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Riester, Markus

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Riester

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Markus

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Riester, Markus
Author's Publications: search.filters.isAuthorOfPublication.0e773b6d-6b30-4ab7-b36d-c2433a116f09

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    Aberration in DNA Methylation in B-Cell Lymphomas Has a Complex Origin and Increases with Disease Severity
    (Public Library of Science, 2013) De, Subhajyoti; Shaknovich, Rita; Riester, Markus; Elemento, Olivier; Geng, Huimin; Kormaksson, Matthias; Jiang, Yanwen; Woolcock, Bruce; Johnson, Nathalie; Polo, Jose M.; Cerchietti, Leandro; Gascoyne, Randy D.; Melnick, Ari; Michor, Franziska
    Despite mounting evidence that epigenetic abnormalities play a key role in cancer biology, their contributions to the malignant phenotype remain poorly understood. Here we studied genome-wide DNA methylation in normal B-cell populations and subtypes of B-cell non-Hodgkin lymphoma: follicular lymphoma and diffuse large B-cell lymphomas. These lymphomas display striking and progressive intra-tumor heterogeneity and also inter-patient heterogeneity in their cytosine methylation patterns. Epigenetic heterogeneity is initiated in normal germinal center B-cells, increases markedly with disease aggressiveness, and is associated with unfavorable clinical outcome. Moreover, patterns of abnormal methylation vary depending upon chromosomal regions, gene density and the status of neighboring genes. DNA methylation abnormalities arise via two distinct processes: i) lymphomagenic transcriptional regulators perturb promoter DNA methylation in a target gene-specific manner, and ii) aberrant epigenetic states tend to spread to neighboring promoters in the absence of CTCF insulator binding sites.
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    Identification of Nine Genomic Regions of Amplification in Urothelial Carcinoma, Correlation with Stage, and Potential Prognostic and Therapeutic Value
    (Public Library of Science, 2013) Chekaluk, Yvonne; Wu, Chin-Lee; Rosenberg, Jonathan; Riester, Markus; Dai, Qishan; Lin, Sharron; Guo, Yanan; McDougal, William; Kwiatkowski, David
    We performed a genome wide analysis of 164 urothelial carcinoma samples and 27 bladder cancer cell lines to identify copy number changes associated with disease characteristics, and examined the association of amplification events with stage and grade of disease. Multiplex inversion probe (MIP) analysis, a recently developed genomic technique, was used to study 80 urothelial carcinomas to identify mutations and copy number changes. Selected amplification events were then analyzed in a validation cohort of 84 bladder cancers by multiplex ligation-dependent probe assay (MLPA). In the MIP analysis, 44 regions of significant copy number change were identified using GISTIC. Nine gene-containing regions of amplification were selected for validation in the second cohort by MLPA. Amplification events at these 9 genomic regions were found to correlate strongly with stage, being seen in only 2 of 23 (9%) Ta grade 1 or 1–2 cancers, in contrast to 31 of 61 (51%) Ta grade 3 and T2 grade 2 cancers, p<0.001. These observations suggest that analysis of genomic amplification of these 9 regions might help distinguish non-invasive from invasive urothelial carcinoma, although further study is required. Both MIP and MLPA methods perform well on formalin-fixed paraffin-embedded DNA, enhancing their potential clinical use. Furthermore several of the amplified genes identified here (ERBB2, MDM2, CCND1) are potential therapeutic targets.
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    curatedOvarianData: clinically annotated data for the ovarian cancer transcriptome
    (Oxford University Press, 2013) Ganzfried, Benjamin Frederick; Riester, Markus; Haibe-Kains, Benjamin; Risch, Thomas; Tyekucheva, Svitlana; Jazic, Ina; Wang, Xin; Ahmadifar, Mahnaz; Birrer, Michael J.; Parmigiani, Giovanni; Huttenhower, Curtis; Waldron, Levi
    This article introduces a manually curated data collection for gene expression meta-analysis of patients with ovarian cancer and software for reproducible preparation of similar databases. This resource provides uniformly prepared microarray data for 2970 patients from 23 studies with curated and documented clinical metadata. It allows users to efficiently identify studies and patient subgroups of interest for analysis and to perform meta-analysis immediately without the challenges posed by harmonizing heterogeneous microarray technologies, study designs, expression data processing methods and clinical data formats. We confirm that the recently proposed biomarker CXCL12 is associated with patient survival, independently of stage and optimal surgical debulking, which was possible only through meta-analysis owing to insufficient sample sizes of the individual studies. The database is implemented as the curatedOvarianData Bioconductor package for the R statistical computing language, providing a comprehensive and flexible resource for clinically oriented investigation of the ovarian cancer transcriptome. The package and pipeline for producing it are available from http://bcb.dfci.harvard.edu/ovariancancer. Database URL: http://bcb.dfci.harvard.edu/ovariancancer