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      <image:caption>Ijssennagger et al., J Hep Reports 2021</image:caption>
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      <image:caption>Artist: Matthijs J.D. Baars</image:caption>
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      <image:caption>To study how chronic inflammation contributes to cancer initiation, we are studying a unique cohort of patients with severe inflammatory bowel disease, who are at high risk of developing colorectal cancer. To identify the underlying mechanisms, we apply spatial omics, which allows us to identify relevant cell types and signaling pathways, that localize in and around early cancerous tissue, that are further investigated and targeted in model systems, such as in vitro organoid culture systems. Our long-term aim here is to identify risk factors for cancer development and progress, and eventually molecular targets for safe preventive treatment.</image:caption>
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      <image:title>Research - Immune therapy in cancer</image:title>
      <image:caption>Different cancer immune therapy strategies have demonstrated their potency in the clinic, and T cell activation plays a major role in response. We are investigating mechanisms of action of cancer immune therapies, response and toxicity, for checkpoint inhibition therapy, and a novel IgA-based therapy. We study these processes in patient tissue biopsies, and in in vitro culture assays to assess mechanisms of action.</image:caption>
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      <image:title>Research - Signal transduction errors</image:title>
      <image:caption>Patients with inborn errors of immunity have defects in their immune system, and suffer from recurrent infections. Counterintuitively, these patients can also suffer from severe autoimmunity with high morbidity. Treating autoimmunity is difficult in these patients, since immune suppression may increase risk of infection. Therefore, we aim to unravel the underlying mechanisms of the disease, by modeling signal transduction upon in vitro receptor stimulation in T cells, and visualizing the inflammatory processes in the tissue affected by autoimmunity.</image:caption>
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      <image:title>Research - Tissue heterogeneity: Segmentation and Spatial Analysis</image:title>
      <image:caption>Spatial tissue architectural information is generally ignored by downstream single-cell data analyses. We aim to develop spatial analysis tool for extracting quantitative and comprehensible information on the complex spatial relationships between different cell types and their microenvironments and their organizational features in complex tissues.</image:caption>
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