GLIOMATCH: The malignant Glioma immuno-oncology matchmaker: towards data-driven precision medicine using spatially resolved radio-multiomics
Lead Participant:
UNIVERSITY OF EDINBURGH
Abstract
Adult and paediatric malignant glioma (GBM and pHGG) remain among the most difficult-to-treat cancers with 5-year survival rates
of <5% despite intensive standard-of-care therapy. The differences among patients and the heterogeneous and plastic nature of each
individual tumour have resulted in all therapeutic clinical trials failing during the past 20 years. Recently, immunotherapy has been
showing great promise, but only in subsets of patients. Identifying those patients cannot be done a priori as biomarkers are still largely
missing, nor are we able to follow-up on therapeutic efficacy when patients get treated. The GLIOMATCH project aims at improving
the clinical outcome of GBM/pHGG patients by enabling immunology-based patient stratification to empower personalised matching
of appropriate immunotherapy, while improving follow-up of clinical responses to existing/novel therapeutics. This will be achieved
by integrating spatially resolved, multi-layered tissue maps (using integrated single-cell multiomics), with non-invasive MRI images.
This integration will fuel into a novel MRI Radio-multiomics hub, that will be made available to clinical professionals through which
they can perform tumour-host based patient stratification and personalised therapy matching while interpreting longitudinal follow-up
and treatment efficacy. The proposed data-driven models will be developed by analysing the largest cohort of immuno-oncology (I/O)
treated GBM/pHGG patients (n>300, including pre-post treatment samples) with matched controls (n>300) and exceptionally long-term
surviving GBM patients (n~140), in which various tumour-host niches will be studied in how they respond to I/O perturbations and
lead to improved clinical outcome. This will be empowered by deploying an UNCAN-compatible data lake, to which incremental data
collection will be used to further refine the machine learning models, while proposing novel treatment options. This action is part of the
Cancer Mission cluster of projects on “Understanding (tumour-host interactions)".
of <5% despite intensive standard-of-care therapy. The differences among patients and the heterogeneous and plastic nature of each
individual tumour have resulted in all therapeutic clinical trials failing during the past 20 years. Recently, immunotherapy has been
showing great promise, but only in subsets of patients. Identifying those patients cannot be done a priori as biomarkers are still largely
missing, nor are we able to follow-up on therapeutic efficacy when patients get treated. The GLIOMATCH project aims at improving
the clinical outcome of GBM/pHGG patients by enabling immunology-based patient stratification to empower personalised matching
of appropriate immunotherapy, while improving follow-up of clinical responses to existing/novel therapeutics. This will be achieved
by integrating spatially resolved, multi-layered tissue maps (using integrated single-cell multiomics), with non-invasive MRI images.
This integration will fuel into a novel MRI Radio-multiomics hub, that will be made available to clinical professionals through which
they can perform tumour-host based patient stratification and personalised therapy matching while interpreting longitudinal follow-up
and treatment efficacy. The proposed data-driven models will be developed by analysing the largest cohort of immuno-oncology (I/O)
treated GBM/pHGG patients (n>300, including pre-post treatment samples) with matched controls (n>300) and exceptionally long-term
surviving GBM patients (n~140), in which various tumour-host niches will be studied in how they respond to I/O perturbations and
lead to improved clinical outcome. This will be empowered by deploying an UNCAN-compatible data lake, to which incremental data
collection will be used to further refine the machine learning models, while proposing novel treatment options. This action is part of the
Cancer Mission cluster of projects on “Understanding (tumour-host interactions)".
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
Participant |
||
| UNIVERSITY OF EDINBURGH |
People |
ORCID iD |
| Kathrin Cresswell (Project Manager) |