Glioblastoma IDH (Isocitrate Dehydrogenase) Wildtype
Conditions
Keywords
Glioblastoma, IHD-wildtype, MRI, Biomarkers, Perfussion, Tumor heterogenity, Peritumoral edema, Tumor Infiltration, Machine learning, Medical device validation, Immunosuppression, Overall survival, MGMT status
Brief summary
The goal of this clinical trial is to validate ONCOhabitats, an advanced imaging software, as a medical device for the clinical management of IDH-wildtype glioblastoma. The study aims to evaluate whether imaging biomarkers derived from pre-surgical MRI using ONCOhabitats can predict overall survival and support clinical decision-making. The primary research questions are: * Can ONCOhabitats identify vascular and molecular characteristics within the peritumoral infiltrated edema (IPE) that are associated with patient prognosis? * Can these imaging biomarkers aid in stratifying patients according to their response to treatment, including temozolomide and immunotherapy? Participants will: * Be adults diagnosed with high-grade glioma who are scheduled for surgical tumor resection * Undergo preoperative MRI processed with ONCOhabitats to segment the tumor into four biological habitats (HAT, LAT, IPE, and VPE) * Provide tissue samples from each habitat when feasible, based on surgical and clinical considerations Researchers will analyze: * Imaging biomarkers (e.g., relative cerebral blood volume, rCBV) * Molecular and histopathological features (e.g., MGMT promoter methylation, gene expression profiles associated with immunosuppression) * Clinical and survival outcomes This study seeks to enhance glioblastoma characterization and support personalized treatment strategies through the clinical validation of a software platform.
Interventions
DEVICEThe ONCOhabitats software for MRI-based habitat segmentation
ONCOhabitats is an MRI-based software platform designed to segment IDH-wildtype glioblastomas into four biologically distinct habitats (HAT, LAT, IPE, and VPE) based on vascular heterogeneity. In this study, the software is applied preoperatively to generate imaging biomarkers that guide surgical sampling and are assessed for their ability to predict overall survival and stratify patients accordingly. The intervention includes advanced perfusion imaging processing using the HTS methodology, non-invasive tumor characterization, and integration with molecular and histopathological data.
Sponsors
Hospital Clínico Universitario de Valencia
Hospital Universitario de Canarias
Hospital General Universitario de Alicante
Hospital Universitario Virgen de la Arrixaca
Hospital Vall d'Hebron
Juan M Garcia-Gomez
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Adults (≥18 years old) at the time of diagnosis * Radiological diagnosis of high-grade glioma * Candidates for surgical resection * Availability of complete preoperative MRI studies, including: * T1-weighted MRI (pre- and post-gadolinium) * T2-weighted MRI * FLAIR (Fluid-Attenuated Inversion Recovery) * T2\*-weighted DSC perfusion MRI * Signed informed consent to participate in the clinical study
Exclusion criteria
* Patients who do not provide informed consent * Patients deemed inoperable Withdrawal criteria: * MRI data that cannot be processed using ONCOhabitats * Patient withdraws informed consent at any time
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Association of ONCOhabitats-Derived Vascular Biomarkers in the IPE Region With Overall Survival | Imaging biomarkers at surgery (baseline); overall survival followed for up to 24 months post-surgery | Imaging biomarkers-including relative cerebral blood volume (rCBV), volume (cm³), and radiomic vascular heterogeneity metrics-will be extracted from the peritumoral infiltrated edema (IPE) habitat using the ONCOhabitats platform on preoperative MRI. These biomarkers will be quantitatively assessed for their association with overall survival. Overall survival is defined as the time from surgical resection to death from any cause, with a follow-up of up to 24 months. Statistical analysis will include Kaplan-Meier survival estimation and Cox proportional hazards regression models. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Histopathological Features in Tumor (HAT, LAT) and Edema (IPE, VPE) Habitats Defined by ONCOhabitats in IDH-Wildtype Glioblastoma | Tissue samples collected at the time of surgical resection | Histopathological analysis will be conducted on tissue samples obtained from four MRI-derived habitats segmented using the ONCOhabitats software platform: * HAT (High Angiogenic Tumor) and LAT (Low Angiogenic Tumor), corresponding to tumor regions * IPE (Infiltrated Peritumoral Edema) and VPE (Vasogenic Peritumoral Edema), corresponding to peritumoral edema regions Tissue sections will be evaluated using hematoxylin and eosin (H&E) staining and immunohistochemistry to characterize features such as cellularity, necrosis, microvascular proliferation, immune cell infiltration, and other relevant histopathological traits. The aim is to describe and compare the biological composition of tumor versus edema habitats. |
| Levels of Immunosuppressive Gene Expression in MRI-Derived Habitats (IPE, HAT, VPE) | Tissue samples collected at the time of surgical resection | Tissue samples will be collected from three MRI-derived habitats defined by the ONCOhabitats platform in patients with IDH-wildtype glioblastoma: * IPE (Infiltrated Peritumoral Edema) * HAT (High Angiogenic Tumor) * VPE (Vasogenic Peritumoral Edema) Immunohistochemical and transcriptomic analyses will be performed to quantify the expression of immunosuppressive markers, including but not limited to PD-L1, CTLA-4, TGF-β, and IDO1. The level of immunosuppressive activity in each habitat will be characterized to explore spatial heterogeneity in the tumor microenvironment. |
| Association Between Perfusion Imaging Biomarkers and Molecular Markers in IDH-Wildtype Glioblastoma | MRI performed preoperatively; molecular analysis from tissue samples collected during surgery | Quantitative perfusion biomarkers-such as relative cerebral blood volume (rCBV), cerebral blood flow (CBF), and Ktrans-will be obtained from preoperative MRI processed with the ONCOhabitats platform. These imaging-derived parameters will be correlated with molecular markers obtained from tumor and edema tissue samples, including MGMT promoter methylation, IDH mutation status, and expression of immune-related genes (e.g., PD-L1, CTLA-4). The aim is to explore associations between vascular imaging features and the underlying molecular profile of IDH-wildtype glioblastoma. |
| Gene Expression Profiles in the IPE Region Associated With Poor Response to Immunotherapy in IDH-Wildtype Glioblastoma | Tissue samples collected at surgery; clinical follow-up for up to 24 months | Gene expression analysis will be performed on tissue samples obtained from the peritumoral infiltrated edema (IPE) region during surgical resection. RNA sequencing (RNA-seq) or targeted transcriptomic panels will be used to identify differential expression of immunosuppressive and immune-regulatory genes (e.g., PD-L1, CTLA-4, TGF-β, IDO1) in patients with IDH-wildtype glioblastoma. These molecular profiles will be correlated with clinical response to immunotherapy, as defined by progression-free survival (PFS) and overall survival (OS), |
| Stratification Biomarkers for Surgical Resection of the IPE Region or Local Immunotherapy in the Resection Cavity | Biomarker data collected at surgery; follow-up up to 24 months | Histopathological, molecular, and imaging biomarkers will be analyzed to identify features that allow for patient stratification regarding two therapeutic approaches: (1) surgical resection of the infiltrated peritumoral edema (IPE) region, and (2) administration of local therapies such as immunotherapy in the resection cavity. Biomarkers may include, among others, perfusion imaging parameters (e.g., rCBV), gene expression profiles related to immune activation or suppression, and histopathological indicators of tumor infiltration and immune cell presence. These variables will be evaluated for their potential to guide individualized treatment decisions in IDH-wildtype glioblastoma. |
| Patient Stratification Based on MGMT Promoter Methylation Status and rCBV for Response to Temozolomide in IDH-Wildtype Glioblastoma | MGMT and rCBV data collected at baseline (before treatment); follow-up up to 24 months | The association between MGMT promoter methylation status and relative cerebral blood volume (rCBV)-measured from preoperative dynamic susceptibility contrast (DSC) MRI using the ONCOhabitats platform-will be evaluated to stratify patients with IDH-wildtype glioblastoma according to their response to temozolomide (TMZ) treatment. Response will be assessed based on progression-free survival (PFS) and overall survival (OS) over a follow-up period of up to 24 months. The predictive value of the combined biomarkers will be analyzed using multivariate models and ROC curve analysis. |
| Correlation Between MGMT Methylation Status Assessed by Immunohistochemistry and MLPA and Response to Temozolomide in IDH-Wildtype Glioblastoma | MGMT methylation status assessed at baseline; clinical follow-up up to 24 months | MGMT promoter methylation status will be assessed in tumor tissue samples using two methods: immunohistochemistry (IHC) and multiplex ligation-dependent probe amplification (MLPA). The results of both techniques will be compared to evaluate their concordance and their respective predictive value for response to temozolomide (TMZ) in patients with IDH-wildtype glioblastoma. Response will be measured using progression-free survival (PFS) and overall survival (OS) over a 24-month follow-up period. |
| Predictive Value of Combined Imaging, Histopathological, Molecular, and Cellular Biomarkers in IDH-Wildtype Glioblastoma | Biomarker data collected at surgery; clinical follow-up up to 24 months post-surgery | Multimodal biomarkers-including perfusion imaging features (e.g., relative cerebral blood volume \[rCBV\], cerebral blood flow \[CBF\]), histopathological traits (e.g., vascular proliferation, immune infiltration), molecular alterations (e.g., MGMT promoter methylation, gene expression profiles), and cellular markers (e.g., CD3+, CD8+ lymphocyte density)-will be integrated using multivariate models and artificial intelligence (AI) techniques to predict clinical outcomes in patients with IDH-wildtype glioblastoma. These outcomes include diagnosis, prognosis (e.g., overall survival), and treatment response-based patient stratification. |
Countries
Spain
Contacts
Primary ContactJuan Miguel García Gómez, PhD, Full Professor
Outcome results
None listed