摘要
目的探讨血浆miR-18a-5p对宫颈癌诊断及预后的预测价值。方法采用qRT-PCR法检测60例宫颈癌患者血浆miR-18a-5p表达量,并分析其对宫颈癌的临床病理特征、诊断及预后的关系。结果宫颈癌患者血浆miR-18a-5p表达水平明显高于术后组及对照组,差异均有统计学意义(P<0.001)。ROC曲线显示血浆miR-18a-5p诊断宫颈癌的曲线下面积为0.928,95%置信区间为0.876-0.979;诊断灵敏度为76.7%,特异度为96.7%。血浆miR-18a-5p表达水平与宫颈癌患者肿瘤分化程度(P=0.032)、临床分期(P=0.001)及淋巴结转移(P=0.001)相关,而与其他临床特征无关。Kaplan-Meier分析表明miR-18a-5p高表达患者的总体生存率显著低于低表达患者(P<0.05)。结论血浆miR-18a-5p表达水平可作为宫颈癌潜在标志物用于临床诊断及预后评估。
Objective To evaluate the diagnostic and prognostic value of plasma miR-18a-5p in cervical carcinoma. Methods Sixty patients with cervical carcinoma and thirty healthy controls were recruited in this study. Blood samples were collected from each partici pa nt, and total RNA was extracted from the plasma. miR-18a-5p expression level was detected by qRT-PCR. Results The levels of plasma miR-18a-5p in cervical carcinoma was significantly higher than those in patients with post-operation diseases and healthy group (P < 0.001 ). ROC curve analysis showed that plasma miR-18a-5p levels could be used to predict the risk of cervical carcinoma, with AUC values of 0. 928 (95% CI: 0.876-0.979 ). The miR-18a-5p level in cervical carcinoma patients was positively correlated with degree of differentiation (P =0.032), clinical stage ( P = 0.001 ) and lymph node metastasis (P=0.001 ), but no significant correlation with other clinical parameters. Kaplan-Meier analysis indicated that the survival time of plasma miR-18a-5p low expression group in patients with cervical cancer was significantly higher than that in high expression group( P <0.05 ). Conclusion Plasma miR-18a-5p expression level could be used as a potentia.marker for clinical diagnosis and prognostic evaluation of cervical carcinoma.
作者
危敏
雷洁
韩璐好
余海浪
王涵多
WEI Min;LEI Jie;HAN Lu-hao;YU Hai-lang;WANG Han-duo(Genetic Room, Clinical Laboratory, Nanshan Maternity and Child Health - care Hospital, Shenzhen, Guangdong 518054, China)
出处
《中国卫生检验杂志》
CAS
2019年第17期2053-2056,共4页
Chinese Journal of Health Laboratory Technology
基金
国家自然科学基金项目(81672754)
广东省自然科学基金项目(2015A030313249)
广东省医学科研基金(A2017112)
深圳市南山区科技计划项目(2017006)