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作 者:牛智平 王娟 汪富涛[1] 成勇[1] 舒俊伟 杜嘉源 NIU Zhi-ping;WANG Juan;WANG Fu-tao;CHENG Yong;SHU Jun-wei;DU Jia-yuan(Department of General Surgery,Ankang People’s Hospital,Shaanxi Ankang 725000,China;Department of Obstetrics,Xi’an Daxing Hospital,Xi’an 710014,China)
机构地区:[1]安康市人民医院普外科,陕西安康725000 [2]西安大兴医院妇产科,西安710014
出 处:《现代检验医学杂志》2020年第5期134-136,共3页Journal of Modern Laboratory Medicine
摘 要:目的探讨乳腺癌组织中lncRNA PVT1的表达与患者临床特征及总体生存率的关系。方法采用实时荧光定量PCR法检测乳腺癌组织及其相应癌旁正常组织中lncRNA PVT1的相对表达量;分析lncRNA PVT1表达水平与乳腺癌患者临床特征与总体生存率间的关系。结果lncRNA PVT1在乳腺癌组织中的相对表达量显著高于癌旁正常组织(0.0075 vs 0.003),其差异具有统计学意义(P=0.0186)。lncRNA PVT1表达水平与乳腺癌患者的年龄(χ^2=5.948,P=0.015)、临床分期(χ^2=12.349,P=0.006)、淋巴结转移(χ^2=20.942,P<0.001)、远端转移(χ^2=5.330,P=0.021)和Her2(χ^2=5.221,P=0.022)显著相关。lncRNA PVT1高表达组患者的总体生存率(overall survival,OS)显著低于lncRNA PVT1低表达组,差异具有统计学意义(P=0.036)。结论lncRNA PVT1是一种可预测乳腺癌患者预后的有潜力的生物学指标。Objective To investigate the relationship between the expression of lncRNA PVT1 in breast cancer tissues and the clinical characteristics and overall survival rate of patients.Methods The relative expression of lncRNA PVT1 in breast cancer tissues and adjacent normal tissues was detected by quantitative real-time PCR.Analyzed the relationship between the expression level of lncRNA PVT1 and the clinical characteristics and overall survival rate of breast cancer patients.Results The relative expression of lncRNA PVT1 in breast cancer tissues was significantly higher than that in adjacent normal tissues,and the difference was statistically significant(P=0.0186).The expression level of lncRNA PVT1 was significantly correlated with age(χ^2=5.948,P=0.015),clinical stage(χ^2=12.349,P=0.006),lymph node metastasis(χ^2=20.942,P<0.001),distal metastasis(χ^2=5.330,P=0.021),and Her2(χ^2=5.221,P=0.022)in breast cancer patients.Overall survival rate(OS)of patients with high expression of lncRNA PVT1 was significantly lower than that of patients with low expression of lncRNAPVT1,and the difference was statistically significant(P=0.036).Conclusion LncRNA PVT1 is a potential biological indicator to predict the prognosis of breast cancer patients.
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