Facilitating cross-border, data-driven cancer research
Across a number of sectors, including healthcare, we are increasingly reliant on computational support to handle sharp increases in the volume and complexity of data. To ensure that Europe can fully benefit from such innovations though, this data needs to be harmonised, and researchers and clinical staff need ways of accessing and sharing information across borders. To achieve this, the EU-funded EOSC4Cancer project was launched. Running until March 2025, it brings together cancer research centres, research infrastructures, hospitals and supercomputing centres across 14 European countries.
From cancer prevention to diagnosis and treatment
The EOSC4Cancer project consortium is applying these principles to a number of use cases that cover the patient journey. A key element is ensuring that such data sets are harmonised, machine-actionable and amenable to artificial intelligence approaches. One use case focuses on cancer screening programmes, which are critical for improving survival rates through early detection. Screening programmes typically produce data sets that can be used for further data-driven research. The project team correlated a subset of data, extracted from screening programmes in three countries, to evaluate the risk/benefit of colorectal cancer screening and to help optimise screening strategies. A key aim is to achieve better data flow, and facilitate collaborative research by making this information accessible through federated data spaces. A second use case is looking at multiomics for the effective diagnosis and treatment of colorectal cancer. Data sets covering medical images, genomics and other factors have been collected, with a focus on ensuring that such data is harmonised. The project team plans to deliver standardised templates that researchers and clinical staff can use for sharing multiomic data such as this. Another use case is exploring how tumour molecular data can be optimised, in the context of precision cancer medicine. The aim is to build a clinical decision support system (CDSS) to help clinicians make biomarker-driven precision medicine interventions. The project team is currently investigating the data infrastructures and format specifications required for the CDSS to fulfil this task. This element of the project builds on the work being carried out by the Molecular Tumor Board Portal, which uses bioinformatic tools to identify treatment opportunities.
Effective evidence-based medical research
The data sets being collected from these and other specific use cases, as well as the project work being done to ensure that such data is accessible, sharable and reusable, will help lay the foundations for further collaborative cancer research. The complex nature of cancer means that broad cooperation is critical in order to bring effective new therapies to patients. The EOSC4Cancer project’s key contribution here is ensuring that diverse types of cancer data – genomics, imaging, medical, clinical, environmental and socio-economic – can be securely processed and reused across borders, using federated and interoperable systems. Investment in such research infrastructure will ultimately pay dividends, through fostering effective evidence-based medical research that leads to better health outcomes.
Keywords
EOSC4Cancer, cancer, diagnosis, genomics, medical, data, multiomics