Sunday, November 24, 2024
11/24/2024
PROJECT SUMMARY/ABSTRACT Despite advances in surgical techniques and clinical regimens, malignant gliomas usually progress or recur after treatment. Currently, visual inspection of imaging data is the mainstay to monitor glioma progression; however, this approach may not be accurate or refined enough to monitor treatment response or evolving prognostic subtypes. Imaging data has limited ability to distinguish 1) gliomas from other tumors (e.g., primary central nervous system lymphoma), 2) progression from pseudoprogression (pseudoPD) resulting from therapy-induced necrosis, or 3) minimal or remnant tumoral burden. Recently, we and others found that potential drivers of glioma progression are mediated by gene mutation and epigenetic abnormalities. Generally, cancer molecular signatures are identifiable in tumoral tissue; however, several groups have reported that tumor specific signatures using both genetics and DNA methylation can be captured by non- or minimally-invasive approach such as liquid biopsy (LB) using biospecimens such as blood and cerebrospinal fluid. To address this knowledge gap in the role of LB to monitor glioma progression/recurrence, we aim to establish a novel approach to detect postoperative malignant glioma using DNA methylation of blood-derived cell-free DNA (cfDNA) markers with the ultimate goal to fine-tune surveillance and treatment in real time. With available DNA methylation data extracted from serum/plasma cfDNA at initial diagnosis, we will develop a non-invasive Glioma-score that is associated with prognostically relevant subtypes of glioma (e.g., G-CIMP-high vs -low), gliomas harboring unique and druggable genetic alterations (FGFR3-TACC3 [F3-T3]) and gliomas developing in patients with Neurofibromatosis type 1 (NF1-glioma) (Aim 1). From available cohorts spanning longitudinal specimens accrued for more than a decade, we will profile the epigenome of paired primary and recurrent sets (e.g., first, second /or third recurrence), and develop a Glioma recurrence (GliomaR)-score associated with recurrence, and response to therapy (Aim 2). Based on our defined scores, we will classify patients into defined prognostic groups (e.g., good and poor outcome) and risk to recur as a more aggressive subtype upon recurrence subgroups. This will assess the accuracy of LB to monitor postoperative progression of different molecular subtypes of glioma throughout an individual’s disease. We will utilize the quantitative and semi-quantitative imaging features routinely used in the diagnosis and monitoring of glioma to correlate the epigenomic markers of the LB Glioma-score with well established glioma imaging standards and tailor the LB score towards the resolution of the current limitations of imaging data for human glioma (e.g., pseudoPD and radiation necrosis) (Aim 3). Our study will be the first to investigate glioma whole-epigenome LB markers to detect aggressive gliomas at initial diagnosis and during tumor progression. Accurate diagnosis through a simple blood test will allow clinicians to detect the evolution of the disease in real-time, thus identifying high-risk patients who may benefit from more aggressive therapy at an earlier point when intervention could be more effective.
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