Wang Jing, Meng Xinyao, Chen Ke, Feng Jiexiong
Department of Pediatric Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Front Oncol. 2022 Dec 1;12:1014845. doi: 10.3389/fonc.2022.1014845. eCollection 2022.
This study aimed to identify autophagy-related long non-coding RNAs (lncRNAs) associated with progression of neuroblastoma (NB), and to build an autophagy-related lncRNA signature that helps to predict progression-free survival (PFS) of NB.
Three independent gene expression datasets were utilized in this study. Autophagy-related genes (ARG) associated with PFS of NB patients were firstly identified by univariate Cox survival analysis. lncRNAs correlated with those PFS-related ARGs were then identified. The least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses were performed to select out those lncRNAs with the best prognostic value for PFS. The Receiver Operating Characteristic (ROC) and Area Under Curve (AUC) analyses were performed to assess the prediction accuracy.
Four autophagy-related lncRNAs (AL356599.1, AC022075.1, AC020928.1 and LINC02076) were found to be with the best prognostic value and integrated into a four-lncRNA risk signature for predicting PFS of NB patients. The four-lncRNA signature significantly stratify NB patients into two risk groups, with high-risk group has significantly poorer PFS than the low-risk group. The prognostic role of the lncRNA signature was independent with other clinical risk factors. The ROC curves revealed that the lncRNA signature has a good performance in predicting PFS (AUC > 0.70). A nomogram based on COG (Children's Oncology Group) risk and the lncRNA risk score was constructed, showing good prediction accuracy (C-index = 0.700). The prognostic ability of the nomogram was better than that of COG risk alone (AUC = 0.790 versus AUC = 0.748). GSEA analyses revealed that multiple autophagy-related gene sets are significantly enriched in the low-risk group.
We identified an autophagy-related four-lncRNA signature that could help to predict the PFS of NB patients. Autophagy-related gene sets are significantly enriched in low-risk group, suggesting tumor suppressive roles of autophagy in NB.
本研究旨在鉴定与神经母细胞瘤(NB)进展相关的自噬相关长链非编码RNA(lncRNA),并构建有助于预测NB无进展生存期(PFS)的自噬相关lncRNA特征。
本研究使用了三个独立的基因表达数据集。首先通过单变量Cox生存分析鉴定与NB患者PFS相关的自噬相关基因(ARG)。然后鉴定与这些PFS相关ARG相关的lncRNA。进行最小绝对收缩和选择算子(LASSO)回归和多变量Cox回归分析,以筛选出对PFS具有最佳预后价值的lncRNA。进行受试者工作特征(ROC)和曲线下面积(AUC)分析以评估预测准确性。
发现四个自噬相关lncRNA(AL356599.1、AC022075.1、AC020928.1和LINC02076)具有最佳预后价值,并整合为一个四lncRNA风险特征,用于预测NB患者的PFS。该四lncRNA特征将NB患者显著分为两个风险组,高危组的PFS明显低于低危组。lncRNA特征的预后作用独立于其他临床风险因素。ROC曲线显示lncRNA特征在预测PFS方面表现良好(AUC>0.70)。构建了基于儿童肿瘤学组(COG)风险和lncRNA风险评分的列线图,显示出良好的预测准确性(C指数=0.700)。列线图的预后能力优于单独的COG风险(AUC=0.790对AUC=0.748)。基因集富集分析(GSEA)显示多个自噬相关基因集在低风险组中显著富集。
我们鉴定了一个自噬相关的四lncRNA特征,可有助于预测NB患者的PFS。自噬相关基因集在低风险组中显著富集,表明自噬在NB中具有肿瘤抑制作用。