ABSTRACT
BACKGROUND: Esophagogastric junction cancer (EJC) refers to malignant tumors that develop at the junction between the stomach and the esophagus. TUSC1 is a recently identified tumor suppressor gene known for its involvement in various types of cancer. The objective of this investigation was to elucidate the regulatory influence of DNA methylation on TUSC1 expression and its role in the progression of EJC. METHODS: Bioinformatics software was utilized to analyze the expression of TUSC1, enriched pathways, and highly methylated sites in the promoter region. TUSC1 expression in EJC was assessed using quantitative reverse transcription polymerase chain reaction (qRT-PCR), western blot (WB), and immunohistochemistry. Methylation-specific PCR was employed to detect the methylation level of TUSC1. To analyze the effects of TUSC1 and 5-AZA-2 on tumor cell proliferation, migration, invasion, cell cycle, and apoptosis, several assays including CCK-8, colony formation, transwell, and flow cytometry were conducted. The expression of MDM2 was assessed using qRT-PCR and WB. WB detected the expression of p53, and p-p53, markers for EJC cell proliferation, epithelial-mesenchymal transition, and apoptosis. The role of TUSC1 in tumor occurrence in vivo was examined using a xenograft mouse model. RESULTS: TUSC1 expression was significantly downregulated in EJC. Overexpression of TUSC1 and treatment with 5-AZA-2 inhibited the malignant progression of EJC cells. In EJC, low methylation levels promoted the expression of TUSC1. Upregulation of TUSC1 suppressed the expression of MDM2 and activated the p53 signaling pathway. Inactivation of this pathway attenuated the inhibitory effect of TUSC1 overexpression on EJC cell proliferation, migration, invasion, and other behaviors. Animal experiments demonstrated that TUSC1 overexpression inhibited EJC tumor growth and metastasis in vivo. CONCLUSION: TUSC1 was commonly downregulated in EJC and regulated by methylation. It repressed the malignant progression of EJC tumors by mediating the p53 pathway, suggesting its potential as a diagnostic and therapeutic target for EJC.
Subject(s)
Cell Proliferation , DNA Methylation , Esophageal Neoplasms , Gene Expression Regulation, Neoplastic , Tumor Suppressor Proteins , Humans , DNA Methylation/genetics , Animals , Tumor Suppressor Proteins/genetics , Mice , Cell Line, Tumor , Gene Expression Regulation, Neoplastic/genetics , Cell Proliferation/genetics , Cell Proliferation/drug effects , Esophageal Neoplasms/genetics , Esophageal Neoplasms/pathology , Disease Progression , Esophagogastric Junction/pathology , Stomach Neoplasms/genetics , Stomach Neoplasms/pathology , Apoptosis/genetics , Promoter Regions, Genetic/genetics , Tumor Suppressor Protein p53/genetics , Male , Cell Movement/genetics , Cell Movement/drug effects , Down-Regulation/genetics , Female , Mice, NudeABSTRACT
OBJECTIVES: This research aimed to construct a prediction model for stages II and III cardia carcinoma (CC), and provide an effective preoperative evaluation tool for clinicians. METHODS: CC mRNA expression matrix was obtained from Gene Expression Omnibus and The Cancer Genome Atlas databases. Non-negative matrix factorization was used to cluster data to obtain subgroup information, and weighted gene co-expression network analysis was used to uncover key modules linked to different subgroups. Gene-set enrichment analysis analyzed biological pathways of different subgroups. The related pathways of multiple modules were scrutinized with Kyoto Encyclopedia of Genes and Genomes. Key modules were manually annotated to screen CC-related genes. Subsequently, quantitative real-time polymerase chain reaction assessed CC-related gene expression in fresh tissues and paraffin samples, and Pearson correlation analysis was performed. A classification model was constructed and the predictive ability was evaluated by the receiver operating characteristic curve. RESULTS: CC patients had four subgroups that were associated with brown, turquoise, red, and black modules, respectively. The CC-related modules were mainly associated with abnormal cell metabolism and inflammatory immune pathways. Then, 76 CC-elated genes were identified. Pearson correlation analysis presented that THBS4, COL14A1, DPYSL3, FGF7, and SVIL levels were relatively stable in fresh and paraffin tissues. The area under the curve of 5-gene combined prediction for staging was 0.8571, indicating good prediction ability. CONCLUSIONS: The staging classifier for CC based on THBS4, COL14A1, DPYSL3, FGF7, and SVIL has a good predictive effect, which may provide effective guidance for whether CC patients need emergency surgery.
