Wu Jiahui, Luo Huidan, Wang Kun, Yi Bin
Department of Clinical Laboratory and Medical Research Center, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.
National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.
Cancer Manag Res. 2023 Sep 27;15:1053-1062. doi: 10.2147/CMAR.S402572. eCollection 2023.
The mortality rate of nasopharyngeal carcinoma (NPC) remains high due to the absence of quick and accurate diagnostic approaches at its early stage. Our aim is to evaluate the diagnostic value of the elevated expression of Aurora kinase A (AURKA) and the oxidative stress markers (such as glutathione, superoxide dismutase and malondialdehyde) in serum of NPC patients and to establish a nomogram model for predicting NPC on the ground of these biomarkers.
Serum samples from 93 NPC patients and 94 healthy subjects were collected. Enzyme-linked immunosorbent assay (ELISA) was adopted to determine the AURKA level, while oxidative stress markers were measured by commercially available appropriate kits. Logistic regression was used for NPC predictor identification and nomogram construction. The training and validation cohorts (3:1) were randomly split up from the participants. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCAs) were performed to validate the nomogram.
AURKA and malondialdehyde (MDA) levels were significantly high in the NPC population compared to the healthy controls ( < 0.0001). The nomogram resulted in an area under the curve (AUC) of 0.897 (95% confidence interval: 0.848-0.947) in the training set and AUC of 0.770 (0.628-0.912) in the validation set. The predicted probability and the actual probability matched well in the nomogram ( > 0.05). DCAs showed good results too.
Serum levels of AURKA, SOD, and MDA have diagnostic values in NPC. The nomogram based on the identified biomarkers is favorable for NPC prediction.
由于缺乏早期快速准确的诊断方法,鼻咽癌(NPC)的死亡率仍然很高。我们的目的是评估Aurora激酶A(AURKA)表达升高以及氧化应激标志物(如谷胱甘肽、超氧化物歧化酶和丙二醛)在NPC患者血清中的诊断价值,并基于这些生物标志物建立预测NPC的列线图模型。
收集93例NPC患者和94例健康受试者的血清样本。采用酶联免疫吸附测定(ELISA)法测定AURKA水平,同时使用市售的合适试剂盒测量氧化应激标志物。采用逻辑回归进行NPC预测指标的识别和列线图构建。训练组和验证组(3:1)从参与者中随机划分。进行受试者操作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)以验证列线图。
与健康对照组相比,NPC患者群体中AURKA和丙二醛(MDA)水平显著升高(<0.0001)。列线图在训练集中的曲线下面积(AUC)为0.897(95%置信区间:0.848 - 0.947),在验证集中的AUC为0.770(0.628 - 0.912)。列线图中的预测概率与实际概率匹配良好(>0.05)。DCA结果也显示良好。
血清中AURKA、SOD和MDA水平在NPC中具有诊断价值。基于所识别生物标志物的列线图有利于NPC的预测。