Cell-Free DNA Methylation Patterns as a Biomarker for Tumor Biology and Clinical Outcomes for Glioblastoma Patients

ABSTRACT Glioblastoma is a uniformly lethal brain tumor despite aggressive and toxic standard of care treatments including surgery, radiation, and chemotherapy. One of the main barriers to understanding glioblastoma tumor biology and developing more effective therapies is the dependence on invasive surgical procedures for diagnosis. The need

to obtain tumor tissue for initial diagnosis in patients with glioblastoma is limited by 1) intratumoral heterogeneity (genomic and epigenomic), 2) temporal heterogeneity, 3) sampling error, and 4) surgical eligibility. Additionally, surveillance of glioblastoma remains a diagnostic challenge since recurrent disease is often indistinguishable

from treatment-induced inflammation, termed pseudoprogression, on conventional imaging, which contributes to diagnostic ambiguity and treatment delays. The identification of a non-invasive, prognostic biomarker for longitudinal molecular profiling of glioblastoma could overcome these challenges, improving risk stratification,

clinical trial design, surveillance, and standard of care. Our prior work revealed that changes in peripheral immune cell populations from whole-blood samples of patients with primary and recurrent glioblastoma correlate with treatment response and overall survival, thus supporting the concept of a local and systemic tumor

microenvironment. In non-CNS tumors, circulating tumor DNA (ctDNA) has received considerable attention to assess tumor burden, predict treatment response, and select therapies. However, classical ctDNA approaches using somatic mutation analysis are limited in glioblastoma due to the lack of recurrent somatic mutations,

significant intertumoral heterogeneity, and low detectability of somatic mutations in blood. We hypothesize that methylation profiling of cell-free DNA (cfDNA) can overcome these limitations, as epigenetic modifications are detectable in cfDNA, correspond to the cell of origin and cell state, are stable and detectable with a low input of

genomic DNA (