OMIC-04. IDENTIFICATION AND CHARACTERIZATION OF CIRCULATING RNAS (CODING AND NONCODING) AND METABOLITES IN CEREBROSPINAL FLUID IN MEDULLOBLASTOMA PATIENTS. (1st June 2021)

• Record Type: Journal Article
• Authors: Lee, Bongyong; Stapleton, Stacie; Pokhrel, Rudramani; Bettegowda, Chetan; Jallo, George; Perera, Ranjan
• Is Part Of: Neuro-oncology. Volume 23(2021)Supplement 1
• Page Start: i37
• Page End: i37
• Publication Date: 2021-06-01
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noab090.151
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: Medulloblastoma (MB) is the most common malignant brain tumor in children, and monitoring patients for treatment response and recurrence can be challenging with available current technologies in neuro-imaging and performing a biopsy to confirm response or recurrence carries risks, whereas cerebrospinal fluid (CSF) can be obtained with a little invasiveness. MB has altered cellular metabolism due to changes in gene expression, therefore, we hypothesized that any changes in MB cells lead to changes in cell-free transcripts and metabolites in CSF. To test this, we applied RNA-sequencing and mass spectrometry to analyze transcripts and metabolites including lipid in CSF from patients with different sub-groups of MB tumors (i.e., WNT, SHH, G3/4, G4, and unknown) and compared them to non-cancerous CSF. Tumor and sub-group specific transcriptomic and metabolic signatures were shown by unsupervised hierarchical clustering facilitating tumor type differentiation. By comparison with previously published tumor tissue RNA-seq data, we were able to identify a group of upregulated molecular signatures in both tumor tissue and CSF. We also identified a group of lipids that differentiate each MB sub-group from normal CSF, and Pathway analysis confirmed alterations in multiple metabolic pathways. Finally, we attempted to integrate RNA-seq data with lipidomics data, and results depict that the combinatorial analysis of CSF RNAs and metabolites can be useful in diagnosing and monitoring patients with MB tumors. (This research was conducted using samples made available by The Children's Brain Tumor Network.)