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自身抗体标志物作为鼻咽癌检测的生物标志物面板。

Autoantibody Signatures as a Biomarker Panel for the Detection of Nasopharyngeal Carcinoma.

机构信息

Key Laboratory of Molecular Biology in High Cancer Incidence Coastal Chaoshan Area of Guangdong Higher Education Institutes, Shantou University Medical College, Shantou, Guangdong, China; Department of Preventive Medicine, Shantou University Medical College, Shantou, Guangdong, China; Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou, Guangdong, China.

Key Laboratory of Molecular Biology in High Cancer Incidence Coastal Chaoshan Area of Guangdong Higher Education Institutes, Shantou University Medical College, Shantou, Guangdong, China; Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou, Guangdong, China.

出版信息

Arch Med Res. 2021 Aug;52(6):620-626. doi: 10.1016/j.arcmed.2021.02.007. Epub 2021 Feb 28.

Abstract

OBJECTIVE

The early symptoms of nasopharyngeal carcinoma (NPC) are not obvious, and it is difficult to make early diagnosis. A case-control study was conducted to identify potential biomarkers and established a diagnosis model for nasopharyngeal carcinoma.

METHODS

Plasma samples of 131 cases of NPC and 132 cases of healthy individuals were incubated with the Ray Biotech Human Lung Cancer IgG Autoantibody Detection Array G1, and signal values were used to develop a risk prediction model for NPC diagnosis.

RESULTS

Of the 30 autoantibodies, high expression of MAGE-A4, NY-ESO-1, HuD, Survivin, IMDH2, Ubiquilin-1, IMP1, PGP9.5, IMP3, C-Myc and low expression of Cyclin B1 were potential biomarkers for NPC diagnosis (p <0.05), among which Survivin, MAGE-A4 and IMP3 shows higher AUC of 0.674, 0.652 and 0.650 respectively, the specificity of them was 89.39% (95% CI: 82.85-94.08%), 90.15% (95% CI: 83.75-94.65%) and 88.64% (81.95-93.50%).The risk probability analysis for NPC diagnosis based on the panel of Cyclin B1, NY-ESO-1, Survivin, and IMP3 displayed the best diagnosis performance with an AUC of 0.779, p (Yi = 1) = 1/(1+EXP[8.316+1.672CyclinB1-1.152NY-ESO-1-2.052Survivin-0.950IMP3]), the specificity of that was 86.36% (95% CI: 79.31-91.71%).

CONCLUSIONS

Our findings demonstrated that the panel of Cyclin B1, NY-ESO-1, Survivin, and IMP3 has a good performance in the detection of NPC, and all 11 autoantibodies may also have a certain significance for the prognosis of NPC.

摘要

目的

鼻咽癌(NPC)的早期症状不明显,难以做出早期诊断。本研究采用病例对照研究方法,旨在寻找潜在的生物标志物,并建立 NPC 诊断模型。

方法

用 Ray Biotech 公司的 Human Lung Cancer IgG Autoantibody Detection Array G1 孵育 131 例 NPC 患者和 132 例健康对照者的血浆样本,根据信号值建立 NPC 诊断风险预测模型。

结果

在 30 种自身抗体中,MAGE-A4、NY-ESO-1、HuD、Survivin、IMDH2、Ubiquilin-1、IMP1、PGP9.5、IMP3、C-Myc 高表达和 Cyclin B1 低表达可能是 NPC 诊断的潜在生物标志物(p<0.05),其中 Survivin、MAGE-A4 和 IMP3 的 AUC 分别为 0.674、0.652 和 0.650,其特异性分别为 89.39%(95%CI:82.85-94.08%)、90.15%(95%CI:83.75-94.65%)和 88.64%(81.95-93.50%)。基于 Cyclin B1、NY-ESO-1、Survivin 和 IMP3 构建的 NPC 风险概率分析显示,其诊断效能最佳,AUC 为 0.779,p(Yi=1)=1/(1+EXP[8.316+1.672CyclinB1-1.152NY-ESO-1-2.052Survivin-0.950IMP3]),其特异性为 86.36%(95%CI:79.31-91.71%)。

结论

本研究发现,Cyclin B1、NY-ESO-1、Survivin 和 IMP3 联合检测在 NPC 诊断中具有良好的性能,11 种自身抗体可能对 NPC 的预后也具有一定的意义。

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