POLAR

Proteomics for Lymphoma Diagnostics and Prognosis

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

The platform project POLAR aims to systematically integrate proteome data into routine diagnostics and prognostic assessment of lymphoma. The platform is based on extensive clinical data, established analysis algorithms, and biobanks with more than 2,500 patient samples. In combination with ultrafast proteomics technology and innovative visualization and analysis methods, multidimensional (multi-omics) datasets will be analyzed and predictive models developed for lymphoma subtyping.

POLAR is being developed further for both research purposes and clinical applications in prognostic assessment and treatment optimization. In the future, the platform will be closely linked to the LOOP BMIP, creating 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 currently building the world’s largest systematic proteome 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 not only strengthens translational research in Switzerland but also promotes international collaboration. In the long term, the project will contribute to establishing a national lymphoma registry and further raise Switzerland’s profile as a center of 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.