-JAK2, MYD88, and TIMP1-were selected for further investigation. ROC curves confirmed their strong diagnostic performance for both diseases. Immune infiltration analysis showed that these core genes were significantly correlated with the infiltration levels of various immune cell types. Molecular docking indicated that quercetin exhibited stable binding affinity with the proteins encoded by these genes. qPCR validation further confirmed the upregulation of these three genes, supporting the anti-inflammatory effects of quercetin as a potential targeted therapy. CONCLUSION: JAK2, MYD88, and TIMP1 were identified as shared core genes in sepsis and AMI. These genes not only serve as potential diagnostic biomarkers but also offer novel targets for developing common therapeutic strategies for both conditions. Furthermore, quercetin emerges as a promising candidate for targeted treatment.

Humans↗

PubMed2025

scPOEM: robust co-embedding of peaks and genes revealing peak-gene regulation.

MOTIVATION: Identifying regulatory elements in various chromosomal regions that influence gene expression is a fundamental challenge in epigenomics, with profound implications for understanding gene regulation and disease mechanisms. The advent of paired single-cell RNA sequencing and single-cell ATAC sequencing has created unprecedented opportunities to address this challenge by enabling simultaneous profiling of gene expression and chromatin accessibility at single-cell resolution. However, the inherent signals between them are weak due to the highly sparse and noisy nature of data. RESULTS: This article proposes single-cell meta-Path based Omics Embedding (scPOEM), a novel embedding method that jointly projects chromatin accessibility peaks and expressed genes into a shared low-dimensional space. By integrating the relationships among peak-peak, peak-gene, and gene-gene interactions, scPOEM assigns closer representations in the embedding space to related peak-gene pairs. Our experiments demonstrate that scPOEM generates stable representations of peaks and genes, outperforms existing methods in recovering biologically meaningful peak-gene regulatory relationships and enables new insights in subgroup and differential analysis of gene regulation. These results highlight its potential to uncover gene regulatory mechanisms and enhance the understanding of transcriptional regulation at single-cell resolution. AVAILABILITY AND IMPLEMENTATION: The source code of scPOEM is available at https://github.com/Houyt23/scPOEM. The datasets can be obtained from the 10× Genomics (https://www.10xgenomics.com/datasets/pbmc-from-a-healthy-donor-granulocytes-removed-through-cell-sorting-10-k-1-standard-1-0-0) and GEO database under access codes GSE194122 and GSE239916.

Gene Expression Regulation↗

PubMed2005

Skeletal muscle gene expression profiling in mitochondrial disorders.

Extremely variable clinic and genetic features characterize mitochondrial encephalomyopathy (MEM). Pathogenic mitochondrial DNA (mtDNA) defects can be divided into large-scale rearrangements and single point mutations. Clinical manifestations become evident when a threshold percentage of the total mtDNA is mutated. In some MEM, the "mutant load" in an affected tissue is directly related to the severity of the phenotype. However, the clinical phenotype is not simply a direct consequence of the relative abundance of mutated mtDNA. Other factors, such as nuclear background, can contribute to the disease process, resulting in a wide range of phenotypes caused by the same mutation. Using Affymetrix oligonucleotide cDNA microarrays (HG-U133A), we studied the gene expression profile of muscle tissue biopsies obtained from 12 MEM patients [4 common 4977 bp deleted mtDNA and 8 A3243G: 4 progressive external ophthalmoplegia (PEO) and 4 mitochondrial myopathy, encephalopathy, lactic cidosis, and stroke-like episodes syndrome (MELAS) phenotypes] compared with age-matched healthy individuals. We found several differentially expressed genes: 35 were markedly up-regulated in the mtDNA macro-deletion group (vs. the control group) and 4 decreased; 56 genes were dysregulated in A3243G-related disorders (53 down-regulated in PEO and 3 up-regulated in MELAS). Finally, 12 genes were similarly regulated in the majority of the MEM patients under study. Amongst these, we identified an increased expression of genes related to the metabolism of the amino groups, as well as of several genes involved in genetic information processing. Moreover, few genes were similarly decreased in MEM patients vs. the control group. Real-time PCR demonstrated excellent reproducibility of the microarray-based findings. The observed expression changes are likely to represent a molecular signature for mitochondrial disorders. Furthermore, the differential expression profile of MELAS(A3243G) vs. PEO(A3243G) may support a role of nuclear background in contributing to these different clinical phenotypes. MEM microarray data are available from GEO database (http://www.ncbi.nlm.nih.gov/geo/) with the accession number: GSE1462.

Adolescent↗

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↗

PubMed2025

Integrated data mining and network pharmacology to explore the prescription patterns from a senior TCM oncologist's clinical practice in treating chemotherapy-induced hand-foot syndrome.

Hand-foot syndrome (HFS) is a common and refractory adverse effect of chemotherapy lacking specific therapeutic strategies currently. Traditional Chinese medicine (TCM) has shown empirical efficacy in clinical HFS management. This study integrated data mining and network pharmacology to systematically elucidate the medication principles and molecular mechanisms underlying Professor Gang Xie's prescriptions for HFS. All medical records from Professor Xie's specialist clinic (January 2020 to March 2025) were retrospectively collected and standardized in Excel. Prescriptions were analyzed through frequency statistics, association and clustering. Active ingredients of core herb pairs and their disease-related targets were identified using TCMSP, HERB, GeneCards, PharmGKB and GEO databases. Protein-protein interaction (PPI) networks, gene ontology (GO), and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses were performed. Molecular docking validated interactions between key bioactive compounds and targets. This study involved 217 prescriptions containing 150 herbs. Core herb combinations comprised Radix Astragali (Huangqi), Poria (Fuling), and Radix Pseudostellariae (Taizishen), predominantly classified as spleen-tonifying agents with warm properties, targeting lung, spleen, and stomach meridians. Network analysis identified 67 bioactive compounds and 899 disease targets. Quercetin, kaempferol, acacetin and luteolin were identified the key ingredients. The core targets (TP53, STAT3, PIK3CA, HSP90AA1, AKT1, CTNNB1, PI3KR1, MAPK1) were enriched in MAPK and PI3K-Akt signaling pathways. Molecular docking confirmed strong binding affinity between key compounds and targets. Professor Xie's therapeutic strategy for HFS emphasizes "spleen fortification, phlegm elimination, and stasis resolution." The core herb combination likely exerts anti-HFS effects via modulation of MAPK and PI3K-Akt pathways, providing a pharmacological basis for TCM-driven HFS management.

Network Pharmacology↗

PubMed2026

Screening of biomarkers related to lung adenocarcinoma based on construction of ceRNA regulation network.

BACKGROUND: Lung adenocarcinoma (LUAD) is a common malignant tumor with a poor prognosis and limited effective therapeutic targets. The underlying molecular regulatory mechanisms driving its progression remain largely unclear. The study objectives were to build a circRNA-miRNA-mRNA ceRNA regulation network of LUAD and to identify miRNAs and mRNAs significantly related to the prognosis . METHODS: The gene expression data and GSE101684 were downloaded from the UCSC Xene and NCBI-GEO databases, respectively. The differentially expressed RNAs (DEcircRNAs, DEmiRNAs, and DEmRNAs; DERs) were obtained by the Limma package in R. Then, the differential LUAD-related genes were identified, and the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the differential LUAD-related genes were analyzed. Moreover, the circRNA-miRNA-mRNA ceRNA network of LUAD was built. The Kaplan-Meier (K-M) survival curve analysis of ceRNA network nodes was performed. In addition, the proliferation-related ceRNA network was built. RESULTS: A total of 382 DEcircRNAs, 1907 DEmRNAs and 156 DEmiRNAs were acquired. A total of 245 differential LUAD-related genes were acquired, which were significantly associated with 189 GO biological processes (BP) and 17 KEGG pathways. Moreover, the ceRNA network of LUAD was built. The K-M survival curve analysis of ceRNA network nodes revealed that a total of 2 miRNAs (hsa-miR-96-5p and hsa-miR-125b-2-3p) and 22 mRNAs (CGNL1, CTHRC1, TK1, etc) were significantly related to the prognosis. mRNAs were significantly enriched in 92 GO BPs (such as cell division, cell adhesion) and 9 KEGG pathways (such as cell cycle, HTLV-1 infection). In addition, the proliferation-related ceRNA network was built. CONCLUSION: This research built a ceRNA regulation network of LUAD and is of great significance for identifying biomarkers related to the prognosis in LUAD.

Humans↗

PubMed2026

Identification of a necroptosis-related lncRNA prognostic signature and the hub RBP HNRNPK in esophageal squamous cell carcinoma.

ObjectiveEsophageal squamous cell carcinoma (ESCC) is a malignant tumor with poor prognosis. Necroptosis is important for tumor immunity, but its role in ESCC remains unclear. This retrospective bioinformatics study aimed to investigate the prognostic value of necroptosis-related long non-coding RNAs (lncRNAs) and to identify key lncRNA-binding proteins (RBPs) in ESCC patients.MethodsRNA transcriptome and clinical data of ESCC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Necroptosis-related lncRNAs were identified through correlation analysis with necroptosis-related genes, subjected to consensus cluster analysis, and used to construct a prognostic risk model via least absolute shrinkage and selection operator (LASSO) regression. The hub RBP was experimentally validated by quantitative polymerase chain reaction (qPCR) using 30 pairs of ESCC and adjacent normal tissues from patients who underwent surgical resection.ResultsA total of 30 necroptosis-related lncRNAs were significantly correlated with overall survival (OS). The upregulated lncRNAs in the risk model were associated with high immune scores, innate immune cell infiltration, cluster 2 classification, and advanced T-stage disease (p < 0.05). Three hub RBPs (HNRNPA1, HNRNPC, and HNRNPK) were identified through protein-protein interaction network analysis. qPCR confirmed that HNRNPK was significantly overexpressed in ESCC tissues compared to adjacent normal tissues (p < 0.05).ConclusionsThe necroptosis-related lncRNA risk model is an independent prognostic factor for ESCC patients. HNRNPK was identified as a hub RBP significantly overexpressed in ESCC tissues. We hypothesize that HNRNPK may promote tumor progression through regulating proto-oncogene expression or modulating the immune microenvironment, though this requires further mechanistic validation.

Humans↗

PubMed2024

Comprehensive analysis of circRNA-miRNA-mRNA network related to angiogenesis in recurrent implantation failure.

BACKGROUND: Abnormal endometrial blood flow causes a decrease in endometrial receptivity and is considered a relatively independent risk factor for recurrent implantation failure (RIF). This study aimed to explore the potentially functional circRNA-miRNA-mRNA network in RIF, and further explore its mechanism. METHODS: Datasets were downloaded from the GEO database to identify differentially expressed circRNAs, miRNAs and mRNAs. The circRNA-miRNA-mRNA and PPI networks were constructed using Cytoscape 3.6.0 and the STRING database, the hub genes were identified with the cytoHubba plug-in, and a circRNA-miRNA-hub mRNA regulatory sub-network was constructed. Then, GO and KEGG pathway enrichment analyses of the hub genes were performed to comprehensively analyze the mechanism of hub mRNAs in RIF. Due to the results of circRNAs-miRNAs-hub mRNAs regulatory network, we verified the expression of circRNA_0001721, circRNA_0000714, miR-17-5p, miR-29b-3p, HIF1A and VEGFA in the RIF mouse model by qRT‒PCR and western blotting. RESULTS: We initially identified 175 DEmRNAs, 48 DEmiRNAs and 56 DEcircRNAs in RIF associated with angiogenesis and constructed a circRNA-miRNA‒mRNA network and PPI network. We further identified six hub genes in the acquired network. Based on these genes, functional enrichment analysis revealed that the HIF-1 signaling pathway plays a vital role in endometrial angiogenesis in RIF. In addition, the interaction networks of circRNA_0001721/miR-17-5p/HIF1A and the circRNA_0000714/miR-29b-3p/VEGFA axis were predicted. In the RIF mouse model, circRNA_0001721, circRNA_0000714, HIF1A and VEGFA were down-regulated, whereas miR-17-5p and miR-29b-3p were up-regulated according to qRT‒PCR and western blotting. CONCLUSION: This study revealed that the HIF-1 signaling pathway plays a vital role in endometrial angiogenesis in RIF. The circRNA_0001721/miR-17-5p/HIF1A and circRNA_0000714/miR-29b-3p/VEGFA axes might play a role in the pathogenesis of endometrial angiogenesis in RIF.

MicroRNAs↗

PubMed2024

Analysis of different expression RNA binding protein genes in mouse microglia cell from the brains of mice 72 h after subarachnoid hemorrhage or sham operation.

BACKGROUND: The prognosis of brain injury caused by subarachnoid hemorrhage (SAH) is poor. Previous studies showed that abnormal function of RBPs might be involved in brain injury, neuroinflammation and further affect microglia homeostasis. However, no studies have systematically analyzed the genome-wide abnormal expression of RBPs genes in microglia during SAH. METHODS: RNA-seq data of microglia from the SAH mouse group (SAH) and control sham-operated mouse group (sham) were downloaded from the GEO database in GSE167957, including four samples from the sham group and four samples from the SAH group for subsequent analysis.Utilizing GO and KEGG functional enrichment analyses, we conducted a comprehensive study of differentially expressed genes (DEGs), alternative splicing patterns, and co-expression networks to gain deeper insights into the differential expression of RNA-binding proteins (RBPs) and differential alternative splicing events (ASEs) between the SAH (subarachnoid hemorrhage) and sham groups. This analysis aimed to elucidate the potential mechanisms underlying the aberrant expression of RBPs in microglia during brain injury caused by SAH. RESULTS: ASEs and co-expression analyses of differentially expressed RBPs and differential ASEs were carried out in microglia in terms of gene expression. GO and KEGG functional enrichment analysis showed that aberrantly expressed RBPs such as Mcm7, Mtdh, SRSF3, and Hnrnpa2b1 may affect and regulate downstream Csnk1d, Uckl1 and other protein phosphorylation-related genes by alterative splicing. CONCLUSION: RBPs were aberrantly expressed in microglia during the development of brain injury secondary to SAH, regulating alterative splicing of downstream genes and influencing the progression of SAH brain injury in this study. This implies that RBPs are important for the identification of new therapeutic targets for brain injury after SAH.

Animals↗

PubMed2025

FOSB is a key factor in the genetic link between inflammatory bowel disease and acute myocardial infarction: multiple bioinformatics analyses and validation.

BACKGROUND: Inflammatory Bowel Disease (IBD), which includes Crohn's disease and ulcerative colitis, is associated with an increased risk of Acute Myocardial Infarction (AMI). The genetic mechanisms underlying this link are not well understood. METHODS: We downloaded IBD and AMI-related microarray datasets from the NCBI Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified and analyzed using enrichment analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Machine learning techniques, including LASSO, random forest, and Boruta, were employed to screen for hub genes. These genes were validated through qRT-PCR and Western blotting. Single-cell sequencing was used to confirm findings. Additionally, potential therapeutic targets were identified using the Connectivity Map (CMap) database. RESULTS: Five key hub genes-THBD, FOSB, ADGPR3, IL1R2, and PLAUR-were identified as significantly involved in both IBD and AMI pathogenesis. A diagnostic model for AMI constructed using these hub genes demonstrated high predictive accuracy. Single-cell sequencing analysis and several potential drugs targeting these hub genes were identified, offering new therapeutic avenues. CONCLUSION: This study highlights the crucial role of FOSB and other hub genes in the comorbidity of IBD and AMI. The findings provide novel insights for early diagnosis and potential therapeutic strategies, emphasizing the importance of further investigation into these genetic links.

Humans↗

PubMed2025

Comprehensive analysis of diagnostic biomarkers related to histone acetylation in acute myocardial infarction.

BACKGROUND: Acute myocardial infarction (AMI) has become a serious disease that endangers human health, with high morbidity and mortality. Numerous studies have reported histone acetylation can result in the occurrence of cardiovascular diseases. This article aims to explore the potential biomarkers of histone acetylation regulatory genes (ARGs) in AMI patients. METHODS: Five AMI datasets were downloaded from the Gene Expression Omnibus (GEO) database. Next, ARG-related genes were gathered by gene set variation analysis (GSVA) and Spearman's correlation analysis. Subsequently, weighted gene co-expression network analysis (WGCNA) was performed to identify the module genes related to histone acetylation regulation. In the GSE60993 and GSE48060 datasets, the common differentially expressed genes (DEGs) between AMI and control samples were screened. Importantly, the intersecting genes were obtained by overlapping ARGs-related genes, common DEGs, and module genes. Then, the biomarkers in AMI were determined by machine learning, receiver operating characteristic (ROC) curves, and quantitative PCR (qPCR). In addition, immune analysis, drug prediction, molecular docking, and the lncRNA-miRNA-mRNA regulatory network targeting the biomarkers were analyzed, respectively. RESULTS: Here, a total of 18 intersecting genes were identified by overlapping 7,349 ARGs-related genes, 5,565 module genes, and 25 common DEGs. Further, five biomarkers (AQP9, HLA-DQA1, MCEMP1, NKG7, and S100A12) were obtained, and a nomogram was constructed and verified based on these biomarkers. Notably, the biomarkers were significantly associated with CD8 T cells and neutrophils. In addition, the drugs related to biomarkers were predicted, and ATOGEPANT with the molecular target (S100A12) had a high binding affinity (docking score = -10 kcal/mol). CONCLUSION: AQP9, HLA-DQA1, MCEMP1, NKG7, and S100A12 were identified as biomarkers related to ARGs in AMI, which provides a new perspective to study the relationship between ARGs and AMI.

Humans↗

PubMed2025

Identification and validation of the important role of KIF11 in the development and progression of endometrial cancer.

BACKGROUND: Human kinesin family member 11 (KIF11) plays a vital role in regulating the cell cycle and is implicated in the tumorigenesis and progression of various cancers, but its role in endometrial cancer (EC) is still unclear. Our current research explored the prognostic value, biological function and targeting strategy of KIF11 in EC through approaches including bioinformatics, machine learning and experimental studies. METHODS: The GSE17025 dataset from the GEO database was analyzed via the limma package to identify differentially expressed genes (DEGs) in EC. Functional enrichment analysis of the DEGs was conducted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. DEGs were further screened for hub genes through protein-protein interaction (PPI) network analysis and machine learning. The role of the hub gene KIF11 in EC was analyzed using clinical data from the TCGA database. The expression of KIF11 in EC was subsequently validated in clinical samples. In vitro experiments were utilized to evaluate the effects of KIF11 on biological functions such as proliferation, migration, apoptosis, and the cell cycle in endometrial cancer cells. RESULTS: A total of 877 DEGs, which are widely involved in important biological processes such as cell division, tubulin binding, and the cell cycle, were identified. Through PPI network analysis and machine learning, KIF11 was selected as the hub gene for subsequent analysis and experimental validation. An analysis of TCGA data revealed that KIF11 is highly expressed in EC and is associated with tumor grade, stage, and a low survival rate. The overexpression of KIF11 in tumor tissues was further confirmed in EC patient samples. KIF11 knockdown had inhibitory effects on cell proliferation, migration and invasion. Flow cytometry analysis revealed that KIF11 knockdown induced G2/M phase arrest and promoted apoptosis in EC cells. CONCLUSION: Our study demonstrated that KIF11 was upregulated in EC and was strongly associated with a poor prognosis. Notably, we found that reduced KIF11 expression inhibited EC cell proliferation, migration and invasion. KIF11 knockdown caused more EC cells to arrest in the G2/M phase and undergo apoptosis. The findings of our study emphasized that KIF11 may be a promising prognostic biomarker and therapeutic target for EC patients.

Humans↗

PubMed2025

An anti-androgen resistance-related gene signature acts as a prognostic marker and increases enzalutamide efficacy via PLK1 inhibition in prostate cancer.

BACKGROUND: Anti-androgen resistance remains a major clinical challenge in the treatment of prostate cancer (PCa), leading to disease progression and treatment failure. Despite extensive research on resistance mechanisms, a reliable prognostic model for predicting patient outcomes and guiding therapeutic strategies is still lacking. This study aimed to develop a novel gene signature related to anti-androgen resistance and evaluate its prognostic and therapeutic implications. METHODS: Anti-androgen resistance-related differentially expressed genes (ARRDEGs) were identified through transcriptomic analysis of enzalutamide- and dual enzalutamide abiraterone-resistant PCa cell lines from the GEO database. Functional enrichment analysis was performed to determine the biological roles of these genes. A prognostic gene signature was developed using univariate Cox regression, LASSO, and multivariate Cox regression models. The model was validated in independent PCa cohorts from The Cancer Genome Atlas (TCGA). Additionally, we assessed the correlation between the signature, immune infiltration, immune checkpoint expression, and drug sensitivity. The efficacy of PLK1 inhibition combined with enzalutamide was further explored using in vitro and in vivo experiments. RESULTS: We identified 304 ARRDEGs, from which three key genes (LMNB1, SSPO, and PLK1) were selected to construct a prognostic signature. This gene signature effectively stratified PCa patients into high- and low-risk groups, with the high-risk group exhibiting shorter recurrence-free survival and distinct immune characteristics. High-risk patients demonstrated elevated immune checkpoint expression (B7H3, CTLA-4, B7-1, and TIGIT), increased M2 macrophage infiltration, and enhanced sensitivity to chemotherapy and targeted therapy. Mechanistically, PLK1 inhibition potentiated the antitumor effect of enzalutamide by downregulating SLC7A11 and inducing ferroptosis, providing a potential therapeutic strategy to overcome anti-androgen resistance. CONCLUSION: We established a novel ARRDEGs-based prognostic signature that predicts PCa progression and response to chemotherapy and targeted therapy. The integration of this signature with immune profiling and drug sensitivity analysis provides a valuable tool for precision oncology in PCa. Our findings highlight the potential of PLK1 inhibition as a therapeutic strategy to enhance enzalutamide efficacy and overcome resistance.

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↗