The current paradigm for glioblastoma (GBM) therapy is based on the concept that each patient is treated with a protocol that is most likely to prolong life (temozolomide and radiation) in a majority of patients. The treatment may not be efficacious for any given individual even though it may work with most patients with a similar pathology. If the treatment fails, second-line treatments, usually experimental are administered, although by this time it may be too late for many GBM patients. This concept is obviously unacceptable in the current era wherein the technology for whole genome sequencing is a reality thus enabling personalized medicine using targeted agents based on genetic alterations of each patient is possible. Unfortunately this concept is not financially practical. Project 1 of the P01 will investigate if stratification of patients based on our current understanding of dominant GBM subtypes will lead to significantly improved outcomes.
Specific Aim 1 will utilize a set of primary patient derived xenograft models each of which has been classified according to the molecular signatures of GBM using genetic profiling. The response of these human explants to the standard of care (SOC) therapy will be investigated to establish the relative sensitivities of each GBM subclass to SOC.
Aim 1 will also investigate the genetic basis for the three subclasses of response to SOC observed in our recent clinical trial using imaging as a biomarker.
Specific Aim 2 will extend these studies to targeted single agent therapeutic paradigms for each of the molecular subtypes using cell based assays and in vivo orthotopic primary mouse models. Since GBM is a heterogeneous disease targeted inhibition of a single agent may be compensated by activation of compensatory oncogenic pathways. Based on the above studies.
Specific Aim 3 will design and validate combination therapies for each of the molecular subtypes. Based on our existing expertise in mouse models of cancer and the application of molecular imaging combined with proteomics and genomics to rationally design therapeutic paradigms for distinct molecular subclasses of GBM, Project 1 will provide proof of principle results that will allow stratification of patients based on their molecular signature. This we believe will ultimately result in greatly improved outcomes for this disease. The ultimate goal of this project is to impact the patient outcomes through an optimized/rationale design of clinical trials in Project 3 wherein imaging biomarkers are paired with the most efficacious combination therapies for each of the GBM subtypes during clinical translation.

Public Health Relevance

Glioblastoma Multiforme, the most malignant and deadly type of brain tumors is no longer considered as a single tumor type but composed of several different subtypes or classifications. Optimal treatment for each molecular subtype is anticipated to be different. This research effort will identify and characterize the drug sensitivity profiles for each subtype using mono or combination therapies with the goal of improving patient outcomes.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA085878-11
Application #
8745100
Study Section
Special Emphasis Panel (ZCA1-RPRB-W)
Project Start
Project End
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
11
Fiscal Year
2014
Total Cost
$359,201
Indirect Cost
$88,260
Name
University of Michigan Ann Arbor
Department
Type
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Galbán, Stefanie; Apfelbaum, April A; Espinoza, Carlos et al. (2017) A Bifunctional MAPK/PI3K Antagonist for Inhibition of Tumor Growth and Metastasis. Mol Cancer Ther 16:2340-2350
Hu, Xin; Martinez-Ledesma, Emmanuel; Zheng, Siyuan et al. (2017) Multigene signature for predicting prognosis of patients with 1p19q co-deletion diffuse glioma. Neuro Oncol 19:786-795
Nyati, Shyam; Young, Grant; Ross, Brian Dale et al. (2017) Quantitative and Dynamic Imaging of ATM Kinase Activity. Methods Mol Biol 1596:131-145
Chen, Daiqin; Yang, Dongzhi; Dougherty, Casey A et al. (2017) In Vivo Targeting and Positron Emission Tomography Imaging of Tumor with Intrinsically Radioactive Metal-Organic Frameworks Nanomaterials. ACS Nano 11:4315-4327
Galbán, C J; Hoff, B A; Chenevert, T L et al. (2017) Diffusion MRI in early cancer therapeutic response assessment. NMR Biomed 30:
Martinez, Carlos H; Diaz, Alejandro A; Meldrum, Catherine et al. (2017) Age and Small Airway Imaging Abnormalities in Subjects with and without Airflow Obstruction in SPIROMICS. Am J Respir Crit Care Med 195:464-472
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
Yang, Dongzhi; Comeau, Anthony; Bowen, Wayne D et al. (2017) Design and Investigation of a [18F]-Labeled Benzamide Derivative as a High Affinity Dual Sigma Receptor Subtype Radioligand for Prostate Tumor Imaging. Mol Pharm 14:770-780
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
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

Showing the most recent 10 out of 163 publications