POLAR

Proteomics for Lymphoma Diagnostics and Prognosis

Integrating molecular (proteomic) data into the LOOP BMIP to improve diagnostics and treatment prognosis in lymphoma

The POLAR platform project aims to systematically integrate proteomic data into routine diagnostics and prognostic assessment of lymphomas. The platform builds on extensive clinical data, established analysis algorithms, and biobanks containing more than 2,500 patient samples. Combined with ultrafast proteomics technology and innovative visualization and analysis methods, it will be used to analyze multidimensional (multi-omics) datasets and to develop predictive models for lymphoma subtyping.

POLAR is being further developed for both research and clinical applications in prognostic assessment and treatment optimization. Going forward, the platform will be closely linked to the LOOP BMIP, providing a data-driven basis for decision-making in personalized oncology.

Selected Research Results

In 2025, the POLAR project made decisive progress and established itself as one of the world’s leading platforms for proteomics research in lymphoma. With more than 1,000 samples analyzed to date, it is building the world’s largest systematic proteomic database for lymphoma—a unique resource for research and clinical application.

Significance for Medical Research

POLAR lays the foundation for a new generation of molecular diagnostics in lymphoma. The planned database and analysis platform will not only strengthen translational research in Switzerland but also foster international collaboration. In the long term, the project will contribute to establishing a national lymphoma registry and further strengthen Switzerland’s profile as a hub for innovation in oncological systems medicine.

Oncology

The Consortium

Thorsten Zenz, University Hospital Zurich, Department of Medical Oncology and Hematology.

Valentina Boeva, ETH Zurich, Department of Computer Science.

Marco M Bühler, University Hospital Zurich, Department of Pathology and Molecular Pathology.

Christoph Messner, University of Zurich, Precision Proteomics Center Davos, SIAF.