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Berlin Brandenburg

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  • 1
    In: Journal of the National Cancer Institute, 2011, Vol. 103(15), pp.1141-1143
    Description: Glioblastoma is the most common primary brain tumor, comprising 52% of all primary brain tumors. Despite advances in treatment, glioblastoma remains virtually incurable, with a median survival of approximately 15 months. A chief cause of the high mortality of glioblastoma is the invasive nature of the tumor, which renders full resection of tumor cells practically impossible. Thus, understanding the mechanisms that underlie glioblastoma invasion is crucial for developing new treatment approaches for this devastating disease.
    Keywords: Brain Cancer ; Brain Damage ; Pathogenesis ; Proteins;
    ISSN: 0027-8874
    E-ISSN: 1460-2105
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  • 2
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 10 May 2016, Vol.113(19), pp.5394-9
    Description: We show that visualizing large molecular and clinical datasets enables discovery of molecularly defined categories of highly similar patients. We generated a series of linked 2D sample similarity plots using genome-wide single nucleotide alterations (SNAs), copy number alterations (CNAs), DNA methylation, and RNA expression data. Applying this approach to the combined glioblastoma (GBM) and lower grade glioma (LGG) The Cancer Genome Atlas datasets, we find that combined CNA/SNA data divide gliomas into three highly distinct molecular groups. The mutations commonly used in clinical evaluation of these tumors are regionally distributed in these plots. One of the three groups is a mixture of GBM and LGG that shows similar methylation and survival characteristics to GBM. Altogether, our approach identifies eight molecularly defined glioma groups with distinct sequence/expression/methylation profiles. Importantly, we show that regionally clustered samples are enriched for specific drug targets.
    Keywords: Big Data ; Biomarkers ; Glioma ; Precision Medicine ; Visualization ; Databases, Genetic ; Datasets As Topic ; User-Computer Interface ; Data Mining -- Methods ; High-Throughput Nucleotide Sequencing -- Methods ; Neoplasm Proteins -- Genetics
    ISSN: 00278424
    E-ISSN: 1091-6490
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  • 3
    In: Brain, 2017, Vol. 140(3), pp.e17-e17
    Keywords: Medicine;
    ISSN: 0006-8950
    E-ISSN: 1460-2156
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  • 4
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 08 April 2014, Vol.111(14), pp.5248-53
    Description: Glioblastoma is the most common adult primary brain tumor and has a dismal median survival. Radiation is a mainstay of treatment and significantly improves survival, yet recurrence is nearly inevitable. Better understanding the radiation response of glioblastoma will help improve strategies to treat this devastating disease. Here, we present a comprehensive study of the in vivo radiation response of glioma cells in a mouse model of proneural glioblastoma. These tumors are a heterogeneous mix of cell types with differing radiation sensitivities. To explicitly study the gene expression changes comprising the radiation response of the Olig2(+) tumor bulk cells, we used translating ribosome affinity purification (TRAP) from Olig2-TRAP transgenic mice. Comparing both ribosome-associated and total pools of mRNA isolated from Olig2(+) cells indicated that the in vivo gene expression response to radiation occurs primarily at the total transcript level. Genes related to apoptosis and cell growth were significantly altered. p53 and E2F were implicated as major regulators of the radiation response, with p53 activity needed for the largest gene expression changes after radiation. Additionally, radiation induced a marked shift away from a proneural expression pattern toward a mesenchymal one. This shift occurs in Olig2(+) cells within hours and in multiple genetic backgrounds. Targets for Stat3 and CEBPB, which have been suggested to be master regulators of a mesenchymal shift, were also up-regulated by radiation. These data provide a systematic description of the events following radiation and may be of use in identifying biological processes that promote glioma radioresistance.
    Keywords: Transcription, Genetic ; Brain Neoplasms -- Pathology ; Glioblastoma -- Pathology ; Mesoderm -- Metabolism ; Neurons -- Metabolism ; Radiation Tolerance -- Genetics ; Tumor Suppressor Protein P53 -- Physiology
    ISSN: 00278424
    E-ISSN: 1091-6490
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  • 5
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 21 February 2012, Vol.109(8), pp.3041-6
    Description: Glioblastoma (GBM) is distinguished by a high degree of intratumoral heterogeneity, which extends to the pattern of expression and amplification of receptor tyrosine kinases (RTKs). Although most GBMs harbor RTK amplifications, clinical trials of small-molecule inhibitors targeting individual RTKs have been disappointing to date. Activation of multiple RTKs within individual GBMs provides a theoretical mechanism of resistance; however, the spectrum of functional RTK dependence among tumor cell subpopulations in actual tumors is unknown. We investigated the pattern of heterogeneity of RTK amplification and functional RTK dependence in GBM tumor cell subpopulations. Analysis of The Cancer Genome Atlas GBM dataset identified 34 of 463 cases showing independent focal amplification of two or more RTKs, most commonly platelet-derived growth factor receptor α (PDGFRA) and epidermal growth factor receptor (EGFR). Dual-color fluorescence in situ hybridization was performed on eight samples with EGFR and PDGFRA amplification, revealing distinct tumor cell subpopulations amplified for only one RTK; in all cases these predominated over cells amplified for both. Cell lines derived from coamplified tumors exhibited genotype selection under RTK-targeted ligand stimulation or pharmacologic inhibition in vitro. Simultaneous inhibition of both EGFR and PDGFR was necessary for abrogation of PI3 kinase pathway activity in the mixed population. DNA sequencing of isolated subpopulations establishes a common clonal origin consistent with late or ongoing divergence of RTK genotype. This phenomenon is especially common among tumors with PDGFRA amplification: overall, 43% of PDGFRA-amplified GBM were found to have amplification of EGFR or the hepatocyte growth factor receptor gene (MET) as well.
    Keywords: Gene Amplification ; Genetic Heterogeneity ; Erbb Receptors -- Genetics ; Glioblastoma -- Enzymology ; Intercellular Signaling Peptides and Proteins -- Metabolism ; Receptor, Platelet-Derived Growth Factor Alpha -- Genetics
    ISSN: 00278424
    E-ISSN: 1091-6490
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  • 6
    Language: English
    In: PLoS ONE, 2011, Vol.6(9), p.e24454
    Description: Primary glioblastomas are subdivided into several molecular subtypes. There is an ongoing debate over the cell of origin for these tumor types where some suggest a progenitor while others argue for a stem cell origin. Even within the same molecular subgroup, and using lineage tracing in mouse models, different groups have reached different conclusions. We addressed this problem from a combined mathematical modeling and experimental standpoint. We designed a novel mathematical framework to identify the most likely cells of origin of two glioma subtypes. Our mathematical model of the unperturbed in vivo system predicts that if a genetic event contributing to tumor initiation imparts symmetric self-renewing cell division (such as PDGF overexpression), then the cell of origin is a transit amplifier. Otherwise, the initiating mutations arise in stem cells. The mathematical framework was validated with the RCAS/tv-a system of somatic gene transfer in mice. We demonstrated that PDGF-induced gliomas can be derived from GFAP-expressing cells of the subventricular zone or the cortex (reactive astrocytes), thus validating the predictions of our mathematical model. This interdisciplinary approach allowed us to determine the likelihood that individual cell types serve as the cells of origin of gliomas in an unperturbed system.
    Keywords: Research Article ; Computer Science ; Mathematics ; Medicine ; Oncology ; Computer Science ; Mathematics
    E-ISSN: 1932-6203
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  • 7
    Language: English
    In: Leder, Kevin, Eric C. Holland, and Franziska Michor. 2010. The Therapeutic Implications of Plasticity of the Cancer Stem Cell Phenotype. PLoS ONE 5(12): e14366.
    Description: The cancer stem cell hypothesis suggests that tumors contain a small population of cancer cells that have the ability to undergo symmetric self-renewing cell division. In tumors that follow this model, cancer stem cells produce various kinds of specified precursors that divide a limited number of times before terminally differentiating or undergoing apoptosis. As cells within the tumor mature, they become progressively more restricted in the cell types to which they can give rise. However, in some tumor types, the presence of certain extra- or intracellular signals can induce committed cancer progenitors to revert to a multipotential cancer stem cell state. In this paper, we design a novel mathematical model to investigate the dynamics of tumor progression in such situations, and study the implications of a reversible cancer stem cell phenotype for therapeutic interventions. We find that higher levels of dedifferentiation substantially reduce the effectiveness of therapy directed at cancer stem cells by leading to higher rates of resistance. We conclude that plasticity of the cancer stem cell phenotype is an important determinant of the prognosis of tumors. This model represents the first mathematical investigation of this tumor trait and contributes to a quantitative understanding of cancer.
    Keywords: Cell Biology ; Oncology ; Computational Biology/Evolutionary Modeling ; Computational Biology/Systems Biology
    ISSN: 1932-6203
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  • 8
    In: EMBO Journal, 17 September 2014, Vol.33(18), pp.1984-1986
    Description: Heterogeneity within tumors is becoming increasingly recognized as an important cause of treatment failure in cancer. Two recent studies use fate‐mapping and limiting dilution transplantation assays to identify (sex determining region Y)‐box 2 (Sox2) as cancer stem‐cell marker and driver of cancer stemness. The identification of Sox2 as cancer stem‐cell marker and driver of cancer stemness in distinct tumor types suggests that each tumor resembles the hierarchical organization of the tissue from which it arises.
    Keywords: Biology ; Chemistry;
    ISSN: 0261-4189
    E-ISSN: 1460-2075
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  • 9
    Language: English
    In: PLoS ONE, 2012, Vol.7(2), p.e32453
    Description: The tumor microenvironment contains normal, non-neoplastic cells that may contribute to tumor growth and maintenance. Within PDGF-driven murine gliomas, tumor-associated astrocytes (TAAs) are a large component of the tumor microenvironment. The function of non-neoplastic astrocytes in the glioma microenvironment has not been fully elucidated; moreover, the differences between these astrocytes and normal astrocytes are unknown. We therefore sought to identify genes and pathways that are increased in TAAs relative to normal astrocytes and also to determine whether expression of these genes correlates with glioma behavior. ; We compared the gene expression profiles of TAAs to normal astrocytes and found the Antigen Presentation Pathway to be significantly increased in TAAs. We then identified a gene signature for glioblastoma (GBM) TAAs and validated the expression of some of those genes within the tumor. We also show that TAAs are derived from the non-tumor, stromal environment, in contrast to the Olig2+ tumor cells that constitute the neoplastic elements in our model. Finally, we validate this GBM TAA signature in patients and show that a TAA-derived gene signature predicts survival specifically in the human proneural subtype of glioma. ; Our data identifies unique gene expression patterns between populations of TAAs and suggests potential roles for stromal astrocytes within the glioma microenvironment. We show that certain stromal astrocytes in the tumor microenvironment express a GBM-specific gene signature and that the majority of these stromal astrocyte genes can predict survival in the human disease.
    Keywords: Research Article ; Biology ; Medicine ; Oncology ; Neuroscience ; Developmental Biology
    E-ISSN: 1932-6203
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  • 10
    Language: English
    In: PLoS ONE, 2012, Vol.7(3), p.e33844
    Description: Glioblastoma (GBM) and other malignant gliomas are aggressive primary neoplasms of the brain that exhibit notable refractivity to standard treatment regimens. Recent large-scale molecular profiling has revealed distinct disease subclasses within malignant gliomas whose defining genomic features highlight dysregulated molecular networks as potential targets for therapeutic development. The “proneural” designation represents the largest and most heterogeneous of these subclasses, and includes both a large fraction of GBMs along with most of their lower-grade astrocytic and oligodendroglial counterparts. The pathogenesis of proneural gliomas has been repeatedly associated with dysregulated PDGF signaling. Nevertheless, genomic amplification or activating mutations involving the PDGF receptor (PDGFRA) characterize only a subset of proneural GBMs, while the mechanisms driving dysregulated PDGF signaling and downstream oncogenic networks in remaining tumors are unclear. MicroRNAs (miRNAs) are a class of small, noncoding RNAs that regulate gene expression by binding loosely complimentary sequences in target mRNAs. The role of miRNA biology in numerous cancer variants is well established. In an analysis of miRNA involvement in the phenotypic expression and regulation of oncogenic PDGF signaling, we found that miR-34a is downregulated by PDGF pathway activation in vitro . Similarly, analysis of data from the Cancer Genome Atlas (TCGA) revealed that miR-34a expression is significantly lower in proneural gliomas compared to other tumor subtypes. Using primary GBM cells maintained under neurosphere conditions, we then demonstrated that miR-34a specifically affects growth of proneural glioma cells in vitro and in vivo . Further bioinformatic analysis identified PDGFRA as a direct target of miR-34a and this interaction was experimentally validated. Finally, we found that PDGF-driven miR-34a repression is unlikely to operate solely through a p53-dependent mechanism. Taken together, our data support the existence of reciprocal negative feedback regulation involving miR-34 and PDGFRA expression in proneural gliomas and, as such, identify a subtype specific therapeutic potential for miR-34a.
    Keywords: Research Article ; Biology ; Medicine ; Genetics And Genomics ; Computational Biology ; Oncology
    E-ISSN: 1932-6203
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