Function Shapes Content: DNA-Methylation Marker Genes and their Impact for Molecular Mechanisms of Glioma


  • Lydia Hopp Interdisciplinary Centre for Bioinformatics, Universität Leipzig, Härtelstr, 16–18, 04107 Leipzig, Germany
  • Edith Willscher Interdisciplinary Centre for Bioinformatics, Universität Leipzig, Härtelstr, 16–18, 04107 Leipzig, Germany
  • Henry Löffler-Wirth Interdisciplinary Centre for Bioinformatics, Universität Leipzig, Härtelstr, 16–18, 04107 Leipzig, Germany
  • Hans Binder Interdisciplinary Centre for Bioinformatics, Universität Leipzig, Härtelstr, 16–18, 04107 Leipzig, Germany



Glioma, molecular subtypes, DNA methylation, gene regulation, bioinformatics.


 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.


Chibon F. Cancer gene expression signatures – The rise and fall? European Journal of Cancer 2013; 49: 2000-2009.

Quackenbush J. Microarrays--Guilt by Association. Science 2003; 302: 240-241.

Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Lander ES. Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring. Science 1999; 286: 531-537.

Kulis M, Esteller M. 2 - DNA Methylation and Cancer. In Advances in Genetics; Zdenko, H, Toshikazu, U, Eds, Academic Press 2010; Vol. 70: pp. 27-56.

Sturm D, Witt H, Hovestadt V, Khuong-Quang D-A, Jones David TW, Konermann C, Pfister Stefan M. Hotspot Mutations in H3F3A and IDH1 Define Distinct Epigenetic and Biological Subgroups of Glioblastoma. Cancer Cell 2012; 22: 425-437.

Martinez R, Martin-Subero JI, Rohde V, Kirsch M, Alaminos M, Fernández AF, Esteller M. A microarray-based DNA methylation study of glioblastoma multiforme. Epigenetics 2009; 4: 255-264.

Martin-Subero JI, Ammerpohl O, Bibikova M, Wickham-Garcia E, Agirre X, Alvarez S, Siebert R. A Comprehensive Microarray-Based DNA Methylation Study of 367 Hematological Neoplasms. PLOS One 2009; 4: e6986.

Noushmehr H, Weisenberger DJ, Diefes K, Phillips HS, Pujara K, Berman BP, Aldape K. Identification of a CpG Island Methylator Phenotype that Defines a Distinct Subgroup of Glioma. Cancer Cell 2010; 17: 510-522.

Toyota M, Ahuja N, Ohe-Toyota M, Herman JG, Baylin SB, Issa J-PJ. CpG island methylator phenotype in colorectal cancer. Proc Natl Acad Sci USA 1999; 96: 8681-8686.

Figueroa ME, Lugthart S, Li Y, Erpelinck-Verschueren C, Deng X, Christos PJ, Melnick A. DNA Methylation Signatures Identify Biologically Distinct Subtypes in Acute Myeloid Leukemia. Cancer Cell 2010; 17: 13-27.

Brennan, Cameron W, Verhaak Roel GW, McKenna A, Campos B, Noushmehr H, Salama Sofie R, McLendon R. The Somatic Genomic Landscape of Glioblastoma. Cell 155: 462-477.

Colman H, Zhang L, Sulman EP, McDonald JM, Shooshtari NL, Rivera A, Aldape K. A multigene predictor of outcome in glioblastoma. Neuro-Oncology 2010; 12: 49-57.

Laffaire J, Everhard S, Idbaih A, Crinière E, Marie Y, de Reyniès A, Ducray F. Methylation profiling identifies 2 groups of gliomas according to their tumorigenesis. Neuro-Oncology 2011; 13: 84-98.

Kim Y-W, Koul D, Kim SH, Lucio-Eterovic AK, Freire PR, Yao J, Yung WKA. Identification of prognostic gene signatures of glioblastoma: a study based on TCGA data analysis. Neuro-Oncology 2013; 15: 829-839.

Nutt CL, Mani DR, Betensky RA, Tamayo P, Cairncross JG, Ladd C, Louis DN. Gene Expression-based Classification of Malignant Gliomas Correlates Better with Survival than Histological Classification. Cancer Research 2003; 63: 1602-1607.

Phillips HS, Kharbanda S, Chen R, Forrest WF, Soriano RH, Wu TD, Aldape K. Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer Cell 2006; 9: 157-173.

Dang L, Jin S, Su SM. IDH mutations in glioma and acute myeloid leukemia. Trends in Molecular Medicine 2010; 16: 387-397.

Christensen BC, Smith AA, Zheng S, Koestler DC, Houseman EA, Marsit CJ, Wiencke JK. DNA Methylation, Isocitrate Dehydrogenase Mutation, and Survival in Glioma. Journal of the National Cancer Institute 2011; 103: 143-153.

Gorovets D, Kannan K, Shen R, Kastenhuber ER, Islamdoust N, Campos C, Huse JT. IDH Mutation and Neuroglial Developmental Features Define Clinically Distinct Subclasses of Lower Grade Diffuse Astrocytic Glioma. Clinical Cancer Research 2012; 18: 2490-2501.

Reifenberger G, Weber RG, Riehmer V, Kaulich K, Willscher E, Wirth H, Glioma N. Molecular characterization of long-term survivors of glioblastoma using genome- and transcriptome-wide profiling. International Journal of Cancer 2014; 135: 1822-1831.

Weller M, Weber R, Willscher E, Riehmer V, Hentschel B, Kreuz M, Reifenberger G. Molecular classification of diffuse cerebral WHO grade II/III gliomas using genome- and transcriptome-wide profiling improves stratification of prognostically distinct patient groups. Acta Neuropathologica 2015; 1-15.

Brulard C, Chibon F. Robust gene expression signature is not merely a significant P value. European Journal of Cancer 2013; 49: 2771-2773.

Venet D, Dumont JE, Detours V. Most Random Gene Expression Signatures Are Significantly Associated with Breast Cancer Outcome. PLoS Comput Biol 2011; 7: e1002240.

Wirth H, Loeffler M, von Bergen M, Binder H. Expression cartography of human tissues using self organizing maps. BMC Bioinformatics 2011; 12: 306.

Hopp L, Lembcke K, Binder H, Wirth H. Portraying the Expression Landscapes of B-Cell Lymphoma- Intuitive Detection of Outlier Samples and of Molecular Subtypes. Biology 2013; 2: 1411-1437.

Hopp L, Wirth H, Fasold M, Binder H. Portraying the expression landscapes of cancer subtypes: A glioblastoma multiforme and prostate cancer case study. Systems Biomedicine 2013; 1.

Wirth H, von Bergen M, Binder H. Mining SOM expression portraits: Feature selection and integrating concepts of molecular function. BioData Mining 2012; 5: 18.

Du P, Zhang X, Huang C-C, Jafari N, Kibbe WA, Hou L, Lin SM. Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics 2010; 11: 587-587.

Hopp L, Wirth-Loeffler H, Binder H. Epigenetic heterogeneity of B-cell lymphoma: DNA-methylation, gene expression and chromatin states. Genes 2015; in press.

Sturm D, Bender S, Jones DTW, Lichter P, Grill J, Becher O, Pfister SM. Paediatric and adult glioblastoma: multiform (epi)genomic culprits emerge. Nat Rev Cancer 2014; 14: 92-107.

Verhaak RGW, Hoadley KA, Purdom E, Wang V, Qi Y, Wilkerson MD, Hayes DN. Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell 2010; 17: 98-110.

Binder H, Hopp L, Lembcke K, Wirth H. Personalized Disease Phenotypes from Massive OMICs Data. In Big Data Analytics in Bioinformatics and Healthcare; Baoying, W, Ruowang, L, William, P, Eds, IGI Global: Hershey, PA, USA, 2015; pp. 359-378.

Wirth-Loeffler H, Kalcher M, Binder H. oposSOM: R-package for high-dimensional portraying of genome-wide expression landscapes on Bioconductor. Bioinformatics 2015; in revision.

Binder H, Wirth H, Arakelyan A, Lembcke K, Tiys ES, Ivanishenko V, Larina IM. Time-course human urine proteomics in space-flight simulation experiments. BMC Genomics 2014; 15: S2.

Toronen P, Ojala P, Marttinen P, Holm L. Robust extraction of functional signals from gene set analysis using a generalized threshold free scoring function. BMC Bioinformatics 2009; 10: 307.

Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Mesirov JP. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 2005; 102: 15545-15550.

Ernst J, Kellis M. Discovery and characterization of chromatin states for systematic annotation of the human genome. Nat Biotech 2010; 28: 817-825.

Ernst J, Kheradpour P, Mikkelsen TS, Shoresh N, Ward LD, Epstein CB, Bernstein BE. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 2011; 473: 43-49.

Läuter J, Glimm E, Eszlinger M. Search for relevant sets of variables in a high-dimensional setup keeping the familywise error rate. Statistica Neerlandica 2005; 59: 298-312.

Walker E, Manias JL, Chang WY, Stanford WL. PCL2 modulates gene regulatory networks controlling self-renewal and commitment in embryonic stem cells. Cell Cycle 2011; 10: 45-51.

Mikkelsen TS, Ku M, Jaffe DB, Issac B, Lieberman E, Giannoukos G, Bernstein BE. Genome-wide maps of chromatin state in pluripotent and lineage-committed cells. Nature 2007; 448: 553-560.

Meissner A, Mikkelsen TS, Gu H, Wernig M, Hanna J, Sivachenko A, Lander ES. Genome-scale DNA methylation maps of pluripotent and differentiated cells. Nature 2008; 454: 766-770.

Ben-Porath I, Thomson MW, Carey VJ, Ge R, Bell GW, Regev A, Weinberg RA. An embryonic stem cell-like gene expression signature in poorly differentiated aggressive human tumors. Nat Genet 2008; 40: 499-507.

Meissner A. Epigenetic modifications in pluripotent and differentiated cells. Nat Biotech 2010; 28: 1079-1088.

Lee TI, Jenner RG, Boyer LA, Guenther MG, Levine SS, Kumar RM, Young RA. Control of Developmental Regulators by Polycomb in Human Embryonic Stem Cells. Cell 2006; 125: 301-313.

Kim YH, Girard L, Giacomini CP, Wang P, Hernandez-Boussard T, Tibshirani R, Pollack JR. Combined microarray analysis of small cell lung cancer reveals altered apoptotic balance and distinct expression signatures of MYC family gene amplification. Oncogene 2005; 25: 130-138.

Shinawi T, Hill VK, Krex D, Schackert G, Gentle D, Morris MR, Latif F. DNA methylation profiles of long- and short-term glioblastoma survivors. Epigenetics 2013; 8: 149-156.

Rothbart SB, Strahl BD. Interpreting the language of histone and DNA modifications. Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms 2014; 1839: 627-643.

Hebenstreit D, Fang M, Gu M, Charoensawan V, van Oudenaarden A, Teichmann SA. RNA sequencing reveals two major classes of gene expression levels in metazoan cells. Mol Syst Biol 2011; 7.

Rose NR, Klose RJ. Understanding the relationship between DNA methylation and histone lysine methylation. Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms 2014; 1839: 1362-1372.

Li G, Warden C, Zou Z, Neman J, Krueger JS, Jain A, Chen M. Altered Expression of Polycomb Group Genes in Glioblastoma Multiforme. PLOS One 2013; 8: e80970.

Watson CT, Disanto G, Sandve GK, Breden F, Giovannoni G, Ramagopalan SV. Age-Associated Hyper-Methylated Regions in the Human Brain Overlap with Bivalent Chromatin Domains. PLOS One 2012; 7: e43840.

Voigt P, Reinberg D. Putting a halt on PRC2 in pediatric glioblastoma. Nat Genet 2013; 45: 587-589.

Epigenetic Dysregulation Promotes Gene Activation in Pediatric Glioma. Cancer Discovery 2013; 3: OF15.

Xiao M, Yang H, Xu W, Ma S, Lin H, Zhu H, Guan K-L. Inhibition of α-KG-dependent histone and DNA demethylases by fumarate and succinate that are accumulated in mutations of FH and SDH tumor suppressors. Genes & Development 2012; 26: 1326-1338.

Chen L, Shi Y, Liu S, Cao Y, Wang X, Tao Y. PKM2: The Thread Linking Energy Metabolism Reprogramming with Epigenetics in Cancer. International Journal of Molecular Sciences 2014; 15: 11435-11445.

Kannan K, Inagaki A, Silber J, Gorovets D, Zhang J, Kastenhuber ER, Huse JT. Whole-exome sequencing identifies ATRX mutation as a key molecular determinant in lower-grade glioma 2012; Vol. 3.

Pfister Sophia X, Ahrabi S, Zalmas L-P, Sarkar S, Aymard F, Bachrati Csanád Z, Humphrey Timothy C. SETD2-Dependent Histone H3K36 Trimethylation Is Required for Homologous Recombination Repair and Genome Stability. Cell Reports 2014; 7: 2006-2018.

Pai C-C, Deegan RS, Subramanian L, Gal C, Sarkar S, Blaikley EJ, Humphrey TC. A histone H3K36 chromatin switch coordinates DNA double-strand break repair pathway choice. Nat Commun 2014; 5.

Lu T, Pan Y, Kao S-Y, Li C, Kohane I, Chan J, Yankner BA. Gene regulation and DNA damage in the ageing human brain. Nature 2004; 429: 883-891.

Lee C-K, Klopp RG, Weindruch R, Prolla TA. Gene Expression Profile of Aging and Its Retardation by Caloric Restriction. Science 1999; 285: 1390-1393.

Winter SC, Buffa FM, Silva P, Miller C, Valentine HR, Turley H, Harris AL. Relation of a Hypoxia Metagene Derived from Head and Neck Cancer to Prognosis of Multiple Cancers. Cancer Research 2007; 67: 3441-3449.




How to Cite

Lydia Hopp, Edith Willscher, Henry Löffler-Wirth, & Hans Binder. (2015). Function Shapes Content: DNA-Methylation Marker Genes and their Impact for Molecular Mechanisms of Glioma. Journal of Cancer Research Updates, 4(4),  127–148.