摘要
目的验证针对表皮生长因子受体(EGFR)基因经典突变——19de1E746.A750/211858R的特异性抗体敏感度和特异度,从而探讨应用免疫组织化学检测EGFR基因突变的临床意义。方法应用免疫组织化学方法(EnVision二步法)、Q评分体系及ROC曲线检测309例肺腺癌标准EGFR基因突变状态,并与聚合酶链反应(PCR)-DNA测序结果做比较,评价de1EGFR和L858R两种特异性抗体检测EGFR基因突变状态的诊断价值。结果经过PCR—DNA直接测序的肺腺癌标本中,92例为外显子19de1E746-A750突变,110例为外显子21L858R点突变。用delEGFR抗体检测外显子19de1E746-A750突变的敏感度为84.8%(78/92),特异度为77.6%(83/107),ROC曲线下面积为0.885,最佳分界值为85.00;用L858R抗体检测外显子21L858R点突变的敏感度为94.5%(104/110),特异度为62.5%(55/88),ROC曲线下面积为0.924,最佳分界值为97.50。结论delEGFR和L858R两种EGFR突变特异性抗体可用于检测EGFR基因的突变状态,并且结果判读使用Q评分及ROC曲线评价检测结果有较好的临床应用价值。
Objective To examine the sensitivity and specificity of the two epidermal growth factor receptor hotspot mutation antibodies-delE746-A750 and L858R in lung adenocarcinoma, and to discuss the value of the two antibodies for detecting these two "classic mutations" by immunohistochemistry. Methods With Q-scoring assessment and ROC curve analysis, immunohistochemistry was used to screen a panel of 309 paraffin-embedded non-small cell lung cancer (NSCLC) tumor samples, of which EGFR gene mutational status was previously documented by PCR-DNA sequencing. Results Three hundred and nine NSCLC tumor samples conclude 92 NSCLC cases with 19delE746-A750 and 110 with 21L858R. Using DelEGFR antibody to detect 19delE746-A750 demonstrated sensitivity and specificity of 84. 8% (78/92) and 77. 6% (83/107), respectively. Choosing the best cut-off value of 85.00, it achieved the maximum area under the curve (AUC: 0. 885 ). L858R antibody to detect 21L858R showed sensitivity and specificity of 94. 5% (104/110) and 62.5% (55/88), respectively. Choosing the best cut-off value of 97.50, it achieved the maximum area under the curve ( AUC : 0. 924). Conclusion By using Q-scoring assessment and ROC curve analysis, the two antibodies (delEGFR and L858R) can been used to identify EGFR gene mutations present in lung adenocarcinomas.
出处
《中华病理学杂志》
CAS
CSCD
北大核心
2013年第3期168-172,共5页
Chinese Journal of Pathology
关键词
肺肿瘤
腺癌
突变
受体
表皮生长因子
免疫组织化学
ROC曲线
Lung neoplasms
Adenocarcinoma
Mutation
Receptor, epidermal growthfactor
Immunohistochemistry
ROC curve