340 Predicting Progression and Recurrence of Pediatric Low Grade Gliomas Using miRNA Composition in Plasma and CSF. (April 2023) - Coyle, Anne; Rathi, Komal; Koptyra, Mateusz; Foster, Jessica; Hollawell, Madison; Beck, Christopher; Choudhari, Namrata; Storm, Phillip B.; Resnick, Adam C.; Tucker, Alexander M.; Madsen, Peter J.
Abstract : INTRODUCTION: Liquid biopsy is a non-invasive method of diagnosing and monitoring brain tumor patients. miRNA profiling from cerebrospinal fluid (CSF) and plasma has become an increasingly attractive biomarker, however targets have yet to be established in CNS tumors. Low grade glioma (LGG) patients often have excellent outcomes, but some have progressive disease or unresectable lesions. There has been limited work in establishing a clinically approved liquid biopsy assay for such patients. METHODS: miRNA profiling of 17 plasma and 12 CSF samples from 10 pediatric LGG and 7 DMG patients was performed using the HTG EdgeSeq platform. Clinical information was obtained through chart review. miRNA expression was evaluated with unsupervised consensus clustering and differential analysis. RESULTS: At time of data analysis, 5 LGG had progression or recurrence. The remaining LGG (5) had stable or no evidence of disease. Mean follow-up was 23 months. miRNA consensus clustering revealed that LGG with a recurrence, progression, or malignant transformation clustered with DMG rather than with tumors of similar histology or WHO classification. Pilocytic astrocytoma could be identified by miRNA composition in CSF. In plasma, 103 unique miRNAs were identified with significant differential expression between the progression/recurrence LGG cohort versus those with stable or no evidence of disease (logFC > 1, FDR < 0.05). miR-16-5p, a miRNA correlated with tumor growth and invasion in non-CNS tumors, had higher expression in the more aggressive cohort (p = 0.0022). Over 100 miRNAs correlated with histology, survival, disease state, and presence of leptomeningeal disease (p < 0.05). CONCLUSIONS: miRNA profiling of CSF and plasma in patients with LGG may predict disease course to better inform patient care and treatment monitoring.