The molecular mechanisms that instigate a healthy cell to become malignant are fueled by (epi)genetic alterations in so-called driver genes. While the Holy Grail of precision medicine is to... Show moreThe molecular mechanisms that instigate a healthy cell to become malignant are fueled by (epi)genetic alterations in so-called driver genes. While the Holy Grail of precision medicine is to identify these genetic dependencies and to target them with specific compounds in a personalized fashion, this has proven a daunting task, as tumors are exquisitely characterized by genetic instability and a mutator phenotype. Genetically engineered mouse models (GEMMs) are uniquely suited for functional in vivo validation of genotype-phenotype relationships, as they enable in vivo assessment of de novo tumorigenesis in a mammalian organism with intact immune and stromal compartments upon perturbation of (combinations of) oncogenes and/or tumor suppressor genes. Somatic modeling of cancer using CRISPR technology in vivo proved to be a true game-changing tool, allowing for rapid functional validation of candidate cancer genes enrolling from forward genetic screens and catalogs of alterations in human tumors. In this work, I showed how CRISPR approaches were deployed to precisely engineer tumorigenic events in the mouse mammary gland for dissecting oncogenic cascades, unraveling new therapeutic vulnerabilities and mechanisms of therapy resistance in different breast cancer subtypes. Show less
To improve cancer treatments, personalized medicine approaches have aimed to identify exactly which mutations are driving tumor development in a given patient and specifically target these... Show moreTo improve cancer treatments, personalized medicine approaches have aimed to identify exactly which mutations are driving tumor development in a given patient and specifically target these mutations using precision therapies. However, one of the main challenges of this approach is identifying which mutations are true drivers, as tumors typically contain many additional passenger mutations that do not actually contribute to tumor development. Besides this, many patients often relapse after prolonged treatment due to the emergence of acquired resistance, limiting the clinical effectiveness of targeted treatments. In this thesis, we focussed on using genetically engineered mouse models to identify candidate cancer genes and therapy resistance mechanisms in two different breast cancers: invasive lobular carcinoma (ILC) and triple-negative breast cancer (TNBC). For ILC, we used transposon-based insertional mutagenesis (TIM) to uncover several novel cancer genes driving ILC development. Besides this, we also developed a novel computational approach (IM-Fusion) for improving the discovery of cancer genes from TIM screens and explored mechanisms of resistance in Fgfr2-driven ILC. For TNBC, we used CRISPR-based iterative mouse modeling combined with comparative oncogenomics to identify novel drivers of BRCA1-deficient TNBC. Finally, using combined in-vivo/in-vitro screens, we identified Parg as a driver of treatment resistance in BRCA2-deficient TNBC. Show less
