Experimental Assessment of Leptomeningeal Metastasis Diagnosis in Medulloblastoma Using Cerebrospinal Fluid Metabolomic Profiles

Abstract

Diagnosing leptomeningeal metastasis (LM) in medulloblastoma is currently based on positive cerebrospinal fluid (CSF) cytology or magnetic resonance imaging (MRI) finding. However, the relevance of discordant results has not been established. We evaluated the diagnostic potential of CSF metabolomic profiles in the medulloblastoma LM assessment. A total of 83 CSF samples from medulloblastoma patients with documented MRI and CSF cytology results at the time of sampling for LM underwent low-mass ions (LMIs) analysis using liquid chromatography-mass spectrometry. Discriminating LMIs were selected by a summed sensitivity and specificity (>160%) and LMI discriminant equation (LOME) algorithms, evaluated by measuring diagnostic accuracy for verifying LM groups of different MRI/cytology results. Diagnostic accuracy of LM in medulloblastoma was 0.722 for cytology and 0.889 for MRI. Among 6572 LMIs identified in all sample, we identified 27 discriminative LMIs differentiating MRI (+)/cytology (+) from MRI (–)/cytology (–). Using LMI discriminant equation (LOME) analysis, we selected 9 LMIs with a sensitivity of 100% and a specificity of 93.6% for differentiating MRI (+)/cytology (+) from MRI (–)/cytology (–). Another LOME of 20 LMIs significantly differentiated sampling time relative to treatment (p = 0.007) and the presence or absence of LM-related symptoms (p = 0.03) in the MRI (+)/cytology (–) group. CSF metabolomics of medulloblastoma patients revealed significantly different profiles among LM diagnosed with different test results. We suggest that LM patients could be screened by appropriately selected LOME-generated LMIs to support LM diagnosis by either MRI or cytology alone.

From Molecular Mechanisms to Therapeutics: Understanding MicroRNA-21 in Cancer

“…MiRNAs can exist in biofluids as either a part of an extracellular vesicle (EV) or a non-vesicle-associated ribonucleoprotein complex and can be used to distinguish patho-logies at various stages of disease progression [ 103 ]. Given that miR-21 is highly expressed in a wide variety of cancers and linked to several oncogenic characteristics, it has been evaluated as a diagnostic and prognostic cancer biomarker [ 104 , 105 , 106 , 107 , 108 , 109 ].…”