EPEN-21. Developing a sensitive method for detection of minimal residual disease in ependymoma using metabolomic analysis of cerebrospinal fluid

Abstract

INTRODUCTION: Ependymoma (EPN) is the second most common malignant paediatric brain tumour with poor survival and significant neuro-cognitive impairment from current treatments (surgery and radiotherapy). Relapse occurs in 50% of patients within 2 years, despite no evidence of tumour on MRI. This suggests that they have minimal residual disease (MRD) at the end of treatment. Developing an accurate MRD detection method could help select patients who would benefit from further continuation chemotherapy, thereby improving survival. There is also an unmet need for an accurate test to diagnose relapse early when the disease could be more treatable. METHODS: Pilot untargeted liquid chromatography-mass spectrometry (LC-MS) analysis was carried out in cerebrospinal fluid (CSF) samples from patients with ependymoma. CSF from patients in remission from leukemia were used as controls. RESULTS: Pilot data from analysis of CSF using LC-MS demonstrates that this is a feasible approach to characterise CSF metabolomic profile. Also, EPN CSF profile is significantly different from control CSF, with significant elevation of few key metabolites (Vitamin D derivatives and betaine) in EPN CSF compared to control CSF. Immunohistochemical analysis of EPN tumour tissue microarrays confirms the expression of betaine / one-carbon pathway enzymes such as methionine synthase and betaine—homocysteine S-methyltransferase. Further validation of CSF profile with tumour metabolomic profile and serial CSF sample profiling is currently underway. Subgroup-specific differences and targeted analysis to develop a panel of biomarkers is also being explored. CONCLUSION: Early results suggest that CSF-based metabolite profiling using LC-MS is feasible and could help detect minimal residual disease in ependymoma. Further validation is required to analyse subgroup-specific differences and correlate quantitative changes in metabolites with changing disease burden.