Jul 2026· Gene· pp.
150319
· 0 citations· 51 references
Medicine
TL;DR
This study attempted to investigate the pathogenic mechanism of endometritis and discover potential biomarkers for diagnosing and treating endometritis, finding hub genes (ALDH3A2 and ACSS3) play critical roles in the pathogenesis of endometritis by interacting with different metabolites.
Abstract
Endometritis is an inflammatory endometrium condition affecting reproductive outcomes. However, the pathology of endometritis is poorly understood. Thus, we attempted to investigate the pathogenic mechanism of endometritis and discover potential biomarkers. Transcriptome sequencing was performed on endometritis patient-derived endometrial tissues (n = 3) and normal controls (n = 5). Differentially expressed genes (DEGs) between disease and control groups were identified. Mitochondrial genes were filtered based on MitoCarta3.0. Small RNA sequencing (9 disease samples vs. 6 controls) was combined with differentially expressed (DE) mitochondrial genes to generate a competing endogenous RNA (ceRNA) network, followed by protein-protein interaction network analysis. Metabolome analysis was conducted to explore differentially expressed metabolites (4 cases vs. 4 controls). Comparative analysis revealed a total of 1,507 DEGs in disease group relative to controls, which were implicated in adaptive immune response, cell chemotaxis, and chemotaxis signaling pathways. In total, 28 mitochondrial genes were differentially expressed and mapped to the ceRNA network. ALDH3A2, ACSS3, CYP24A1, and KMO were identified as hub genes and were closely associated with the infiltration of CD8 T cells. CYP24A1 was found to be the target of four drugs, including calcitriol and deferasirox. Five metabolic pathways were significantly enriched, including the citrate cycle (TCA cycle) and taurine and hypotaurine metabolism. ALDH3A2, ACSS3, and KMO showed interactions with metabolites and significant pathways. Hub genes (ALDH3A2 and ACSS3) play critical roles in the pathogenesis of endometritis by interacting with different metabolites. Our study offers candidate biomarkers for diagnosing and treating endometritis.
It is suggested that OEM is associated with concurrent immune-related and metabolic alterations detectable in the circulation and provides limited independent support for a platelet-associated circulating signal, with PPBP showing the most consistent validation.
Na Chen, Yubing Hu, Tianxia Xiao et al.· Frontiers in Medicine· 0 citations
Background Endometriosis is a chronic, estrogen‐dependent inflammatory disorder characterized by the ectopic implantation of endometrial‐like tissue. Although retrograde menstruation is highly prevalent, only a subset of women develops the disease. This epidemiologic paradox suggests that intrinsic molecular alterations in the eutopic endometrium may precondition refluxed cells to survive under inflammatory and oxidative stress. Methods Eutopic endometrial transcriptomes from the GSE6364 dataset (21 endometriosis patients and 16 controls) were analyzed across menstrual phases. Differential expression analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and hallmark inflammatory gene set profiling were performed. Protein–protein interaction (PPI) networks and three machine‐learning algorithms maximal clique centrality (MCC), random forest (RF), and least absolute shrinkage and selection operator (LASSO) were applied to identify robust feature genes. Immune cell infiltration was estimated using CIBERSORT . Excision repair cross‐complementation group 1 (ERCC1) was further evaluated via cross‐species evolutionary conservation and in silico structural modeling of high‐risk variants. Additionally, an exploratory stemness–related single‐sample gene set enrichment analysis (ssGSEA) was conducted, and correlations between the stemness score and the feature genes were examined. Results A total of 443 differentially expressed genes (DEGs) were identified, which were significantly enriched in inflammatory cascades, including the NF‐κB, Toll‐like receptor, and cytokine signaling pathways. Four convergent feature genes ERCC1, SOX3, P75NTR (encoded by NGFR), and FPR1 were prioritized. Immune deconvolution revealed selective immune remodeling in the eutopic endometrium, characterized by elevated activated natural killer (NK) cells and reduced CD8+ T cells, which correlated significantly with the expression of the feature genes. ERCC1 exhibited high evolutionary conservation, and structural modeling of missense variants predicted the disruption of protein function within conserved DNA repair domains. Exploratory stemness analysis revealed no significant overall case–control difference after adjusting for menstrual phase, though the early secretory subset exhibited a marginally higher score in endometriosis. Conclusions These findings highlight a stress‐adaptive transcriptomic state in the eutopic endometrium driven by inflammatory signaling, selective immune remodeling, and altered DNA repair capacity. Specifically, ERCC1 may serve as a critical mechanistic link between inflammatory pressure and impaired genomic maintenance, thereby facilitating cellular persistence and lesion establishment. Furthermore, our data indicate that this four‐gene signature primarily reflects a DNA‐repair‐adaptive program rather than a global bulk‐tissue stemness shift.
Juan Wang, Wangshu Li, Jiu-Xiang Feng et al.· Stem Cells International· 0 citations
It is confirmed that ESCC exhibits significant amino acid metabolic dysregulation, with arginine related metabolic pathways being significantly enriched, and NO can serve as a potential non-invasive biomarker for distinguishing ESCC.
Kaiyuan Yao, Shunshun Zhang, Siya Tang et al.· Frontiers in Molecular Biosc...· 0 citations
Hypertrophic scar (HTS) is a fibrotic skin disease characterized by excessive extracellular matrix accumulation and chronic inflammation. This study aimed to investigate cellular heterogeneity, immune alterations, and nucleotide metabolism-related biomarkers in HTS and to explore their potential mechanisms. Single-cell RNA sequencing data were analyzed using Seurat for cell clustering and annotation. Nucleotide metabolism activity was evaluated to identify key cell populations and candidate genes. Bulk transcriptomic datasets from the Gene Expression Omnibus (GEO) were used for differential expression analysis, and machine learning algorithms were applied to develop a diagnostic model. Sixteen cell clusters were identified, with macrophages showing prominent activation of nucleotide metabolism pathways and immune-related signaling. The optimal Enet + svmLinear model achieved strong predictive performance (AUC = 0.934), and SHAP analysis identified NCF1 and GPR34 as key predictive genes. These genes were also associated with immune cell infiltration. In vitro validation using THP-1-derived M2 macrophages showed that NCF1 and GPR34 promoted TGF-β1 secretion and enhanced fibroblast activation, while their knockdown reduced α-SMA and collagen I expression. Collectively, this study reveals the important role of macrophage-associated nucleotide metabolism in HTS and identifies NCF1 and GPR34 as potential biomarkers and therapeutic targets.
Qiyun Luo, Xia Yang, Jiang-Yong Shen et al.· Journal of Burn Care & Resea...· 0 citations
Molecular changes in the gynecological cancers are complex and play a pivotal role in disease onset, progression and drug resistance. Transcriptomics is a powerful tool to discover the altered genes and pathways in cervical cancer. The present study aimed to identify differentially expressed genes and enriched molecular pathways associated with cervical cancer and to highlight potential mechanistic and therapeutic targets. A secondary transcriptomic dataset comprising cervical, endometrial, and vulvar cancer and normal tissue samples was analyzed, with a focused comparison between cervical cancer and normal cervical tissues. Genes with low variance were filtered, probe identifiers were mapped to gene symbols, and differential expression analysis was performed using a threshold of p < 0.01 and |log2 fold change| ≥ 1. Functional interpretation was carried out using Gene Ontology and KEGG pathway enrichment analyses for both upregulated and downregulated gene sets. A total of 628 differentially expressed genes were identified, including 323 upregulated and 305 downregulated genes. Upregulated genes were primarily enriched in DNA replication, DNA metabolic processes, mitotic spindle organization, cell cycle regulation, p53 signaling, and homologous recombination, with key candidates including MCM4, MCM2, FEN1, CDK1, CCNB1, and PCNA. In contrast, downregulated genes were associated with extracellular matrix assembly, epithelial development, muscle contraction, Wnt signaling, and focal adhesion, including ZFP36L2, LTBP4, MYL9, and TAGLN. These findings indicate a transcriptional shift toward enhanced proliferative and genome maintenance activity alongside suppression of structural and differentiation-related processes. The results provide mechanistic insight into cervical cancer etiology and identify candidate molecular targets for further validation and therapeutic exploration.
D. S, Dr. P Vinod Kumar, Dr Sk Erfanul Haque· Genetics and Molecular Resea...· 0 citations
INTRODUCTION
Preeclampsia (PE) pathogenesis involves immune dysregulation, but key drivers remain unclear. This study aimed to identify placental immune regulators in PE using integrative transcriptomics and scPagwas analysis.
METHODS
We integrated single-cell RNA sequencing (GSE173193, n = 4) and bulk transcriptomic data (GSE75010, n = 157) from placental tissues. scPagwas algorithm assessed genetic associations. Pseudotime trajectory was constructed using Monocle. Key genes were identified by intersecting LASSO and random forest algorithms. Immune infiltration was evaluated by CIBERSORT, pathway enrichment by GSEA/GSVA, and regulatory networks/drug interactions predicted using RcisTarget, miRcode, and CTD.
RESULTS
Ten placental cell subtypes were characterized. Macrophages showed the highest genetic correlation with PE and exhibited abnormal stemness in lesions. Three hub genes (ARL4C, SLC16A10, DAB2) were significantly dysregulated in PE macrophages, correlating with altered immune infiltration (elevated eosinophils/plasma cells; reduced M2 macrophages/neutrophils). They were enriched in TNF signaling, PI3K-AKT-mTOR, oxidative phosphorylation, and complement cascades, and correlated with established PE genes (FLT1, FURIN). Upstream transcription factors, 128 miRNA-mRNA pairs, and candidate drugs were identified.
DISCUSSION
This study identifies macrophages as central immune mediators in PE and pinpoints ARL4C, SLC16A10, and DAB2 as key regulators of macrophage polarization, representing promising diagnostic and therapeutic targets.
Hongbiao Yu, Ling Chen, Ping Du et al.· Journal of Reproductive Immu...· 0 citations