医学
肿瘤科
比例危险模型
多元分析
甲基化
内科学
生物标志物
单变量
单变量分析
癌症
多元统计
生存分析
免疫组织化学
生物
基因
遗传学
统计
数学
作者
Qinfu Zhao,Jiayu Lian,Kai Pang,Ping Wang,Ruiyin Ge,Yanliu Chu
出处
期刊:Medicine
[Ovid Technologies (Wolters Kluwer)]
日期:2023-04-25
卷期号:102 (17): e33603-e33603
被引量:1
标识
DOI:10.1097/md.0000000000033603
摘要
Junctional adhesion molecule 3 (JAM3) can be used as a prognostic marker in multiple cancer types. However, the potential prognostic role of JAM3 in gastric cancer (GC) remains unclear. The purpose of this research was to gauge JAM3 expression and methylation as potential biomarkers for GC patient survival. Through bioinformatics research, we analyzed JAM3 expression, methylation, prognosis, and immune cell infiltrations. JAM3 methylation acts as a negative regulator of JAM3, leading to reduced expression of JAM3 in GC tissues relative to normal tissues. Patients with GC who expressed little JAM3 have a better chance of living a long time free of the disease, according to the Cancer Genome Atlas (TCGA) database. Through univariate and multivariate Cox regression analysis, inadequate JAM3 expression was labeled as an isolated indicator for overall survival (OS). The GSE84437 dataset was also used to confirm JAM3 prognostic role in GC, with consistent findings. A meta-analysis also found that low levels of JAM3 expression were significantly associated with longer OS. Finally, there was a strong correlation between JAM3 expression and a subset of immune cells. According to the TCGA database, low JAM3 expression could predict favorable OS and progression-free-survival (PFS) in GC patients ( P < .05). The univariate and multivariate Cox regression demonstrated that low JAM3 expression was independent biomarker for OS ( P < .05). Moreover, GSE84437 dataset was utilized to verify the prognostic role of JAM3 in GC, and the similar results were reached ( P < .05). A meta-analysis revealed that low JAM3 expression was closely relevant to better OS. Finally, JAM3 expression exhibited a close correlation with some immune cells ( P < .05). JAM3 might be a viable predictive biomarker and likely plays a crucial part in immune cell infiltration in individuals with GC.
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