高危MYCN未扩增神经母细胞瘤中一种新型五基因特征的鉴定与验证
Identification and validation of a novel five-gene signature in high-risk MYCN-not-amplified neuroblastoma.
作者信息
Wang Jin-Xia, Zhang Hong-Yang, Yan Zi-Jun, Cao Zi-Yang, Shao Jing-Bo, Zou Lin
机构信息
Clinical Research Unit, Shanghai Children's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200062, China.
Institute of Pediatric Infection, Immunity, and Critical Care Medicine, Shanghai Children's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200062, China.
出版信息
Discov Oncol. 2024 Sep 18;15(1):456. doi: 10.1007/s12672-024-01318-0.
OBJECTIVE
High-risk neuroblastoma patients often have poor outcomes despite multi-treatment options. The risk stratification of high-risk MYCN-not-amplified (HR-MYCN-NA) patients remains difficult. This study aims to identify a gene set signature that can help further stratify HR-MYCN-NA patients for a potential personalized therapeutic strategy.
METHODS
Three microarrays and one single-cell RNA sequence dataset were acquired and analyzed. Firstly, the prognostic-related genes (PRGs) in HR-MYCN-NA tumor cells were identified using TARGET-NB and GSE137804 datasets. Then, the prognostic model was established by LASSO-Cox regression, and verified in external cohort (GSE49710, GSE45547). Moreover, a time-dependent receiver operating characteristic curve (ROC) and area under the ROC (AUC) was used to assess survival prediction. A nomogram was established to predict the 1-, 3- and 5-year overall survival (OS) of HR-MYCN-NA patients.
RESULTS
In the training set, a five-PRGs signature, which include GAL, GFRA3, MARCKS, PSMD13, and ZNHIT3 genes, was identified and successfully stratified HR-MYCN-NA patients into ultra-high risk (UHR) and high-risk (HR) subtypes (HR = 4.29, P < 0.001). ROC curve analysis confirmed its predictive power (AUC = 0.74-0.82), suggesting a good predictive efficacy. Consistently, high-risk scores also predicted worse OS (HR = 2, P = 0.033) in the external validation dataset (AUC = 0.67-0.71). Moreover, the overall C-index of the nomogram was 0.75 (P < 0.001), which indicated good agreement between the observed and predicted survival rates. Further integrating the five PRGs signature with clinical factors, these 5 gene signature (HR = 4.45, P < 0.001) and tumor grade (HR = 4.15, P = 0.02) were found to be independent prognostic factors for HR-MYCN-NA patients.
CONCLUSION
The novel five PRGs signature could well predict the survival of HR-MYCN-NA patients, which may provide constructive information for these subsets.
目的
尽管有多种治疗选择，但高危神经母细胞瘤患者的预后往往较差。高危MYCN未扩增（HR-MYCN-NA）患者的风险分层仍然困难。本研究旨在确定一种基因集特征，以帮助进一步对HR-MYCN-NA患者进行分层，从而制定潜在的个性化治疗策略。
方法
获取并分析了三个微阵列和一个单细胞RNA序列数据集。首先，使用TARGET-NB和GSE137804数据集鉴定HR-MYCN-NA肿瘤细胞中的预后相关基因（PRG）。然后，通过LASSO-Cox回归建立预后模型，并在外部队列（GSE49710、GSE45547）中进行验证。此外，使用时间依赖性受试者工作特征曲线（ROC）和ROC曲线下面积（AUC）评估生存预测。建立了列线图以预测HR-MYCN-NA患者的1年、3年和5年总生存率（OS）。
结果
在训练集中，鉴定出一个包含GAL、GFRA3、MARCKS、PSMD13和ZNHIT3基因的五PRG特征，并成功将HR-MYCN-NA患者分为超高风险（UHR）和高风险（HR）亚型（HR = 4.29，P < 0.001）。ROC曲线分析证实了其预测能力（AUC = 0.74 - 0.82），表明具有良好疗效。同样，在外部验证数据集中，高风险评分也预测了更差的OS（HR = 2，P = 0.033）（AUC = 0.67 - 0.71）。此外，列线图的总体C指数为0.75（P < 0.001）表明观察到的和预测的生存率之间具有良好的一致性。进一步将五PRG特征与临床因素相结合，发现这5个基因特征（HR = 4.45，P < 0.001）和肿瘤分级（HR = 4.15，P = 0.02）是HR-MYCN-NA患者的独立预后因素。
结论
新的五PRG特征可以很好地预测HR-MYCN-NA患者的生存情况，这可能为这些亚组提供建设性信息。
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