Sun Hao, Shi Jian-Xiang, Zhang Hong-Fei, Xing Meng-Tao, Li Pei, Dai Li-Ping, Luo Cheng-Lin, Wang Xiao, Wang Peng, Ye Hua, Li Liu-Xia, Zhang Jian-Ying
1 Affiliated Cancer Hospital of Zhengzhou University, College of Public Health, Zhengzhou University, Zhengzhou, China.
2 Department of Biological Sciences, The University of Texas at El Paso, El Paso, TX, USA.
Tumour Biol. 2017 Jun;39(6):1010428317699132. doi: 10.1177/1010428317699132.
In this study, enzyme-linked immunosorbent assay has been used to examine the frequencies of serum autoantibodies against two candidate tumor-associated antigens intensively selected from the Human Protein Atlas database, in combination with 13 tumor-associated antigens available from our lab in sera from 44 OC patients and 50 normal healthy controls. Conventional evaluation (mean + 3SD as the cutoff value to determine a positive reactivity), receiver operating characteristic curve analyses, and classification tree analysis were further used to evaluate the diagnostic performance of autoantibodies against these tumor-associated antigens (anti-tumor-associated antigens) in ovarian cancer. For single anti-tumor-associated antigen, when the cutoff values were set as mean + 3SD of normal healthy controls, NPM1, MDM2, PLAT, p53, and c-Myc could achieve sensitivity higher than 20% at 98% specificity. Combinational utilization of autoantibodies against MDM2, PLAT, NPM1, 14-3-3 Zeta, p53, and RalA achieved the optimal diagnostic performance with 72.7% sensitivity at 96% specificity. Receiver operating characteristic curve analysis showed that the area under the receiver operating characteristic curves of autoantibodies against c-Myc, NPM1, MDM2, p16, p53, and 14-3-3 Zeta were greater than 0.80. This indicated that these tumor-associated antigens held high potential to serve as diagnostic biomarkers in ovarian cancer detection. Decision tree analysis indicated that anti-c-Myc held high potential in the detection of ovarian cancer. Further studies are warranted to validate the diagnostic performance of these anti-tumor-associated antigens with high area under the receiver operating characteristic curve, including autoantibodies against c-Myc, MDM2, PLAT, NPM1, 14-3-3 Zeta, p53, and RalA.
在本研究中，酶联免疫吸附测定法已用于检测血清中针对从人类蛋白质图谱数据库中精心挑选的两种候选肿瘤相关抗原的自身抗体频率，并结合我们实验室提供的13种肿瘤相关抗原，检测了44例卵巢癌患者和50例正常健康对照者血清中的这些抗体。进一步采用传统评估方法（以平均值+3标准差作为确定阳性反应性的临界值）、受试者工作特征曲线分析和分类树分析，来评估这些肿瘤相关抗原（抗肿瘤相关抗原）的自身抗体在卵巢癌诊断中的性能。对于单一抗肿瘤相关抗原，当临界值设定为正常健康对照者的平均值+3标准差时，NPM1、MDM2、PLAT、p53和c-Myc在特异性为98%时可达到高于20%的敏感性。联合使用针对MDM2、PLAT、NPM1、14-3-3 Zeta、p53和RalA的自身抗体，在特异性为96%时达到了72.7%的敏感性，实现了最佳诊断性能。受试者工作特征曲线分析表明，针对c-Myc、NPM1、MDM2、p16、p53和14-3-3 Zeta的自身抗体的受试者工作特征曲线下面积大于0.80。这表明这些肿瘤相关抗原在卵巢癌检测中具有作为诊断生物标志物的高潜力。决策树分析表明，抗c-Myc在卵巢癌检测中具有高潜力。有必要进行进一步研究，以验证这些受试者工作特征曲线下面积较高的抗肿瘤相关抗原的诊断性能，包括针对c-Myc、MDM2、PLAT、NPM1、14-3-3 Zeta、p53和RalA的自身抗体。
