Improving personalised glioblastoma care by intertwined immunomics and artificial intelligence approaches

There is an urgent need for new treatment strategies to improve both the care and quality of life for patients with glioblastoma (GBM). The standard treatment has remained unchanged for over 15 years, and the median survival for GBM patients is less than 15 months. Approximately 25% of clinical trials in GBM are exploring immunotherapy, with several reporting improved survival in 10-20% of patients. Tumor mutational burden (TMB) and inflammation have been associated with immunotherapy response in GBM, but a clear clinical effect has so far been hindered by the lack of reliable biomarkers in this highly heterogeneous disease. Nearly all GBM tumors recur, and can only be combated through a treatment strategy that simultaneously considers both clinical and immunological factors. In addition, the IPerGlio project will investigate how these factors are influenced by gender and age. To achieve this, these variables must be integrated with lifestyle and environmental factors using artificial intelligence (AI). This represents an innovative approach that can lead to more precise and personalized treatment for GBM patients. In the IPerGlio project, clinical and immunological data from 260 GBM patients at hospitals in Oslo and Rome will be combined with lifestyle and environmental data. Using AI, the project will develop models to identify new biomarkers for prognosis and treatment, leading to better combination therapies with immunotherapy in future clinical trials. To strengthen the analyses, the project's data will be validated against publicly available datasets. Ethical challenges related to data security and sharing, which are critical in both personalized medicine and AI-based approaches, will be carefully addressed through close collaboration with stakeholders and patient involvement. Through this work, IPerGlio will contribute to improving clinical decision-making in GBM, identifying risk factors that can limit cancer progression, and ensuring that AI-guided, personalized immunotherapy is delivered in an effective and responsible manner.

New treatment strategies to improve patient care and quality of life (QoL) of glioblastoma (GBM) patients are urgently needed. Standard therapy has not changed for over 15 years, and GBM patients have a median survival of less than 15 months. Around 25% of clinical trials in GBM evaluate immunotherapies and several have reported long-term survival benefits in 10-20% of patients. Tumour mutational burden (TMB) and inflammation have been linked to immunotherapy responsiveness in GBM. A clear clinical benefit of immunotherapy has been hampered by the lack of biomarkers in this highly heterogeneous disease. All GBMs recur and recurrence can be limited only via a strategy considering clinical and immunological correlates evaluated in a sex- and age-specific perspective. These correlates must be integrated with key lifestyle/environmental (LE) factors using artificial intelligence (AI) technologies. This represents a novel and potent approach to guide personalised interventions improving GBM patient care and QoL. In IPerGlio, clinical and immune parameters (phenotypical, molecular, functional, and imaging data sets) from 260 GBM patients from three centres will be integrated with LE data by Business Intelligence (BI). By applying AI generated models to these data, IPerGlio will deliver GBM prognostic markers driving decisions for combination treatment with immunotherapy in clinical trials. To improve the learning process, project-derived data will be cross-checked with public datasets (e.g., IVY GBM Atlas Project, GBM Bio Discovery Portal). The ethical challenges regarding data security and sharing posed by personalised medicine and AI approaches will be inclusively addressed by IPerGlio through active stakeholder and patient involvement. Thus, the IPerGlio project will strongly improve GBM clinical decision-making by identifying risk factors amenable to reinforce tertiary prevention and ensuring effective and responsible delivery of AI-guided personalised immunotherapy.