In short, Edwin Cuppen's research entails the following:
Cancer tissue of origin detection using genome-wide mutational characteristics
'About 3% of cancer patients are diagnosed annually with a Cancer of Unknown Primary (CUP) and there is also a significant fraction of patients with indeterminate, uncertain, or differential diagnoses, especially in metastatic or poorly differentiated tumors. Patients for which the primary tumor type is unknown have a worse prognosis, often due to complicated and laborious diagnostics and lack of therapeutic options as treatment options are almost exclusively driven by primary tumor type classification. Whole genome sequencing (WGS) is an emerging diagnostic approach and has already provided useful for the identification of matching personalized targeted treatments, but the obtained genome-wide knowledge also offers important potential for the identification of tumor tissue of origin. In the proposed project, we will use machine learning approaches to develop a WGS-based CUP classifier that can annotate cancers for which the primary tumor mass could not be identified. For this, we will consolidate, integrate and analyse the largest pan-cancer whole genome sequenced datasets worldwide, consisting of more than 8,000 patients. This project will be performed in a close collaboration between the research group of Edwin Cuppen at the UMC Utrecht, the pathology department of the Netherlands Cancer Institute and the Hartwig Medical Foundation and should drive implementation of the established algorithm in diagnostic patient reporting.'
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