The goal of this project is to develop tools for using 1H MR echo planar spectroscopic imaging (EPSI) and novel hyperpolarized 13C imaging to improve the management of in patients with glioma. We will tailor metabolic acquisitions for the specific molecular markers, such as 1p19q co-deletion, IDH mutation status and TERT promotor mutation (TERTp), which have been recently incorporated into the new WHO 2016 classification. In the previous cycle of this P01, we have identified several molecular markers to differentiate IDH mutation status and predict malignant progression based on ex vivo 1H HRMAS-NMR spectroscopy from image-guided tissue samples and in vivo 1H EPSI, and we have also developed, implemented and optimized acquisitions, post- processing and quantification of 1H EPSI and hyperpolarized [1-13C]pyruvate metabolic imaging for patients with glioma. In this proposed project, we will expand upon sequences used for 1H metabolic imaging and upon the agents used for hyperpolarized 13C imaging in order to determine which markers are the most relevant for evaluating patients from different molecular subgroups.
In Aim 1 we will develop an integrated protocol that combines 1H lactate edited EPSI and [1-13C]pyruvate for patients with IDH-negative TERTp+ glioblastoma, and investigate the impact of treatment with RT and temozolomide on multiple metabolites, as well as their association with outcome.
In Aim 2 we will evaluate metabolic changes during treatment with RT and temozolomide for patients with IDH+ astrocytoma in order to determine markers for early decision making by using 1H methods to detect 2-hydroxyglutarate (2HG) and hyperpolarized [2-13C]pyruvate metabolic imaging to detect differences in glutamate.
In Aim 3 we will explore whether estimates of 2HG from 1H spectra or estimates obtained using hyperpolarized [1-13C]?-ketoglutarate metabolic imaging are more sensitive for identifying regions of malignant progression in recurrent tumor for patients with IDH+, 1p/19q co-deleted and TERTp+ oligodendroglioma. The results of the project will identify metabolic parameters that are indicative of early treatment effectiveness for patients from different molecular sub-groups and will enable rapid selection of the most appropriate therapies.

Public Health Relevance

In this project we will implement 1H and novel hyperpolarized 13C MR metabolic imaging strategies to improve the evaluation for patients with specific molecular sub-types of glioma, which have recently been shown to have significantly different outcomes. This study will determine which metabolic signatures are the most relevant for use as surrogate markers of response to therapy and for predicting malignant progression.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
2P01CA118816-11A1
Application #
9790513
Study Section
Special Emphasis Panel (ZCA1)
Project Start
Project End
Budget Start
2019-08-01
Budget End
2020-07-31
Support Year
11
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Type
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94118
Mancini, Andrew; Xavier-Magalhães, Ana; Woods, Wendy S et al. (2018) Disruption of the ?1L Isoform of GABP Reverses Glioblastoma Replicative Immortality in a TERT Promoter Mutation-Dependent Manner. Cancer Cell 34:513-528.e8
Vareth, Maryam; Lupo, Janine; Larson, Peder et al. (2018) A comparison of coil combination strategies in 3D multi-channel MRSI reconstruction for patients with brain tumors. NMR Biomed 31:e3929
Li, Yan; Lafontaine, Marisa; Chang, Susan et al. (2018) Comparison between Short and Long Echo Time Magnetic Resonance Spectroscopic Imaging at 3T and 7T for Evaluating Brain Metabolites in Patients with Glioma. ACS Chem Neurosci 9:130-137
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Zhang, Chenan; de Smith, Adam J; Smirnov, Ivan V et al. (2017) Non-additive and epistatic effects of HLA polymorphisms contributing to risk of adult glioma. J Neurooncol 135:237-244
Autry, Adam; Phillips, Joanna J; Maleschlijski, Stojan et al. (2017) Characterization of Metabolic, Diffusion, and Perfusion Properties in GBM: Contrast-Enhancing versus Non-Enhancing Tumor. Transl Oncol 10:895-903
Anwar, Mekhail; Molinaro, Annette M; Morin, Olivier et al. (2017) Identifying Voxels at Risk for Progression in Glioblastoma Based on Dosimetry, Physiologic and Metabolic MRI. Radiat Res 188:303-313

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