A c-Myc-regulated stem cell-like signature in high-risk neuroblastoma: A systematic discovery (Target neuroblastoma ESC-like signature)

Abstract

c-Myc dysregulation is hypothesized to account for the 'stemness' - self-renewal and pluripotency - shared between embryonic stem cells (ESCs) and adult aggressive tumours. High-risk neuroblastoma (HR-NB) is the most frequent, aggressive, extracranial solid tumour in childhood. Using HR-NB as a platform, we performed a network analysis of transcriptome data and presented a c-Myc subnetwork enriched for genes previously reported as ESC-like cancer signatures. A subsequent drug-gene interaction analysis identified a pharmacogenomic agent that preferentially interacted with this HR-NB-specific, ESC-like signature. This agent, Roniciclib (BAY 1000394), inhibited neuroblastoma cell growth and induced apoptosis in vitro. It also repressed the expression of the oncogene c-Myc and the neural ESC marker CDK2 in vitro, which was accompanied by altered expression of the c-Myc-targeted cell cycle regulators CCND1, CDKN1A and CDKN2D in a time-dependent manner. Further investigation into this HR-NB-specific ESC-like signature in 295 and 243 independent patients revealed and validated the general prognostic index of CDK2 and CDKN3 compared with CDKN2D and CDKN1B. These findings highlight the very potent therapeutic benefits of Roniciclib in HR-NB through the targeting of c-Myc-regulated, ESC-like tumorigenesis. This work provides a hypothesis-driven systems computational model that facilitates the translation of genomic and transcriptomic signatures to molecular mechanisms underlying high-risk tumours.

Figure 1

Systems biology analysis workflow. (a) Multi-scale data collection (inputs). (b) Systems computational approaches for hypothesis testing. Enriched gene-sets gain overlap at the biological pathway level. Thus, we identified recurrently dysregulated pathways and pathway genes from multi-scale data. Subsequently, we identified critical topological features from the HR-NB-associated PPI subnetwork. Finally, we scanned pharmacological agents for the over-representation of their interacting targets among the gene signatures that were recurrent at the pathway and protein levels. Notably, this computational work links clinical relevance to an ESC-like signal. (c) Generation of new hypotheses based on the above computational analysis and literature review and the subsequent design of biological experiments. (d) Biological in vitro evaluation and clinical application validated for data from independent patients.

Figure 2

An HR-NB-associated PPI subnetwork suggests that MYC regulation is the common thread linking the cancer-activated ESC-like signature to HR-NB. (a) A Venn diagram of c-Myc interacting proteins, hubs in the NB-associated PPI subnetwork, and the HR signature. c-Myc gains significant interactions with other network hubs (P = 2e-7, OR = 5.6), as evidenced by 17 of its 221 neighbours that are hubs (of the 4,460 connected proteins). (B) c-Myc is among the leading PPI hubs, with a high network degree that exhibits significance in both the theoretical test (FET P < 1e-5, OR > 2, plotted in nodes) and an empirical test (P < 0.01, plotted in crosses). The green horizontal line indicates the criteria of “hub” (P = 1e-5). The orange dotted horizontal line marks an average degree of 41. The gene symbol colour corresponds to MYCN-dependent over-expression (red: MA, blue: MN; black: NS). (c) Seventeen c-Myc-interacting PPI hubs over-represented GO terms for biological-process (BP). The reported biological processes met the following significance criteria: (1) FET odds ratio >2; (2) FET FDR <0.01; (3) FAIME score >0; and 4) at least five gene members. (d) The HR-specific PPI sub-network identified 26 proteins as both hubs and bottlenecks (STRING), eleven of which are featured as hubs and bottlenecks using BioGRID (the bold italic symbols). Eleven of these proteins are part of the ESC-like cancer signature (the boxed nodes). Gene symbols are coloured as in panel B.

Figure 3

The cyclin-dependent kinase inhibitor Roniciclib induces morphological changes and cell apoptosis in human neuroblastoma cells. (a) Roniciclib is the only drug that is commonly over-represented in the ESC-like cancer-activated signature, HR genes, and the MA-dependently expressed MA or MN genes. (b) Roniciclib induces apoptotic cell death in SY5Y in a concentration-dependent manner. Proliferating SY5Y cells were exposed to different concentrations of Roniciclib for 72 h. Caspase-3 activity was measured by monitoring Ac-DEVD-R110 fluorescence. The data are represented as the mean ± SD of three independent experiments. (c) Morphological changes and cell number decrease in human neuroblastoma cells observed under an inverted microscope (magnification, 20x): Blank control group, dimethyl sulfoxide-treated group (0.1% DMSO, 72 h), and Roniciclib-treated group (1 μmol/L, 72 h).

Figure 4

Identification of prognostic biomarkers and clinical evaluation. (a) The identification of prognostic CDK and CDKN genes (indicated by arrows). The genes indicated in red are poor-outcome candidates among HR-signature genes that are highly expressed in embryonic neural stem cells (ENSCs) compared with adult neural cell (ANC) samples (log2 FC > 1.5). The genes indicated in blue are good-outcome candidates among the LR genes that are highly expressed in ANC compared with ENSC. (b) Hazard ratios of survival analysis for all 42 possible gene-set pairs. The top subpanel shows the density of the hazard ratio distribution for the event-free survival (EFS) analysis. A value larger than 1 indicates an unfavourable outcome. The bottom subpanel is a hex-binned heatmap of EFS hazard ratios compared with overall survival (OS) hazard ratios. The dashed line indicates two analyses that have the same hazard ratios. (c,d,e) Kaplan-Meier plots for the EFS of patients. The subpanels c-e depict patients with HR-NB, HR-NB patients without MYCN amplification (MN), and all NB patients without MYCN amplification, respectively. Subpanels 1 and 2 depict the training and validation datasets, respectively. In all subpanels, positive I-scores (i.e., higher CDK2 and CDKN3 expression compared with CDKN1B and CDKN2D) significantly indicate poor outcome for HR-NB (P < 0.005).

Figure 5

Prediction and validation of ESC-like signature genes that interact with Roniciclib, which are used as new biomarkers. (a) Venn diagram of the computational prediction of new biomarkers irrespective of MYCN status. Among the ten Roniciclib-interacting genes, four CDKs are inhibited and are underlined. Data resource: DGIdb. The gene symbol colour corresponds to MYCN-dependent over-expression (red: MA, blue: MN; black: NS). (b) Roniciclib alters c-Myc and CCND1 protein expression. The SY5Y cells were plated in 60 mm dishes one day before treatment. The cells were treated with or without vehicle control (DMSO) or Roniciclib (1 μM) for the indicated times. Then, 100 μg of protein was loaded and resolved by 10% SDS-PAGE. β-actin was used as a loading control. (c) Quantitative analysis of mRNA expression in a human HR-NB cell line after Roniciclib treatment for 24, 48, 72 or 96 h. The relative expression levels were normalized to the mean expression level of GAPDH. The data shown are the mean relative expression levels ± SD of replicate experiments after normalization to the non-treated control. The significance (NS > 0.1, . ≤0.1, *<0.05, **<0.01) was estimated by a two-tailed Welch’s corrected t-test that compares Roniciclib with DMSO in each scenario, followed by the number of biological replicates.

Figure 6

c-Myc plays a role in the Roniciclib-impacted tumour-initiating cell mechanisms in HR-NB. (a) Genomic view of four gene promoters showing chromatin accessibility with c-MYC/MAX occupancy (ENCODE data, hg19 assembly). The view scale of c-MYC/MAX is between 0 and 50, whereas that of DNase is between 0 and 80 in each sub-panel. (b) Quantitative analysis of mRNA expression in human HR-NB cells after Roniciclib treatment for 24 h. The relative expression levels were normalized to mean GAPDH expression. The data shown are the mean relative expression levels ± SD of replicate experiments after normalization to the non-treated vehicle. The p-value of a two-tailed Welch’s corrected t-test that compares Roniciclib to DMSO is given in each scenario, followed by the number of biological replicates. (c) Proposed model of c-Myc-regulated tumour initiating cell markers that were targeted by Roniciclib in a time-dependent manner in HR-NB. The genes indicated in red are potential neural stem cell markers that are highly expressed, and the genes indicated in blue are neural cell differentiation markers that are repressed in HR-NB compared with LR-NB. The two origin arrows along with each gene indicate the expression changes corresponding to Roniciclib treatment at an early and later phase, respectively.