目的: 以血浆中游离的微RNAs（microRNAs,miRNAs）作为检测靶标构建神经母细胞瘤（neuroblastoma,NB）危险度分级无创诊断模型。方法: 基于转录组学技术筛选高危NB组织与中低危NB组织异常表达miRNAs,进一步在血浆水平上确证可用于NB危险度分级的关键miRNAs,最终基于确证的关键miRNAs利用Logistic回归分析法建立NB无创危险度分级诊断模型并使用受试者工作特征（receiver operating characteristic,ROC）曲线分析模型的诊断效能。结果: 基于转录组学技术筛选获得高危NB组织异常表达miRNAs共19条,进一步通过NB血浆水平验证确证获得三个NB危险度分级关键miRNAs（miR-488-3p、miR-514a-3p、miR-887-3p）,最后基于Logistic回归分析法建立的NB无创危险度分级诊断模型为Y=2.639-1.827×X1（miR-488-3p）+1.201×X2（miR-514a-3p）-1.484×X3（miR-887-3p）,该模型用于NB危险度分级的灵敏度及特异性分别为84.00%和95.56%。结论: 本研究构建的模型有望为NB危险度分级提供新的策略。
Abstract
Objective To establish a non-invasive risk classification diagnostic model for neuroblastoma (NB) by utilizing plasma-free microRNAs (miRNAs) as detection targets. Methods Based on transcriptomics technology, the abnormal expression of miRNAs between high-risk and medium-low-risk NB tissues was systematically screened. Key miRNAs for NB risk classification were further identified at the plasma level. Subsequently, a non-invasive risk classification diagnostic model was established using logistic regression analysis based on these key miRNAs. The diagnostic efficiency of the model was evaluated by analyzing the receiver operating characteristic (ROC) curve. Results A total of 19 miRNAs with abnormal expression in high-risk NB tissues were screened based on transcriptomics technology, and three key miRNAs for NB risk classification (miR-488-3p, miR-514a-3p, miR-887-3p) were further confirmed at the NB plasma level. Finally, based on logistic regression analysis, a non-invasive risk classification diagnostic model at the NB plasma level was established: Y=2.639-1.827×X1(miR-488-3p) + 1.201×X2(miR-514a-3p) - 1.484×X3(miR-887-3p). The sensitivity and specificity of this model for NB risk classification were 84.00% and 95.56%, respectively. Conclusion The model developed in this study is anticipated to offer a novel and effective strategy for NB risk classification.
关键词
神经母细胞瘤 /
微RNAs /
危险度分级 /
诊断模型 /
循环肿瘤RNA
Key words
neuroblastoma /
miRNAs /
risk classification /
diagnostic model /
circulating tumor RNA
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基金
国家自然科学基金委员会 “基于高危神经母细胞瘤关键分子的活体病理诊断新策略研究”（32201237）
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