Abstract
BACKGROUND: As a major histopathological subtype of gastric cancer (GC), stomach adenocarcinoma (STAD) is an important malignant tumor in the digestive system. Increasing evidence also indicates that endoplasmic reticulum (ER) stress plays a pivotal role in the pathogenesis and progression of GC. Therefore, this study aims to screen and identify vital ER stress-related genes that could contribute to the malignant development and poor prognosis for STAD. METHODS: A novel ER stress-related risk score signature was developed employing machine learning techniques. Then, a prognostic prediction nomogram was also built based on the clinicopathological characteristics and the risk score signature. The tumor immune microenvironment characteristics and pathway enrichment analysis in different risk groups were also explored. Furthermore, through the single-cell RNA sequencing (scRNA-seq) analysis, the study highlighted Cytochrome P450 Family 19 Subfamily A Member 1 (CYP19A1) as the pivotal research target and detected its effect on cell proliferation by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) and the expression of ER stress-related genes by RT-qPCR in STAD. RESULTS: Based on the evaluation of five screened key ER stress-related genes (AKR1B1, SERPINE1, ADCYAP1, MATN3, CYP19A1), our ER stress-related risk score signature offers a novel approach for assessing STAD prognosis hazards. The novel prognostic prediction nomogram based on the signature also accurately predicted the survival outcomes of patients with STAD. Furthermore, the expression of CYP19A1 is significantly higher in STAD tissues than in normal tissues. High expression of CYP19A1 was related to a poor survival outcome for patients with STAD. Besides, compared to normal gastric epithelial cells, the expression of CYP19A1 was significantly higher in STAD cell lines. Silencing the expression of CYP19A1 significantly inhibited the cell proliferation ability and decreased the expression of ER stress-related genes, including ATF4, DDIT3 and XBP1 in STAD. CONCLUSIONS: In conclusion, our study developed a novel prognosis prediction signature and identified the novel diagnostic and therapeutic target CYP19A1 for patients with STAD.