Primary GBM, accounting for over 90% of human GBMs, develops rapidly or de novo with no prior clinical disease. Large-scale genomic analyses have contributed greatly to the definition of the overall glioma landscape and datasets (TCGA) have enabled the division of GBMs into subclasses based on their genomic, transcriptomic, and signal transduction patterns. Sadly, despite these insights into the genetics of the disease and advances in neurosurgery, radiation and chemotherapy, its dismal prognosis has not changed significantly. The current paradigm for glioblastoma (GBM) therapy is based on the concept that each patient is treated with the standard of care consisting of temozolomide and ionizing radiation (TMZ/IR) with no upfront knowledge if they will benefit from first-line therapy. Following completion of treatment, a month delay (or more) is needed to assess outcome. Patients found nonresponsive are assigned to a second-line treatment and so on. Care of GBM patients is sub-optimal in the current era wherein the technology for whole genome sequencing is a reality and thus enabling personalized medicine using targeted agents based on genetic alterations of each patient is possible. This Project will establish the accuracy of voxel-based quantitative MRI-derived metrics for detection of early treatment response and tumor recurrence during TMZ/IR treatment and during administration of molecularly targeted therapies.
Specific Aim 1 will conduct a multi-center validation of the parametric response map (PRM) as a voxel-based imaging biomarker of early response in standard of care treatment of newly diagnosed glioblastoma. Tumors harvested at the time of initial surgical excision will be genetically profiled by Project 1 for stratification with responsiveness.
Specific Aim 2 will evaluate PRM early response imaging metrics in Phase II (MCC-15412/ABTC-0703) and Phase 1 (RTOG-0825/ACR1N-6686) clinical trials of molecularly targeted agents in patients with newly diagnosed malignant glioma.
Specific Aim 3 will develop and evaluate a novel PRM approach for automated and objective detection and spatial depiction of early GBM progression prior to detection by currently available conventional MRI-based criteria. Overall, this Project is designed to advance the clinical application and utility of novel MRI-based biomarker metrics as quantitative and predictive surrogates of patient tumor status. These approaches will provide for significant improvements in how imaging can be integrated into clinical trials as well as in improving clinical management and care of GBM patients. Overall, this effort is anticipated to lead to improved outcome for this patient population.

Public Health Relevance

This research effort will yield new and validated imaging biomarkers which will be used for significantly improving the care of GBM patients. Imaging biomarkers and patient-derived primary xenografts developed as part of this effort will allow determination of an individual GBM subtype will respond (or fail) therapy much earlier than currently possible. These capabilities will provide the foundation for changing clinical care to an individualized approach which will yield improved outcomes and lower cost to the health care system.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA085878-14
Application #
9327973
Study Section
Special Emphasis Panel (ZCA1)
Project Start
2001-09-05
Project End
2019-06-30
Budget Start
2017-07-01
Budget End
2018-06-30
Support Year
14
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Type
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Smith, Andrew; Pawar, Mercy; Van Dort, Marcian E et al. (2018) Ocular Toxicity Profile of ST-162 and ST-168 as Novel Bifunctional MEK/PI3K Inhibitors. J Ocul Pharmacol Ther 34:477-485
Akgül, Seçkin; Li, Yinghua; Zheng, Siyuan et al. (2018) Opposing Tumor-Promoting and -Suppressive Functions of Rictor/mTORC2 Signaling in Adult Glioma and Pediatric SHH Medulloblastoma. Cell Rep 24:463-478.e5
Pal, Anupama; Rehemtulla, Alnawaz (2018) Imaging Proteolytic Activities in Mouse Models of Cancer. Methods Mol Biol 1731:247-260
Durmo, Faris; Lätt, Jimmy; Rydelius, Anna et al. (2018) Brain Tumor Characterization Using Multibiometric Evaluation of MRI. Tomography 4:14-25
Pompe, Esther; Galbán, Craig J; Ross, Brian D et al. (2017) Parametric response mapping on chest computed tomography associates with clinical and functional parameters in chronic obstructive pulmonary disease. Respir Med 123:48-55
Irtenkauf, Susan M; Sobiechowski, Susan; Hasselbach, Laura A et al. (2017) Optimization of Glioblastoma Mouse Orthotopic Xenograft Models for Translational Research. Comp Med 67:300-314
Belloli, Elizabeth A; Degtiar, Irina; Wang, Xin et al. (2017) Parametric Response Mapping as an Imaging Biomarker in Lung Transplant Recipients. Am J Respir Crit Care Med 195:942-952
Peng, Yayun; Yang, Dongzhi; Lu, Weifei et al. (2017) Positron emission tomography (PET) guided glioblastoma targeting by a fullerene-based nanoplatform with fast renal clearance. Acta Biomater 61:193-203
Van Dort, Marcian E; Galbán, Stefanie; Nino, Charles A et al. (2017) Structure-Guided Design and Initial Studies of a Bifunctional MEK/PI3K Inhibitor (ST-168). ACS Med Chem Lett 8:808-813
Galbán, Stefanie; Al-Holou, Wajd N; Wang, Hanxiao et al. (2017) MRI-Guided Stereotactic Biopsy of Murine GBM for Spatiotemporal Molecular Genomic Assessment. Tomography 3:9-15

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