# Cell-Free DNA Methylation Patterns as a Biomarker for Tumor Biology and Clinical Outcomes for Glioblastoma Patients > **NIH NIH K38** · DUKE UNIVERSITY · 2024 · $100,586 ## Abstract 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 (<250 ng), and offer a greater breadth of information about the state of the cell of origin and differential responses of clonal lineages to treatment. To our knowledge, cfDNA methylation has not been evaluated in a prospective clinical trial as a biomarker for brain tumor biology or correlated with clinical outcomes. To test this hypothesis, we will employ prospective blood sample from patients with glioblastoma enrolled in the completed randomized Phase II VERTU trial (NCT02152982) to determine whether cfDNA methylation patterns cluster with specific tumor tissue DNA methylation patterns (Aim 1). We will then characterize the impact of changes in cfDNA methylation patterns on clinical outcomes, including survival (Aim 2). Finally, we will evaluate whether the activation state of circulating immune cell populations, inferred from cfDNA methylation patterns, can be used to non-invasively distinguish pseudoprogression from recurrent disease (Aim 3). These translational ai... ## Key facts - **NIH application ID:** 10950255 - **Project number:** 1K38CA292995-01 - **Recipient organization:** DUKE UNIVERSITY - **Principal Investigator:** Eugene Vaios - **Activity code:** K38 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $100,586 - **Award type:** 1 - **Project period:** 2024-08-01 → 2026-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10950255 ## Citation > US National Institutes of Health, RePORTER application 10950255, Cell-Free DNA Methylation Patterns as a Biomarker for Tumor Biology and Clinical Outcomes for Glioblastoma Patients (1K38CA292995-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10950255. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*