Yang Shaoyu, Li Juan, Cai Xiaohui
College of Marine Sciences, Guangxi Key Laboratory of Beibu Gulf Marine Biodiversity Conservation, Beibu Gulf University, Qinzhou 535011, China.
Nanchang Institute of Technology, Nanchang, 330044, China.
Heliyon. 2023 Jul 17;9(7):e18291. doi: 10.1016/j.heliyon.2023.e18291. eCollection 2023 Jul.
Gastric cancer has high mortality rates worldwide. Therefore, there is a need to identify prognostic biomarkers. This study evaluated the association between expression levels with clinicopathological features and prognosis in gastric cancer using data extracted from The Cancer Genome Atlas (TCGA) database and a series of algorithms. Survival analysis was performed using the Kaplan-Meier method. Univariate and multivariate Cox regression analyses were used to analyze the association between different clinical features and survival. Single-sample gene set enrichment analysis (GSEA) was used to examine the correlation between expression and immune infiltration. The results showed that the expression of in tumor samples was significantly lower than that in normal samples. High expression of was significantly associated with histological type, histologic grade, and worse overall survival, disease-specific survival, and progression-free survival. The univariate Cox analysis showed that the expression of was significantly correlated with T stage, N stage, M stage, and age. The multivariate analysis identified expression as an independent prognostic factor for gastric cancer. GSEA showed that might regulate the calcium signaling pathway, focus adhesion, olfactory conduction, the extracellular matrix glycoproteins, and response to the Leishmania parasitic infection. showed a significant moderate positive correlation with the infiltration of mast cells. In summary, a high expression of may contribute to poor survival in gastric cancer patients and could be used as a potential prognostic biomarker.
胃癌在全球范围内具有较高的死亡率。因此，有必要识别预后生物标志物。本研究使用从癌症基因组图谱（TCGA）数据库中提取的数据和一系列算法，评估了[具体基因名称]表达水平与胃癌临床病理特征及预后之间的关联。采用Kaplan-Meier方法进行生存分析。单因素和多因素Cox回归分析用于分析不同临床特征与生存之间的关联。单样本基因集富集分析（GSEA）用于检验[具体基因名称]表达与免疫浸润之间的相关性。结果显示，肿瘤样本中[具体基因名称]的表达明显低于正常样本。[具体基因名称]的高表达与组织学类型、组织学分级以及较差的总生存期、疾病特异性生存期和无进展生存期显著相关。单因素Cox分析表明，[具体基因名称]的表达与T分期、N分期、M分期和年龄显著相关。多因素分析确定[具体基因名称]表达为胃癌的独立预后因素。GSEA显示，[具体基因名称]可能调节钙信号通路、粘着斑、嗅觉传导、细胞外基质糖蛋白以及对利什曼原虫寄生虫感染的反应。[具体基因名称]与肥大细胞浸润呈显著的中度正相关。总之，[具体基因名称]的高表达可能导致胃癌患者生存不良，并可作为潜在的预后生物标志物。
