Comparative cerebrospinal fluid metabolites profiling in glioma patients to predict malignant transformation and leptomeningeal metastasis with a potential for preventive personalized medicine

• Published in: The EPMA journal Vol. 11; no. 3; pp. 469 - 484
• Main Authors: Im, Ji Hye, Yoo, Byong Chul, Lee, Jun Hwa, Kim, Kyung-Hee, Kim, Tae Hoon, Lee, Kyue-Yim, Kim, Jong Heon, Park, Jong Bae, Kwon, Ji-Woong, Shin, Sang Hoon, Yoo, Heon, Gwak, Ho-Shin
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.09.2020; BioMed Central Ltd; Springer Nature B.V
• Subjects: Biomedical and Life Sciences; Biomedicine; Brain cancer; Brain tumors; Cancer metastasis; Cerebrospinal fluid; Development and progression; Glioma; Gliomas; Health aspects; Mass spectrometry; Medical research; Medicine/Public Health; Metabolites; Metastasis; Precision medicine; Scientific imaging; Metabolome; Leptomeningeal metastasis; Grade; Cerebrospinal fluid; Glioma; Predictive preventive personalized medicine
• ISSN: 1878-5077; 1878-5085
• DOI: 10.1007/s13167-020-00211-4

Glioma shows progression presenting as malignant transformation or leptomeningeal metastasis (LM). However, longitudinal biopsy of brain parenchyma is difficult due to its critical location, whereas cerebrospinal fluid (CSF) can be obtained serially with a little invasiveness of puncture. Thus, if we could find a biomarker for glioma progression, we could predict such event and determine therapeutic interventions as early as possible. In this study, we examined whether cerebrospinal fluid (CSF) metabolome profiles can reflect glioma grade, difference with non-glial tumor, and LM status. We selected 32 CSF samples from glioma patients, and compared them with 10 non-tumor control and seven non-glial brain tumor (medulloblastoma) samples. A total of 10,408 low-mass ions (LMIs) were detected as a candidate of metabolites using mass spectrometry, and representative LMIs were identified via the Human Metabolome Database. Grade IV gliomas showed eight LMIs, including acetic acid, of higher levels (summed sensitivity and specificity > 180%) than grade III gliomas. Grade IV gliomas demonstrated more abundant 30 LMIs, including glycerophosphate, compared with medulloblastoma, but none was mutually exclusive. Phospholipid derivatives were significantly more abundant in LM (−) than LM (+) gliomas regardless of glioma grade. LMIs representative of LM (+) gliomas were derivatives of glycolysis. We also verified discriminative LMIs based on mean expression level of each LMI (Student t test, p < 0.05) and evaluated the differences of the above analyses. Over 90% of metabolite pathways indicated from two analytical models were common to each other. Non-targeted mass spectrometry of CSF metabolites revealed significantly different profiles across gliomas that possibly permitted differentiation between glioma grades, LM, and non-glial brain tumors.