| 1. |
- Almstedt, Elin, 1988-, et al.
(författare)
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Integrative discovery of treatments for high-risk neuroblastoma
- 2020
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Despite advances in the molecular exploration of paediatric cancers, approximately 50% of children with high-risk neuroblastoma lack effective treatment. To identify therapeutic options for this group of high-risk patients, we combine predictive data mining with experimental evaluation in patient-derived xenograft cells. Our proposed algorithm, TargetTranslator, integrates data from tumour biobanks, pharmacological databases, and cellular networks to predict how targeted interventions affect mRNA signatures associated with high patient risk or disease processes. We find more than 80 targets to be associated with neuroblastoma risk and differentiation signatures. Selected targets are evaluated in cell lines derived from high-risk patients to demonstrate reversal of risk signatures and malignant phenotypes. Using neuroblastoma xenograft models, we establish CNR2 and MAPK8 as promising candidates for the treatment of high-risk neuroblastoma. We expect that our method, available as a public tool (targettranslator.org), will enhance and expedite the discovery of risk-associated targets for paediatric and adult cancers.
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| 2. |
- Weinstein, John N., et al.
(författare)
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The cancer genome atlas pan-cancer analysis project
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:10, s. 1113-1120
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Forskningsöversikt (refereegranskat)abstract
- The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile. © 2013 Nature America, Inc. All rights reserved.
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| 3. |
- Abenius, Tobias, 1979, et al.
(författare)
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System-scale network modeling of cancer using EPoC
- 2012
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Ingår i: Advances in Experimental Medicine and Biology. - New York, NY : Springer New York. - 0065-2598. - 9781441972095 ; 736:5, s. 617-643
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Tidskriftsartikel (refereegranskat)abstract
- One of the central problems of cancer systems biology is to understand the complex molecular changes of cancerous cells and tissues, and use this understanding to support the development of new targeted therapies. EPoC (Endogenous Perturbation analysis of Cancer) is a network modeling technique for tumor molecular profiles. EPoC models are constructed from combined copy number aberration (CNA) and mRNA data and aim to (1) identify genes whose copy number aberrations significantly affect target mRNA expression and (2) generate markers for long- and short-term survival of cancer patients. Models are constructed by a combination of regression and bootstrapping methods. Prognostic scores are obtained from a singular value decomposition of the networks. We have previously analyzed the performance of EPoC using glioblastoma data from The Cancer Genome Atlas (TCGA) consortium, and have shown that resulting network models contain both known and candidate disease-relevant genes as network hubs, as well as uncover predictors of patient survival. Here, we give a practical guide how to perform EPoC modeling in practice using R, and present a set of alternative modeling frameworks.
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| 4. |
- Allen, Marie, et al.
(författare)
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Origin of the U87MG glioma cell line : Good news and bad news
- 2016
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Ingår i: Science Translational Medicine. - : American Association for the Advancement of Science (AAAS). - 1946-6234 .- 1946-6242. ; 8:354
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Tidskriftsartikel (refereegranskat)abstract
- Human tumor-derived cell lines are indispensable tools for basic and translational oncology. They have an infinite life span and are easy to handle and scalable, and results can be obtained with high reproducibility. However, a tumor-derived cell line may not be authentic to the tumor of origin. Two major questions emerge: Have the identity of the donor and the actual tumor origin of the cell line been accurately determined? To what extent does the cell line reflect the phenotype of the tumor type of origin? The importance of these questions is greatest in translational research. We have examined these questions using genetic profiling and transcriptome analysis in human glioma cell lines. We find that the DNA profile of the widely used glioma cell line U87MG is different from that of the original cells and that it is likely to be a bona fide human glioblastoma cell line of unknown origin.
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| 5. |
- Almstedt, Elin, 1988-
(författare)
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New targeted therapies for malignant neural tumors : From systematic discovery to zebrafish models
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 6. |
- Almstedt, Elin, et al.
(författare)
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Real-time evaluation of glioblastoma growth in patient-specific zebrafish xenografts
- 2021
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Ingår i: Neuro-Oncology. - : Oxford University Press. - 1522-8517 .- 1523-5866. ; 24:5, s. 726-738
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Tidskriftsartikel (refereegranskat)abstract
- Background: Patient-derived xenograft (PDX) models of glioblastoma (GBM) are a central tool for neuro-oncology research and drug development, enabling the detection of patient-specific differences in growth, and in vivo drug response. However, existing PDX models are not well suited for large-scale or automated studies. Thus, here, we investigate if a fast zebrafish-based PDX model, supported by longitudinal, AI-driven image analysis, can recapitulate key aspects of glioblastoma growth and enable case-comparative drug testing.Methods: We engrafted 11 GFP-tagged patient-derived GBM IDH wild-type cell cultures (PDCs) into 1-day-old zebrafish embryos, and monitored fish with 96-well live microscopy and convolutional neural network analysis. Using light-sheet imaging of whole embryos, we analyzed further the invasive growth of tumor cells.Results: Our pipeline enables automatic and robust longitudinal observation of tumor growth and survival of individual fish. The 11 PDCs expressed growth, invasion and survival heterogeneity, and tumor initiation correlated strongly with matched mouse PDX counterparts (Spearman R = 0.89, p < 0.001). Three PDCs showed a high degree of association between grafted tumor cells and host blood vessels, suggesting a perivascular invasion phenotype. In vivo evaluation of the drug marizomib, currently in clinical trials for GBM, showed an effect on fish survival corresponding to PDC in vitro and in vivo marizomib sensitivity.Conclusions: Zebrafish xenografts of GBM, monitored by AI methods in an automated process, present a scalable alternative to mouse xenograft models for the study of glioblastoma tumor initiation, growth, and invasion, applicable to patient-specific drug evaluation.
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| 7. |
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| 8. |
- Barretina, Jordi, et al.
(författare)
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Subtype-specific genomic alterations define new targets for soft-tissue sarcoma therapy.
- 2010
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Ingår i: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 42:8, s. 715-21
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Tidskriftsartikel (refereegranskat)abstract
- Soft-tissue sarcomas, which result in approximately 10,700 diagnoses and 3,800 deaths per year in the United States, show remarkable histologic diversity, with more than 50 recognized subtypes. However, knowledge of their genomic alterations is limited. We describe an integrative analysis of DNA sequence, copy number and mRNA expression in 207 samples encompassing seven major subtypes. Frequently mutated genes included TP53 (17% of pleomorphic liposarcomas), NF1 (10.5% of myxofibrosarcomas and 8% of pleomorphic liposarcomas) and PIK3CA (18% of myxoid/round-cell liposarcomas, or MRCs). PIK3CA mutations in MRCs were associated with Akt activation and poor clinical outcomes. In myxofibrosarcomas and pleomorphic liposarcomas, we found both point mutations and genomic deletions affecting the tumor suppressor NF1. Finally, we found that short hairpin RNA (shRNA)-based knockdown of several genes amplified in dedifferentiated liposarcoma, including CDK4 and YEATS4, decreased cell proliferation. Our study yields a detailed map of molecular alterations across diverse sarcoma subtypes and suggests potential subtype-specific targets for therapy.
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| 9. |
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| 10. |
- Baskaran, Sathishkumar, 1988-
(författare)
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New Molecular Approaches to Glioblastoma Therapy
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Glioblastoma (GBM) is the most common high-grade brain tumor diagnosed in patients who are more than 50 years of age. The standard of care treatment is surgery, followed by radiotherapy and chemotherapy. The median life expectancy of patients is only between 12 to 15 months after receiving current treatment regimes. Hence, identification of new therapeutic compounds and gene targets are highly warranted. This thesis describes four interlinked studies to attain this goal. In study 1, we explored drug combination effects in a material of 41 patient-derived GBM cell (GC) cultures. Synergies between three compounds, pterostilbene, gefitinib, and sertraline, resulted in effective killing of GC and can be predicted by biomarkers. In study 2, we performed a large-scale screening of FDA approved compounds (n=1544) in a larger panel of GCs (n=106). By combining the large-scale drug response data with GCs genomics data, we built a novel computational model to predict the sensitivity of each compound for a given GC. A notable finding was that GCs respond very differently to proteasome inhibitors in both in-vitro and in-vivo. In study 3, we explored new gene targets by RNAi (n=1112) in a panel of GC cells. We found that loss of transcription factor ZBTB16/PLZF inhibits GC cell viability, proliferation, migration, and invasion. These effects were due to downregulation of c-MYC and Cyclin B1 after the treatment. In study 4, we tested the genomic stability of three GCs upon multiple passaging. Using molecular and mathematical analyses, we showed that the GCs undergo both systematic adaptations and sequential clonal takeovers. Such changes tend to affect a broad spectrum of pathways. Therefore, a systematic analysis of cell culture stability will be essential to make use of primary cells for translational oncology.Taken together, these studies deepen our knowledge of the weak points of GBM and provide several targets and biomarkers for further investigation. The work in this thesis can potentially facilitate the development of targeted therapies and result in more accurate tools for patient diagnostics and stratification.
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