This clinical trial uses a type of imaging scan called magnetic resonance imaging (MRI) to study brain tumor biology in patients with glioblastoma that can be removed by surgery (resectable). Malignant gliomas are the second leading cause of cancer mortality in people under the age of 35 in the United States. Glioblastoma is a type of malignant glioma with very poor patient prognosis. There are currently only about 3 drugs approved by the Food and Drug Administration (FDA) for the treatment of glioblastoma, one of them being administration of bevacizumab, which is very expensive. It is the most widely used treatment for glioblastoma with dramatic results. However, previous clinical trials have not demonstrated an overall survival benefit across all patient populations with glioblastoma that has returned after treatment (recurrent). The study aims to identify which patients who will benefit from bevacizumab therapy by observing MRI images and corresponding imaging biomarkers.
Patients > 18 years of age
Patients with newly diagnosed, suspected or recurrent glioblastoma (GBM) patients with enhancing tumors greater than 1.5 mL clinically indicated for surgical resection. Recurrent GBM must have occurred more than 3 months after the end of radiation therapy per Response Assessment in Neuro-Oncology Criteria (RANO) guidelines
Counterindication to magnetic resonance imaging (MRI) (Patient has a pacemaker or metal in the body)
Patients < 18 years of age
Single group
Biospecimen Collection
Procedure/Surgerypatients will receive 1-3 image-guided biopsies within tumor tissue already designated for resection or removal.
Magnetic Resonance Imaging
Procedure/SurgeryUndergo MRI scan
Medical Chart Review
Other interventionReview Medical Chart
Decorin (DCN) expression
Will use a two-sided t-test to compare DCN immunohistochemistry (IHC), in-situ hybridization (ISH), and ribonucleic acid (RNA) sequencing positivity between low apparent diffusion coefficient (ADCL) \< 1.24 um\^2/ms and ADCL \> 1.24 um2/ms groups.
DCN expression correlated to ADCL
Will assess whether DCN IHC, ISH, and RNA expression within the tumor is linearly correlated with continuous values of ADCL. To test this, will examine Pearson's correlation coefficient (R\^2) and test whether the slope of the linear regression line is significantly different from zero. After purification, will also quantify the particular genotype or cell states represented by tumor cells for each ADCL phenotype.
Incidence of tumors with high diffusion measurements among MES-like cells
Will assess whether MES-like cells have higher frequency of incidence of ADCL \> 1.24 um\^2/ms compared to other genotypes. To test this, will use a chi-squared goodness of fit test to assess the frequency of observations and an analysis of variance (ANOVA) to look at DCN protein, deoxyribonucleic acid (DNA), and RNA expression between genotypes.
DCN expression among Mesenchymal-Like (MES-like) cells
Will assess whether MES-like cells have higher overall DCN expression levels compared to other genotypes. To test this, will use a chi-squared goodness of fit test to assess the frequency of observations and an ANOVA to look at DCN protein, DNA, and RNA expression between genotypes.
DCN protein concentration in blood plasma
Will compare DCN protein concentration in blood plasma and use a two-sided t-test to compare DCN concentration between ADCL \< 1.24 um\^2/ms and ADCL \> 1.24 um\^2/ms cohorts. We will also test whether blood plasma concentrations of DCN are linearly correlated with tumor IHC levels using Pearson's correlation coefficient (R\^2) and test whether the slope of the linear regression line is significantly different from zero.
Click on the lead sponsor to view all of their trials.
Jonsson Comprehensive Cancer Center
Lead sponsor
National Cancer Institute (NCI)
Collaborator
