Integrated Analysis of Therapy Response and Resistence in Embryonal Tumors and Gliomas (BZKF-AYA)

Prospective Collection of Clinical and Imaging Data, Radiotherapy Planning and Biomaterials for Integrated Analysis of Therapy Response and Resistance and Detection of Molecular Targets in Adolescents and Young Adults With CNS Tumors

The treatment of adolescents and young adults (AYA, 15 to 39 years) with malignant intra-axial CNS parenchymal tumors such as IDH-mutated gliomas, medulloblastomas and ependymomas is still not curative in all cases. The tumor biology and clinical needs to diagnose and treat these tumors are comparable across all age groups, so an integrated treatment environment overseen by adult and pediatric neuro-oncology specialists seems promising to leverage synergisms and advance diagnostic and therapeutic development in these tumors. A comprehensive, prospective and integrated biomaterial and imaging-based pipeline for the multi-faceted evaluation of AYAs has not yet been established for AYA patients with brain tumors in Germany. Current diagnostic platforms neglect the integrative processing of data from MRI and FET-PET imaging, radiotherapy plans, tumor tissue, liquid biopsies and clinical data as well as prognostic markers. A prospective AYA pipeline can therefore enable a better understanding of the aforementioned high-risk CNS malignancies and promises clinical advances for AYA patients and the clinical and scientific research landscape.

Study Overview

• Status: Not yet recruiting
• Conditions: Ependymoma; Medulloblastoma; Glioma, Malignant; Embryonal Tumor
• Intervention / Treatment: Diagnostic test: Tissue, blood, cerebrospinal-spinal fluid

Detailed Description

Objectives: We are conducting a non-interventional study for AYAs with malignant intraaxial CNS parenchymal tumors. All 6 Bavarian BZKF sites are involved in the study. We will collect data on diagnostic and prognostic MRI and FET-PET imaging, quality assurance in radiotherapy and radiotherapy treatment patterns, diagnostic and predictive liquid biopsies from CSF and blood and targeted therapy approaches and integrate them bioinformatically with clinical data.

Work packages: WP01 Prediction of diagnosis by artificial intelligence (AI)-assisted processing of MRI and FET-PET; WP02 Analysis of response and relapse patterns by AI-assisted processing of MRI and FET-PET; WP03 Quality control of radiotherapy planning and patterns-of-care analysis; WP04 Prediction of response, relapse and treatment density using markers identified in liquid biopsies from CSF and blood; WP05 Identification of targets for targeted therapy from paraffin-embedded tissue (FFPE), CSF and blood; WP06 Investigation of clinical patterns and progression (PFS) or WP07 Bioinformatic integration of data to predict PFS, OS and patterns of response, relapse, treatment density and potential molecular targets.

Inclusion criteria: (1) first diagnosis of high-risk CNS tumors including IDHmutated gliomas, medulloblastomas, ependymomas, and other intra-axial primary brain tumors; (2) adolescents and young adults (AYA; 15 to 39 years); (3) Karnofsky status of 60 or higher; (4) multimodality therapy planned at the discretion of the medical professional; (5) expected survival min. 6 months; (6) informed consent by patient and (for patients under 18 years) legal representative; (7) complete material collection expected.

Exclusion criteria: (1) synchronous independent tumor disease, except basal cell carcinoma and carcinoma in situ; (2) participation in interventional clinical trial, except in standard arms of interventional clinical trials.

• Study Type: Observational
• Enrollment (Estimated): 72

Contacts and Locations

• Study Contact: Name: Peter Hau, Prof.; Phone Number: 18740 +49941944; Email: peter.hau@ukr.de

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult
• Accepts Healthy Volunteers: N/A

• Sampling Method: Probability Sample

Study Population

A total of 72 patients with complete data and biomaterial collection will be recruited into the study, including 36 patients with glioma IDHmutated and 36 patients with pediatric primary intra-axial brain tumors (medulloblastoma, ependymoma, ATRT, others).

Description

Inclusion Criteria:

1. first diagnosis of high-risk CNS tumors including glioma IDHmutated, medulloblastoma, ependymoma and other intra-axial primary brain tumors
2. adolescents and young adults (AYA; 15 to 39 years)
3. Karnofsky status of 60 or higher
4. resection, extended biopsy or stereotactic biopsy with sufficient tissue volume
5. multimodal therapy planned at the discretion of the treating specialist
6. expected survival time of at least 6 months
7. informed consent from the patient or the patient's legal guardian prior to the first study procedure
8. complete material collection expected.

Exclusion Criteria:

1. synchronous independent tumor disease other than basal cell carcinoma and carcinoma in situ
2. participation in interventional clinical trial except in standard arms of interventional clinical trials.

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Embryonal; Embryonal tumors, including medulloblastoma and ATRT	Diagnostic test: Tissue, blood, cerebrospinal-spinal fluid; Processing, analysis
Glioma, IDH-mutated; IDH-mutated gliomas, including WHO grades 2, 3 and 4	Diagnostic test: Tissue, blood, cerebrospinal-spinal fluid; Processing, analysis

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
AI processing of MRI fand PET or diagnosis	Prediction of diagnosis by artificial intelligence (AI)-assisted processing of magnetic resonance imaging (MRI) and Fluorethyltyrosin-Positron Emission Tomography (FET-PET)	March 2026
AI processing of MRI and PET for evaluation of response and relapse	Analysis of response and relapse patterns by artificial intelligence (AI)-assisted processing of magnetic resonance imaging (MRI) and Fluorethyltyrosin-Positron Emission Tomography (FET-PET)	March 2026
Quality control analysis in radiotherapy	Quality control of radiotherapy planning and patterns-of-care analysis	March 2026
Analysis of response in liquid biopsies	Prediction of response using markers detected in liquid biopsies from cerebrospinal fluid and blood	March 2026
Target molecules in tissue and liquid biopsies	Identification of target molecules for targeted therapy from paraffin-embedded tissue (FFPE), cerebrospinal fluid and blood	March 2026
Evaluation of progression free survival	Investigation of clinical patterns of response in view of progression free survival (PFS)	March 2026

Collaborators and Investigators

• Sponsor: University Hospital Regensburg
• Investigators: Principal Investigator: Peter Hau, Prof., University Hospital Regensburg

Study record dates

Study Major Dates

• Study Start (Estimated): June 1, 2024
• Primary Completion (Estimated): September 1, 2025
• Study Completion (Estimated): March 1, 2026

Study Registration Dates

• First Submitted: March 1, 2024
• First Submitted That Met QC Criteria: March 14, 2024
• First Posted (Actual): March 21, 2024

Study Record Updates

• Last Update Posted (Estimated): May 15, 2024
• Last Update Submitted That Met QC Criteria: May 13, 2024
• Last Verified: May 1, 2024

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Neoplasms by Histologic Type; Neoplasms; Neoplasms, Glandular and Epithelial; Neoplasms, Neuroepithelial; Neuroectodermal Tumors; Neoplasms, Germ Cell and Embryonal; Neoplasms, Nerve Tissue; Neuroectodermal Tumors, Primitive; Glioma; Ependymoma; Medulloblastoma
• Other Study ID Numbers: BZKF-AYA_1.0

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Internal analysis in BZKF network

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No