A feasibility study of enzymatic methylation sequencing of cell-free DNA from cerebrospinal fluid of pediatric central nervous system tumor patients for molecular classification

Abstract

Background: Array-based DNA methylation profiling is the gold standard for central nervous system (CNS) tumor molecular classification, but requires over 100 ng input DNA from surgical tissue. Cell-free tumor DNA (cfDNA) in cerebrospinal fluid (CSF) offers an alternative for diagnosis and disease monitoring. This study aimed to test the utilization of enzymatic DNA methylation sequencing (EM-seq) methods to overcome input DNA limitations.

Methods: We used the NEBNext EM-seq v2 kit on various amounts of cfDNA, as low as 0.1 ng, extracted from archival CSF samples of 10 patients with CNS tumors. Tumor classification was performed via MNP-Flex using CpG sites overlapping those on the MethylationEPIC array.

Results: EM-seq provided sufficient genomic coverage for 10 and 1 ng input DNA samples to generate global DNA methylation profiles. Samples with 0.1 ng input showed lower coverage due to read duplication. Methylation levels for CpG sites with at least 5× coverage were highly correlated across various input DNA amounts, indicating that lower input cfDNA can still be used for tumor classification. The MNP-Flex classifier, trained on tissue DNA methylation data, successfully predicted CNS tumor types for 7 out of 10 CSF samples using EM-seq methylation data with only 1 ng of input cfDNA, consistent with diagnoses based on tissue MethylationEPIC classification and/or histopathology. Additionally, we detected focal and arm-level copy number alterations previously identified via clinical cytogenetics of tumor tissue.

Conclusions: This study demonstrated the feasibility of CNS tumor molecular classification based on CSF using the EM-seq approach, and establishes potential sample quality limitations for future studies.

Keywords: CNS tumor classification; MNP-flex; cell-free DNA; enzymatic methylation sequencing; molecular diagnosis.

Figure 1.

Overview of EM-seq analysis of CSF samples. (A) Schematic workflow of CSF sample preparation, sequencing, and analysis. Prepared using the NIAID NIH BIOART Source (https://bioart.niaid.nih.gov/). (B) DNA fragment size profile of extracted cfDNA from HGG47 and MB11 samples by TapeStation. Vertical blue lines represent the size range of cfDNA within the CSF (50–700 bp). (C) Average methylation values for spike-in controls for varying input DNA amounts in both HGG47 and MB11 samples. pUC19 (methylated) control shown in black, lambda (unmethylated) DNA shown in white. (D) Average methylation values for different cytosine contexts (CpG, CHG, CHH) for varying input DNA amounts in both HGG47 and MB11 samples.

Figure 2.

Pearson correlation between methylation values of CpG sites with at least 10× coverage across all input cfDNA values for (A) HGG47 and (B) MB11.

Figure 3.

Arm-level copy number alterations detected in cfDNA from CSF. Copy number calculated from read depth across 100kbp bins using CNVpytor. For each sample, (A) MB26 and (B) MB11, arm-level copy number alterations listed were detected via tumor chromosomal microarray of the tumor tissue taken at the same time point as the CSF collection and listed in the cytogenetics report for that case. Arm-level copy number gains (red) and losses (blue) corresponding to the those detected in tissue are circled for each sample.