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.