ABSTRACT
INTRODUCTION: The underlying mechanisms of gastric cancer (GC) remain unknown. Therefore, in this study, we employed a comprehensive approach, combining computational and experimental methods, to identify potential key genes and unveil the underlying pathogenesis and prognosis of GC. METHODS: Gene expression profiles from GEO databases (GSE118916, GSE79973, and GSE29272) were analyzed to identify DEGs between GC and normal tissues. A PPI network was constructed using STRING and Cytoscape, followed by hub gene identification with CytoHubba. Investigations included expression and promoter methylation analysis, survival modeling, mutational and miRNA analysis, gene enrichment, drug prediction, and in vitro assays for cellular behaviors. RESULTS: A total of 83 DEGs were identified in the three datasets, comprising 41 up-regulated genes and 42 down-regulated genes. Utilizing the degree and MCC methods, we identified four hub genes that were hypomethylated and up-regulated: COL1A1, COL1A2, COL3A1, and FN1. Subsequent validation of their expression and promoter methylation on clinical GC samples through targeted bisulfite sequencing and RT-qPCR analysis further confirmed the hypomethylation and overexpression of these genes in local GC patients. Furthermore, it was observed that these hub genes regulate tumor proliferation and metastasis in in vivo and exhibited mutations in GC patients. CONCLUSION: We found four potential diagnostic and prognostic biomarkers, including COL1A1, COL1A2, COL3A1, and FN1 that may be involved in the occurrence and progression of GC.
Subject(s)
DNA Methylation , Gene Expression Regulation, Neoplastic , Stomach Neoplasms , Stomach Neoplasms/genetics , Stomach Neoplasms/pathology , Humans , DNA Methylation/genetics , Promoter Regions, Genetic/genetics , Biomarkers, Tumor/genetics , Biomarkers, Tumor/metabolism , Computer Simulation , Prognosis , Cell Line, Tumor , Gene Expression Profiling , Protein Interaction Maps/genetics , Gene Regulatory Networks , Databases, Genetic , Computational Biology , Cell Proliferation/genetics , MicroRNAs/genetics , MicroRNAs/metabolism , Fibronectins , Collagen Type IABSTRACT
OBJECTIVES: Cancer remains a global health challenge, necessitating the identification of novel biomarkers and therapeutic targets. Cuproptosis, a recently recognized form of cell death linked to copper metabolism, presents a promising avenue for anticancer strategies. We investigated the clinical significance of SLC31A1, a key regulator of cuproptosis, in multiple cancer types, aiming to elucidate its potential as a diagnostic biomarker, prognostic, indicator and therapeutic target. METHODS: We conducted a pan-cancer analysis through TIMER2.0, evaluating SLC31A1 expression across multiple cancer types. Survival analysis was performed using KM plotter. Expression validation was carried out using UALCAN and Human Protein Atlas (HPA) databases. Methylation analysis was conducted with the help of ULACAN and OncoDB. Mutational analysis was performed using cBioPortal database. Immune infiltration analysis via the TIMER2.0 and gene enrichment analysis via the Metascape were performed to gain insights into the potential mechanisms underlying SLC31A1's role in cancer. Finally, Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was employed to confirm SLC31A1 expression in clinical samples. RESULTS: Out of analyzed cancer, SLC31A1 exhibited significant up-regulation and correlation with worse overall survival (OS) across Breast Cancer (BRCA), Cervical Squamous Cell Carcinoma (CESC), Head and Neck Squamous Cell Carcinoma (HNSC), and Esophageal Carcinoma (ESCA). Mutational and promoter methylation analyses further revealed that hypomethylation is the major cause of SLC31A1 overexpression among BRCA, CESC, HNSC, and ESCA. Immune infiltration analysis showed significant associations between SLC31A1 expression and the presence of CD8+ T cells, CD4+ T cells, and macrophages in the tumor microenvironment. Gene enrichment analysis provided valuable insights into potential molecular pathways in context to BRCA, CESC, HNSC, and ESCA. Furthermore, when SLC31A1 was analyzed using clinical samples through RT-qPCR, this gene showed promising diagnostic potential, reflected by high Area Under the Curve (AUC) values. CONCLUSION: Our pan-cancer study highlights the up-regulation of SLC31A1 and its correlation with worse OS in BRCA, CESC, HNSC, and ESCA. In sum, outcomes of this study showed that SLC31A1 could be a potential biomarker and novel therapeutic target of BRCA, CESC, HNSC, and ESCA.
ABSTRACT
Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors, and lung adenocarcinoma (LUAD) accounts for up to 40% of NSCLC. Ring finger protein 213(RNF213) has been demonstrated to suppress several cancers, including glioblastoma and breast cancer. Nonetheless, the role of RNF213 in LUAD has not been investigated. The expression of RNF213 in LUAD tissues was analyzed by western blotting, The Cancer Genome Atlas, Genotype Tissue Expression Project, and Gene Expression Omnibus databases. Prognostic value analysis was performed through the Kaplan-Meier Plotter database. We determined the role of RNF213 in LUAD cells through cell counting kit8 assay, migration, and invasion assay. The clinical roles of RNF213 were evaluated by immunohistochemical staining assay (IHC) and Kaplan-Meier survival analysis. RNF213 expression was reduced in LUAD, thus affecting the prognosis of LUAD. And RNF213 could suppress the migration and invasion of LUAD cells to prevent tumor development. the expression of RNF213 is positively correlated with the overall survival, providing a novel marker in the prognosis of LUAD patients.
