摘要
目的:建立改良多重实时荧光定量PCR法,检测抑癌基因MGMR、p16、CDH13和RASSF1A基因甲基化,探讨其在肺癌早期诊断中的应用。方法:选取30例病理确诊为肺癌的患者作为肺癌组,30例病理确诊为良性病变的患者作为对照组。建立改良实时荧光定量PCR体系。检测受试者血清MGMT、p16、CDH13和RASSF1A基因甲基化,对比两组基因甲基化阳性率,计算四项基因甲基化单独及联合用于肺癌早期诊断的敏感度和特异度。结果:肺癌组受试者血清MGMT、p16、CDH13和RASSF1A显著高于对照组(P<0.05);MGMT、p16、CDH13和RASSF1A四项基因甲基化联合检测用于肺癌早期诊断的敏感度和特异度显著高于单项指标检测(P<0.05)。结论:建立了多重实时荧光定量PCR法用于MGMT、p16、CDH13和RASSF1A基因甲基化检测,联合检测用于肺癌早期诊断具有较高的敏感度和特异度。
Objective: A modified multiplex real-time fluorescence quantitative PCR method was established to detect the methylation of tumor suppressor genes MGMR, p16, CDH13 and RASSF1A, and to explore its application in early diagnosis of lung cancer. Methods: Thirty patients with lung cancer were confirmed by pathology and selected as lung cancer group and 30 patients with benign disease confirmed by pathology as control group. Establish a modified real-time fluorescence quantitative PCR system. Methylation of MGMT, p16, CDH13, and RASSF1A genes was detected in the subjects, and the positive rate of methylation was compared between the two groups. The sensitivity and specificity of the gene methylation alone and in combination for the early diagnosis of lung cancer were calculated. Results: Serum MGMT, p16, CDH13, and RASSF1A levels were significantly higher in lung cancer group than in the control group(P<0.05). The sensitivity and specificity of MGMT, p16, CDH13, and RASSF1A genes for the early diagnosis of lung cancer were significantly higher than those diagnosed separately(P<0.05). Conclusion: The established multiplex real-time fluorescence quantitative PCR method has been used to detect the methylation of MGMT, p16, CDH13 and RASSF1A genes. Which has high sensitivity and specificity for the early diagnosis of lung cancer.
作者
钟云华
李燕
ZHONG Yunhua;LI Yan(Department of Geriatrics,the First People's Hospital of Yunnan,Affiliated Hospital of Kunming University of Science and Technology,Kunming 650032,China)
出处
《东南大学学报(医学版)》
CAS
2019年第1期33-38,共6页
Journal of Southeast University(Medical Science Edition)
基金
云南省应用基础研究(昆医联合)专项(2017FE467(-116))
云南省卫生科技计划项目(2016NS204)