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Determination of genetic and therapeutic dependencies of patient-derived models of brain cancer

Precision cancer medicine is about matching the right treatment to the right patient. Advances have recently been made using population-based genomics to predict drug responses based on the presence of certain genetic alterations in the tumors of responders vs. non-responders. However, the limitations of these approaches are becoming increasingly evident, as every tumor displays a unique, complex genetic profile that makes accurate predictions of drug responses difficult. Matching cancer genotypes and drug response phenotypes therefore require the availability of libraries of relevant preclinical models that accurately recapitulate the biology and heterogeneity of human tumors. So far, cancer research models built on so-called conventional cell lines, but these turn out to poorly represent clinical biology. Libraries of patient-derived tumor cell lines (PDCLs) are therefore gaining traction as novel, more representative cancer models. Methods to create PDCLs of Glioblastoma (GBM), the most common and aggressive primary central nervous system malignancy with a median survival of 15 months in spite of maximal standard-of-care therapy, are becoming increasingly efficient. Even though the genetic aberrations have been studied extensively in GBM, treatment options remain limited and very inefficient. This project therefore aims at developing a “living tissue bank” of well-characterized, short-cultured patient-derived GBM cancer cell lines that maximally preserve phenotypic and genomic heterogeneity, and for which we will add functional analyses by: (i) identifying the patient-specific, genetic driver events using the CRISPR/Cas9 technology, (ii) measuring responses to existing and novel therapies, and (iii) pursuing a novel approach that directly evaluates the vulnerabilities of freshly isolated tumor cells to intervention by functional testing – a concept called “functional diagnostics” – using state-of-the art single cell mass cytometry. Samples will be collected at the University Hospitals Leuven (about 60/year) and will include primary and/or recurrent GBM tumor biopsies, and metastatic samples. All PDCLs will be stored in a repository, which will become available to researchers and contain matching patient and experimental data. The feasibility of this topical project will be ensured by the unique and close collaboration of both clinical (UZLeuven) and fundamental (KULeuven) research experts, with strong external partners (Dana-Farber Cancer Institute, Boston USA).
Date:1 Oct 2017 →  30 Sep 2021
Disciplines:Morphological sciences, Oncology