Sanja Vickovic – Spatial mapping of cellular function in complex tissues

Cancer biology

One major focus of the group is cancer biology and the role of inflammation and immune cells in tumour development. Using high-definition spatial transcriptomics and spatial multi-omics, we profile gene and protein expression directly within patient tissues. These data are combined with deep learning and computer vision to build digital pathology platforms that map cell–cell interactions and predict responses to immunotherapy.

Our work aims to improve the understanding of tumour microenvironments and support more precise cancer treatment.

Neurodegenerative disease

In parallel, we study neurodegenerative disease, with a particular focus on amyotrophic lateral sclerosis (ALS). Using patient-derived stem cell models and multimodal single-cell profiling, we investigate how cellular stress disrupts motor neuron function. By integrating transcriptomic, morphological, and genetic data with computational models, we systematically identify and validate therapeutic targets.

Colorectal cancer – disease progression and therapy resistance

We also investigate cancer evolution and tumour plasticity in. By combining single-cell sequencing, spatial transcriptomics, functional genomics, and real-time RNA sensing, we track how cancer cells transition between different functional states. Large-scale CRISPR and drug screens, together with machine learning approaches, enable us to identify molecular drivers of progression and therapy resistance.

Improved diagnostics and treatments

Across all projects, we place strong emphasis on developing scalable experimental platforms and robust computational frameworks. Our goal is to generate predictive models of complex biological systems and to translate fundamental discoveries into improved diagnostics and treatments for patients.