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Cancers in the neural system presents a major health challenge. The most aggressive brain tumor in adults, glioblastoma, has a median survival of 15 months and few therapeutic options. High-risk neuroblastoma, a childhood tumor originating in the sympathetic nervous system, has a 5-year survival under 50%, despite extensive therapy. Molecular characterization of these tumors has had some, but so far limited, clinical impact. In neuroblastoma, patients with ALK mutated tumors can benefit from treatment with ALK inhibitors. In glioblastoma, molecular subgroups have not yet revealed any subgroup-specific gene dependencies due to tumor heterogeneity and plasticity. In this thesis, we identify novel treatment candidates for neuroblastoma and glioblastoma. 

In paper I, we discover novel drug targets for high-risk neuroblastoma by integrating patient data, large-scale pharmacogenomic profiles, and drug-protein interaction maps. Using a novel algorithm, TargetTranslator, we identify more than 80 targets for this patient group. Activation of cannabinoid receptor 2 (CNR2) or inhibition of mitogen-activated protein kinase 8 (MAPK8) reduces tumor growth in zebrafish and mice models of neuroblastoma, establishing TargetTranslator as a useful tool for target discovery in cancer. 

In paper II, we screen approximately 1500 compounds across 100 molecularly characterized cell lines from patients to uncover heterogeneous responses to drugs in glioblastoma. We identify several connections between pathway activities and drug response. Sensitivity to proteasome inhibition is linked to oxidative stress response and p53 activity in cells, and can be predicted using a gene signature. We also discover sigma receptors as novel drug targets for glioblastoma and find a synergistic vulnerability in targeting cholesterol homeostasis.

In paper III, we systematically explore novel targets for glioblastoma using an siRNA screen. Downregulation of ZBTB16 decreases cell cycle-related proteins and transcripts in patient-derived glioblastoma cells. Using a zebrafish assay, we find that ZBTB16 promotes glioblastoma invasion in vivo. 

In paper IV, we characterized the growth of seven patient-derived glioblastoma cell lines in orthotopic zebrafish xenografts. Using automated longitudinal imaging, we find that tumor engraftment strongly correlates with tumor initiation capacity in mice xenografts and that the heterogeneous response to proteasome inhibitors is maintained in vivo. 

In summary, this thesis identifies novel targets for glioblastoma and neuroblastoma using systematic approaches. Treatment candidates are evaluated in novel zebrafish xenograft models that are developed for high-throughput glioblastoma and neuroblastoma drug evaluation. Together, this thesis provides promising evidence of new therapeutic options for malignant neural tumors.

Glioblastoma (GBM) is the most common and aggressive primary brain cancer. GBM cells migrate away from the primary lesion and invade healthy brain tissue. The invading cells escape surgical resection, radiotherapy and develop resistance to chemotherapy. Consequently, despite treatment, recurrence is inevitable, and survival is only 14 months. For this purpose, we conducted four studies where we integrated experimental data from extensive patient material with image analysis and mathematical modeling.

In study 1, we developed a tool, TargetTranslator, integrating different data modalities to identify new treatments. We implemented an image analysis pipeline to validate our results using a deep artificial neural network to quantify neuroblastoma cell differentiation.

In study 2, we integrated the zebrafish and image analysis from study 1 to develop a high-throughput in vivo assay. Zebrafish were orthotopically injected with GBM cells, and each fish's tumor growth and vital status were automatically measured. We characterized the in vivo proliferation rate, survival, and treatment response to the drug marizomib for several patient-derived cell cultures. Light-sheet imaging also revealed two distinct growth types. The first set of cell cultures grew as bulk tumors, whereas the second set invaded vasculature as single cells.

In study 3, we used the image analysis from study 1, coupled with an agent-based model to estimate in vitro cell migration and proliferation from single end-point images. The method was validated by a time series data set and applied to a large high-content drug screen of GBM cells. We identified three promising candidates for reducing GBM cell migration. The method can estimate migration on any end-point images of adherent cells without any additional experimental cost.

Study 4 characterized the growth and invasive patterns of 45 patient-derived GBM cell cultures in orthogonal mouse xenografts. We found that up to four independent axes of variation could describe the phenotypes and were associated with distinct transcriptomic pathways. The transcriptomic pathways were in part associated with common genomic alterations and subtypes in GBM. We further identified a particularly aggressive GBM phenotype.

In conclusion, this thesis was interdisciplinary and aimed to measure survival, invasion, and morphology from extensive patient material. The work had given us new insight into GBM invasion and growth and developed several scalable models suitable for evaluating new therapies.

The adult brain tumor glioblastoma is characterized by extensive heterogeneity and invasion, with intertumoral and intratumoral variation. This heterogeneity is partly driven by cellular plasticity, which permits glioblastoma cells to transition between cellular states. The plastic cells invade the brain, commonly via perivascular spaces, and diffuse invasion into the white matter, termed invasion routes. In this thesis, we investigate whether cellular states influence invasion routes using patient-derived models and develop new tools for real-time monitoring of glioblastoma across models. 

In Paper I, we connect cellular states to invasion routes by characterizing six patient-derived cell culture and xenograft models using single-cell RNA profiling and spatial proteomics. We connect bulk-forming capacity and perivascular invasion to MES-like and OPC-like cells, driven by ANXA1. NPC-like and AC-like cells, we link to diffuse invasion, driven by HOPX and RFX4. Perturbation of these genes shifts cellular state composition and invasion routes, suggesting that cellular state shapes invasion.

To directly monitor cellular states, paper II introduces the CRISPR-tag, which we use to fluorescently label genes representative of cellular states in patient-derived cells. In vitro, we observe differences and oscillations in protein levels. Ex vivo, we monitor CRISPR-tagged cells and detect spatially-dependent expression of cellular-state markers. During differentiation treatment, SOX2 expression remains high outside the tumor core, whereas it is lost in the central tumor regions. ANXA1-expressing cells display higher expression closer to a vessel. We performed a whole-genome knock-out screen to identify genetic dependencies that increase or decrease ANXA1 expression and identified several candidate genes that regulate ANXA1 expression.

Finally, in Paper III, we characterize eleven patient-derived cell cultures in a zebrafish model and monitor tumor initiation and growth using AI. The freely swimming fish are automatically imaged every four to six hours and display heterogeneity in growth and survival. Further characterization using light-sheet imaging revealed intratumoral variability in bulk-forming ability, tumor spread, and the presence of cells near vessels.

Together, our findings suggest an association between cellular states and invasion routes and introduce new tools to monitor cellular plasticity and tumor growth.