KOTK NEXT-GENERATION MULTIPLEX PATHOLOGY:
Next-generation multiplex pathology: enabling precision medicine by improving cancer diagnostics and biomarker identification |
Financing: Other Funding Agencies (OTHER)
Description: 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 enormousrevolution over the last decade, current standard pathological methods are significantly lagging behind to cope with theincreasing 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, 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 the tissue. SMC people involved in the project:
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