Project description:Neuroblastoma is a pediatric cancer of the developing sympathetic nervous system. High-risk neuroblastoma patients typically undergo an initial remission in response to treatment, followed by recurrence of aggressive tumors that have become refractory to further treatment. The need for biomarkers that can select patients not responding well to therapy in an early phase is therefore needed. In this study, we used next generation sequencing technology to determine the expression profiles in high-risk neuroblastoma cell lines established before and after therapy. Using partial least squares-discriminant analysis (PLS-DA) with least absolute shrinkage and selection operator (LASSO) and leave-one-out cross-validation, we identified a panel of 55 messenger RNAs and 17 long non-coding RNAs (lncRNAs) which were significantly altered in the expression between cell lines isolated from primary and recurrent tumors. From a neuroblastoma patient cohort, we found 20 of the 55 protein-coding genes to be differentially expressed in patients with unfavorable compared with favorable outcome. We further found a twofold increase or decrease in hazard ratios in these genes when comparing patients with unfavorable and favorable outcome. Gene set enrichment analysis (GSEA) revealed that these genes were involved in proliferation, differentiation and regulated by Polycomb group (PcG) proteins. Of the 17 lncRNAs, 3 upregulated (NEAT1, SH3BP5-AS1, NORAD) and 3 downregulated lncRNAs (DUBR, MEG3, DHRS4-AS1) were also found to be differentially expressed in favorable compared with unfavorable outcome. Moreover, using expression profiles on both miRNAs and mRNAs in the same cohort of cell lines, we found 13 downregulated and 18 upregulated experimentally observed miRNA target genes targeted by miR-21, -424 and -30e, -29b, -138, -494, -181a, -34a, -29b, respectively. The advantage of analyzing biomarkers in a clinically relevant neuroblastoma model system enables further studies on the effect of individual genes upon gene perturbation. In summary, this study identified several genes, which may aid in the prediction of response to therapy and tumor recurrence.

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