Publications

8 Publications matching the given criteria: (Clear all filters)
Programme: Glioma8

Abstract (Expand)

Molecular mechanisms of lower grade (II- III) diffuse gliomas (LGG) are still poorly understood, mainly because of their heterogeneity. They split into astrocytoma- (IDH-A) and oligodendro-glioma-like (IDH-O) tumors both carrying mutations(s) at the Isocitrate dehydrogenase (IDH) gene and into IDH wild type (IDH-wt) gliomas of glioblastoma-resemblance. We generated de-tailed maps of the transcriptomes and DNA-methylomes revealing that cell functions divide into three major archeotypic hallmarks: (i) increased proliferation in IDH-wt and, to a less degree, IDH-O, (ii) increased inflammation in IDH-A and IDH-wt, and (iii) the loss of synaptic transmis-sion in all subtypes. Immunogenic properties of IDH-A are diverse partly resembling signatures observed in grade IV mesenchymal glioblastomas or in grade I pilocytic astrocytomas. We ana-lyzed details of coregulation between gene expression and DNA-methylation and of the immu-nogenic micro-environment presumably driving tumor development and treatment resistance. Our transcriptome and methylome maps support personalized, case-by-case views to decipher the heterogeneity of glioma states in terms of data portraits. Thereby molecular cartography provides a graphical coordinate system, which links gene-level information with glioma sub-types, their phenotypes and clinical context.

Authors: Hans Binder, Maria Schmidt, Lydia Hopp, Arsen Arakelyan, Henry Löffler-Wirth

Date Published: No date defined

Publication Type: Journal article

Human Diseases: brain glioma

Abstract (Expand)

BACKGROUND: Diffuse lower WHO grade II and III gliomas (LGG) are slowly progressing brain tumors, many of which eventually transform into a more aggressive type. LGG is characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the heterogeneity of the DNA methylome, its function in tumor biology, coupling with the transcriptome and tumor microenvironment and its possible impact for tumor development. METHODS: We here present novel DNA methylation data of an LGG-cohort collected in the German Glioma Network containing about 85% isocitrate dehydrogenase (IDH) mutated tumors and performed a combined bioinformatics analysis using patient-matched genome and transcriptome data. RESULTS: Stratification of LGG based on gene expression and DNA-methylation provided four consensus subtypes. We characterized them in terms of genetic alterations, functional context, cellular composition, tumor microenvironment and their possible impact for treatment resistance and prognosis. Glioma with astrocytoma-resembling phenotypes constitute the largest fraction of nearly 60%. They revealed largest diversity and were divided into four expression and three methylation groups which only partly match each other thus reflecting largely decoupled expression and methylation patterns. We identified a novel G-protein coupled receptor and a cancer-related 'keratinization' methylation signature in in addition to the glioma-CpG island methylator phenotype (G-CIMP) signature. These different signatures overlap and combine in various ways giving rise to diverse methylation and expression patterns that shape the glioma phenotypes. The decrease of global methylation in astrocytoma-like LGG associates with higher WHO grade, age at diagnosis and inferior prognosis. We found analogies between astrocytoma-like LGG with grade IV IDH-wild type tumors regarding possible worsening of treatment resistance along a proneural-to-mesenchymal axis. Using gene signature-based inference we elucidated the impact of cellular composition of the tumors including immune cell bystanders such as macrophages. CONCLUSIONS: Genomic, epigenomic and transcriptomic factors act in concert but partly also in a decoupled fashion what underpins the need for integrative, multidimensional stratification of LGG by combining these data on gene and cellular levels to delineate mechanisms of gene (de-)regulation and to enable better patient stratification and individualization of treatment.

Authors: H. Binder, E. Willscher, H. Loeffler-Wirth, L. Hopp, D. T. W. Jones, S. M. Pfister, M. Kreuz, D. Gramatzki, E. Fortenbacher, B. Hentschel, M. Tatagiba, U. Herrlinger, H. Vatter, J. Matschke, M. Westphal, D. Krex, G. Schackert, J. C. Tonn, U. Schlegel, H. J. Steiger, W. Wick, R. G. Weber, M. Weller, M. Loeffler

Date Published: 25th Apr 2019

Publication Type: Not specified

Human Diseases: brain glioma

Abstract (Expand)

AIM: We present here a novel method that enables unraveling the interplay between gene expression and DNA methylation in complex diseases such as cancer. MATERIALS & METHODS: The method is based on self-organizing maps and allows for analysis of data landscapes from 'governed by methylation' to 'governed by expression'. RESULTS: We identified regulatory modules of coexpressed and comethylated genes in high-grade gliomas: two modes are governed by genes hypermethylated and underexpressed in IDH-mutated cases, while two other modes reflect immune and stromal signatures in the classical and mesenchymal subtypes. A fifth mode with proneural characteristics comprises genes of repressed and poised chromatin states active in healthy brain. Two additional modes enrich genes either in active or repressed chromatin states. CONCLUSION: The method disentangles the interplay between gene expression and methylation. It has the potential to integrate also mutation and copy number data and to apply to large sample cohorts.

Authors: L. Hopp, H. Loffler-Wirth, J. Galle, H. Binder

Date Published: 12th Jun 2018

Publication Type: Not specified

Human Diseases: glioblastoma multiforme

Abstract (Expand)

BACKGROUND: The vascular endothelial growth factor (VEGF) and transforming growth factor (TGF)-beta pathways regulate key biological features of glioblastoma. Here we explore whether the TGF-beta pathway, which promotes angiogenesis, invasiveness, and immunosuppression, acts as an escape pathway from VEGF inhibition. METHODS: The role of the TGF-beta pathway in escape from VEGF inhibition was assessed in vitro and in vivo and by gene expression profiling in syngeneic mouse glioma models. RESULTS: We found that TGF-beta is an upstream regulator of VEGF, whereas VEGF pathway activity does not alter the TGF-beta pathway in vitro. In vivo, single-agent activity was observed for the VEGF antibody B20-4.1.1 in 3 and for the TGF-beta receptor 1 antagonist LY2157299 in 2 of 4 models. Reduction of tumor volume and blood vessel density, but not induction of hypoxia, correlated with benefit from B20-4.1.1. Reduction of phosphorylated (p)SMAD2 by LY2157299 was seen in all models but did not predict survival. Resistance to B20 was associated with anti-angiogenesis escape pathway gene expression, whereas resistance to LY2157299 was associated with different immune response gene signatures in SMA-497 and GL-261 on transcriptomic profiling. The combination of B20 with LY2157299 was ineffective in SMA-497 but provided prolongation of survival in GL-261, associated with early suppression of pSMAD2 in tumor and host immune cells, prolonged suppression of angiogenesis, and delayed accumulation of tumor infiltrating microglia/macrophages. CONCLUSIONS: Our study highlights the biological heterogeneity of murine glioma models and illustrates that cotargeting of the VEGF and TGF-beta pathways might lead to improved tumor control only in subsets of glioblastoma.

Authors: D. Mangani, M. Weller, E. Seyed Sadr, E. Willscher, K. Seystahl, G. Reifenberger, G. Tabatabai, H. Binder, H. Schneider

Date Published: 12th Jun 2016

Publication Type: Not specified

Human Diseases: glioblastoma multiforme

Abstract (Expand)

Cerebral gliomas of World Health Organization (WHO) grade II and III represent a major challenge in terms of histological classification and clinical management. Here, we asked whether large-scale genomic and transcriptomic profiling improves the definition of prognostically distinct entities. We performed microarray-based genome- and transcriptome-wide analyses of primary tumor samples from a prospective German Glioma Network cohort of 137 patients with cerebral gliomas, including 61 WHO grade II and 76 WHO grade III tumors. Integrative bioinformatic analyses were employed to define molecular subgroups, which were then related to histology, molecular biomarkers, including isocitrate dehydrogenase 1 or 2 (IDH1/2) mutation, 1p/19q co-deletion and telomerase reverse transcriptase (TERT) promoter mutations, and patient outcome. Genomic profiling identified five distinct glioma groups, including three IDH1/2 mutant and two IDH1/2 wild-type groups. Expression profiling revealed evidence for eight transcriptionally different groups (five IDH1/2 mutant, three IDH1/2 wild type), which were only partially linked to the genomic groups. Correlation of DNA-based molecular stratification with clinical outcome allowed to define three major prognostic groups with characteristic genomic aberrations. The best prognosis was found in patients with IDH1/2 mutant and 1p/19q co-deleted tumors. Patients with IDH1/2 wild-type gliomas and glioblastoma-like genomic alterations, including gain on chromosome arm 7q (+7q), loss on chromosome arm 10q (-10q), TERT promoter mutation and oncogene amplification, displayed the worst outcome. Intermediate survival was seen in patients with IDH1/2 mutant, but 1p/19q intact, mostly astrocytic gliomas, and in patients with IDH1/2 wild-type gliomas lacking the +7q/-10q genotype and TERT promoter mutation. This molecular subgrouping stratified patients into prognostically distinct groups better than histological classification. Addition of gene expression data to this genomic classifier did not further improve prognostic stratification. In summary, DNA-based molecular profiling of WHO grade II and III gliomas distinguishes biologically distinct tumor groups and provides prognostically relevant information beyond histological classification as well as IDH1/2 mutation and 1p/19q co-deletion status.

Authors: M. Weller, R. G. Weber, E. Willscher, V. Riehmer, B. Hentschel, M. Kreuz, J. Felsberg, U. Beyer, H. Loffler-Wirth, K. Kaulich, J. P. Steinbach, C. Hartmann, D. Gramatzki, J. Schramm, M. Westphal, G. Schackert, M. Simon, T. Martens, J. Bostrom, C. Hagel, M. Sabel, D. Krex, J. C. Tonn, W. Wick, S. Noell, U. Schlegel, B. Radlwimmer, T. Pietsch, M. Loeffler, A. von Deimling, H. Binder, G. Reifenberger

Date Published: 19th Mar 2015

Publication Type: Not specified

Human Diseases: brain glioma

Abstract (Expand)

Glioma is a clinically and biologically diverse disease. It challenges diagnosis and prognosis due to its molecular heterogeneity and diverse regimes of biological dysfunctions which are driven by genetic and epigenetic mechanisms. We discover the functional impact of sets of DNA methylation marker genes in the context of brain cancer subtypes as an exemplary approach how bioinformatics and particularly machine learning using self organizing maps (SOM) complements modern high-throughput genomic technologies. DNA methylation changes in gliomas comprise both, hyper- and hypomethylation in a subtype specific fashion. We compared pediatric (2 subtypes) and adult (4) glioblastoma and non-neoplastic brain. The functional impact of differential methylation marker sets is discovered in terms of gene set analysis which comprises a large collection of markers related to biological processes, literature data on gliomas and also chromatin states of the healthy brain. DNA methylation signature genes from alternative studies well agree with our signatures. SOM mapping of gene sets robustly identifies similarities between different marker sets even under conditions of noisy compositions. Mapping of previous sets of glioma markers reveals high redundancy and mixtures of subtypes in the reference cohorts. Consideration of the regulatory level of DNA methylation is inevitable for understanding cancer genesis and progression. It provides suited markers for diagnosis of glioma subtypes and disentangles tumor heterogeneity.

Authors: E. Willscher, H. Loffler-Wirth, H. Binder, Lydia Hopp

Date Published: 2015

Publication Type: Not specified

Human Diseases: brain glioma

Abstract (Expand)

The prognosis of glioblastoma, the most malignant type of glioma, is still poor, with only a minority of patients showing long-term survival of more than three years after diagnosis. To elucidate the molecular aberrations in glioblastomas of long-term survivors, we performed genome- and/or transcriptome-wide molecular profiling of glioblastoma samples from 94 patients, including 28 long-term survivors with >36 months overall survival (OS), 20 short-term survivors with <12 months OS and 46 patients with intermediate OS. Integrative bioinformatic analyses were used to characterize molecular aberrations in the distinct survival groups considering established molecular markers such as isocitrate dehydrogenase 1 or 2 (IDH1/2) mutations, and O(6) -methylguanine DNA methyltransferase (MGMT) promoter methylation. Patients with long-term survival were younger and more often had IDH1/2-mutant and MGMT-methylated tumors. Gene expression profiling revealed over-representation of a distinct (proneural-like) expression signature in long-term survivors that was linked to IDH1/2 mutation. However, IDH1/2-wildtype glioblastomas from long-term survivors did not show distinct gene expression profiles and included proneural, classical and mesenchymal glioblastoma subtypes. Genomic imbalances also differed between IDH1/2-mutant and IDH1/2-wildtype tumors, but not between survival groups of IDH1/2-wildtype patients. Thus, our data support an important role for MGMT promoter methylation and IDH1/2 mutation in glioblastoma long-term survival and corroborate the association of IDH1/2 mutation with distinct genomic and transcriptional profiles. Importantly, however, IDH1/2-wildtype glioblastomas in our cohort of long-term survivors lacked distinctive DNA copy number changes and gene expression signatures, indicating that other factors might have been responsible for long survival in this particular subgroup of patients.

Authors: G. Reifenberger, R. G. Weber, V. Riehmer, K. Kaulich, E. Willscher, H. Wirth, J. Gietzelt, B. Hentschel, M. Westphal, M. Simon, G. Schackert, J. Schramm, J. Matschke, M. C. Sabel, D. Gramatzki, J. Felsberg, C. Hartmann, J. P. Steinbach, U. Schlegel, W. Wick, B. Radlwimmer, T. Pietsch, J. C. Tonn, A. von Deimling, H. Binder, M. Weller, M. Loeffler

Date Published: 15th Oct 2014

Publication Type: Not specified

Human Diseases: brain glioma

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