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Fueling Neuroblastoma: Genomic Analysis of Ketolytic and Glycolytic Gene Expression in Relation to MYCN Oncogene Amplification, Stage, and Prognosis
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  • Joseph W. Molloy,
  • David Lee,
  • Eric Downer,
  • Denis Barry
Joseph W. Molloy
Trinity College Dublin School of Medicine
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David Lee
Trinity College Dublin School of Medicine
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Eric Downer
Trinity College Dublin School of Medicine
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Denis Barry
Trinity College Dublin School of Medicine

Corresponding Author:[email protected]

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Background Neuroblastoma (NB) is a childhood cancer of the sympathetic nervous system, and its prognosis is poor. NB undergoes transcription changes to use aerobic glycolysis as its primary metabolic pathway. Aerobic glycolysis provides an immediate source of ATP in metastasis proliferation, and therefore may be exploited in dietary therapies, such as the ketone diet. Procedure In this study, the expression of glycolytic and ketolytic genes in the context of MYCN oncogene amplification, tumor staging, and Kaplan-Meier survivability was investigated using the R2: Genomics analysis and visualisation platform (http://r2.amc.nl). The R2 database is a platform for gene expression and prognostic data for primary tumour samples. Six NB genomics datasets were accessed and further analysed in GraphPad Prism to investigate the relationships between glycolytic and ketolytic gene expression and prognosis. Results 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 tumorigenicity and low probability of survival. Ketolytic gene expression patterns suggest a decreased reliance for ketolytic energy, which may be exploited to slow tumorigenic growth. Conclusions This study validates the glycolytic gene expression profiles in metastatic and MYCN-amplified NB tumours and suggest the potential use of these genes in prognosis prediction. Furthermore, the study highlights the reliability and utility of the R2 database as an oncogenomic tool for NB research.
30 Aug 2023Submitted to Cancer Reports
31 Aug 2023Assigned to Editor
31 Aug 2023Submission Checks Completed
31 Aug 2023Review(s) Completed, Editorial Evaluation Pending
06 Sep 2023Reviewer(s) Assigned
09 Nov 2023Editorial Decision: Revise Major