摘要
目的:探讨microRNA-381(miR-381)的表达及与胃癌患者临床病理参数和预后的关系。方法:通过定量实时聚合酶链反应(qRT-PCR)检测胃癌组织及癌旁组织中miR-381的表达水平。应用卡方检验分析miR-381表达与临床病理参数的关系。采用Kaplan-Meier曲线进行总生存率分析,并进行对数秩检验;通过Cox回归模型对miR-381的预后价值进行评估。结果:与癌旁组织相比,胃癌组织中miR-381的表达下调(P<0.05),并且其低表达与TNM Ⅲ-Ⅳ期(P=0.013)及淋巴结转移(P=0.004)显著相关。另外,我们发现胃癌患者中低miR-381表达水平的总体生存率低于其高表达水平的患者(P<0.05)。多因素分析表明,miR-381和组织学类型是胃癌患者的独立预后因素(P=0.008,P=0.025)。结论:miR-381与胃癌发生发展密切相关,可能是一个新的胃癌治疗的候选靶点。
Objective:To evaluate the prognostic value of miR-381 in gastric cancer patients.Methods:The expression level of miR-381 in gastric cancer tissues and paired non-cancerous tissues were detected by quantitative Real-time polymerase chain reaction(qRT-PCR).Chi-square test was used to evaluate the relationship between miR-381 expression and clinical parameters.Besides,overall survival analysis was carried out with Kaplan-Meier curve with Log-rank test,and the prognostic value of miR-381 in gastric cancer was evaluated by Cox regression model.Results:miR-381 was down-regulated in gastric cancer tissues,compared with adjacent tissues(P<0.05).Moreover,its decreased level was significantly correlated with advanced TNM Ⅲ-Ⅳ stage(P=0.013) and positive lymph node metastasis(P=0.004).In addition,we found that gastric cancer patients with low miR-381 expression level had poorer overall survival than those with high level(Log-rank test,P<0.05).miR-381 and histologic differentiation were independent prognostic factors for gastric cancer patients(P=0.008,P=0.025).Conclusion:Down-regulated miR-381 in gastric cancer patients is closely related to the occurrence and development of gastric cancer.miR-381 may be a potential prognostic biomarker for gastric cancer.
作者
王丽
田美娟
张佳
Wang Li;Tian Meijuan;Zhang Jia(First Affiliated Hospital,Medical School of Xi'an Jiaotong University,Shaanxi Xi'an 710061,China;Traditional Chinese Hospital of Baoji,Shaanxi Baoji 721000,China)
出处
《现代肿瘤医学》
CAS
2018年第16期2565-2567,共3页
Journal of Modern Oncology
基金
国家自然科学基金青年项目(编号:81702430)
关键词
胃癌
miR-381
临床意义
生存分析
gastric cancer
miR-381
clinical significance
survival analysis