Magnetic Resonance Fingerprinting of Glutamate Metabolism for Guiding Glioma Cancer Care - Project Summary Glioblastoma (GBM) is the most common type of malignant primary brain tumor found in adults and is fatal in all cases with a median survival time of only 14-16 months. Therapeutic targeting of classic cancer growth factor pathways in glioma has had limited success, suggesting that gliomas have unique growth mechanisms. Increasing evidence has implicated the neurotransmitter glutamate (Glu) as playing a critical role in driving glioma growth and invasion. GBM cells downregulate excitatory amino acid transporter-2 (EAAT2) and upregulate system Xc transporter (xCT) activity, increasing the extracellular Glu. Increased Glu causes excitotoxicity, healthy cell death, and autocrine Glu receptor stimulation to enhance GBM cell migration and growth. xCT exchange of Glu for cystine increases glutathione (GSH) synthesis to better resist oxidative stress and chemical insult. Novel therapeutics that target Glu metabolism have shown early promise. In particular, the drug riluzole disrupts GSH synthesis, promotes oxidative stress by inhibiting Glu export via xCT, and promotes astrocytic Glu uptake for reconversion to glutamine (Gln). Riluzole has been shown to be effective in treating in vitro GBM cell lines and preclinical GBM mouse models and the pro-drug troriluzole is under clinical investigation in GBM patients (ClinicalTrials.gov: NCT03970447 and NCT06552260). Similarly, IDH1-mutant glioma cells have been shown to have altered glutamate metabolism compared to wild type cells. Changes in Glu levels have been observed in clinical IDH1-mutant gliomas in response to IDH1-inhibitor therapies. The central role of Glu in these processes strongly suggests that noninvasive, high-resolution Glu imaging would help optimize drugs targeting this critical pathway and improve tumor treatment monitoring. Current methods for measuring glutamate either suffer from low sensitivity or low specificity. We propose to overcome this challenge by developing and optimizing a novel glutamate Chemical Exchange Spin Lock (GluCESL) magnetic resonance fingerprinting (MRF) method that enables accurate quantification of glutamate concentration with high specificity and sensitivity. We hypothesize that the GluCESL-MRF method will enable the acquisition of accurate, high-resolution glutamate concentration maps in acquisition times of less than 10 minutes. To test this hypothesis, we will first optimize the GluCESL-MRF acquisition schedule to maximize the accuracy of the glutamate maps using a deep learning approach for optimizing the glutamate fingerprinting acquisition schedule (Aim 1.2). Next, we will validate the GluCESL-MRF glutamate maps with low resolution glutamate maps obtained from magnetic resonance spectroscopy (Aim 1.3). The reproducibility of the glutamate maps will then be examined in test-retest studies performed at different time points and MRI scanners (Aim 1.4). Finally, the ability of GluCESL-MRF to monitor response to novel glioma therapies that target the glutamate metabolic pathway will be evaluated in two small pilot studies looking at response to troriluzole (Aim 2.1) or the IDH1-inhibitor vorasidenib (Aim 2.2).
