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

Integrated multi-omics analysis and functional experiments reveals PPAP2C as a potential prognostic biomarker and therapeutic target in breast cancer

This study aims to systematically elucidate the clinical significance and biological function of the phospholipid phosphatase (PLPP) family member (PPAP2C) phosphatidic acid phosphatase type 2C in breast cancer, and to evaluate its potential as a prognostic biomarker and therapeutic target. Gene expression data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) databases were integrated to characterize the expression profile of PLPP family members, focusing on PPAP2C in breast cancer. The prognostic value of PPAP2C, initially identified at the mRNA level (TCGA, (METABRIC) Molecular Taxonomy of Breast Cancer International Consortium, Gene Expression Omnibus (GEO)), was confirmed at the protein level by immunohistochemistry (IHC) on tissue microarrays (TMA). The oncogenic functions of PPAP2C were investigated in triple-negative breast cancer (TNBC) cells through CRISPR-Cas9-mediated knockout and ectopic overexpression, with assessment of key phenotypes including proliferation, colony formation, migration, and invasion. In vivo validation was subsequently performed using an MDA-MB-231 xenograft model. PPAP2C exhibits the most significant overexpression pattern across 33 cancer types (upregulated in 16 cancers, downregulated in only 3). Compared with normal tissues, PPAP2C showed specific overexpression in breast cancer tissues and was significantly associated with advanced clinical stages and aggressive subtypes (HER2 + and TNBC). Survival analysis demonstrated that high PPAP2C expression correlated with significantly shorter overall survival and disease-free survival, which was further validated in METABRIC and GEO cohorts. Tissue microarray analysis confirmed higher PPAP2C protein positivity in tumor tissues (94.7%) than in adjacent normal tissues (59.7%), with worse OS and RFS in high-expression groups. Multivariate analysis identified PPAP2C as an independent prognostic factor for OS. Functional experiments revealed that PPAP2C knockout (via 5-bp/1-bp frameshift mutations) suppressed TNBC cell proliferation, colony formation, migration, and invasion, while overexpression enhanced these phenotypes. In vivo studies further demonstrated complete tumor regression in MDA-MB-231 xenografts upon PPAP2C knockout. This study identifies PPAP2C as a key oncogenic driver and a robust independent prognostic biomarker in breast cancer. The findings provide compelling evidence that PPAP2C represents a promising therapeutic target, offering a new strategic avenue for precision therapy, particularly for aggressive breast cancer subtypes.

ERP44 Is Associated With Poor Prognosis and Promotes Proliferation and Temozolomide Resistance in Lower-grade Glioma

Integrative Bioinformatics and Experimental Validation Reveal that METTL9 Drives Lung Adenocarcinoma Progression via TGF-β/Smad-Mediated EMT Activation.

BACKGROUND Methyltransferase-like 9 (METTL9) has been implicated in tumor progression, yet its clinical significance, functional roles, and immunoregulatory functions in lung adenocarcinoma (LUAD) remain unclear. This study aimed to integrate multi-omics datasets and experimental evidence to systematically evaluate the expression profile, prognostic value, molecular mechanisms, and tumor microenvironment (TME)-related functions of METTL9 in LUAD. METHODS Transcriptome and clinical data for LUAD and METTL9 protein expression were obtained from public databases. Survival analysis was performed using Kaplan-Meier analysis and Cox proportional hazards models. METTL9-related differentially expressed genes (DEGs) were screened, followed by functional annotation and pathway enrichment analysis. A protein-protein interaction (PPI) network associated with METTL9 was constructed using STRING. METTL9 gene mutations and promoter methylation levels were analyzed via cBioPortal and UALCAN. Immune infiltration was evaluated through gene set variation analysis (GSVA) and the TIMER platform. The role of METTL9 depletion in regulating transforming growth factor-β (TGF-β)/Smad signaling, epithelial-mesenchymal transition (EMT), as well as the behavior of A549 and H1975 cells was investigated. RESULTS METTL9 was markedly elevated in LUAD, which was confirmed in external datasets and immunohistochemistry. Increased METTL9 expression showed a strong association with advanced TNM stage, unfavorable clinicopathological parameters, and poor survival outcomes in univariate analysis. Receiver operating characteristic (ROC) analysis indicated that METTL9 showed moderate diagnostic utility for LUAD, with an Area Under the Curve (AUC) of 0.704 (95% Confidence Interval [CI]: 0.650-0.758) in the The Cancer Genome Atlas (TCGA) dataset and 0.815 (95% CI: 0.758-0.872) in the GSE31210 dataset. Moreover, high METTL9 expression was significantly correlated with poor survival outcomes (Hazard Ratio [HR] = 1.349, 95% CI: 1.010-1.802, p = 0.043). METTL9 interacted with multiple oncogenic proteins in the PPI network and showed significant correlations with cuproptosis-related genes. Immune infiltration analysis further demonstrated that METTL9 expression showed significantly associated with immune cell infiltration and the tumor immune microenvironment in LUAD. METTL9 knockdown suppressed LUAD cell proliferation, migration, invasion, and EMT, while promoting apoptosis and reducing the expression of B-cell lymphoma 2 (Bcl-2), phosphorylated Smad2 (p-smad2), and phosphorylated Smad3 (p-smad3). CONCLUSION METTL9 is upregulated in LUAD and correlates with an unfavorable prognosis. Our results indicate that METTL9 may contribute to LUAD progression and EMT, potentially in relation to the TGF-β/Smad signaling pathway.

Identification and analysis of EphrinB2/EphB4 signaling pathway and angiogenesis related biomarkers in coronary artery disease based on bioinformatics.

BACKGROUND EphrinB2 and its receptor EphB4 have been reported to play a crucial role in the development of the cardiovascular system, and the process of coronary artery disease (CAD) is closely related to angiogenesis. The aim of this study is to identify and analyze the therapeutic value of the EphrinB2/EphB4 signaling pathway and angiogenesis-related biomarkers. METHODS The CAD chip data (GSE42148) was used for differential analysis to identify differently expressed genes (DEGs). Key module genes associated with CAD were identified using WGCNA. Machine learning and expression validation were executed for screening biomarkers. In addition, the biological functions of biomarkers were explored using enrichment analyses. Finally, the diagnostic and therapeutic value of biomarkers was explored through immune infiltration analysis and drug prediction. RESULTS Totally, 927 DEGs were identified in CAD and control groups. A total of 1,605 key CAD-related module genes were obtained for subsequent analyses. Then, PTX3, DLL4, and CITED4 were identified as biomarkers. Enrichment analysis suggested that three biomarkers were associated with allograft rejection. Analysis of 28 immune cell infiltrates revealed that CD56dim natural killer cell, eosinophil, mast cell, and MDSC etc. were significantly different between CAD and control groups. Finally, small-molecule drugs, notably simvastatin and calcitriol, were predicted and validated via molecular docking (binding energies < -6.0 kcal/mol) to have a potential therapeutic role in CAD by targeting PTX3 and CITED4, respectively. CONCLUSION We obtained three EphrinB2/EphB4 signaling pathway and angiogenesis-related biomarkers (PTX3, DLL4, and CITED4) linked with CAD, which provide new references for the treatment of CAD.

A Glutathione Metabolism-Related Transcriptomic Signature for Prognostic Assessment and Biological Characterization of Lung Adenocarcinoma

Background Glutathione metabolism plays an important role in redox homeostasis, oxidative stress responses, and metabolic adaptation in cancer. However, its prognostic significance in lung adenocarcinoma (LUAD) remains incompletely understood. This study aimed to develop a glutathione metabolism-related prognostic signature and investigate its associations with immune characteristics, genomic alterations, and biological pathways in LUAD. Methods Transcriptomic, clinical, and somatic mutation data from TCGA-LUAD were analyzed, and GSE50081 was used as an independent validation cohort. Glutathione metabolism-related genes were identified through differential expression and Cox regression analyses, followed by least absolute shrinkage and selection operator (LASSO) Cox regression to construct a prognostic signature. Survival analysis, time-dependent receiver operating characteristic (ROC) analysis, Cox regression, immune infiltration analysis, Gene Set Enrichment Analysis (GSEA), mutation profiling, tumor mutation burden (TMB) analysis, and drug-sensitivity prediction were subsequently performed. Results A glutathione metabolism-related signature stratified patients into high- and low-risk groups with significantly different overall survival in both the TCGA training cohort and the GSE50081 validation cohort. The risk score remained an independent prognostic factor in multivariable Cox regression analysis. High-risk tumors exhibited reduced B-cell and dendritic-cell infiltration, enrichment of cell-cycle- and metabolism-related pathways, higher frequencies of TP53 and KEAP1 mutations, and elevated tumor mutation burden. Computational drug-sensitivity analysis identified differences in predicted responses to several therapeutic agents between risk groups. Conclusions The proposed glutathione metabolism-related signature demonstrated prognostic value in both training and validation cohorts and was associated with immune characteristics, pathway enrichment patterns, genomic alterations, and tumor mutation burden in LUAD. These findings provide additional insights into glutathione metabolism-related heterogeneity in LUAD and warrant further biological and clinical validation.

Phosphoinositide metabolism-related prognostic genes and their prognostic value in cervical cancer: an investigation based on transcriptome, single-cell analyses and verification.

BACKGROUND Cervical cancer (CESC) is a major gynecological malignancy, and abnormalities in phosphoinositide metabolism (PPM) are closely linked to tumor progression. This study aimed to screen phosphoinositide metabolism-related genes (PPM-RGs) with prognostic value for CESC and explore their molecular mechanisms and clinical significance. METHODS CESC transcriptomic datasets and PPM-RGs were retrieved from public databases. Differentially expressed genes were intersected with PPM-RGs to obtain candidate genes. Prognostic genes were screened via univariate Cox regression and proportional hazards assumption test, and a risk model was constructed using random survival forest (RSF). Independent prognostic analysis and nomogram establishment were performed, followed by pathway enrichment, immune infiltration, somatic mutation and single-cell analyses to characterize the tumor microenvironment. Immunohistochemical staining was used to verify the protein expression of key genes in CESC tissues. RESULTS Twenty candidate genes were initially identified, and two protective prognostic genes VAC14 and INPP5K were finally determined. The risk model showed favorable predictive performance with area under the curve (AUC) over 0.7, and high-risk patients had poorer survival. The nomogram combining risk score and M stage presented high accuracy. The high-risk group exhibited distinct pathway enrichment, altered immune infiltration and low somatic mutation rates. Monocytes were identified as potential key cells with impaired communication and differentiation in CESC. Immunohistochemistry confirmed downregulated expression of the two genes in CESC epithelial cells. CONCLUSION VAC14 and INPP5K were PPM-related prognostic genes for CESC. Monocytes played critical roles in CESC progression. The risk model and nomogram aided prognosis prediction, providing new insights for CESC treatment.