Frederik De Smet (KU Leuven)
Budget uitgereikt door Kom op tegen Kanker:
Providing the right therapy to each cancer patient heavily relies on an interdisciplinary interaction between surgeons, oncologists and pathologists. While not readily visible to patients, pathological assessments - commonly a combination of microscopic, immunohistochemical and genetic/molecular analyses of resected tissues and biopsies – remain essential to determine the correct diagnosis, a feature that largely defines the prognosis and success of the therapeutic plan. While next-generation sequencing procedures to identify genetic aberrations have witnessed an enormous revolution over the last decade, current standard pathological methods are significantly lagging behind to cope with the increasing numbers of putative biomarkers that could lead to more precise diagnostics and better therapy selections. Recently, this consortium has implemented a novel platform for multiplex immunohistochemistry (MILAN method) which allows for the analysis of multiple (50-100) proteins and biomarkers in single tissue sections at single cell level. In this project, we now want to analyse ~2500 previously and newly annotated tumor samples at single-cell and spatial resolution across 9 cancer types (i.e. melanoma, renal cancer, head & neck cancer, colorectal cancer, lung cancer, breast cancer, adult and paediatric glioma, liver cancer and lymphoma) from patients that were/are treated at UZLeuven, with the aim of identifying putative biomarkers for immunotherapy and improving cancer diagnostics. For each cancer type, we will optimize disease-tailored multiplex panels to detect known and novel markers (>50 proteins), allowing us to spatially resolve the cellular and genetic composition of a tumor and its microenvironment, data that will also be correlated to clinical features such as responsiveness to therapy. As such, we will generate one of the most detailed pathological cancer atlases accessible to clinicians and researchers. This multiplex approach was recently proven particularly important in the context of immunotherapy (e.g. checkpoint inhibitors) for which tumor tissue samples of patients responsive to immune-checkpoint inhibition contained a different spectrum of inflammatory cells within and around the tumor, features that could only be measured using multiplexed immunohistochemistry in the spatial context of a tissue. Since MILAN produces enormous amounts of data (“big data”), a close collaboration with STADIUS (Engineering dept., KULeuven) will ensure proper data analysis and management. In conclusion, by performing next-generation pathology using the MILAN platform, we will greatly enhance biological insights required for therapy selections, most specifically for patients receiving immunomodulatory therapies. This consortium harbours all required expertise to translate this technology and insights to a clinical setting, emphasizing that patients will get access to the most advanced cancer diagnostics as soon as possible.