Patients with non-enhancing malignant gliomas are typically young and may survive 2-10 years before succumbing to their disease. Co-deletion of chromosomes 1p and 19q (1p-19q-) is a marker of chemosensitivity in oligodendroglioma (OD) and mixed oligoastrocytoma (OA). P53 immunopositivity (p53+) is readily observed in Grade 4 astrocytomas that have progressed from lower grades. Amplification of the epidermal growth factor receptor (EGFR+) gene is a marker of poor prognosis irrespective of histologic subtype. Despite the existence of these prognostic molecular markers, clinical management of patients with these tumors remains difficult and the disease is ultimately fatal. Thus, understanding the mechanisms - downstream from molecular alterations - that govern the balance between proliferation and invasion in these tumors is of critical importance for effective longitudinal monitoring and therapeutic intervention.In this project, we will use MRS, high angular diffusion-weighted imaging (HARDI), and histology to investigate the hypotheses that: (1) tCre is positively associated with ADC in 1p19q co-deleted OD/OA, and that tumor cells co-exist with normal neurons (ie non-disruptive infiltration), (2) NAA is positively associated with directional diffusivity in p53+ AS, and histologic examination of tissue biopsies will reveal only a small proportion or no normal intact neurons within the tumor (ie disruptive infiltration), and (3) the combination of MRS and HARDI data, when considered in conjunction with the molecular subtype, can be used to predict the time course and/or peritumoral location of malignant progression. We will (1) compare the metabolic profile and infiltration pattern of non-enhancing oligodendroglial tumors with and without co-deletion of chromosomes 1p and 19q, (2) compare the metabolic profile and infiltration pattern of non-enhancing astrocytoma with differential expression of p53 and EGFR, and (3) Compare the metabolic and diffusion parameters of non-enhancing glioma with time to progression. Understanding the metabolism and infiltration pattern of molecular subtypes of glioma will help to identify synergistic targets for therapy and improve the interpretation of neuroimaging data from patients with these tumors.

Public Health Relevance

The overall survival for patients with glial brain tumors (gliomas) ranges from 1 to 8 years but ultimately all patients succumb to their disease. Indicators such as appearance on magnetic resonance images, pathologic classification, and molecular genetic markers expressed by the glioma provide some predictive estimates of survival times but the reasons why certain tumors grow more rapidly than others and spread into normal brain regions that govern basic function are still largely unknown. This study is an attempt to combine the existing information with new information regarding energy production and growth characteristics of glioma to better understand the mechanisms underlying glioma aggressiveness and identify new targets for therapeutic intervention.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Clinical Molecular Imaging and Probe Development (CMIP)
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Zhang, Huiming
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University of California San Francisco
Schools of Medicine
San Francisco
United States
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Luks, Tracy L; McKnight, Tracy Richmond; Jalbert, Llewellyn E et al. (2018) Relationship of In Vivo MR Parameters to Histopathological and Molecular Characteristics of Newly Diagnosed, Nonenhancing Lower-Grade Gliomas. Transl Oncol 11:941-949
Jalbert, Llewellyn E; Elkhaled, Adam; Phillips, Joanna J et al. (2017) Metabolic Profiling of IDH Mutation and Malignant Progression in Infiltrating Glioma. Sci Rep 7:44792
Hashizume, Rintaro; Smirnov, Ivan; Liu, Sharon et al. (2012) Characterization of a diffuse intrinsic pontine glioma cell line: implications for future investigations and treatment. J Neurooncol 110:305-13
McKnight, Tracy R; Smith, Kenneth J; Chu, Philip W et al. (2011) Choline metabolism, proliferation, and angiogenesis in nonenhancing grades 2 and 3 astrocytoma. J Magn Reson Imaging 33:808-16
Khayal, Inas S; Vandenberg, Scott R; Smith, Kenneth J et al. (2011) MRI apparent diffusion coefficient reflects histopathologic subtype, axonal disruption, and tumor fraction in diffuse-type grade II gliomas. Neuro Oncol 13:1192-201