Search Results (5)

Peri-implantitis (PI) is a chronic inflammatory disease that ultimately leads to the dysfunction and loss of implants with established osseointegration. Ferroptosis has been implicated in the progression of PI, but its precise mechanisms remain unclear. This study explores the molecular mechanisms of ferroptosis in the pathology of PI through bioinformatics, offering new insights into its diagnosis and treatment. The microarray datasets for PI (GSE33774 and GSE106090) were retrieved from the GEO database. The differentially expressed genes (DEGs) and ferroptosis-related genes (FRGs) were intersected to obtain PI-Ferr-DEGs. Using three machine learning algorithms, the Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Boruta, we successfully identified the most crucial biomarkers. Additionally, these key biomarkers were validated using a verification dataset (GSE223924). Gene set enrichment analysis (GSEA) was also utilized to analyze the associated gene enrichment pathways. Moreover, immune cell infiltration analysis compared the differential immune cell profiles between PI and control samples. Also, we targeted biomarkers for drug prediction and conducted molecular docking analysis on drugs with potential development value. A total of 13 PI-Ferr-DEGs were recognized. Machine learning and validation confirmed toll-like receptor-4 (TLR4) and FMS-like tyrosine kinase 3 (FLT3) as ferroptosis biomarkers in PI. In addition, GSEA was significantly enriched by the biomarkers in the cytokine–cytokine receptor interaction and chemokine signaling pathway. Immune infiltration analysis revealed that the levels of B cells, M1 macrophages, and natural killer cells differed significantly in PI. Ibudilast and fedratinib were predicted as potential drugs for PI that target TLR4 and FLT3, respectively. Finally, the occurrence of ferroptosis and the expression of the identified key markers in gingival fibroblasts under inflammatory conditions were validated by RT-qPCR and immunofluorescence analysis. This study identified TLR4 and FLT3 as ferroptosis and immune cell infiltration signatures in PI, unraveling potential novel targets to treat PI. Full article

Among the most common malignant tumors, hepatocellular carcinoma (HCC) is a primary liver cancer type that has a high mortality rate. HCC often presents insidiously, is prone to recurrence, and has limited treatment efficacy. Ferroptosis regulates tumorigenesis, progression, and metastasis, which is a novel form of iron-dependent cell death. Numerous studies suggest that HCC is sensitive to ferroptosis, indicating that targeted therapies aimed at inducing ferroptosis may represent a promising new approach to cancer treatment. This study aims to find genes associated with HCC and ferroptosis, as well as to screen for potential agents that may cause ferroptosis in HCC. Transcriptome and clinical sample data were obtained from the TCGA database to identify differentially expressed genes related to ferroptosis. Using various regression and survival analysis techniques, we developed a prognostic model based on four core genes and evaluated its predictive potential. Subsequently, we screened for potential therapeutic agents in the Connective Map (CMap) database, designated as compound Atorvastatin, based on differential genes from two risk groups and related to ferroptosis. Through experiments conducted in vivo and in vitro, we demonstrated that Atorvastatin can induce ferroptosis in HCC cells while inhibiting their growth and migration. In conclusion, this research targets ferroptosis therapy and provides new insights for improving the prediction and prevention of HCC. Full article

Cutaneous melanoma (CM) is one of the most aggressive skin tumors with a poor prognosis. Ferroptosis is a newly discovered form of regulated cell death that is closely associated with cancer development and immunotherapy. The aim of this study was to establish and validate a ferroptosis-related gene (FRG) DNA methylation signature to predict the prognosis of CM patients using data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. A reliable four-FRG DNA methylation prognostic signature was constructed via Cox regression analysis based on TCGA database. Kaplan–Meier analysis showed that patients in the high-risk group tended to have a shorter overall survival (OS) than the low-risk group in both training TCGA and validation GEO cohorts. Time-dependent receiver operating characteristic (ROC) analysis showed the areas under the curve (AUC) at 1, 3, and 5 years were 0.738, 0.730, and 0.770 in TCGA cohort and 0.773, 0.775, and 0.905 in the validation cohort, respectively. Univariate and multivariate Cox regression analyses indicated that the signature was an independent prognostic indicator of OS in patients with CM. Immunogenomic profiling showed the low-risk group of patients had a higher immunophenoscore, and most immune checkpoints were negatively associated with the risk signature. Functional enrichment analysis revealed that immune response and immune-related pathways were enriched in the low-risk group. In conclusion, we established and validated a four-FRG DNA methylation signature that independently predicts prognosis in CM patients. This signature was strongly correlated with the immune landscape, and may serve as a biomarker to guide clinicians in making more precise and personalized treatment decisions for CM patients. Full article

Ferroptosis, a newly discovered iron-dependent type of cell death, has been found to play a crucial role in the depression of tumorigenesis. However, the prognostic value of ferroptosis-related genes (FRGs) in lung adenocarcinoma (LUAD) remains to be further elucidated. Differential expression analysis and univariate Cox regression analysis were utilized in this study to search for FRGs that were associated with the prognosis of LUAD patients. The influences of candidate markers on LUAD cell proliferation, migration, and ferroptosis were evaluated by CCK8, colony formation, and functional experimental assays in association with ferroptosis. To predict the prognosis of LUAD patients, we constructed a predictive signature comprised of six FRGs. We discovered a critical gene (GCLC) after intersecting the prognostic analysis results of all aspects, and its high expression was associated with a bad prognosis in LUAD. Correlation research revealed that GCLC was related to a variety of clinical information from LUAD patients. At the same time, in the experimental verification, we found that GCLC expression was upregulated in LUAD cell lines, and silencing GCLC accelerated ferroptosis and decreased LUAD cell proliferation and invasion. Taken together, this study established a novel ferroptosis-related gene signature and discovered a crucial gene, GCLC, that might be a new prognostic biomarker of LUAD patients, as well as provide a potential therapeutic target for LUAD patients. Full article

Hepatocellular carcinoma (HCC) is a malignant disease with an increasing incidence and a high mortality rate. Ferroptosis, a novel type of cell death, has been reported to be closely associated with the progression of HCC. The aim of our study was to construct a novel ferroptosis-related signature (nFRGs) for prediction of prognosis, immune features and drug sensitivity of HCC patients. Data were obtained from the TCGA, ICGC, GSE104580, CCLE and IMvigor210 datasets, and the least absolute shrinkage and selection operator (LASSO) was used to construct nFRGs. In addition, the analyses involved in prognoses, molecular function, stemness indices, somatic mutation, responses to immunologic therapy, efficacy of transcatheter arterial chemoembolization (TACE) therapy and drug sensitivity were performed using diverse packages of R 4.1.3 between the low- and high-risk groups. The nFRGs included seven ferroptosis-related genes. Our results showed that nFRGs was an independent risk factor for prognoses of HCC patients, and HCC patients in the high-risk group presented with worse prognosis. Compared with the results of other studies, nFRGs was superior to other promising signatures in predicting prognoses of patients with HCC. In addition, most of the enriched pathways of differentially expressed genes (DEGs) between these subgroups were related to immune features. The molecular functions, genetic mutation and mRNAsi were varied between the high- and low-risk groups. Moreover, we observed significant immunosuppression state in the high-risk group. Patients in the high-risk group might benefit from immunotherapy, whereas patients in the low-risk group may be susceptible to TACE therapy. Finally, five sensitive drugs and four sensitive drugs were screened for patients in the high- and low-risk groups, respectively. nFRGs may served as a novel biomarker of prognosis and aid in personalized therapeutic strategies for patients with HCC. Full article