Eliminating Silent Risks
Pancreatic cancer
Early detection of pancreatic cancer through blood-based biomarkers and AI.
Challenging the Status Quo
The Challenge: Confronting a Silent Killer
This Use Case focuses on pancreatic cancer, one of the most aggressive and deadly cancers in Europe. In 2020, approximately 140,000 new cases were diagnosed across European countries, with age-standardized incidence rates reaching up to 11 per 100,000 in some countries. Mortality is high because the disease is often detected too late for effective treatment.
Aggressive Nature
Pancreatic cancer remains one of the most deadly cancers in Europe, requiring urgent shifts in detection speed.
Fragmented Care
Data is often scattered across hospitals and registries, which limits large-scale research and innovation.
Key challenges include the complex and heterogeneous nature of the disease and fragmented care pathways, which make early intervention difficult. Data on pancreatic cancer are often scattered across hospitals, biobanks, and registries, limiting opportunities for large-scale research and innovation.
Better availability and integration of clinical and molecular data is therefore critical. By connecting and harmonizing diverse datasets, the Use Case enables researchers to identify blood-based protein biomarkers that could indicate pancreatic cancer at an earlier, treatable stage. Integrated data also support the development of artificial intelligence models trained decentrally across multiple countries, improving the accuracy of risk predictions.
This approach contributes to earlier detection, more personalized care, and bridging gaps between research and clinical practice. By making high-quality data accessible and reusable across institutions, the Use Case ensures that future studies and innovations can benefit patients across Europe.
Precision Biomarker Discovery
The Use Case Objectives
This Use Case aims to detect pancreatic cancer earlier and more reliably, addressing one of the most challenging and deadly cancers in Europe. It serves as a practical application of the UNCAN-Connect platform, demonstrating how integrated, high-quality data can generate actionable insights for research and patient care.
- Develop a predictive model for individual disease risk based on blood protein analyses.
- Connect and harmonize diverse datasets for secure, ethical, and federated research.
- Analyze approximately 3,000 blood samples to identify sensitive disease-specific protein patterns.
- Validate models with 1,000 additional samples from five European clinical centers.
The main objective is to develop a predictive model for individual disease risk based on blood protein analyses. This model will help identify patients at higher risk earlier than current clinical methods allow. The Use Case contributes to UNCAN-Connect by demonstrating how diverse datasets can be connected and harmonized for secure, ethical, and federated research.
The data contributed are multimodal and highly valuable. They include clinical information (patient demographics, disease history, laboratory results) and blood-based protein data, obtained from high-throughput OlinkTM proteomics profiling, which allows sensitive and precise measurement of disease-specific protein patterns.
Initially, the team will analyze around 3,000 blood samples from patients and healthy controls in collaboration with a Danish partner. Later, the AI model will be validated using 1,000 additional patient samples from five European clinical centers, ensuring robust evaluation and cross-site applicability.
What makes these data particularly valuable is their quality, breadth, and interoperability. Retrospective and prospective samples are collected under strict ethical approvals and patient consent. Each record is linked to standardized clinical and molecular information, allowing robust biomarker validation. Data are federated across multiple hubs, ensuring secure, privacy-preserving access.
This Use Case not only addresses the urgent clinical challenge of pancreatic cancer but also demonstrates the utility of UNCAN-Connect as a European federated data platform, providing a model for future cancer research initiatives across Europe.
A Collaborative Framework for Europe
Expected Impact
This Use Case is expected to have a significant impact on cancer research and patient care by providing high-quality, integrated datasets that support early detection of pancreatic cancer. The data generated, combining clinical and blood-based protein information, contribute to improved data interoperability and reuse across European research centers. By standardizing and harmonizing these datasets, the Use Case helps ensure that insights can be shared securely and efficiently, enabling more robust and inclusive cancer research.
For researchers
For researchers, this Use Case provides access to well-characterized, multimodal datasets that allow the development and validation of predictive models, fostering innovation in biomarker discovery and artificial intelligence applications.
For healthcare professionals
For healthcare professionals and healthcare systems, the insights derived from these data may support earlier diagnosis, risk-adjusted monitoring, and more informed treatment decisions, ultimately improving patient outcomes.
For policymakers
Policymakers can benefit from the aggregated and anonymized evidence generated by the Use Case, informing strategies to improve cancer detection and management at a population level.
For patients & citizens
Patients and citizens benefit indirectly from the potential for earlier interventions and more personalized care, as well as from the enhanced efficiency and collaboration in European cancer research enabled by these data.
A SUSTAINABLE RESEARCH LEGACY
By demonstrating the value of federated, privacy-preserving data integration, this Use Case contributes to a sustainable European cancer data ecosystem. It illustrates how high-quality, standardized datasets can be leveraged across institutions while respecting privacy, ensuring long-term usability and scalability. Ultimately, the Use Case strengthens the UNCAN-Connect project’s capacity to generate actionable knowledge and supports a collaborative framework that can benefit future cancer research across Europe.