Glioblastoma, Recurrent Glioblastoma, Resectable Glioblastoma
Conditions
Brief summary
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.
Detailed description
PRIMARY OBJECTIVES: I. Enhancing tumors with high diffusion measurements (low apparent diffusion coefficient \[ADCL\] \> 1.24 um\^2/ms) will have higher DCN protein expression compared with tumors exhibiting low diffusion measurements (ADCL \< 1.24 um\^2/ms.) (Aim 1A) II. Enhancing tumors with high diffusion measurements (low apparent diffusion coefficient \[ADCL\] \> 1.24 um\^2/ms) will have higher deoxyribonucleic acid (DNA) expression compared with tumors exhibiting low diffusion measurements (ADCL \< 1.24 um\^2/ms.) (Aim 1B) III. Enhancing tumors with high diffusion measurements (low apparent diffusion coefficient \[ADCL\] \> 1.24 um\^2/ms) will have higher ribonucleic acid (RNA) expression compared with tumors exhibiting low diffusion measurements (ADCL \< 1.24 um\^2/ms.) (Aim 1C) IV. Mesenchymal-Like (MES-like) cells will have higher frequency of incidence of tumors with high diffusion measurements (ADCL \> 1.24 um\^2/ms) and higher overall DCN expression levels compared to other genotypes. SECONDARY OBJECTIVE: I. DCN immunohistochemistry (IHC), in-situ hybridization (ISH), and RNA expression within the tumor will be linearly correlated with continuous values of diffusion measurements (ADCL). OUTLINE: Patients undergo one MRI scan over approximately 1 hour prior to surgery.
Interventions
PROCEDUREBiospecimen Collection
patients will receive 1-3 image-guided biopsies within tumor tissue already designated for resection or removal.
PROCEDUREMagnetic Resonance Imaging
Undergo MRI scan
OTHERMedical Chart Review
Review Medical Chart
Sponsors
National Cancer Institute (NCI)
Jonsson Comprehensive Cancer Center
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
SCREENING
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* 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
Exclusion criteria
* Counterindication to magnetic resonance imaging (MRI) (Patient has a pacemaker or metal in the body) * Patients \< 18 years of age
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Decorin (DCN) expression | Up to 5 years | 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 | Up to 5 years | 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 | Up to 5 years | 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 | Up to 5 years | 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. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| DCN protein concentration in blood plasma | Up to 5 years | 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. |
Countries
United States
Outcome results
None listed