Logo: to the web site of Uppsala University

uu.sePublications from Uppsala University
Change search
Refine search result
12 1 - 50 of 66
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Allen, Marie
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Bjerke, Mia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab. Karolinska Inst, Dept Lab Med, SE-14186 Stockholm, Sweden..
    Edlund, Hanna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Westermark, Bengt
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Origin of the U87MG glioma cell line: Good news and bad news2016In: Science Translational Medicine, ISSN 1946-6234, E-ISSN 1946-6242, Vol. 8, no 354, article id 354re3Article in journal (Refereed)
    Abstract [en]

    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.

  • 2.
    Almstedt, Elin
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Elgendy, Ramy
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Hekmati, Neda
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Rosén, Emil
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Wärn, Caroline
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Olsen, Thale Kristin
    Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden..
    Dyberg, Cecilia
    Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden..
    Doroszko, Milena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Larsson, Ida
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Sundström, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Arsenian Henriksson, Marie
    Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.
    Påhlman, Sven
    Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Lund, Sweden..
    Bexell, Daniel
    Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Lund, Sweden..
    Vanlandewijck, Michael
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology. Department of Medicine, Integrated Cardio-Metabolic Centre Single Cell Facility, Karolinska Institutet, Stockholm, Sweden..
    Kogner, Per
    Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden.
    Jörnsten, Rebecka
    Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden..
    Krona, Cecilia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Integrative discovery of treatments for high-risk neuroblastoma2020In: Nature Communications, E-ISSN 2041-1723, Vol. 11, no 1, article id 71Article in journal (Refereed)
    Abstract [en]

    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.

    Download full text (pdf)
    fulltext
  • 3.
    Almstedt, Elin
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Rosén, Emil
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Gloger, Marleen
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Rebecka, Stockard
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Hekmati, Neda
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Koltowska, Katarzyna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Krona, Cecilia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Real-time evaluation of glioblastoma growth in patient-specific zebrafish xenografts2021In: Neuro-Oncology, ISSN 1522-8517, E-ISSN 1523-5866, Vol. 24, no 5, p. 726-738Article in journal (Refereed)
    Abstract [en]

    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.

    Download full text (pdf)
    fulltext
  • 4.
    Baskaran, Sathishkumar
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Mayrhofer, Markus
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Göransson Kultima, Hanna
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
    Bergström, Tobias
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Elfineh, Lioudmila
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Cavelier, Lucia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    Isaksson, Anders
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Primary glioblastoma cells for precision medicine: a quantitative portrait of genomic (in)stability during the first 30 passages2018In: Neuro-Oncology, ISSN 1522-8517, E-ISSN 1523-5866, Vol. 20, no 8, p. 1080-1091Article in journal (Refereed)
    Abstract [en]

    Background: Primary glioblastoma cell (GC) cultures have emerged as a key model in brain tumor research, with the potential to uncover patient-specific differences in therapy response. However, there is limited quantitative information about the stability of such cells during the initial 20-30 passages of culture.

    Methods: We interrogated 3 patient-derived GC cultures at dense time intervals during the first 30 passages of culture. Combining state-of-the-art signal processing methods with a mathematical model of growth, we estimated clonal composition, rates of change, affected pathways, and correlations between altered gene dosage and transcription.

    Results: We demonstrate that GC cultures undergo sequential clonal takeovers, observed through variable proportions of specific subchromosomal lesions, variations in aneuploid cell content, and variations in subpopulation cell cycling times. The GC cultures also show significant transcriptional drift in several metabolic and signaling pathways, including ribosomal synthesis, telomere packaging and signaling via the mammalian target of rapamycin, Wnt, and interferon pathways, to a high degree explained by changes in gene dosage. In addition to these adaptations, the cultured GCs showed signs of shifting transcriptional subtype. Compared with chromosomal aberrations and gene expression, DNA methylations remained comparatively stable during passaging, and may be favorable as a biomarker.

    Conclusion: Taken together, GC cultures undergo significant genomic and transcriptional changes that need to be considered in functional experiments and biomarker studies that involve primary glioblastoma cells.

    Download full text (pdf)
    fulltext
  • 5.
    Boot, James
    et al.
    Queen Mary Univ, Blizard Inst, Barts & London Sch Med & Dent, London, England..
    Rosser, Gabriel
    Queen Mary Univ, Blizard Inst, Barts & London Sch Med & Dent, London, England..
    Kancheva, Dailya
    Vrije Univ Brussel, Lab Mol & Cellular Therapy, Brussels, Belgium..
    Vinel, Claire
    Queen Mary Univ, Blizard Inst, Barts & London Sch Med & Dent, London, England..
    Lim, Yau Mun
    Univ Coll London Hosp NHS Fdn Trust, Natl Hosp Neurol & Neurosurg, Div Neuropathol, London, England.;UCL, Inst Neurol, Dept Neurodegenerat Dis, Queen Sq, London, England..
    Pomella, Nicola
    Queen Mary Univ, Blizard Inst, Barts & London Sch Med & Dent, London, England..
    Zhang, Xinyu
    Queen Mary Univ, Blizard Inst, Barts & London Sch Med & Dent, London, England..
    Guglielmi, Loredana
    Queen Mary Univ, Blizard Inst, Barts & London Sch Med & Dent, London, England..
    Sheer, Denise
    Queen Mary Univ, Blizard Inst, Barts & London Sch Med & Dent, London, England..
    Barnes, Michael
    Queen Mary Univ London, William Harvey Res Inst, Ctr Translat Bioinformat, Barts & London Sch Med & Dent, London, England..
    Brandner, Sebastian
    Univ Coll London Hosp NHS Fdn Trust, Natl Hosp Neurol & Neurosurg, Div Neuropathol, London, England.;UCL, Inst Neurol, Dept Neurodegenerat Dis, Queen Sq, London, England..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neurooncology and neurodegeneration.
    Movahedi, Kiavash
    Vrije Univ Brussel, Lab Mol & Cellular Therapy, Brussels, Belgium..
    Marino, Silvia
    Queen Mary Univ, Blizard Inst, Barts & London Sch Med & Dent, London, England..
    Global hypo-methylation in a proportion of glioblastoma enriched for an astrocytic signature is associated with increased invasion and altered immune landscape2022In: eLIFE, E-ISSN 2050-084X, Vol. 11, article id e77335Article in journal (Refereed)
    Abstract [en]

    We describe a subset of glioblastoma, the most prevalent malignant adult brain tumour, harbouring a bias towards hypomethylation at defined differentially methylated regions. This epigenetic signature correlates with an enrichment for an astrocytic gene signature, which together with the identification of enriched predicted binding sites of transcription factors known to cause demethylation and to be involved in astrocytic/glial lineage specification, point to a shared ontogeny between these glioblastomas and astroglial progenitors. At functional level, increased invasiveness, at least in part mediated by SRPX2, and macrophage infiltration characterise this subset of glioblastoma.

    Download full text (pdf)
    FULLTEXT01
  • 6.
    Cancer, Matko
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Drews, Lisa F.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Bengtsson, Johan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Bolin, Sara
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Rosén, Gabriela
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Westermark, Bengt
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Nelander, Sven
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Forsberg Nilsson, Karin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Uhrbom, Lene
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Weishaupt, Holger
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Johansson, Fredrik K.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    BET and Aurora Kinase A inhibitors synergize against MYCN-positive human glioblastoma cells2019In: Cell Death and Disease, E-ISSN 2041-4889, Vol. 10, article id 881Article in journal (Refereed)
    Abstract [en]

    Glioblastoma multiforme (GBM) is the most common primary malignant brain tumor in adults. Patients usually undergo surgery followed by aggressive radio- and chemotherapy with the alkylating agent temozolomide (TMZ). Still, median survival is only 12-15 months after diagnosis. Many human cancers including GBMs demonstrate addiction to MYC transcription factor signaling and can become susceptible to inhibition of MYC downstream genes. JQ1 is an effective inhibitor of BET Bromodomains, a class of epigenetic readers regulating expression of downstream MYC targets. Here, we show that BET inhibition decreases viability of patient-derived GBM cell lines. We propose a distinct expression signature of MYCN-elevated GBM cells that correlates with significant sensitivity to BET inhibition. In tumors showing JQ1 sensitivity, we found enrichment of pathways regulating cell cycle, DNA damage response and repair. As DNA repair leads to acquired chemoresistance to TMZ, JQ1 treatment in combination with TMZ synergistically inhibited proliferation of MYCN-elevated cells. Bioinformatic analyses further showed that the expression of MYCN correlates with Aurora Kinase A levels and Aurora Kinase inhibitors indeed showed synergistic efficacy in combination with BET inhibition. Collectively, our data suggest that BET inhibitors could potentiate the efficacy of either TMZ or Aurora Kinase inhibitors in GBM treatment.

    Download full text (pdf)
    FULLTEXT01
  • 7.
    Castell, Alina
    et al.
    Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden..
    Yan, Qinzi
    Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden..
    Fawkner, Karin
    Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.
    Bazzar, Wesam
    Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden..
    Zhang, Fan
    Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden..
    Wickström, Malin
    Karolinska Inst, Dept Womens & Childrens Hlth, Stockholm, Sweden..
    Alzrigat, Mohammad
    Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden..
    Franco, Marcela
    Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden..
    Krona, Cecilia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neurooncology and neurodegeneration.
    Cameron, Donald P.
    Karolinska Inst, Dept Cell & Mol Biol, Stockholm, Sweden..
    Dyberg, Cecilia
    Karolinska Inst, Dept Womens & Childrens Hlth, Stockholm, Sweden..
    Olsen, Thale Kristin
    Karolinska Inst, Dept Womens & Childrens Hlth, Stockholm, Sweden..
    Verschut, Vasiliki
    Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden..
    Schmidt, Linnea
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Lim, Sheryl Y.
    Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden..
    Mahmoud, Loay
    Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden..
    Hydbring, Per
    Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden..
    Lehmann, Sören
    Karolinska Univ Hosp, Dept Med, Huddinge, Sweden..
    Baranello, Laura
    Karolinska Inst, Dept Cell & Mol Biol, Stockholm, Sweden..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neurooncology and neurodegeneration.
    Johnsen, John Inge
    Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden.
    Larsson, Lars-Gunnar
    Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden..
    MYCMI-7: A Small MYC-Binding Compound that Inhibits MYC: MAX Interaction and Tumor Growth in a MYC-Dependent Manner2022In: Cancer Research Communications, E-ISSN 2767-9764, Vol. 2, no 3, p. 182-201Article in journal (Refereed)
    Abstract [en]

    Deregulated expression of MYC family oncogenes occurs frequently in human cancer and is often associated with aggressive disease and poor prognosis. While MYC is a highly warranted target, it has been considered "undruggable," and no specific anti-MYC drugs are available in the clinic. We recently identified molecules named MYCMIs that inhibit the interaction between MYC and its essential partner MAX. Here we show that one of these molecules, MYCMI-7, efficiently and selectively inhibits MYC:MAX and MYCN:MAX interactions in cells, binds directly to recombinant MYC, and reduces MYC-driven transcription. In addition, MYCMI-7 induces degradation of MYC and MYCN proteins. MYCMI-7 potently induces growth arrest/apoptosis in tumor cells in a MYC/MYCN-dependent manner and downregulates the MYC pathway on a global level as determined by RNA sequencing. Sensitivity to MYCMI-7 correlates with MYC expression in a panel of 60 tumor cell lines and MYCMI-7 shows high efficacy toward a collection of patient-derived primary glioblastoma and acute myeloid leukemia (AML) ex vivo cultures. Importantly, a variety of normal cells be- come G1 arrested without signs of apoptosis upon MYCMI-7 treatment. Finally, in mouse tumor models of MYC-driven AML, breast cancer, and MYCN-amplified neuroblastoma, treatment with MYCMI-7 downregu- lates MYC/MYCN, inhibits tumor growth, and prolongs survival through apoptosis with few side effects. In conclusion, MYCMI-7 is a potent and selective MYC inhibitor that is highly relevant for the development into clinically useful drugs for the treatment of MYC-driven cancer.Significance: Our findings demonstrate that the small-molecule MYCMI-7 binds MYC and inhibits interaction between MYC and MAX, thereby ham- pering MYC-driven tumor cell growth in culture and in vivo while sparing normal cells.

    Download full text (pdf)
    fulltext
  • 8.
    Constantinou, Myrianni
    et al.
    Queen Mary Univ London, Blizard Inst, Brain Tumour Res Ctr, Barts & London Sch Med & Dent, London, England..
    Nicholson, James
    Queen Mary Univ London, Blizard Inst, Brain Tumour Res Ctr, Barts & London Sch Med & Dent, London, England..
    Zhang, Xinyu
    Queen Mary Univ London, Blizard Inst, Brain Tumour Res Ctr, Barts & London Sch Med & Dent, London, England..
    Maniati, Eleni
    Queen Mary Univ London, Barts & London Sch Med & Dent, Barts Canc Inst, London EC1M 6AS, England..
    Lucchini, Sara
    Queen Mary Univ London, Blizard Inst, Brain Tumour Res Ctr, Barts & London Sch Med & Dent, London, England..
    Rosser, Gabriel
    Queen Mary Univ London, Blizard Inst, Brain Tumour Res Ctr, Barts & London Sch Med & Dent, London, England..
    Vinel, Claire
    Queen Mary Univ London, Blizard Inst, Brain Tumour Res Ctr, Barts & London Sch Med & Dent, London, England..
    Wang, Jun
    Queen Mary Univ London, Barts & London Sch Med & Dent, Barts Canc Inst, London EC1M 6AS, England..
    Lim, Yau Mun
    UCL, Univ Coll London Hosp NHS Fdn Trust, Natl Hosp Neurol & Neurosurg, Div Neuropathol, Queen Sq, London, England.;UCL, Inst Neurol, Dept Neurodegenerat Dis, Queen Sq, London, England..
    Brandner, Sebastian
    UCL, Univ Coll London Hosp NHS Fdn Trust, Natl Hosp Neurol & Neurosurg, Div Neuropathol, Queen Sq, London, England.;UCL, Inst Neurol, Dept Neurodegenerat Dis, Queen Sq, London, England..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neurooncology and neurodegeneration.
    Badodi, Sara
    Queen Mary Univ London, Blizard Inst, Brain Tumour Res Ctr, Barts & London Sch Med & Dent, London, England..
    Marino, Silvia
    Queen Mary Univ London, Blizard Inst, Brain Tumour Res Ctr, Barts & London Sch Med & Dent, London, England..
    Lineage specification in glioblastoma is regulated by METTL7B2024In: Cell Reports, E-ISSN 2211-1247, Vol. 43, no 6, article id 114309Article in journal (Refereed)
    Abstract [en]

    Glioblastomas are the most common malignant brain tumors in adults; they are highly aggressive and heterogeneous and show a high degree of plasticity. Here, we show that methyltransferase-like 7B (METTL7B) is an essential regulator of lineage specification in glioblastoma, with an impact on both tumor size and invasiveness. Single-cell transcriptomic analysis of these tumors and of cerebral organoids derived from expanded potential stem cells overexpressing METTL7B reveal a regulatory role for the gene in the neural stem cell-to-astrocyte differentiation trajectory. Mechanistically, METTL7B downregulates the expression of key neuronal differentiation players, including SALL2, via post-translational modifications of histone marks.

    Download full text (pdf)
    fulltext
  • 9. Cvijovic, Marija
    et al.
    Almquist, Joachim
    Hagmar, Jonas
    Hohmann, Stefan
    Kaltenbach, Hans-Michael
    Klipp, Edda
    Krantz, Marcus
    Mendes, Pedro
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology.
    Nielsen, Jens
    Pagnani, Andrea
    Przulj, Natasa
    Raue, Andreas
    Stelling, Joerg
    Stoma, Szymon
    Tobin, Frank
    Wodke, Judith A. H.
    Zecchina, Riccardo
    Jirstrand, Mats
    Bridging the gaps in systems biology2014In: Molecular Genetics and Genomics, ISSN 1617-4615, E-ISSN 1617-4623, Vol. 289, no 5, p. 727-734Article, review/survey (Refereed)
    Abstract [en]

    Systems biology aims at creating mathematical models, i.e., computational reconstructions of biological systems and processes that will result in a new level of understanding-the elucidation of the basic and presumably conserved "design" and "engineering" principles of biomolecular systems. Thus, systems biology will move biology from a phenomenological to a predictive science. Mathematical modeling of biological networks and processes has already greatly improved our understanding of many cellular processes. However, given the massive amount of qualitative and quantitative data currently produced and number of burning questions in health care and biotechnology needed to be solved is still in its early phases. The field requires novel approaches for abstraction, for modeling bioprocesses that follow different biochemical and biophysical rules, and for combining different modules into larger models that still allow realistic simulation with the computational power available today. We have identified and discussed currently most prominent problems in systems biology: (1) how to bridge different scales of modeling abstraction, (2) how to bridge the gap between topological and mechanistic modeling, and (3) how to bridge the wet and dry laboratory gap. The future success of systems biology largely depends on bridging the recognized gaps.

  • 10.
    Dalmo, Erika
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Johansson, Patrik
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Niklasson, Mia
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Gustavsson, Ida
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Nelander, Sven
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Westermark, Bengt
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Growth-Inhibitory Activity of Bone Morphogenetic Protein 4 in Human Glioblastoma Cell Lines Is Heterogeneous and Dependent on Reduced SOX2 Expression2020In: Molecular Cancer Research, ISSN 1541-7786, E-ISSN 1557-3125, Vol. 18, no 7, p. 981-991Article in journal (Refereed)
    Abstract [en]

    Glioblastoma multiforme continues to have a dismal prognosis. Even though detailed information on the genetic aberrations in cell signaling and cell-cycle checkpoint control is available, no effective targeted treatment has been developed. Despite the advanced molecular defects, glioblastoma cells may have remnants of normal growth-inhibitory pathways, such as the bone morphogenetic protein (BMP) signaling pathway. We have evaluated the growth-inhibitory effect of BMP4 across a broad spectrum of patient samples, using a panel of 40 human glioblastoma initiating cell (GIC) cultures. A wide range of responsiveness was observed. BMP4 sensitivity was positively correlated with a proneural mRNA expression profile, high SOX2 activity, and BMP4-dependent upregulation of genes associated with inhibition of the MAPK pathway, as demonstrated by gene set enrichment analysis. BMP4 response in sensitive cells was mediated by the canonical BMP receptor pathway involving SMAD1/5/9 phosphorylation and SMAD4 expression. SOX2 was consistently downregulated in BMP4-treated cells. Forced expression of SOX2 attenuated the BMP4 sensitivity including a reduced upregulation of MAPK-inhibitory genes, implying a functional relationship between SOX2 downregulation and sensitivity. The results show an extensive heterogeneity in BMP4 responsiveness among GICs and identify a BMP4-sensitive subgroup, in which SOX2 is a mediator of the response.

  • 11.
    Dalmo, Erika
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Rosén, Gabriela
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Niklasson, Mia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Bergström, Tobias
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Miletic, Hrvoje
    University of Bergen, Department of Biomedicine; Haukeland University Hospital, Department of Pathology.
    Lindskog, Cecilia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Forsberg Nilsson, Karin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Uhrbom, Lene
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Swartling, Fredrik J.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Westermark, Bengt
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Targeting SOX2 in glioblastoma cells reveals heterogeneity in SOX2 dependencyManuscript (preprint) (Other academic)
    Abstract [en]

    Glioblastoma (GBM) is a lethal disease with no curative treatment. SOX2 is a stem cell transcription factor which is widely expressed across human GBM tumors. Downregulation of SOX2 inhibits tumor formation and its depletion leads to a complete stop of cell proliferation. Despite its known important role in GBM, there is a lack of SOX2 overexpression studies in human GBM cells cultured under stem cell conditions. Previous work in our lab suggests that SOX2 levels need to be precisely maintained for GBM cells to thrive. In this project, we have investigated how altered SOX2 expression affects primary human GBM lines. We found that elevated SOX2 expression inhibited proliferation in a dose-dependent manner in three out of four GBM cell lines. Global gene expression in the resistant line was shifted towards that of the proliferation-inhibited lines upon SOX2 induction. However, SOX2 induction also led to an increase in a GBM stem cell injury response phenotype, which was not present in proliferation-inhibited lines. Furthermore, CRISPR/Cas9-mediated SOX2 knockout revealed a SOX2 independence in the resistant cell line, where SOX2-negative cells could be propagated both in vitro and in vivo.

  • 12.
    Darmanis, Spyros
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Gallant, Caroline Julie
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Marinescu, Voichita Dana
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Niklasson, Mia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Segerman, Anna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Flamourakis, Georgios
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Fredriksson, Simon
    Olink Biosci, S-75237 Uppsala, Sweden..
    Assarsson, Erika
    Olink Biosci, S-75237 Uppsala, Sweden..
    Lundberg, Martin
    Olink Biosci, S-75237 Uppsala, Sweden..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Westermark, Bengt
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Landegren, Ulf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular tools.
    Simultaneous Multiplexed Measurement of RNA and Proteins in Single Cells2016In: Cell Reports, E-ISSN 2211-1247, Vol. 14, no 2, p. 380-389Article in journal (Refereed)
    Abstract [en]

    Significant advances have been made in methods to analyze genomes and transcriptomes of single cells, but to fully define cell states, proteins must also be accessed as central actors defining a cell's phenotype. Methods currently used to analyze endogenous protein expression in single cells are limited in specificity, throughput, or multiplex capability. Here, we present an approach to simultaneously and specifically interrogate large sets of protein and RNA targets in lysates from individual cells, enabling investigations of cell functions and responses. We applied our method to investigate the effects of BMP4, an experimental therapeutic agent, on early-passage glioblastoma cell cultures. We uncovered significant heterogeneity in responses to treatment at levels of RNA and protein, with a subset of cells reacting in a distinct manner to BMP4. Moreover, we found overall poor correlation between protein and RNA at the level of single cells, with proteins more accurately defining responses to treatment.

    Download full text (pdf)
    fulltext
  • 13.
    Dijksterhuis, Jacomijn P.
    et al.
    Karolinska Inst, Sect Receptor Biol & Signaling, Deptartment Physiol & Pharmacol, S-17177 Stockholm, Sweden..
    Arthofer, Elisa
    Karolinska Inst, Sect Receptor Biol & Signaling, Deptartment Physiol & Pharmacol, S-17177 Stockholm, Sweden..
    Marinescu, Voichita D.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Uhlen, Mathias
    KTH Royal Inst Technol, Sci Life Lab, SE-17121 Stockholm, Sweden..
    Ponten, Frederik
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Mulder, Jan
    Karolinska Inst, Dept Neurosci, Sci Life Lab, S-17177 Stockholm, Sweden..
    Schulte, Gunnar
    Karolinska Inst, Sect Receptor Biol & Signaling, Deptartment Physiol & Pharmacol, S-17177 Stockholm, Sweden.;Masaryk Univ, Fac Sci, Inst Expt Biol, CS-61137 Brno, Czech Republic..
    High levels of WNT-5A in human glioma correlate with increased presence of tumor-associated microglia/monocytes2015In: Experimental Cell Research, ISSN 0014-4827, E-ISSN 1090-2422, Vol. 339, no 2, p. 280-288Article in journal (Refereed)
    Abstract [en]

    Malignant gliomas are among the most severe types of cancer, and the most common primary brain tumors. Treatment options are limited and the prognosis is poor. WNT-5A, a member of the WNT family of lipoglycoproteins, plays a role in oncogenesis and tumor progression in various cancers, whereas the role of WNT-5A in glioma remains obscure. Based on the role of WNT-5A as an oncogene, its potential to regulate microglia cells and the glioma-promoting capacities of microglia cells, we hypothesize that WNT-5A has a role in regulation of immune functions in glioma. We investigated WNT-5A expression by in silico analysis of the cancer genome atlas (TCGA) transcript profiling of human glioblastoma samples and immunohistochemistry experiments of human glioma tissue microarrays (TMA). Our results reveal higher WNT-5A protein levels and mRNA expression in a subgroup of gliomas (WNT-5A(high)) compared to non-malignant control brain tissue. Furthermore, we show a significant correlation between WNT-5A in the tumor and presence of major histocompatibility complex Class II-positive microglia/monocytes. Our data pinpoint a positive correlation between WNT-5A and a proinflammatory signature in glioma. We identify increased presence of microglia/monocytes as an important aspect in the inflammatory transformation suggesting a novel role for WNT-5A in human glioma.

  • 14.
    Fedele, Vita
    et al.
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Dai, Fangping
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Masilamani, Anie P.
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Heiland, Dieter H.
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Kling, Eva
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Gätjens-Sanchez, Ana M.
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Ferrarese, Roberto
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Platania, Leonardo
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Soroush, Doostkam
    Univ Freiburg, Neuroctr, Inst Neuropathol, Freiburg, Germany.;Univ Freiburg, Ctr Comprehens Canc, Freiburg, Germany.;Univ Freiburg, BIOSS Ctr Biol Signalling Studies, Freiburg, Germany..
    Kim, Hyunsoo
    Jackson Lab Genom Med, Farmington, CT USA..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Weyerbrock, Astrid
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Prinz, Marco
    Univ Freiburg, Neuroctr, Inst Neuropathol, Freiburg, Germany.;Univ Freiburg, Ctr Comprehens Canc, Freiburg, Germany.;Univ Freiburg, BIOSS Ctr Biol Signalling Studies, Freiburg, Germany..
    Califano, Andrea
    Columbia Univ, Inst Canc Genet, New York, NY USA.;Columbia Univ, Dept Biomed Informat, New York, NY USA.;Columbia Univ, Dept Syst Biol, New York, NY USA..
    Iavarone, Antonio
    Columbia Univ, Inst Canc Genet, New York, NY USA.;Columbia Univ, Med Ctr, Dept Pathol, New York, NY USA.;Columbia Univ, Med Ctr, Dept Neurol, New York, NY USA..
    Bredel, Markus
    Univ Alabama Birmingham, Sch Med, Ctr Comprehens Canc, Dept Radiat Oncol, Birmingham, AL USA.;Stanford Univ, Sch Med, Stanford Canc Inst, Dept Neurosurg, Stanford, CA 94305 USA..
    Carro, Maria S.
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Epigenetic Regulation of ZBTB18 Promotes Glioblastoma Progression2017In: Molecular Cancer Research, ISSN 1541-7786, E-ISSN 1557-3125, Vol. 15, no 8, p. 998-1011Article in journal (Refereed)
    Abstract [en]

    Glioblastoma (GBM) comprises distinct subtypes characterized by their molecular profile. Mesenchymal identity in GBM has been associated with a comparatively unfavorable prognosis, primarily due to inherent resistance of these tumors to current therapies. The identification of molecular determinants of mesenchymal transformation could potentially allow for the discovery of new therapeutic targets. Zinc Finger and BTB Domain Containing 18 (ZBTB18/ZNF238/RP58) is a zinc finger transcriptional repressor with a crucial role in brain development and neuronal differentiation. Here, ZBTB18 is primarily silenced in the mesenchymal subtype of GBM through aberrant promoter methylation. Loss of ZBTB18 contributes to the aggressive phenotype of glioblastoma through regulation of poor prognosis-associated signatures. Restitution of ZBTB18 expression reverses the phenotype and impairs tumor-forming ability. These results indicate that ZBTB18 functions as a tumor suppressor in GBM through the regulation of genes associated with phenotypically aggressive properties.

  • 15.
    Gerlee, Philip
    et al.
    Chalmers Univ Technol, Math Sci, Gothenburg, Sweden.;Univ Gothenburg, Math Sci, Gothenburg, Sweden..
    Altrock, Philipp M.
    H Lee Moffitt Canc Ctr & Res Inst, Dept Integrated Math Oncol, Tampa, FL USA.;Max Planck Inst Evolutionary Biol, Dept Evolutionary Theory, Plon, Germany..
    Malik, Adam
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Krona, Cecilia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Autocrine signaling can explain the emergence of Allee effects in cancer cell populations2022In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 18, no 3, article id e1009844Article in journal (Refereed)
    Abstract [en]

    In many human cancers, the rate of cell growth depends crucially on the size of the tumour cell population. Low, zero, or negative growth at low population densities is known as the Allee effect; this effect has been studied extensively in ecology, but so far lacks a good explanation in the cancer setting. Here, we formulate and analyze an individual-based model of cancer, in which cell division rates are increased by the local concentration of an autocrine growth factor produced by the cancer cells themselves. We show, analytically and by simulation, that autocrine signaling suffices to cause both strong and weak Allee effects. Whether low cell densities lead to negative (strong effect) or reduced (weak effect) growth rate depends directly on the ratio of cell death to proliferation, and indirectly on cellular dispersal. Our model is consistent with experimental observations from three patient-derived brain tumor cell lines grown at different densities. We propose that further studying and quantifying population-wide feedback, impacting cell growth, will be central for advancing our understanding of cancer dynamics and treatment, potentially exploiting Allee effects for therapy.

    Download full text (pdf)
    FULLTEXT01
  • 16.
    Gerlee, Philip
    et al.
    Chalmers, Math Sci, S-41296 Gothenburg, Sweden.;Univ Gothenburg, S-41296 Gothenburg, Sweden..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Travelling wave analysis of a mathematical model of glioblastoma growth2016In: Mathematical Biosciences, ISSN 0025-5564, E-ISSN 1879-3134, Vol. 276, p. 75-81Article in journal (Refereed)
    Abstract [en]

    In this paper we analyse a previously proposed cell-based model of glioblastoma (brain tumour) growth, which is based on the assumption that the cancer cells switch phenotypes between a proliferative and motile state (Gerlee and Nelander, 2012). The dynamics of this model can be described by a system of partial differential equations, which exhibits travelling wave solutions whose wave speed depends crucially on the rates of phenotypic switching. We show that under certain conditions on the model parameters, a closed form expression of the wave speed can be obtained, and using singular perturbation methods we also derive an approximate expression of the wave front shape. These new analytical results agree with simulations of the cell-based model, and importantly show that the inverse relationship between wave front steepness and speed observed for the Fisher equation no longer holds when phenotypic switching is considered.

  • 17. Gerlee, Philip
    et al.
    Schmidt, Linnea
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Monsefi, Naser
    Kling, Teresia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Jornsten, Rebecka
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Searching for Synergies: Matrix Algebraic Approaches for Efficient Pair Screening2013In: PLOS ONE, E-ISSN 1932-6203, Vol. 8, no 7, p. e68598-Article in journal (Refereed)
    Abstract [en]

    Functionally interacting perturbations, such as synergistic drugs pairs or synthetic lethal gene pairs, are of key interest in both pharmacology and functional genomics. However, to find such pairs by traditional screening methods is both time consuming and costly. We present a novel computational-experimental framework for efficient identification of synergistic target pairs, applicable for screening of systems with sizes on the order of current drug, small RNA or SGA (Synthetic Genetic Array) libraries (>1000 targets). This framework exploits the fact that the response of a drug pair in a given system, or a pair of genes' propensity to interact functionally, can be partly predicted by computational means from (i) a small set of experimentally determined target pairs, and (ii) pre-existing data (e.g. gene ontology, PPI) on the similarities between targets. Predictions are obtained by a novel matrix algebraic technique, based on cyclical projections onto convex sets. We demonstrate the efficiency of the proposed method using drug-drug interaction data from seven cancer cell lines and gene-gene interaction data from yeast SGA screens. Our protocol increases the rate of synergism discovery significantly over traditional screening, by up to 7-fold. Our method is easy to implement and could be applied to accelerate pair screening for both animal and microbial systems.

    Download full text (pdf)
    fulltext
  • 18.
    Heiland, Dieter H.
    et al.
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Ferrarese, Roberto
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Claus, Rainer
    Univ Freiburg, Med Ctr, Dept Hematol Oncol & Stem Cell Transplantat, Freiburg, Germany..
    Dai, Fangping
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Masilamani, Anie P.
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Kling, Eva
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Weyerbrock, Astrid
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    Kling, Teresia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Carro, Maria S.
    Univ Freiburg, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Med, Freiburg, Germany..
    c-Jun-N-terminal phosphorylation regulates DNMT1 expression and genome wide methylation in gliomas2017In: Oncotarget, E-ISSN 1949-2553, Vol. 8, no 4, p. 6940-6954Article in journal (Refereed)
    Abstract [en]

    High-grade gliomas (HGG) are the most common brain tumors, with an average survival time of 14 months. A glioma-CpG island methylator phenotype (G-CIMP), associated with better clinical outcome, has been described in low and high-grade gliomas. Mutation of IDH1 is known to drive the G-CIMP status. In some cases, however, the hypermethylation phenotype is independent of IDH1 mutation, suggesting the involvement of other mechanisms. Here, we demonstrate that DNMT1 expression is higher in low-grade gliomas compared to glioblastomas and correlates with phosphorylated c-Jun. We show that phospho-c-Jun binds to the DNMT1 promoter and causes DNA hypermethylation. Phospho-c-Jun activation by Anisomycin treatment in primary glioblastoma-derived cells attenuates the aggressive features of mesenchymal glioblastomas and leads to promoter methylation and downregulation of key mesenchymal genes (CD44, MMP9 and CHI3L1). Our findings suggest that phospho-c-Jun activates an important regulatory mechanism to control DNMT1 expression and regulate global DNA methylation in Glioblastoma.

  • 19.
    Hillerton, Thomas
    et al.
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, S-17121 Solna, Sweden.
    Secilmi, Deniz
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, S-17121 Solna, Sweden.
    Nelander, Sven
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Sonnhammer, Erik L. L.
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, S-17121 Solna, Sweden.
    Valencia, Alfonso
    Associate Editor.
    Fast and accurate gene regulatory network inference by normalized least squares regression2022In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 38, no 8, p. 2263-2268, article id btac103Article in journal (Refereed)
    Abstract [en]

    Motivation: Inferring an accurate gene regulatory network (GRN) has long been a key goal in the field of systems biology. To do this, it is important to find a suitable balance between the maximum number of true positive and the minimum number of false-positive interactions. Another key feature is that the inference method can handle the large size of modern experimental data, meaning the method needs to be both fast and accurate. The Least Squares Cut-Off (LSCO) method can fulfill both these criteria, however as it is based on least squares it is vulnerable to known issues of amplifying extreme values, small or large. In GRN this manifests itself with genes that are erroneously hyper-connected to a large fraction of all genes due to extremely low value fold changes.

    Results: We developed a GRN inference method called Least Squares Cut-Off with Normalization (LSCON) that tackles this problem. LSCON extends the LSCO algorithm by regularization to avoid hyper-connected genes and thereby reduce false positives. The regularization used is based on normalization, which removes effects of extreme values on the fit. We benchmarked LSCON and compared it to Genie3, LASSO, LSCO and Ridge regression, in terms of accuracy, speed and tendency to predict hyper-connected genes. The results show that LSCON achieves better or equal accuracy compared to LASSO, the best existing method, especially for data with extreme values. Thanks to the speed of least squares regression, LSCON does this an order of magnitude faster than LASSO.

    Download full text (pdf)
    fulltext
  • 20.
    Ilkhanizadeh, Shirin
    et al.
    Karolinska Inst, Dept Neurosci, S-17177 Stockholm, Sweden..
    Gracias, Aileen
    Karolinska Inst, Dept Neurosci, S-17177 Stockholm, Sweden..
    Aslund, Andreas K. O.
    Linköping Univ, Dept Chem, IFM, S-58183 Linköping, Sweden..
    Back, Marcus
    Linköping Univ, Dept Chem, IFM, S-58183 Linköping, Sweden..
    Simon, Rozalyn
    Linköping Univ, Dept Chem, IFM, S-58183 Linköping, Sweden..
    Kavanagh, Edel
    Karolinska Inst, Inst Environm Med, S-17177 Stockholm, Sweden..
    Migliori, Bianca
    Karolinska Inst, Dept Neurosci, S-17177 Stockholm, Sweden..
    Neofytou, Christina
    Karolinska Inst, Dept Neurosci, S-17177 Stockholm, Sweden..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neurooncology and neurodegeneration. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Westermark, Bengt
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neurooncology and neurodegeneration.
    Uhrbom, Lene
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neurooncology and neurodegeneration.
    Forsberg Nilsson, Karin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neurooncology and neurodegeneration.
    Konradsson, Peter
    Linköping Univ, Dept Chem, IFM, S-58183 Linköping, Sweden..
    Teixeira, Ana I.
    Karolinska Inst, Dept Med Biochem & Biophys, S-17177 Stockholm, Sweden..
    Uhlen, Per
    Karolinska Inst, Dept Med Biochem & Biophys, S-17177 Stockholm, Sweden..
    Joseph, Bertrand
    Karolinska Inst, Inst Environm Med, S-17177 Stockholm, Sweden..
    Hermanson, Ola
    Karolinska Inst, Dept Neurosci, S-17177 Stockholm, Sweden..
    Nilsson, K. Peter R.
    Linköping Univ, Dept Chem, IFM, S-58183 Linköping, Sweden..
    Live Detection of Neural Progenitors and Glioblastoma Cells by an Oligothiophene Derivative2023In: ACS Applied Bio Materials, E-ISSN 2576-6422, Vol. 6, no 9, p. 3790-3797Article in journal (Refereed)
    Abstract [en]

    There is an urgent need for simple and non-invasive identification of live neural stem/progenitor cells (NSPCs) in the developing and adult brain as well as in disease, such as in brain tumors, due to the potential clinical importance in prognosis, diagnosis, and treatment of diseases of the nervous system. Here, we report a luminescent conjugated oligothiophene (LCO), named p-HTMI, for non-invasive and non-amplified real-time detection of live human patient-derived glioblastoma (GBM) stem cell-like cells and NSPCs. While p-HTMI stained only a small fraction of other cell types investigated, the mere addition of p-HTMI to the cell culture resulted in efficient detection of NSPCs or GBM cells from rodents and humans within minutes. p-HTMI is functionalized with a methylated imidazole moiety resembling the side chain of histidine/histamine, and non-methylated analogues were not functional. Cell sorting experiments of human GBM cells demonstrated that p-HTMI labeled the same cell population as CD271, a proposed marker for stem cell-like cells and rapidly migrating cells in glioblastoma. Our results suggest that the LCO p-HTMI is a versatile tool for immediate and selective detection of neural and glioma stem and progenitor cells.

    Download full text (pdf)
    fulltext
  • 21.
    Jiang, Yiwen
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab. Karolinska Inst, Dept Med Biochem & Biophys, S-17177 Stockholm, Sweden..
    Marinescu, Voichita Dana
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Xie, Yuan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Jarvius, Malin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
    Maturi, Naga Prathyusha
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Haglund, Caroline
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
    Olofsson, Sara
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Lindberg, Nanna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Olofsson, Tommie
    Natl Board Forens Med, Dept Forens Med, Box 1024, S-75140 Uppsala, Sweden..
    Leijonmarck, Caroline
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience.
    Hesselager, Göran
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Neurosurgery.
    Alafuzoff, Irina
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Clinical and experimental pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Fryknäs, Mårten
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
    Larsson, Rolf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Uhrbom, Lene
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Glioblastoma Cell Malignancy and Drug Sensitivity Are Affected by the Cell of Origin2017In: Cell Reports, E-ISSN 2211-1247, Vol. 18, no 4, p. 977-990Article in journal (Refereed)
    Abstract [en]

    The identity of the glioblastoma (GBM) cell of origin and its contributions to disease progression and treatment response remain largely unknown. We have analyzed how the phenotypic state of the initially transformed cell affects mouse GBM development and essential GBM cell (GC) properties. We find that GBM induced in neural stem-cell-like glial fibrillary acidic protein (GFAP)-expressing cells in the subventricular zone of adult mice shows accelerated tumor development and produces more malignant GCs (mGC1GFAP) that are less resistant to cancer drugs, compared with those originating from more differentiated nestin- (mGC2NES) or 2,'3'-cyclic nucleotide 3'-phosphodiesterase (mGC3CNP)-expressing cells. Transcriptome analysis of mouse GCs identified a 196 mouse cell origin (MCO) gene signature that was used to partition 61 patient-derived GC lines. Human GC lines that clustered with the mGC1GFAP cells were also significantly more self-renewing, tumorigenic, and sensitive to cancer drugs compared with those that clustered with mouse GCs of more differentiated origin.

    Download full text (pdf)
    fulltext
  • 22.
    Johansson, Patrik
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Krona, Cecilia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Kundu, Soumi
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Doroszko, Milena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Baskaran, Sathishkumar
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Schmidt, Linnea
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Vinel, Claire
    Queen Mary Univ London, Barts & London Sch Med & Dent, Blizard Inst, London E1 2AT, England..
    Almstedt, Elin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Elgendy, Ramy
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Elfineh, Lioudmila
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Gallant, Caroline J.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular tools. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Lundsten, Sara
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Radiation Science. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Gago, Fernando J. Ferrer
    Agcy Sci Technol & Res Star, Singapore 138648, Singapore..
    Hakkarainen, Aleksi
    Univ Turku, Res Ctr Integrat Physiol & Pharmacol, Inst Biomed, Turku 20500, Finland..
    Sipila, Petra
    Univ Turku, Res Ctr Integrat Physiol & Pharmacol, Inst Biomed, Turku 20500, Finland..
    Haggblad, Maria
    Stockholm Univ, Dept Biochem & Biophys, SciLifeLab, S-10405 Stockholm, Sweden..
    Martens, Ulf
    Stockholm Univ, Dept Biochem & Biophys, SciLifeLab, S-10405 Stockholm, Sweden..
    Lundgren, Bo
    Stockholm Univ, Dept Biochem & Biophys, SciLifeLab, S-10405 Stockholm, Sweden..
    Frigault, Melanie M.
    AstraZeneca Oncol, Waltham, MA 02451 USA..
    Lane, David P.
    Agcy Sci Technol & Res Star, Singapore 138648, Singapore.;Karolinska Inst, Dept Microbiol Tumor & Cell Biol, Sci Life Lab, S-17177 Stockholm, Sweden..
    Swartling, Fredrik J
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Uhrbom, Lene
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Nestor, Marika
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Radiation Science.
    Marino, Silvia
    Queen Mary Univ London, Barts & London Sch Med & Dent, Blizard Inst, London E1 2AT, England..
    Nelander, Sven
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    A Patient-Derived Cell Atlas Informs Precision Targeting of Glioblastoma2020In: Cell Reports, E-ISSN 2211-1247, Vol. 32, no 2, article id 107897Article in journal (Refereed)
    Abstract [en]

    Glioblastoma (GBM) is a malignant brain tumor with few therapeutic options. The disease presents with a complex spectrum of genomic aberrations, but the pharmacological consequences of these aberrations are partly unknown. Here, we report an integrated pharmacogenomic analysis of 100 patient-derived GBM cell cultures from the human glioma cell culture (HGCC) cohort. Exploring 1,544 drugs, we find that GBM has two main pharmacological subgroups, marked by differential response to proteasome inhibitors and mutually exclusive aberrations in TP53 and CDKN2A/B. We confirm this trend in cell and in xenotransplantation models, and identify both Bcl-2 family inhibitors and p53 activators as potentiators of proteasome inhibitors in GBM cells, We can further predict the responses of individual cell cultures to several existing drug classes, presenting opportunities for drug repurposing and design of stratified trials. Our functionally profiled biobank provides a valuable resource for the discovery of new treatments for GBM.

    Download full text (pdf)
    FULLTEXT01
  • 23.
    Johansson, Patrik
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Rosén, Emil
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Weishaupt, Holger
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Jörnsten, Rebecka
    Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Exploring large scale integrative networks of glioblastoma using hypothesis driven pattern searchManuscript (preprint) (Other academic)
  • 24.
    Johansson, Patrik
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Schmidt, Linnéa
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Department of Molecular Medicine, Aarhus University, Aarhus, Denmark.
    Baskaran, Sathishkumar
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Kundu, Soumi
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Gallant, Caroline J.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular tools.
    Kling, Teresia
    Sahlgrenska Cancer Center, Department of Pathology and Genetics, University of Gothenburg, Sweden.
    Awe, Olatilewa
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Department of Neurosurgery, University of Iowa, IA, USA.
    Elfineh, Lioudmila
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Holmberg Olausson, Karl
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Almstedt, Elin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Häggblad, Maria
    Department of Biochemistry and Biophysics, Stockholm University, Sweden, BCS, SciLifeLab, Sweden.
    Martens, Ulf
    Department of Biochemistry and Biophysics, Stockholm University, Sweden, BCS, SciLifeLab, Sweden.
    Lundgren, Bo
    Department of Biochemistry and Biophysics, Stockholm University, Sweden, BCS, SciLifeLab, Sweden.
    Lönnstedt, Ingrid
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Walter and Eliza Hall Institute of Medical Research, Australia.
    Frigault, Melanie M.
    Translational Sciences, Oncology, IMED Biotech Unit, AstraZeneca, Boston, US.
    Hurt, Elaine
    Division of Oncology, Medimmune LLC, Gaithersburg, MD, USA.
    Jörnsten, Rebecka
    Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden.
    Krona, Cecilia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Decoding glioblastoma drug responses using an open access library of patient derived cell modelsManuscript (preprint) (Other academic)
  • 25.
    Johard, Helena
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Karolinska Inst, Dept Physiol & Pharmacol, Stockholm, Sweden; Masaryk Univ, Cent European Inst Technol, Brno, Czech Republic.
    Omelyanenko, Anna
    Karolinska Inst, Dept Physiol & Pharmacol, Stockholm, Sweden.
    Fei, Gao
    Karolinska Inst, Dept Physiol & Pharmacol, Stockholm, Sweden; Jilin Univ, Coll Vet Med, Changchun, Jilin, Peoples R China.
    Zilberter, Misha
    Gladstone Inst Neurol Dis, San Francisco, CA USA.
    Dave, Zankruti
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Abu-Youssef, Randa
    Karolinska Inst, Dept Physiol & Pharmacol, Stockholm, Sweden.
    Schmidt, Linnéa
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Harisankar, Aditya
    Karolinska Inst, Dept Med, Huddinge, Sweden.
    Vincent, C. Theresa
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. NYU, Sch Med, Dept Microbiol, New York, NY 10016 USA.
    Walfridsson, Julian
    Karolinska Inst, Dept Med, Huddinge, Sweden.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Harkany, Tibor
    Karolinska Inst, Dept Neurosci, Solna, Sweden; Med Univ Vienna, Ctr Brain Res, Dept Mol Neurosci, Vienna, Austria.
    Blomgren, Klas
    Karolinska Inst, Dept Womens & Childrens Hlth, Stockholm, Sweden; Karolinska Univ Hosp, Pediat Oncol, Stockholm, Sweden.
    Andäng, Michael
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Karolinska Inst, Dept Physiol & Pharmacol, Stockholm, Sweden; Masaryk Univ, Cent European Inst Technol, Brno, Czech Republic.
    HCN Channel Activity Balances Quiescence and Proliferation in Neural Stem Cells and Is a Selective Target for Neuroprotection During Cancer Treatment2020In: Molecular Cancer Research, ISSN 1541-7786, E-ISSN 1557-3125, Vol. 18, no 10, p. 1522-1533Article in journal (Refereed)
    Abstract [en]

    Children suffering from neurologic cancers undergoing chemotherapy and radiotherapy are at high risk of reduced neurocognitive abilities likely via damage to proliferating neural stem cells (NSC). Therefore, strategies to protect NSCs are needed. We argue that induced cell-cycle arrest/quiescence in NSCs during cancer treatment can represent such a strategy. Here, we show that hyperpolarization-activated cyclic nucleotide-gated (HCN) ion channels are dynamically expressed over the cell cycle in NSCs, depolarize the membrane potential, underlie spontaneous calcium oscillations and are required to maintain NSCs in the actively proliferating pool. Hyperpolarizing pharmacologic inhibition of HCN channels during exposure to ionizing radiation protects NSCs cells in neurogenic brain regions of young mice. In contrast, brain tumor-initiating cells, which also express HCN channels, remain proliferative during HCN inhibition.

  • 26.
    Kaffes, Ioannis
    et al.
    Emory Univ, Aflac Canc & Blood Disorders Ctr, Childrens Healthcare Atlanta, Dept Pediat,Winship Canc Inst,Sch Med, Atlanta, GA USA;Max Delbruck Ctr Mol Med, Dept Cellular Neurosci, Helmholtz Assoc, Berlin, Germany.
    Szulzewsky, Frank
    Fred Hutchinson Canc Res Ctr, Dept Human Biol, 1124 Columbia St, Seattle, WA 98104 USA.
    Chen, Zhihong
    Emory Univ, Aflac Canc & Blood Disorders Ctr, Childrens Healthcare Atlanta, Dept Pediat,Winship Canc Inst,Sch Med, Atlanta, GA USA;Emory Univ, Winship Canc Inst, Discovery & Dev Therapeut Program, Atlanta, GA 30322 USA.
    Herting, Cameron J.
    Emory Univ, Aflac Canc & Blood Disorders Ctr, Childrens Healthcare Atlanta, Dept Pediat,Winship Canc Inst,Sch Med, Atlanta, GA USA.
    Gabanic, Ben
    Emory Univ, Aflac Canc & Blood Disorders Ctr, Childrens Healthcare Atlanta, Dept Pediat,Winship Canc Inst,Sch Med, Atlanta, GA USA.
    Vega, Jose E. Velazquez
    Emory Univ, Dept Pathol & Lab Med, Atlanta, GA 30322 USA.
    Shelton, Jennifer
    Emory Univ, Dept Pathol & Lab Med, Atlanta, GA 30322 USA.
    Switchenko, Jeffrey M.
    Emory Univ, Winship Canc Inst, Dept Biostat & Bioinformat, Atlanta, GA 30322 USA.
    Ross, James L.
    Emory Univ, Aflac Canc & Blood Disorders Ctr, Childrens Healthcare Atlanta, Dept Pediat,Winship Canc Inst,Sch Med, Atlanta, GA USA.
    McSwain, Leon F.
    Emory Univ, Aflac Canc & Blood Disorders Ctr, Childrens Healthcare Atlanta, Dept Pediat,Winship Canc Inst,Sch Med, Atlanta, GA USA.
    Huse, Jason T.
    Univ Texas MD Anderson Canc Ctr, Dept Pathol, Houston, TX 77030 USA;Univ Texas MD Anderson Canc Ctr, Dept Translat Mol Pathol, Houston, TX 77030 USA.
    Westermark, Bengt
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Nelander, Sven
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Forsberg Nilsson, Karin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Uhrbom, Lene
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Maturi, Naga Prathyusha
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Cimino, Patrick J.
    Fred Hutchinson Canc Res Ctr, Dept Human Biol, 1124 Columbia St, Seattle, WA 98104 USA;Univ Washington, Dept Pathol, Seattle, WA USA.
    Holland, Eric C.
    Fred Hutchinson Canc Res Ctr, Dept Human Biol, 1124 Columbia St, Seattle, WA 98104 USA.
    Kettenmann, Helmut
    Max Delbruck Ctr Mol Med, Dept Cellular Neurosci, Helmholtz Assoc, Berlin, Germany.
    Brennan, Cameron W.
    Mem Sloan Kettering Canc Ctr, Dept Neurosurg, 1275 York Ave, New York, NY 10021 USA.
    Brat, Daniel J.
    Northwestern Univ, Dept Pathol, Feinberg Sch Med, Ward Bldg Room 3-140,303 E Chicago Ave, Chicago, IL 60611 USA.
    Hambardzumyan, Dolores
    Emory Univ, Aflac Canc & Blood Disorders Ctr, Childrens Healthcare Atlanta, Dept Pediat,Winship Canc Inst,Sch Med, Atlanta, GA USA;Emory Univ, Winship Canc Inst, Discovery & Dev Therapeut Program, Atlanta, GA 30322 USA.
    Human Mesenchymal glioblastomas are characterized by an increased immune cell presence compared to Proneural and Classical tumors2019In: Oncoimmunology, ISSN 2162-4011, E-ISSN 2162-402X, Vol. 8, no 11Article in journal (Refereed)
    Abstract [en]

    Glioblastoma (GBM) is the most aggressive malignant primary brain tumor in adults, with a median survival of 14.6 months. Recent efforts have focused on identifying clinically relevant subgroups to improve our understanding of pathogenetic mechanisms and patient stratification. Concurrently, the role of immune cells in the tumor microenvironment has received increasing attention, especially T cells and tumor-associated macrophages (TAM). The latter are a mixed population of activated brain-resident microglia and infiltrating monocytes/monocyte-derived macrophages, both of which express ionized calcium-binding adapter molecule 1 (IBA1). This study investigated differences in immune cell subpopulations among distinct transcriptional subtypes of GBM. Human GBM samples were molecularly characterized and assigned to Proneural, Mesenchymal or Classical subtypes as defined by NanoString nCounter Technology. Subsequently, we performed and analyzed automated immunohistochemical stainings for TAM as well as specific T cell populations. The Mesenchymal subtype of GBM showed the highest presence of TAM, CD8(+), CD3(+) and FOXP3(+) T cells, as compared to Proneural and Classical subtypes. High expression levels of the TAM-related gene AIF1, which encodes the TAM-specific protein IBA1, correlated with a worse prognosis in Proneural GBM, but conferred a survival benefit in Mesenchymal tumors. We used our data to construct a mathematical model that could reliably identify Mesenchymal GBM with high sensitivity using a combination of the aforementioned cell-specific IHC markers. In conclusion, we demonstrated that molecularly distinct GBM subtypes are characterized by profound differences in the composition of their immune microenvironment, which could potentially help to identify tumors amenable to immunotherapy.

    Download full text (pdf)
    FULLTEXT01
  • 27.
    Kerzeli, Iliana Kyriaki
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Lord, Martin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Doroszko, Milena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Elgendy, Ramy
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Chourlia, Aikaterini
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Stepanek, Ivan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Larsson, Elinor
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Science for Life Laboratory, SciLifeLab.
    van Hooren, Luuk
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Nelander, Sven
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Malmström, Per-Uno
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Urology.
    Dragomir, Anca
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Clinical and experimental pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Segersten, Ulrika
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Urology.
    Mangsbo, Sara
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
    Single-cell RNAseq and longitudinal proteomic analysis of a novel semi-spontaneous urothelial cancer model reveals tumor cell heterogeneity and pretumoral urine protein alterations2021In: PLOS ONE, E-ISSN 1932-6203, Vol. 16, no 7, article id e0253178Article in journal (Refereed)
    Abstract [en]

    Bladder cancer, one of the most prevalent malignancies worldwide, remains hard to classify due to a staggering molecular complexity. Despite a plethora of diagnostic tools and therapies, it is hard to outline the key steps leading up to the transition from high-risk non-muscle-invasive bladder cancer (NMIBC) to muscle-invasive bladder cancer (MIBC). Carcinogen-induced murine models can recapitulate urothelial carcinogenesis and natural anti-tumor immunity. Herein, we have developed and profiled a novel model of progressive NMIBC based on 10 weeks of OH-BBN exposure in hepatocyte growth factor/cyclin dependent kinase 4 (R24C) (Hgf-Cdk4(R24C)) mice. The profiling of the model was performed by histology grading, single cell transcriptomic and proteomic analysis, while the derivation of a tumorigenic cell line was validated and used to assess in vivo anti-tumor effects in response to immunotherapy. Established NMIBC was present in females at 10 weeks post OH-BBN exposure while neoplasia was not as advanced in male mice, however all mice progressed to MIBC. Single cell RNA sequencing analysis revealed an intratumoral heterogeneity also described in the human disease trajectory. Moreover, although immune activation biomarkers were elevated in urine during carcinogen exposure, anti-programmed cell death protein 1 (anti-PD1) monotherapy did not prevent tumor progression. Furthermore, anti-PD1 immunotherapy did not control the growth of subcutaneous tumors formed by the newly derived urothelial cancer cell line. However, treatment with CpG-oligodeoxynucleotides (ODN) significantly decreased tumor volume, but only in females. In conclusion, the molecular map of this novel preclinical model of bladder cancer provides an opportunity to further investigate pharmacological therapies ahead with regards to both targeted drugs and immunotherapies to improve the strategies of how we should tackle the heterogeneous tumor microenvironment in urothelial bladder cancer to improve responses rates in the clinic.

    Download full text (pdf)
    FULLTEXT01
  • 28. Kitambi, Satish Srinivas
    et al.
    Toledo, Enrique M.
    Usoskin, Dmitry
    Wee, Shimei
    Harisankar, Aditya
    Svensson, Richard
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmacy.
    Sigmundsson, Kristmundur
    Kalderen, Christina
    Niklasson, Mia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Kundu, Soumi
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology.
    Aranda, Sergi
    Westermark, Bengt
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Uhrbom, Lene
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology.
    Andang, Michael
    Damberg, Peter
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Arenas, Ernest
    Artursson, Per
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmacy.
    Walfridsson, Julian
    Nilsson, Karin Forsberg
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology.
    Hammarstrom, Lars G. J.
    Ernfors, Patrik
    Vulnerability of Glioblastoma Cells to Catastrophic Vacuolization and Death Induced by a Small Molecule2014In: Cell, ISSN 0092-8674, E-ISSN 1097-4172, Vol. 157, no 2, p. 313-328Article in journal (Refereed)
    Abstract [en]

    Glioblastoma multiforme (GBM) is the most aggressive form of brain cancer with marginal life expectancy. Based on the assumption that GBM cells gain functions not necessarily involved in the cancerous process, patient-derived glioblastoma cells (GCs) were screened to identify cellular processes amenable for development of targeted treatments. The quinine-derivative NSC13316 reliably and selectively compromised viability. Synthetic chemical expansion reveals delicate structure-activity relationship and analogs with increased potency, termed Vacquinols. Vacquinols stimulate death by membrane ruffling, cell rounding, massive macropinocytic vacuole accumulation, ATP depletion, and cytoplasmic membrane rupture of GCs. The MAP kinase MKK4, identified by a shRNA screen, represents a critical signaling node. Vacquinol-1 displays excellent in vivo pharmacokinetics and brain exposure, attenuates disease progression, and prolongs survival in a GBM animal model. These results identify a vulnerability to massive vacuolization that can be targeted by small molecules and point to the possible exploitation of this process in the design of anticancer therapies.

  • 29.
    Kling, Teresia
    et al.
    Gothenburg Univ, Sahlgrenska Acad, Sahlgrenska Canc Ctr, Inst Biomed,Dept Pathol, S-41124 Gothenburg, Sweden..
    Ferrarese, Roberto
    Univ Freiburg, Fac Med, Med Ctr, Dept Neurosurg, Freiburg, Germany..
    Ailin, Darren Oh
    Univ Freiburg, Fac Med, Med Ctr, Dept Neurosurg, Freiburg, Germany.;Univ Freiburg, Fac Biol, Schnzlestr 1, D-79104 Freiburg, Germany..
    Johansson, Patrik
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Heiland, Dieter Henrik
    Univ Freiburg, Fac Med, Med Ctr, Dept Neurosurg, Freiburg, Germany..
    Dai, Fangping
    Univ Freiburg, Fac Med, Med Ctr, Dept Neurosurg, Freiburg, Germany..
    Vasilikos, Ioannis
    Univ Freiburg, Fac Med, Med Ctr, Dept Neurosurg, Freiburg, Germany..
    Weyerbrock, Astrid
    Univ Freiburg, Fac Med, Med Ctr, Dept Neurosurg, Freiburg, Germany..
    Jornsten, Rebecka
    Univ Gothenburg, Math Sci, SE-41296 Gothenburg, Sweden.;Chalmers, SE-41296 Gothenburg, Sweden..
    Carro, Maria Stella
    Univ Freiburg, Fac Med, Med Ctr, Dept Neurosurg, Freiburg, Germany..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Integrative Modeling Reveals Annexin A2-mediated Epigenetic Control of Mesenchymal Glioblastoma2016In: EBioMedicine, E-ISSN 2352-3964, Vol. 12, p. 72-85Article in journal (Refereed)
    Abstract [en]

    Glioblastomas are characterized by transcriptionally distinct subtypes, but despite possible clinical relevance, their regulation remains poorly understood. The commonly used molecular classification systems for GBM all identify a subtype with high expression of mesenchymal marker transcripts, strongly associated with invasive growth. We used a comprehensive data-driven network modeling technique (augmented sparse inverse covariance selection, aSICS) to define separate genomic, epigenetic, and transcriptional regulators of glioblastoma subtypes. Our model identified Annexin A2 (ANXA2) as a novel methylation-controlled positive regulator of the mesenchymal subtype. Subsequent evaluation in two independent cohorts established ANXA2 expression as a prognostic factor that is dependent on ANXA2 promoter methylation. ANXA2 knockdown in primary glioblastoma stem cell-like cultures suppressed known mesenchymal master regulators, and abrogated cell proliferation and invasion. Our results place ANXA2 at the apex of a regulatory cascade that determines glioblastoma mesenchymal transformation and validate aSICS as a general methodology to uncover regulators of cancer subtypes.

    Download full text (pdf)
    fulltext
  • 30.
    Kling, Teresia
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Johansson, Patrik
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Sanchez, Jose
    Chalmers, S-41296 Gothenburg, Sweden..
    Marinescu, Voichita D.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala Univ, Uppsala, Sweden..
    Jornsten, Rebecka
    Chalmers, S-41296 Gothenburg, Sweden..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Efficient exploration of multi-cancer networks by generalized covariance selection and interactive web content2015In: Cancer Research, ISSN 0008-5472, E-ISSN 1538-7445, Vol. 75, no 22, article id B2-35Article in journal (Other academic)
  • 31.
    Kling, Teresia
    et al.
    Univ Gothenburg, Sahlgrenska Canc Ctr, SE-40530 Gothenburg, Sweden.;Univ Gothenburg, Dept Mol & Clin Med, SE-40530 Gothenburg, Sweden..
    Johansson, Patrik
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Sanchez, Jose
    Univ Gothenburg, Math Sci, SE-41296 Gothenburg, Sweden.;Chalmers, SE-41296 Gothenburg, Sweden..
    Marinescu, Voichita D.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Jornsten, Rebecka
    Univ Gothenburg, Math Sci, SE-41296 Gothenburg, Sweden.;Chalmers, SE-41296 Gothenburg, Sweden..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Efficient exploration of pan-cancer networks by generalized covariance selection and interactive web content2015In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 43, no 15, article id e98Article in journal (Refereed)
    Abstract [en]

    Statistical network modeling techniques are increasingly important tools to analyze cancer genomics data. However, current tools and resources are not designed to work across multiple diagnoses and technical platforms, thus limiting their applicability to comprehensive pan-cancer datasets such as The Cancer Genome Atlas (TCGA). To address this, we describe a new data driven modeling method, based on generalized Sparse Inverse Covariance Selection (SICS). The method integrates genetic, epigenetic and transcriptional data from multiple cancers, to define links that are present in multiple cancers, a subset of cancers, or a single cancer. It is shown to be statistically robust and effective at detecting direct pathway links in data from TCGA. To facilitate interpretation of the results, we introduce a publicly accessible tool ( ext-link-type="uri" xlink:href="http://cancerlandscapes.org/">cancerlandscapes.org), in which the derived networks are explored as interactive web content, linked to several pathway and pharmacological databases. To evaluate the performance of the method, we constructed a model for eight TCGA cancers, using data from 3900 patients. The model rediscovered known mechanisms and contained interesting predictions. Possible applications include prediction of regulatory relationships, comparison of network modules across multiple forms of cancer and identification of drug targets.

    Download full text (pdf)
    fulltext
  • 32.
    Larsson, Ida
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Dalmo, Erika
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Elgendy, Ramy
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Niklasson, Mia
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Doroszko, Milena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Segerman, Anna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden.;Uppsala Univ Hosp, Dept Med Sci Canc Pharmacol & Computat Med, Uppsala, Sweden..
    Jornsten, Rebecka
    Chalmers Univ Technol, Math Sci, Gothenburg, Sweden..
    Westermark, Bengt
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Nelander, Sven
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Modeling glioblastoma heterogeneity as a dynamic network of cell states2021In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 17, no 9, article id e10105Article in journal (Refereed)
    Abstract [en]

    Tumor cell heterogeneity is a crucial characteristic of malignant brain tumors and underpins phenomena such as therapy resistance and tumor recurrence. Advances in single-cell analysis have enabled the delineation of distinct cellular states of brain tumor cells, but the time-dependent changes in such states remain poorly understood. Here, we construct quantitative models of the time-dependent transcriptional variation of patient-derived glioblastoma (GBM) cells. We build the models by sampling and profiling barcoded GBM cells and their progeny over the course of 3 weeks and by fitting a mathematical model to estimate changes in GBM cell states and their growth rates. Our model suggests a hierarchical yet plastic organization of GBM, where the rates and patterns of cell state switching are partly patient-specific. Therapeutic interventions produce complex dynamic effects, including inhibition of specific states and altered differentiation. Our method provides a general strategy to uncover time-dependent changes in cancer cells and offers a way to evaluate and predict how therapy affects cell state composition.

  • 33.
    Larsson, Ida
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Lundin, Erika
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Elgendy, Ramy
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Niklasson, Mia
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Doroszko, Milena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Segerman, Anna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden.;Uppsala Univ Hosp, Dept Med Sci Canc Pharmacol & Computat Med, Uppsala, Sweden..
    Jornsten, Rebecka
    Chalmers Univ Technol, Math Sci, Gothenburg, Sweden..
    Westermark, Bengt
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Nelander, Sven
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Modeling glioblastoma heterogeneity as a dynamic network of cell states2021In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 17, no 9, article id e10105Article in journal (Refereed)
    Abstract [en]

    Tumor cell heterogeneity is a crucial characteristic of malignant brain tumors and underpins phenomena such as therapy resistance and tumor recurrence. Advances in single-cell analysis have enabled the delineation of distinct cellular states of brain tumor cells, but the time-dependent changes in such states remain poorly understood. Here, we construct quantitative models of the time-dependent transcriptional variation of patient-derived glioblastoma (GBM) cells. We build the models by sampling and profiling barcoded GBM cells and their progeny over the course of 3 weeks and by fitting a mathematical model to estimate changes in GBM cell states and their growth rates. Our model suggests a hierarchical yet plastic organization of GBM, where the rates and patterns of cell state switching are partly patient-specific. Therapeutic interventions produce complex dynamic effects, including inhibition of specific states and altered differentiation. Our method provides a general strategy to uncover time-dependent changes in cancer cells and offers a way to evaluate and predict how therapy affects cell state composition.

    Download full text (pdf)
    fulltext
  • 34.
    Lundsten, Sara
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Radiation Science.
    Berglund, Hanna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Radiation Science.
    Jha, Preeti
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Radiation Science. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Preparative Medicinal Chemistry.
    Krona, Cecilia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Hariri, Mehran
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Radiation Science.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Lane, David P.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Radiation Science. p53Lab, Agency for Science Technology and Research (A*STAR), Singapore; Department of Microbiology, Tumor and Cell Biology, Karolinska Institute.
    Nestor, Marika
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Radiation Science.
    p53-Mediated Radiosensitization of 177Lu-DOTATATE in Neuroblastoma Tumor Spheroids2021In: Biomolecules, E-ISSN 2218-273X, Vol. 11, no 11, article id 1695Article in journal (Refereed)
    Abstract [en]

    p53 is involved in DNA damage response and is an exciting target for radiosensitization in cancer. Targeted radionuclide therapy against somatostatin receptors with 177Lu-DOTATATE is currently being explored as a treatment for neuroblastoma. The aim of this study was to investigate the novel p53-stabilizing peptide VIP116 in neuroblastoma, both as monotherapy and together with 177Lu-DOTATATE. Five neuroblastoma cell lines, including two patient-derived xenograft (PDX) lines, were characterized in monolayer cultures. Four out of five were positive for 177Lu-DOTATATE uptake. IC50 values after VIP116 treatments correlated with p53 status, ranging between 2.8&ndash;238.2 &mu;M. IMR-32 and PDX lines LU-NB-1 and LU-NB-2 were then cultured as multicellular tumor spheroids and treated with 177Lu-DOTATATE and/or VIP116. Spheroid growth was inhibited in all spheroid models for all treatment modalities. The most pronounced effects were observed for combination treatments, mediating synergistic effects in the IMR-32 model. VIP116 and combination treatment increased p53 levels with subsequent induction of p21, Bax and cleaved caspase 3. Combination treatment resulted in a 14-fold and 1.6-fold induction of MDM2 in LU-NB-2 and IMR-32 spheroids, respectively. This, together with differential MYCN signaling, may explain the varying degree of synergy. In conclusion, VIP116 inhibited neuroblastoma cell growth, potentiated 177Lu-DOTATATE treatment and could, therefore, be a feasible treatment option for neuroblastoma.

    Download full text (pdf)
    fulltext
  • 35.
    Lönnstedt, Ingrid M.
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab. Walter & Eliza Hall Inst Med Res, Bioinformat Div, Melbourne, Vic 3052, Australia..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    FC1000: normalized gene expression changes of systematically perturbed human cells2017In: Statistical Applications in Genetics and Molecular Biology, ISSN 1544-6115, E-ISSN 1544-6115, Vol. 16, no 4, p. 217-242Article in journal (Refereed)
    Abstract [en]

    The systematic study of transcriptional responses to genetic and chemical perturbations in human cells is still in its early stages. The largest available dataset to date is the newly released L1000 compendium. With its 1.3 million gene expression profiles of treated human cells it offers many opportunities for biomedical data mining, but also data normalization challenges of new dimensions. We developed a novel and practical approach to obtain accurate estimates of fold change response profiles from L1000, based on the RUV (Remove Unwanted Variation) statistical framework. Extending RUV to a big data setting, we propose an estimation procedure, in which an underlying RUV model is tuned by feedback through dataset specific statistical measures, reflecting p-value distributions and internal gene knockdown controls. Applying these metrics-termed evaluation endpoints - to disjoint data splits and integrating the results to select an optimal normalization, the procedure reduces bias and noise in the L1000 data, which in turn broadens the potential of this resource for pharmacological and functional genomic analyses. Our pipeline and normalization results are distributed as an R package (nelanderlab.org/FC1000.html).

    Download full text (pdf)
    fulltext
  • 36.
    Marques, Carolina
    et al.
    Spanish Natl Canc Res Ctr, Seve Ballesteros Fdn, Brain Tumor Grp, Madrid, Spain..
    Unterkircher, Thomas
    Fac Med Freiburg, Dept Neurosurg, Freiburg, Germany..
    Kroon, Paula
    Spanish Natl Canc Res Ctr, Seve Ballesteros Fdn, Brain Tumor Grp, Madrid, Spain..
    Oldrini, Barbara
    Spanish Natl Canc Res Ctr, Seve Ballesteros Fdn, Brain Tumor Grp, Madrid, Spain..
    Izzo, Annalisa
    Fac Med Freiburg, Dept Neurosurg, Freiburg, Germany..
    Dramaretska, Yuliia
    Max Delbruck Ctr Mol Med Helmholtz Assoc MDC, Berlin, Germany..
    Ferrarese, Roberto
    Fac Med Freiburg, Dept Neurosurg, Freiburg, Germany..
    Kling, Eva
    Fac Med Freiburg, Dept Neurosurg, Freiburg, Germany..
    Schnell, Oliver
    Fac Med Freiburg, Dept Neurosurg, Freiburg, Germany..
    Nelander, Sven
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Wagner, Erwin F.
    Spanish Natl Canc Res Ctr, Genes Dev & Dis Grp, Madrid, Spain.;Med Univ Vienna, Lab Med Dept, Vienna, Austria.;Med Univ Vienna, Dermatol Dept, Vienna, Austria..
    Bakiri, Latifa
    Spanish Natl Canc Res Ctr, Genes Dev & Dis Grp, Madrid, Spain.;Med Univ Vienna, Lab Med Dept, Vienna, Austria..
    Gargiulo, Gaetano
    Max Delbruck Ctr Mol Med Helmholtz Assoc MDC, Berlin, Germany..
    Carro, Maria Stella
    Fac Med Freiburg, Dept Neurosurg, Freiburg, Germany..
    Squatrito, Massimo
    Spanish Natl Canc Res Ctr, Seve Ballesteros Fdn, Brain Tumor Grp, Madrid, Spain..
    NF1 regulates mesenchymal gliblastoma plasticity and aggressiveness through the AP-1 transcription factor FOSL12021In: eLIFE, E-ISSN 2050-084X, Vol. 10, article id e64846Article in journal (Refereed)
    Abstract [en]

    The molecular basis underlying glioblastoma (GBM) heterogeneity and plasticity is not fully understood. Using transcriptomic data of human patient-derived brain tumor stem cell lines (BTSCs), classified based on GBM-intrinsic signatures, we identify the AP-1 transcription factor FOSL1 as a key regulator of the mesenchymal (MES) subtype. We provide a mechanistic basis to the role of the neurofibromatosis type 1 gene (NF1), a negative regulator of the RAS/MAPK pathway, in GBM mesenchymal transformation through the modulation of FOSL1 expression. Depletion of FOSL1 in NF1-mutant human BTSCs and Kras-mutant mouse neural stem cells results in loss of the mesenchymal gene signature and reduction in stem cell properties and in vivo tumorigenic potential. Our data demonstrate that FOSL1 controls GBM plasticity and aggressiveness in response to NF1 alterations.

    Download full text (pdf)
    FULLTEXT01
  • 37.
    Matuszewski, Damian J.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Krona, Cecilia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Nelander, Sven
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Sintorn, Ida-Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Image-Based Detection of Patient-Specific Drug-Induced Cell-Cycle Effects in Glioblastoma2018In: SLAS Discovery, ISSN 2472-5560, E-ISSN 2472-5552, Vol. 23, no 10, p. 1030-1039Article in journal (Refereed)
    Abstract [en]

    Image-based analysis is an increasingly important tool to characterize the effect of drugs in large-scale chemical screens. Herein, we present image and data analysis methods to investigate population cell-cycle dynamics in patient-derived brain tumor cells. Images of glioblastoma cells grown in multiwell plates were used to extract per-cell descriptors, including nuclear DNA content. We reduced the DNA content data from per-cell descriptors to per-well frequency distributions, which were used to identify compounds affecting cell-cycle phase distribution. We analyzed cells from 15 patient cases representing multiple subtypes of glioblastoma and searched for clusters of cell-cycle phase distributions characterizing similarities in response to 249 compounds at 11 doses. We show that this approach applied in a blind analysis with unlabeled substances identified drugs that are commonly used for treating solid tumors as well as other compounds that are well known for inducing cell-cycle arrest. Redistribution of nuclear DNA content signals is thus a robust metric of cell-cycle arrest in patient-derived glioblastoma cells.

  • 38. Mega, Alessandro
    et al.
    Hartmark Nilsen, Mette
    Leiss, Lina Wik
    Tobin, Nicholas P
    Miletic, Hrvoje
    Sleire, Linda
    Strell, Carina
    Nelander, Sven
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Krona, Cecilia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Hägerstrand, Daniel
    Enger, Per Ø
    Nistér, Monica
    Östman, Arne
    Astrocytes enhance glioblastoma growth.2020In: Glia, ISSN 0894-1491, E-ISSN 1098-1136, Vol. 68, no 2, p. 316-327Article in journal (Refereed)
    Abstract [en]

    Glioblastoma (GBM) is a deadly disease with a need for deeper understanding and new therapeutic approaches. The microenvironment of glioblastoma has previously been shown to guide glioblastoma progression. In this study, astrocytes were investigated with regard to their effect on glioblastoma proliferation through correlative analyses of clinical samples and experimental in vitro and in vivo studies. Co-culture techniques were used to investigate the GBM growth enhancing potential of astrocytes. Cell sorting and RNA sequencing were used to generate a GBM-associated astrocyte signature and to investigate astrocyte-induced GBM genes. A NOD scid GBM mouse model was used for in vivo studies. A gene signature reflecting GBM-activated astrocytes was associated with poor prognosis in the TCGA GBM dataset. Two genes, periostin and serglycin, induced in GBM cells upon exposure to astrocytes were expressed at higher levels in cases with high "astrocyte signature score". Astrocytes were shown to enhance glioblastoma cell growth in cell lines and in a patient-derived culture, in a manner dependent on cell-cell contact and involving increased cell proliferation. Furthermore, co-injection of astrocytes with glioblastoma cells reduced survival in an orthotopic GBM model in NOD scid mice. In conclusion, this study suggests that astrocytes contribute to glioblastoma growth and implies this crosstalk as a candidate target for novel therapies.

  • 39.
    Merisaari, Joni
    et al.
    Univ Turku, Turku Biosci Ctr, Tykistokatu 6A, Turku 20520, Finland.;Abo Akad Univ, Tykistokatu 6A, Turku 20520, Finland.;Univ Turku, Inst Biomed, Turku 20520, Finland..
    Denisova, Oxana, V
    Univ Turku, Turku Biosci Ctr, Tykistokatu 6A, Turku 20520, Finland.;Abo Akad Univ, Tykistokatu 6A, Turku 20520, Finland..
    Doroszko, Milena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Le Joncour, Vadim
    Univ Helsinki, Fac Med, Translat Canc Med Res Program, Helsinki 00014, Finland..
    Johansson, Patrik
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Leenders, William P. J.
    Radboud Inst Mol Life Sci, Dept Biochem, NL-6525 Nijmegen, Netherlands..
    Kastrinsky, David B.
    Icahn Sch Med Mt Sinai, New York, NY 10029 USA.;Donald & Barbara Zucker Sch Med Hofstra Northwell, Hempstead, NY 11549 USA..
    Zaware, Nilesh
    Icahn Sch Med Mt Sinai, New York, NY 10029 USA..
    Narla, Goutham
    Univ Michigan, Dept Internal Med, Div Genet Med, Ann Arbor, MI 48109 USA..
    Laakkonen, Pirjo
    Univ Helsinki, Fac Med, Translat Canc Med Res Program, Helsinki 00014, Finland.;Univ Helsinki, Lab Anim Ctr, Helsinki Inst Life Sci HiLIFE, Helsinki 00014, Finland..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Ohlmeyer, Michael
    Icahn Sch Med Mt Sinai, New York, NY 10029 USA.;Atux Iskay LLC, Plainsboro, NJ 08536 USA..
    Westermarck, Jukka
    Univ Turku, Turku Biosci Ctr, Tykistokatu 6A, Turku 20520, Finland.;Abo Akad Univ, Tykistokatu 6A, Turku 20520, Finland.;Univ Turku, Inst Biomed, Turku 20520, Finland..
    Monotherapy efficacy of blood-brain barrier permeable small molecule reactivators of protein phosphatase 2A in glioblastoma2020In: Brain Communications, E-ISSN 2632-1297, Vol. 2, no 1, article id 02Article in journal (Refereed)
    Abstract [en]

    Glioblastoma is a fatal disease in which most targeted therapies have clinically failed. However, pharmacological reactivation of tumour suppressors has not been thoroughly studied as yet as a glioblastoma therapeutic strategy. Tumour suppressor protein phosphatase 2A is inhibited by non-genetic mechanisms in glioblastoma, and thus, it would be potentially amendable for therapeutic reactivation. Here, we demonstrate that small molecule activators of protein phosphatase 2A, NZ-8-061 and DBK-1154, effectively cross the in vitro model of blood-brain barrier, and in vivo partition to mouse brain tissue after oral dosing. In vitro, small molecule activators of protein phosphatase 2A exhibit robust cell-killing activity against five established glioblastoma cell lines, and nine patient-derived primary glioma cell lines. Collectively, these cell lines have heterogeneous genetic background, kinase inhibitor resistance profile and stemness properties; and they represent different clinical glioblastoma subtypes. Moreover, small molecule activators of protein phosphatase 2A were found to be superior to a range of kinase inhibitors in their capacity to kill patient-derived primary glioma cells. Oral dosing of either of the small molecule activators of protein phosphatase 2A significantly reduced growth of infiltrative intracranial glioblastoma tumours. DBK-1154, with both higher degree of brain/blood distribution, and more potent in vitro activity against all tested glioblastoma cell lines, also significantly increased survival of mice bearing orthotopic glioblastoma xenografts. In summary, this report presents a proof-of-principle data for blood-brain barrier-permeable tumour suppressor reactivation therapy for glioblastoma cells of heterogenous molecular background. These results also provide the first indications that protein phosphatase 2A reactivation might be able to challenge the current paradigm in glioblastoma therapies which has been strongly focused on targeting specific genetically altered cancer drivers with highly specific inhibitors. Based on demonstrated role for protein phosphatase 2A inhibition in glioblastoma cell drug resistance, small molecule activators of protein phosphatase 2A may prove to be beneficial in future glioblastoma combination therapies.

    Download full text (pdf)
    fulltext
  • 40.
    Mitchell, Jonathan S.
    et al.
    Inst Canc Res, Div Genet & Epidemiol, 15 Cotswold Rd, Sutton SM2 5NG, Surrey, England..
    Li, Ni
    Inst Canc Res, Div Genet & Epidemiol, 15 Cotswold Rd, Sutton SM2 5NG, Surrey, England..
    Weinhold, Niels
    Univ Arkansas Med Sci, Myeloma Inst Res & Therapy, Little Rock, AR 72205 USA.;Heidelberg Univ, Dept Internal Med, D-69117 Heidelberg, Germany..
    Försti, Asta
    German Canc Res Ctr, D-69120 Heidelberg, Germany.;Lund Univ, Ctr Primary Hlth Care Res, SE-20502 Malmo, Sweden..
    Ali, Mina
    Dept Lab Med, Hematol & Transfus Med, BMC B13, SE-22184 Lund, Sweden..
    van Duin, Mark
    Erasmus MC Canc Inst, Dept Hematol, NL-3075 EA Rotterdam, Netherlands..
    Thorleifsson, Gudmar
    deCODE Genet, Sturlugata 8, IS-101 Reykjavik, Iceland..
    Johnson, David C.
    Inst Canc Res, Div Mol Pathol, Sutton SM2 5NG, Surrey, England..
    Chen, Bowang
    German Canc Res Ctr, D-69120 Heidelberg, Germany..
    Halvarsson, Britt-Marie
    Dept Lab Med, Hematol & Transfus Med, BMC B13, SE-22184 Lund, Sweden..
    Gudbjartsson, Daniel F.
    deCODE Genet, Sturlugata 8, IS-101 Reykjavik, Iceland.;Univ Iceland, Sch Engn & Nat Sci, IS-101 Reykjavik, Iceland..
    Kuiper, Rowan
    Erasmus MC Canc Inst, Dept Hematol, NL-3075 EA Rotterdam, Netherlands..
    Stephens, Owen W.
    Univ Arkansas Med Sci, Myeloma Inst Res & Therapy, Little Rock, AR 72205 USA..
    Bertsch, Uta
    Heidelberg Univ, Dept Internal Med, D-69117 Heidelberg, Germany.;Natl Ctr Tumor Dis, D-69120 Heidelberg, Germany..
    Broderick, Peter
    Inst Canc Res, Div Genet & Epidemiol, 15 Cotswold Rd, Sutton SM2 5NG, Surrey, England..
    Campo, Chiara
    German Canc Res Ctr, D-69120 Heidelberg, Germany..
    Einsele, Hermann
    Univ Clin Wurzburg, D-97080 Wurzburg, Germany..
    Gregory, Walter A.
    Univ Leeds, Clin Trials Res Unit, Leeds LS2 9PH, W Yorkshire, England..
    Gullberg, Urban
    Dept Lab Med, Hematol & Transfus Med, BMC B13, SE-22184 Lund, Sweden..
    Henrion, Marc
    Inst Canc Res, Div Genet & Epidemiol, 15 Cotswold Rd, Sutton SM2 5NG, Surrey, England..
    Hillengass, Jens
    Heidelberg Univ, Dept Internal Med, D-69117 Heidelberg, Germany..
    Hoffmann, Per
    Univ Bonn, Inst Human Genet, D-53127 Bonn, Germany.;Univ Basel, Div Med Genet, Dept Biomed, CH-4003 Basel, Switzerland..
    Jackson, Graham H.
    Royal Victoria Infirm, Newcastle Upon Tyne NE1 4LP, Tyne & Wear, England..
    Johnsson, Ellinor
    Dept Lab Med, Hematol & Transfus Med, BMC B13, SE-22184 Lund, Sweden..
    Jöud, Magnus
    Dept Lab Med, Hematol & Transfus Med, BMC B13, SE-22184 Lund, Sweden.;Off Med Serv, Clin Immunol & Transfus Med, Lab Med, SE-22185 Lund, Sweden..
    Kristinsson, Sigurjdur Y.
    Natl Univ Hosp Iceland, Dept Hematol, Landspitali, IS-101 Reykjavik, Iceland..
    Lenhoff, Stig
    Skane Univ Hosp, Hematol Clin, SE-22185 Lund, Sweden..
    Lenive, Oleg
    Inst Canc Res, Div Genet & Epidemiol, 15 Cotswold Rd, Sutton SM2 5NG, Surrey, England..
    Mellqvist, Ulf-Henrik
    Sahlgrens Univ Hosp, Sect Hematol, S-41345 Gothenburg, Sweden..
    Migliorini, Gabriele
    Inst Canc Res, Div Genet & Epidemiol, 15 Cotswold Rd, Sutton SM2 5NG, Surrey, England..
    Nahi, Hareth
    Karolinska Inst, Ctr Hematol & Regenerat Med, SE-17177 Stockholm, Sweden..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Nickel, Jolanta
    Heidelberg Univ, Dept Internal Med, D-69117 Heidelberg, Germany..
    Nöthen, Markus M.
    Univ Bonn, Inst Human Genet, D-53127 Bonn, Germany.;Univ Bonn, Dept Genom, Life & Brain Ctr, D-53127 Bonn, Germany..
    Rafnar, Thorunn
    deCODE Genet, Sturlugata 8, IS-101 Reykjavik, Iceland..
    Ross, Fiona M.
    Univ Southampton, Wessex Reg Genet Lab, Salisbury SP2 8BJ, Wilts, England..
    da Silva Filho, Miguel Inacio
    German Canc Res Ctr, D-69120 Heidelberg, Germany..
    Swaminathan, Bhairavi
    Dept Lab Med, Hematol & Transfus Med, BMC B13, SE-22184 Lund, Sweden..
    Thomsen, Hauke
    German Canc Res Ctr, D-69120 Heidelberg, Germany..
    Turesson, Ingemar
    Skane Univ Hosp, Hematol Clin, SE-22185 Lund, Sweden..
    Vangsted, Annette
    Rigshosp, Univ Copenhagen Hosp, Dept Haematol, Blegdamsvej 9, DK-2100 Copenhagen, Denmark..
    Vogel, Ulla
    Natl Res Ctr Working Environm, DK-2100 Copenhagen, Denmark..
    Waage, Anders
    Norwegian Univ Sci & Technol, Dept Canc Res & Mol Med, Box 8905, N-7491 Trondheim, Norway..
    Walker, Brian A.
    Univ Arkansas Med Sci, Myeloma Inst Res & Therapy, Little Rock, AR 72205 USA..
    Wihlborg, Anna-Karin
    Dept Lab Med, Hematol & Transfus Med, BMC B13, SE-22184 Lund, Sweden..
    Broyl, Annemiek
    Erasmus MC Canc Inst, Dept Hematol, NL-3075 EA Rotterdam, Netherlands..
    Davies, Faith E.
    Univ Arkansas Med Sci, Myeloma Inst Res & Therapy, Little Rock, AR 72205 USA..
    Thorsteinsdottir, Unnur
    deCODE Genet, Sturlugata 8, IS-101 Reykjavik, Iceland.;Univ Iceland, Fac Med, IS-101 Reykjavik, Iceland..
    Langer, Christian
    Univ Ulm, Dept Internal Med 3, D-89081 Ulm, Germany..
    Hansson, Markus
    Dept Lab Med, Hematol & Transfus Med, BMC B13, SE-22184 Lund, Sweden.;Skane Univ Hosp, Hematol Clin, SE-22185 Lund, Sweden..
    Kaiser, Martin
    Inst Canc Res, Div Mol Pathol, Sutton SM2 5NG, Surrey, England..
    Sonneveld, Pieter
    Erasmus MC Canc Inst, Dept Hematol, NL-3075 EA Rotterdam, Netherlands..
    Stefansson, Kari
    deCODE Genet, Sturlugata 8, IS-101 Reykjavik, Iceland..
    Morgan, Gareth J.
    Univ Arkansas Med Sci, Myeloma Inst Res & Therapy, Little Rock, AR 72205 USA..
    Goldschmidt, Hartmut
    Heidelberg Univ, Dept Internal Med, D-69117 Heidelberg, Germany.;Natl Ctr Tumor Dis, D-69120 Heidelberg, Germany..
    Hemminki, Kari
    German Canc Res Ctr, D-69120 Heidelberg, Germany.;Lund Univ, Ctr Primary Hlth Care Res, SE-20502 Malmo, Sweden..
    Nilsson, Björn
    Dept Lab Med, Hematol & Transfus Med, BMC B13, SE-22184 Lund, Sweden.;Off Med Serv, Clin Immunol & Transfus Med, Lab Med, SE-22185 Lund, Sweden.;Broad Inst, 7 Cambridge Ctr, Cambridge, MA 02142 USA..
    Houlston, Richard S.
    Inst Canc Res, Div Genet & Epidemiol, 15 Cotswold Rd, Sutton SM2 5NG, Surrey, England..
    Genome-wide association study identifies multiple susceptibility loci for multiple myeloma2016In: Nature Communications, E-ISSN 2041-1723, Vol. 7, article id 12050Article in journal (Refereed)
    Abstract [en]

    Multiple myeloma (MM) is a plasma cell malignancy with a significant heritable basis. Genome-wide association studies have transformed our understanding of MM predisposition, but individual studies have had limited power to discover risk loci. Here we perform a meta-analysis of these GWAS, add a new GWAS and perform replication analyses resulting in 9,866 cases and 239,188 controls. We confirm all nine known risk loci and discover eight new loci at 6p22.3 (rs34229995, P = 1.31 x 10(-8)), 6q21 (rs9372120, P = 9.09 x 10(-15)), 7q36.1 (rs7781265, P = 9.71 x 10(-9)), 8q24.21 (rs1948915, P = 4.20 x 10(-11)), 9p21.3 (rs2811710, P = 1.72 x 10(-13)), 10p12.1 (rs2790457, P = 1.77 x 10(-8)), 16q23.1 (rs7193541, P = 5.00 x 10(-12)) and 20q13.13 (rs6066835, P = 1.36 x 10(-13)), which localize in or near to JARID2, ATG5, SMARCD3, CCAT1, CDKN2A, WAC, RFWD3 and PREX1. These findings provide additional support for a polygenic model of MM and insight into the biological basis of tumour development.

    Download full text (pdf)
    fulltext
  • 41.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Increasing the accuracy of glioblastoma subtypes: Factoring in the tumor's cell of origin2019In: Molecular & Cellular Oncology, E-ISSN 2372-3556, Vol. 6, no 1, article id e1302907Article in journal (Refereed)
    Abstract [en]

    The transcriptional classification of glioblastoma has proven to be a complex issue. In the absence of strong correlations between underlying genomic lesions and transcriptional subtype, there is a need to systematically understand the origins of the glioblastoma subtypes. A recent integrated analysis of data from both mouse models and patient-derived cells supports that the glioblastoma's cell of origin is important in shaping transcriptional diversity and tumor cell malignancy.

    Download full text (pdf)
    fulltext
  • 42.
    Niklasson, Mia
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Maddalo, Gianluca
    Sramkova, Zuzana
    Mutlu, Ercan
    Wee, Shimei
    Sekyrova, Petra
    Schmidt, Linnea
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Fritz, Nicolas
    Dehnisch, Ivar
    Kyriatzis, Gregorios
    Krafcikova, Michaela
    Carson, Brittany B
    Feenstra, Jennifer M
    Marinescu, Voichita
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    Segerman, Anna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Haraldsson, Martin
    Gustavsson, Anna-Lena
    Hammarström, Lars G J
    Jenmalm Jensen, Annika
    Uhrbom, Lene
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Altelaar, A F Maarten
    Linnarsson, Sten
    Uhlén, Per
    Trantirek, Lukas
    Vincent, C Theresa
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Enger, Per Øyvind
    Andäng, Michael
    Membrane-Depolarizing Channel Blockers Induce Selective Glioma Cell Death by Impairing Nutrient Transport and Unfolded Protein/Amino Acid Responses2017In: Cancer Research, ISSN 0008-5472, E-ISSN 1538-7445, Vol. 77, no 7, p. 1741-1752Article in journal (Refereed)
    Abstract [en]

    Glioma-initiating cells (GIC) are considered the underlying cause of recurrences of aggressive glioblastomas, replenishing the tumor population and undermining the efficacy of conventional chemotherapy. Here we report the discovery that inhibiting T-type voltage-gated Ca(2+) and KCa channels can effectively induce selective cell death of GIC and increase host survival in an orthotopic mouse model of human glioma. At present, the precise cellular pathways affected by the drugs affecting these channels are unknown. However, using cell-based assays and integrated proteomics, phosphoproteomics, and transcriptomics analyses, we identified the downstream signaling events these drugs affect. Changes in plasma membrane depolarization and elevated intracellular Na(+), which compromised Na(+)-dependent nutrient transport, were documented. Deficits in nutrient deficit acted in turn to trigger the unfolded protein response and the amino acid response, leading ultimately to nutrient starvation and GIC cell death. Our results suggest new therapeutic targets to attack aggressive gliomas.

  • 43.
    Nordling, Torbjörn E. M.
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Stockholm Bioinformat Ctr, Sci Life Lab, S-17121 Solna, Sweden.;Natl Cheng Kung Univ, Dept Mech Engn, Tainan 70101, Taiwan.;Nordron AB, S-17065 Solna, Sweden..
    Padhan, Narendra
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Claesson-Welsh, Lena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Identification of Biomarkers and Signatures in Protein Data2015In: 2015 IEEE 11Th International Conference On E-Science, 2015, p. 411-419Conference paper (Refereed)
    Abstract [en]

    The correct diagnosis of cancer patients conventionally depends on the pathologist's experience and ability to distinguish cancer tissue from normal tissue under a microscope. Advances in technology for measuring the abundance of, e.g., proteins and mRNAs in tissue samples make it interesting to search for an optimal subset of these for classification of samples as cancer or normal. We discuss issues of identification of biomarkers that provide distinct signatures for prediction of tissues as cancer or normal, exemplified by our recent study of cancer signalling signatures in human colon cancer characterised with regards to protein abundance using high sensitivity isoelectric focusing. We show that the optimal subset for separation of cancer tissues from normal tissues does not contain any of the proteins in the top quintile in terms of significant difference between the groups according to Mann-Whitney U-test or correlation to the diagnosis. Actually, one of the proteins belongs to the tertile with the lowest significance and correlation. This highlights the weakness of the practice of only looking for significant differences in the abundance of individual proteins and raises the question of how many lifesaving discoveries that have been missed due to it. We also demonstrate how Monte Carlo simulations of the separation with random class assignment can be used to calculate p-values for observing any specific separation by chance and selection of the optimal number of proteins in the subset based on these p-values. Both selection of the optimal number of biomarkers and calculation of p-values corrected for multiple hypothesis testing are essential to obtain a subset of biomarkers that yield robust predictions for clinical use.

  • 44. Olsson, Maja
    et al.
    Kling, Teresia
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology.
    Meta-Analysis of Neural Childhood Cancer Networks2014In: Neuro-Oncology, ISSN 1522-8517, E-ISSN 1523-5866, Vol. 16, p. 140-140Article in journal (Other academic)
  • 45.
    Padhan, Narendra
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Nordling, Torbjorn E. M.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Stockholm Bioinformat Ctr, Sci Life Lab, Box 1031, S-17121 Solna, Sweden.;Natl Cheng Kung Univ, Dept Mech Engn, 1 Univ Rd, Tainan 70101, Taiwan..
    Sundström, Magnus
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Åkerud, Peter
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Colorectal Surgery.
    Birgisson, Helgi
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Colorectal Surgery.
    Nygren, Peter
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Experimental and Clinical Oncology.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Claesson-Welsh, Lena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    High sensitivity isoelectric focusing to establish a signaling biomarker for the diagnosis of human colorectal cancer2016In: BMC Cancer, E-ISSN 1471-2407, Vol. 16, article id 683Article in journal (Refereed)
    Abstract [en]

    Background: The progression of colorectal cancer (CRC) involves recurrent amplifications/mutations in the epidermal growth factor receptor (EGFR) and downstream signal transducers of the Ras pathway, KRAS and BRAF. Whether genetic events predicted to result in increased and constitutive signaling indeed lead to enhanced biological activity is often unclear and, due to technical challenges, unexplored. Here, we investigated proliferative signaling in CRC using a highly sensitive method for protein detection. The aim of the study was to determine whether multiple changes in proliferative signaling in CRC could be combined and exploited as a "complex biomarker" for diagnostic purposes. Methods: We used robotized capillary isoelectric focusing as well as conventional immunoblotting for the comprehensive analysis of epidermal growth factor receptor signaling pathways converging on extracellular regulated kinase 1/2 (ERK1/2), AKT, phospholipase C gamma 1 (PLC gamma 1) and c-SRC in normal mucosa compared with CRC stage II and IV. Computational analyses were used to test different activity patterns for the analyzed signal transducers. Results: Signaling pathways implicated in cell proliferation were differently dysregulated in CRC and, unexpectedly, several were downregulated in disease. Thus, levels of activated ERK1 (pERK1), but not pERK2, decreased in stage II and IV while total ERK1/2 expression remained unaffected. In addition, c-SRC expression was lower in CRC compared with normal tissues and phosphorylation on the activating residue Y418 was not detected. In contrast, PLC gamma 1 and AKT expression levels were elevated in disease. Immunoblotting of the different signal transducers, run in parallel to capillary isoelectric focusing, showed higher variability and lower sensitivity and resolution. Computational analyses showed that, while individual signaling changes lacked predictive power, using the combination of changes in three signaling components to create a "complex biomarker" allowed with very high accuracy, the correct diagnosis of tissues as either normal or cancerous. Conclusions: We present techniques that allow rapid and sensitive determination of cancer signaling that can be used to differentiate colorectal cancer from normal tissue.

    Download full text (pdf)
    fulltext
  • 46.
    Ramachandran, Mohanraj
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Clinical Immunology.
    Yu, Di
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Clinical Immunology.
    Dyczynski, Matheus
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Clinical Immunology. Uppsala University, Science for Life Laboratory, SciLifeLab. Karolinska Inst, Dept Pathol & Oncol, CCK, Stockholm, Sweden..
    Baskaran, Sathishkumar
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Zhang, Lei
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Lulla, Aleksei
    Institute of Technology, University of Tartu, Estonia..
    Lulla, Valeria
    Institute of Technology, University of Tartu, Estonia..
    Saul, Sirle
    Institute of Technology, University of Tartu, Estonia..
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Dimberg, Anna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Merits, Andres
    Institute of Technology, University of Tartu, Estonia..
    Leja-Jarblad, Justyna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Clinical Immunology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Essand, Magnus
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Clinical Immunology.
    Safe and effective treatment of experimental neuroblastoma and glioblastoma using systemically administered triple microRNA-detargeted oncolytic Semliki Forest virus2017In: Clinical Cancer Research, ISSN 1078-0432, E-ISSN 1557-3265, Vol. 23, no 6, p. 1519-1530Article in journal (Refereed)
    Abstract [en]

    PURPOSE:

    Glioblastoma multiforme (GBM) and high-risk neuroblastoma are cancers with poor outcome. Immunotherapy in the form of neurotropic oncolytic viruses is a promising therapeutic strategy for these malignancies. Here we evaluate the oncolytic potential of the neurovirulent and partly interferon (IFN)-β-resistant Semliki Forest virus (SFV)-4 in GBMs and neuroblastomas. To reduce neurovirulence we constructed SFV4miRT, which is attenuated in normal CNS cells through insertion of microRNA target sequences for miR124, miR125, miR134 Experimental Design:Oncolytic activity of SFV4miRT was examined in mouse neuroblastoma and GBM cell lines and in patient-derived human glioblastoma cell cultures (HGCC). In vivo neurovirulence and therapeutic efficacy was evaluated in two syngeneic orthotopic glioma models (CT-2A, GL261) and syngeneic subcutaneous neuroblastoma model (NXS2). The role of IFN-β in inhibiting therapeutic efficacy was investigated.

    RESULTS:

    The introduction of microRNA target sequences reduced neurovirulence of SFV4 in terms of attenuated replication in mouse CNS cells and ability to cause encephalitis when administered intravenously. A single intravenous injection of SFV4miRT prolonged survival and cured 4 of 8 mice (50%) with NXS2 and 3 of 11 mice (27%) with CT-2A, but not for GL261 tumor bearing mice. In vivo therapeutic efficacy in different tumor models inversely correlated to secretion of IFN-β by respective cells upon SFV4 infection in vitro Similarly, killing efficacy of HGCC lines inversely correlated to IFN-β response and interferon-α⁄β receptor (IFNAR)-1 expression.

    CONCLUSIONS:

    SFV4miRT has reduced neurovirulence, while retaining its oncolytic potential. SFV4miRT is an excellent candidate for treatment of GBMs and neuroblastomas with low IFN-β secretion.

  • 47.
    Rosén, Emil
    et al.
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Mangukiya, Hitesh
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Elfineh, Lioudmila
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Stockgard, Rebecka
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neurooncology and neurodegeneration. Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Krona, Cecilia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Gerlee, Philip
    Chalmers Univ Technol, Math Sci, Gothenburg, Sweden.;Univ Gothenburg, Math Sci, Gothenburg, Sweden..
    Nelander, Sven
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neurooncology and neurodegeneration. Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Inference of glioblastoma migration and proliferation rates using single time-point images2023In: Communications Biology, E-ISSN 2399-3642, Vol. 6, no 1, article id 402Article in journal (Refereed)
    Abstract [en]

    Cancer cell migration is a driving mechanism of invasion in solid malignant tumors. Anti-migratory treatments provide an alternative approach for managing disease progression. However, we currently lack scalable screening methods for identifying novel anti-migratory drugs. To this end, we develop a method that can estimate cell motility from single end-point images in vitro by estimating differences in the spatial distribution of cells and inferring proliferation and diffusion parameters using agent-based modeling and approximate Bayesian computation. To test the power of our method, we use it to investigate drug responses in a collection of 41 patient-derived glioblastoma cell cultures, identifying migration-associated pathways and drugs with potent anti-migratory effects. We validate our method and result in both in silico and in vitro using time-lapse imaging. Our proposed method applies to standard drug screen experiments, with no change needed, and emerges as a scalable approach to screen for anti-migratory drugs. The spatial positioning of cultured glioblastoma cells is used to estimate cell motility and drug effects from single end-point images in vitro.

    Download full text (pdf)
    FULLTEXT01
  • 48.
    Roy, Ananya
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Coum, Antoine
    Marinescu, Voichita D
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Põlajeva, Jelena
    Smits, Anja
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Neurology.
    Nelander, Sven
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Uhrbom, Lene
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Westermark, Bengt
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Forsberg-Nilsson, Karin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Pontén, Fredrik
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Tchougounova, Elena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology.
    Glioma-derived plasminogen activator inhibitor-1 (PAI-1) regulates the recruitment of LRP1 positive mast cells2015In: Oncotarget, E-ISSN 1949-2553, Vol. 6, no 27, p. 23647-23661Article in journal (Refereed)
    Abstract [en]

    Glioblastoma (GBM) is a high-grade glioma with a complex microenvironment, including various inflammatory cells and mast cells (MCs) as one of them. Previously we had identified glioma grade-dependent MC recruitment. In the present study we investigated the role of plasminogen activator inhibitor 1 (PAI-1) in MC recruitment.PAI-1, a primary regulator in the fibrinolytic cascade is capable of forming a complex with fibrinolytic system proteins together with low-density lipoprotein receptor-related protein 1 (LRP1). We found that neutralizing PAI-1 attenuated infiltration of MCs. To address the potential implication of LRP1 in this process, we used a LRP1 antagonist, receptor-associated protein (RAP), and demonstrated the attenuation of MC migration. Moreover, a positive correlation between the number of MCs and the level of PAI-1 in a large cohort of human glioma samples was observed. Our study demonstrated the expression of LRP1 in human MC line LAD2 and in MCs in human high-grade glioma. The activation of potential PAI-1/LRP1 axis with purified PAI-1 promoted increased phosphorylation of STAT3 and subsequently exocytosis in MCs.These findings indicate the influence of the PAI-1/LRP1 axis on the recruitment of MCs in glioma. The connection between high-grade glioma and MC infiltration could contribute to patient tailored therapy and improve patient stratification in future therapeutic trials.

    Download full text (pdf)
    fulltext
  • 49. Schmidt, Linnea
    et al.
    Kling, Teresia
    Monsefi, Naser
    Olsson, Maja
    Hansson, Caroline
    Baskaran, Sathishkumar
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology.
    Lundgren, Bo
    Martens, Ulf
    Haggblad, Maria
    Westermark, Bengt
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology.
    Nilsson, Karin Forsberg
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology.
    Uhrbom, Lene
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology.
    Karlsson-Lindahl, Linda
    Gerlee, Philip
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer and Vascular Biology.
    Comparative drug pair screening across multiple glioblastoma cell lines reveals novel drug-drug interactions2013In: Neuro-Oncology, ISSN 1522-8517, E-ISSN 1523-5866, Vol. 15, no 11, p. 1469-1478Article in journal (Refereed)
    Abstract [en]

    Glioblastoma multiforme (GBM) is the most aggressive brain tumor in adults, and despite state-of-the-art treatment, survival remains poor and novel therapeutics are sorely needed. The aim of the present study was to identify new synergistic drug pairs for GBM. In addition, we aimed to explore differences in drug-drug interactions across multiple GBM-derived cell cultures and predict such differences by use of transcriptional biomarkers. We performed a screen in which we quantified drug-drug interactions for 465 drug pairs in each of the 5 GBM cell lines U87MG, U343MG, U373MG, A172, and T98G. Selected interactions were further tested using isobole-based analysis and validated in 5 glioma-initiating cell cultures. Furthermore, drug interactions were predicted using microarray-based transcriptional profiling in combination with statistical modeling. Of the 5 465 drug pairs, we could define a subset of drug pairs with strong interaction in both standard cell lines and glioma-initiating cell cultures. In particular, a subset of pairs involving the pharmaceutical compounds rimcazole, sertraline, pterostilbene, and gefitinib showed a strong interaction in a majority of the cell cultures tested. Statistical modeling of microarray and interaction data using sparse canonical correlation analysis revealed several predictive biomarkers, which we propose could be of importance in regulating drug pair responses. We identify novel candidate drug pairs for GBM and suggest possibilities to prospectively use transcriptional biomarkers to predict drug interactions in individual cases.

  • 50.
    Schmidt, Linnéa
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Baskaran, Sathishkumar
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Johansson, Patrik
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Padhan, Narendra
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Matuszewski, Damian J.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Green, Lydia C.
    Elfineh, Ludmila
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Wee, Shimei
    Häggblad, Maria
    Martens, Ulf
    Westermark, Bengt
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Forsberg-Nilsson, Karin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Uhrbom, Lene
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Claesson-Welsh, Lena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Andäng, Michael
    Sintorn, Ida-Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Lundgren, Bo
    Lönnstedt, Ingrid
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Krona, Cecilia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Nelander, Sven
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Case-specific potentiation of glioblastoma drugs by pterostilbene2016In: Oncotarget, E-ISSN 1949-2553, Vol. 7, no 45, p. 73200-73215Article in journal (Refereed)
12 1 - 50 of 66
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf