The study aims at:
1. Perform a multilayer analysis relying on tight integration of in-depth multi-omics approaches with clinical data to discover immune markers, with attention to age and sex differences, predicting prognosis and defining key life/environmental elements, to guide AI-driven personalised treatments and ensure improved care and QoL of glioblastoma patients. 2. To deepen glioblastoma knowledge through the study of glioblastoma stem cell cultures and to assess the sensitivity of glioblastoma stem cell cultures to a number of chemotherapeutics in different experimental conditions. 3. To create a comprehensive, stakeholder-generated guidelines for the ethical use of patient data for artificial intelligence-assisted prediction systems in glioblastoma, including an online, easily accessible patient information brochure to increase patient empowerment in the field.
Have a radiological diagnosis of supratentorial glioblastoma, or
Have a radiological diagnosis of first recurrence of a primary supratentorial glioblastoma (for which a formal histopathologic diagnosis of glioblastoma had made at first surgery), according with RANO criteria;
Be a candidate to neurosurgery for glioblastoma at the Operational Unit of Neurosurgery Fondazione Policlinico Gemelli IRCCS;
Be of an age of 18 years or above;
Have not enough pathological material removed at surgery available both for mandatory routine histopathological diagnosis and for the present study, as judged by the Principal Investigator;
Have not a definitive pathological diagnosis of a primary supratentorial glioblastoma, according with 2021 World Health Organization classification.
Single group
Biological biomarker analysis
Other interventionCollection of tumor and blood samples at T0 (surgery) and T1 (6 months follow-up) Tumor microenvironment and blood multi-omics analysis In-depth functional characterization of tumor microenvironment Cancer stem cells generation and drug testing Data integration by business intelligence and development of AI-based prognostic markers
Identification of immune signatures in glioblastoma predictive of overall survival
Immune omic markers, namely the tumor count of the different lymphocyte subtypes and of T-cell receptor subtypes, will be correlated with overall survival.
identification of lifestyle/environmental signatures predictive of overall survival
A questionnaire investigating lifestyle/environmental patients features, including dietary habits, will be developed. Questionnaire data will be correlated with overall survival.
Cancer stem cell-based chemosensitivity assay
Assessment of the in vitro sensitivity of patient-derived cancer stem cells to chemotherapeutics
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Fondazione Policlinico Universitario Agostino Gemelli IRCCS
Lead sponsor
Oslo University Hospital
Collaborator
Istituto Superiore di Sanità
Collaborator
Luxembourg Institute of Health
Collaborator
Hospital Donostia
Collaborator
University Medical Center Goettingen
Collaborator
National Research Council
Collaborator
