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On-Site Sampling and Extraction of Brain Tumors for Metabolomics and Lipidomics Analysis
Published on: May 31, 2020
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Cerebrospinal fluid methylome-based liquid biopsies for accurate malignant brain neoplasm classification
Jeffrey A Zuccato1,2, Vikas Patil1, Sheila Mansouri1,3
1MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
Neuro-Oncology
|December 1, 2022
Summary
Cerebrospinal fluid (CSF) methylomes can accurately classify brain metastases (BM), glioblastomas (GBM), and central nervous system lymphomas (CNSL) non-invasively. This liquid biopsy approach avoids risky surgical biopsies for brain tumor diagnosis.
Area of Science:
- Neuro-oncology
- Epigenetics
- Liquid Biopsy
Background:
- Distinguishing between brain metastases (BM), glioblastomas (GBM), and central nervous system lymphomas (CNSL) is critical for managing intra-axial brain tumors.
- Current diagnostic methods rely on invasive surgical biopsies, posing risks and morbidity to patients.
- Developing non-invasive diagnostic tools is essential to improve patient outcomes and streamline treatment decisions.
Purpose of the Study:
- To investigate the utility of methylomes from cerebrospinal fluid (CSF) for non-invasive classification of BM, GBM, and CNSL.
- To address the limitations of low target abundance in existing non-invasive diagnostic approaches.
- To establish a reliable liquid biopsy method for differentiating major intra-axial brain tumor types.
Main Methods:
- Development of binomial GLMnet classifiers using CSF methylomes from 57 patients with BM, GBM, CNSL, and controls.
- Utilizing 50 iterations with 80% discovery sets and 20% validation sets for classifier training and testing.
- Validation against publicly available tissue methylation profiles (N=197) and normal brain parenchyma data.
Main Results:
- Classifiers demonstrated reliable discrimination between BM (AUROC=0.93), GBM (AUROC=0.83), and CNSL (AUROC=0.91) in independent validation sets.
- CSF-based methylome signatures accurately distinguished tumor types in external tissue samples and from non-neoplastic controls.
- CSF methylome signals closely correlated with tissue-based signatures, with optimized models showing enhanced accuracy.
Conclusions:
- CSF methylomes offer a reliable basis for liquid biopsy-based classification of the three major malignant brain tumor types.
- Liquid biopsies hold potential to revolutionize brain cancer management by obviating surgical risks.
- This approach can aid in classifying unbiopsiable tumors and guiding surgical planning when resection is necessary.
