Unveiling MYCN regulatory networks in neuroblastoma via integrative analysis of heterogeneous genomics data

Abstract

MYCN, an oncogenic transcription factor of the Myc family, is a major driver of neuroblastoma tumorigenesis. Due to the difficulty in drugging MYCN directly, revealing the molecules in MYCN regulatory networks will help to identify effective therapeutic targets for neuroblastoma therapy. Here we perform ChIP-sequencing and small RNA-sequencing of neuroblastoma cells to determine the MYCN-binding sites and MYCN-associated microRNAs, and integrate various types of genomic data to construct MYCN regulatory networks. The overall analysis indicated that MYCN-regulated genes were involved in a wide range of biological processes and could be used as signatures to identify poor-prognosis MYCN-non-amplified patients. Analysis of the MYCN binding sites showed that MYCN principally served as an activator. Using a computational approach, we identified 32 MYCN co-regulators, and some of these findings are supported by previous studies. Moreover, we investigated the interplay between MYCN transcriptional and microRNA post-transcriptional regulations and identified several microRNAs, such as miR-124-3p and miR-93-5p, which may significantly contribute to neuroblastoma pathogenesis. We also found MYCN and its regulated microRNAs acted together to repress the tumor suppressor genes. This work provides a comprehensive view of MYCN regulations for exploring therapeutic targets in neuroblastoma, as well as insights into the mechanism of neuroblastoma tumorigenesis.

Transcription factor activating protein 4 is synthetically lethal and a master regulator of MYCN-amplified neuroblastoma

“…2e ), indicating that TFAP4 is directly regulated by MYCN. Consistent with our results, Hsu et al [ 26 ], performed ChIP-seq using an anti-MYCN antibody in the MYCN-amplified neuroblastoma cell BE(2)C, demonstrated that TFAP4 is a direct transcriptional MYCN target.…”

Co-expression analysis identifies long noncoding RNA SNHG1 as a novel predictor for event-free survival in neuroblastoma

“…This suggests that SNHG1 is not only correlated with MYCN amplification but also with MYCN expression. Moreover, our ChIP-seq data analysis observed MYCN binding sites in the promoter of SNHG1 ( Supplementary Figure S5 ) [ 33 ]. Furthermore, previous study has pointed out that lncRNAs possess tissue-specific expression [ 34 ].…”

Introduction to Cancer Systems Biology

“…How to integrate and mine these data is an important issue. 4 There is no doubt that bioinformatics or computational biology can help researchers analyze these big omics data. The categories of bioinformatics contain many subfields such as sequence analysis, genome annotation, transcriptome and proteome analyses, as well as network biology and dynamic modeling.…”

“…[7][8][9][10] In addition to target and drug discovery, cancer systems biology represents a valuable contribution to efforts toward understanding the molecular mechanism of drugs in various cancer types 5,11 and regulation in cancer progression. 4 …”

“…Additionally, we identified several microRNAs, such as miR-124-3p and miR-93-5p, and RNA binding proteins: Synaptotagmin binding, cytoplasmic RNAinteracting protein (SYNCRIP) and insulin-like growth factor-2 mRNAbinding protein 3 (IGF2BP3), which could be potential therapeutic targets for NB. 4 Besides genomics and transcriptomics, proteomics can also be used to discover potential targets and biomarkers. 12 In our previous studies, we utilized two dimensional (2D)-based proteomics coupling MS to identify therapeutic targets or biomarkers for breast cancer, 9 lung cancer, 13 and gastric cancer.…”