Unraveling role of arginine-NO metabolism by targeting HIF-1α signaling in mediating esophageal squamous cell carcinoma

Integrated Proteomics and Metabolomics Analysis Provides Insights into Metformin Down-regulating GLUL and SP1 to Inhibit Esophageal Squamous Cell Carcinoma Migration and Invasion.

INTRODUCTION Esophageal Cancer (EC) is a prevalent gastrointestinal malignancy. Despite significant advances in diagnostic and therapeutic approaches, the prognosis of Esophageal Squamous Cell Carcinoma (ESCC) remains poor. The development of new therapeutic agents for ESCC would greatly benefit patients and their families. Metformin has been found to be useful in other tumours, but its role and mechanism in ESCC have not been investigated. METHODS The effect of metformin on inhibiting invasive metastasis in ESCC cells was explored by in vitro cytology experiments. 4D-DIA proteomics and untargeted LC-MS metabolomics provided critical technical support for this study. The roles and mechanisms of differential proteins, metabolites, and key metabolic pathways in ESCC migration and invasion were further explored by identifying differentially expressed proteins and metabolites in metformin-treated ESCC cells using proteomics and metabolomics. RT-qPCR and Western blot were used to confirm metformin's inhibitory effects on key proteins in metabolic pathways associated with ESCC cell migration and invasion. Using the ESCC tissue microarray (TMA) to detect the expression levels of GLUL and SP1. RESULTS This study demonstrated that metformin significantly reduced ESCC cells' viability, proliferation, migration, and invasion, while enhancing apoptosis. Integrated multi-omics pathway analysis revealed the activation of several metabolic pathways following metformin treatment in ESCC cells. In vitro experiments confirmed that metformin significantly downregulated the key proteins GLUL and SP1, as identified in the differential proteomics analysis. Immunohistochemistry (IHC) showed that GLUL and SP1 expression were significantly lower in ESCC tumor tissues from patients with a history of preoperative metformin administration than in those without. DISCUSSION Enhanced glutamine metabolism in tumors promotes cancer progression. Downregulation of GLUL reduces glutamine production from the alanine, aspartate, and glutamate metabolic pathways, thereby inhibiting tumor progression. SP1 is an oncogenic factor in esophageal cancer and an unfavorable prognostic factor. Metformin downregulates both GLUL and SP1, affecting the alanine, aspartate, and glutamate metabolic pathways, as well as the choline metabolic pathway in cancer. CONCLUSION In summary, metformin may inhibit the migration and invasion of ESCC cells through downregulation of GLUL and SP1, which play important roles in the mechanism of metformin's anti-tumor effects. These findings provide new insights into the therapeutic potential of metformin in the treatment of ESCC.

Identification of implications of m6A regulators and autophagy-associated genes for prognosis in ovarian cancer

The most prevalent RNA alteration in the mammalian genome is N-6-methylenediosine (m6A). There is mounting evidence linking dysregulation of m6A regulatory factors and alterations in m6A levels to the development, course, or prognosis of ovarian cancer. Genes having prognostic value were screened using the univariate, multifactorial, and Least Absolute Shrinkage Selection Operator (LASSO) Cox regression analyses. Important genes' m6A expression in clinical material was verified by real-time fluorescent quantitative polymerase chain reaction (RT-qPCR). In present study, all 23 regulators were significantly differentially expressed in ovarian cancer tissues. LASSO regression analysis screened for 10 key genes associ-ated with both autophagy and m6A. A risk score was constructed and nomogram was developed to forecast the prognosis of ovarian cancer patients. Additionally, individuals with ovarian cancer were classified as high-risk or low-risk; and the low-risk group might be more likely to benefit from im-munotherapy. RT-qPCR was used for the bioinformatics study of human ovarian cancer and normal tissues. Lastly, PLK2 and LEPR were confirmed to be associated with tumorigenesis in scRNA-seq. The risk score established by m6A and autophagy can be used to predict prognosis and susceptibility to anticancer drugs in patients with ovarian cancer.

Unveiling Prognostic Biomarker in Colorectal Cancer: ADH6 and BDH1 through Oxidoreductase Gene Family Dysregulation

EPHX2 Expression and Its Association with Prognosis, Metabolic Regulation, and Metastasis-Related Pathways in Lung Adenocarcinoma

Background/Objectives: Epoxide hydrolase 2 (EPHX2), which encodes soluble epoxide hydrolase (sEH), is involved in arachidonic acid metabolism and has been associated with inflammation, lipid metabolism, and tumor biology. However, its prognostic significance and biological associations in lung adenocarcinoma (LUAD) remain unclear. This study aimed to investigate the expression profile, prognostic value, and molecular pathways of EPHX2 in LUAD using bioinformatics analyses. Methods: EPHX2 expression was evaluated using TNMplot, GEPIA2, and GEO datasets, while protein expression was assessed using the Human Protein Atlas and CPTAC/UALCAN platforms. Prognostic analyses were performed using Kaplan–Meier Plotter, GEPIA2, and Human Protein Atlas datasets. Co-expression and gene set enrichment analyses were conducted using LinkedOmics, and functional enrichment analyses were performed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome databases. Correlation and protein–protein interaction (PPI) analyses were evaluated using GEPIA2 and STRING. Results: EPHX2 expression was significantly reduced in LUAD tissues compared with normal lung tissues across datasets, and these findings were supported at the protein level. High EPHX2 expression was associated with better overall survival and retained independent prognostic significance in multivariate Cox analysis. Functional enrichment analyses demonstrated associations with lipid metabolism, arachidonic acid metabolism, cytochrome P450-related pathways, and oxidative processes. Correlation analyses suggested potential associations between EPHX2 and angiogenesis, extracellular matrix remodeling, and hypoxia-related pathways. Conclusions: Bioinformatics analyses suggest that EPHX2 may participate in metabolic and tumor progression-related regulatory networks and may serve as a prognostic biomarker in LUAD.

Researching the role of ubiquitination and macrophage activation-related genes in hepatocellular carcinoma through a systematic study based on gene expression profiling.

Hepatocellular carcinoma (HCC) remains a formidable global health challenge, particularly in developing nations, due to its asymptomatic nature in early stages and consequent late diagnosis. This study aims to identify novel biomarkers and therapeutic targets by focusing on Ubiquitin and Macrophage Activation-Related Genes (UMARGs), which play a crucial role in modulating the tumor microenvironment. Utilizing a comprehensive bioinformatics framework, we integrated transcriptomic data from TCGA and GEO databases with gene signatures from GeneCards. Our methodology included differential gene expression analysis, Cox regression modeling, and protein interaction networking to identify key prognostic determinants and their heterogeneity across HCC molecular subtypes. The analysis revealed two distinct HCC subtypes, Cluster A and Cluster B, each with unique gene expression profiles. Immune microenvironment heterogeneity was highlighted through CIBERSORT deconvolution, showing diverse distributions across 12 cellular subsets, notably activated T cells and macrophages.Survival analysis showed that high expression of HPX was associated with better Overall survival, while high expression of MMP9 was associated with worse Overall survival, and these trends were validated in an external GEO cohort. HPX and MMP9 may serve as candidate prognostic biomarkers for Hepatocellular carcinoma, but their Biological function and clinical application value still require further experimental investigation. Despite limitations, including the lack of experimental validation and reliance on retrospective data, this study provides valuable insights into gene expression dynamics and immune characteristics associated with HCC. These findings lay the groundwork for precision oncology paradigms, facilitating the translational trajectory of these targets to optimize clinical prognosis. Future research should focus on experimental validation and the development of targeted therapies based on these molecular insights. This study underscores the potential of UMARGs in advancing HCC treatment strategies and improving patient outcomes.

Integrative analysis of transcriptomics and metabolomics reveals mitochondria function genes and associated metabolite pathways in endometritis.

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.