Fuelling Neuroblastoma: Genomic Analysis of Ketolytic and Glycolytic Gene Expression in Relation to MYCN Oncogene Amplification, Stage and Prognosis
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Published on: March 31, 2015
Joseph W Molloy1, Karl Keogh1, Mary-Kate McLoughlin1
1Discipline of Anatomy, School of Medicine, Trinity College Dublin, Dublin, Ireland.
Background:
Neuroblastoma (NB) is a childhood cancer of the sympathetic nervous system, and its prognosis is poor. NB cells undergo transcriptional changes to utilise aerobic glycolysis as their primary metabolic pathway, which provides an immediate source of ATP to meet high biosynthetic demands. Alternative metabolic fuel inputs, including ketone bodies which require oxidative phosphorylation, may impact the proliferative capacity of NB.
Aims:
In this exploratory study, the expression of glycolytic and ketolytic genes in the context of MYCN oncogene amplification, tumour staging 1-4 and Kaplan-Meier survivability was investigated using the R2: Genomics analysis and visualisation platform (http://r2.amc.nl), database.
Methods And Results:
Three NB genomics datasets were assessed in the R2 platform and further analysed in GraphPad Prism to investigate the relationships between glycolytic and ketolytic gene expression and prognosis. Glycolytic gene expression is increased in MYCN amplified, metastatic tumours and is associated with worse event free survival. Ketolytic gene expression is lower in metastatic tumours and is associated with better event free survivability. The glycolytic gene expression profile of NB suggests that elevated levels correlate with a low probability of survival. Ketolytic gene expression patterns suggest a decreased reliance for ketolytic energy, which may be exploited to slow tumourigenic growth.
Conclusions:
This study validates glycolytic and ketolytic gene expression profiles in metastatic and MYCN amplified NB tumours and through conditional analysis suggests the potential use of these genes in prognosis prediction. Furthermore, the study highlights the reliability and utility of genomic databases as oncogenomic tools for NB research.
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