5-Hydroxymethylcytosine profiles are prognostic of outcome in neuroblastoma and reveal transcriptional networks that correlate with tumor phenotype

Mark A. Applebaum*, Erin K. Barr, Jason Karpus, Ji Nie, Zhou Zhang, Amy E. Armstrong, Sakshi Uppal, Madina Sukhanova, Wei Zhang, Alexandre Chlenski, Helen R. Salwen, Emma Wilkinson, Marija Dobratic, Robert Grossman, Lucy A. Godley, Barbara E. Stranger, Chuan He, Susan L. Cohn

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

PURPOSE Whole-genome profiles of the epigenetic modification 5-hydroxymethylcytosine (5-hmC) are robust diagnostic biomarkers in adult patients with cancer. We investigated if 5-hmC profiles would serve as novel prognostic markers in neuroblastoma, a clinically heterogeneous pediatric cancer. Because this DNA modification facilitates active gene expression, we hypothesized that 5-hmC profiles would identify transcriptomic networks driving the clinical behavior of neuroblastoma. PATIENTS AND METHODS Nano-hmC-Seal sequencing was performed on DNA from Discovery (n = 51), Validation (n = 38), and Children’s Oncology Group (n = 20) cohorts of neuroblastoma tumors. RNA was isolated from 48 tumors for RNA sequencing. Genes with differential 5-hmC or expression between clusters were identified using DESeq2. A 5-hmC model predicting outcome in high-risk patients was established using linear discriminant analysis. RESULTS Comparison of low- versus high-risk tumors in the Discovery cohort revealed 577 genes with differential 5-hmC. Hierarchical clustering of tumors from the Discovery and Validation cohorts using these genes identified two main clusters highly associated with established prognostic markers, clinical risk group, and outcome. Genes with increased 5-hmC and expression in the favorable cluster were enriched for pathways of neuronal differentiation and KRAS activation, whereas genes involved in inflammation and the PRC2 complex were identified in the unfavorable cluster. The linear discriminant analysis model trained on high-risk Discovery cohort tumors was prognostic of outcome when applied to high-risk tumors from the Validation and Children’s Oncology Group cohorts (hazard ratio, 3.8). CONCLUSION 5-hmC profiles may be optimal DNA-based biomarkers in neuroblastoma. Analysis of transcriptional networks regulated by these epigenomic modifications may lead to a deeper understanding of drivers of neuroblastoma phenotype.

Original languageEnglish (US)
JournalJCO Precision Oncology
Volume3
DOIs
StatePublished - Jan 1 2019

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

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