Eugenia Giannopoulou, PhD

Selected Publications

Giannopoulou E, Elemento O, Ivashkiv LB: Use of RNA-seq to evaluate rheumatic disease patients. Arthritis Research and Therapy 2015, accepted.

Subtil-Rodríguez A, Ceballos-Chávez M, Giannopoulou E, Soronellas D, Elemento O, Beato M, Reyes JC: The chromatin remodeler CHD8 is involved in activation of progesterone receptor-dependent enhancers. PLoS Genetics 2015, accepted.

Walker SR, Liu S, Xiang M, Nicolais M, Hatzi K, Giannopoulou E, Elemento O, Cerchietti L, Melnick A, Frank DA: The transcriptional modulator BCL6 as a molecular target for breast cancer therapy. Oncogene 2014.

Popovic R, Martinez-Garcia E, Giannopoulou E, Zhang Q, Zhang Q, Ezponda T, Shah MY, Zheng Y, Will
CM, Small EC et al: Histone Methyltransferase MMSET/NSD2 Alters EZH2 Binding and
Reprograms the Myeloma Epigenome Through Global and Focal Changes in H3K36 and H3K27
Methylation. Plos Genetics 2014, Accepted.

Park-Min KH, Lim E, Lee MJ, Park SH, Giannopoulou E, Yarilina A, van der Meulen M, Zhao B, Smithers N, Witherington J et al: Inhibition of osteoclastogenesis and inflammatory bone resorption by targeting BET proteins and epigenetic regulation. Nature communications 2014, 5:5418.

Li S, Miller CH, Giannopoulou E, Hu X, Ivashkiv LB, Zhao B: RBP-J imposes a requirement for ITAM-mediated costimulation of osteoclastogenesis. The Journal of clinical investigation 2014, 124(11):5057-5073.

Donlin LT, Jayatilleke A, Giannopoulou EG, Kalliolias GD, Ivashkiv LB: Modulation of TNF-induced macrophage polarization by synovial fibroblasts. Journal of immunology 2014, 193(5):2373-2383.

Chakravarty D, Sboner A, Nair SS, Giannopoulou E, Li R, Hennig S, Mosquera JM, Pauwels J, Park K, Kossai M et al: The oestrogen receptor alpha-regulated lncRNA NEAT1 is a critical modulator of prostate cancer. Nature communications 2014, 5:5383.

Roumeliotis TI, Halabalaki M, Alexi X, Ankrett D, Giannopoulou EG, Skaltsounis A-L, Sayan BS, Alexis MN, Townsend PA, Garbis SD: Pharmacoproteomic study of the natural product Ebenfuran III in DU-145 prostate cancer cells: The quantitative and temporal interrogation of chemically induced cell death at the protein level. Journal of proteome research 2013, 12(4):1591-1603.

Qiao Y, Giannopoulou EG, Chan CH, Park S-h, Gong S, Chen J, Hu X, Elemento O, Ivashkiv LB: Synergistic activation of inflammatory cytokine genes by interferon-γ-induced chromatin remodeling and Toll-like receptor signaling. Immunity 2013, 39(3):454-469.

Lin P-C, Giannopoulou EG, Park K, Mosquera JM, Sboner A, Tewari AK, Garraway LA, Beltran H, Rubin MA, Elemento O: Epigenomic alterations in localized and advanced prostate cancer. Neoplasia 2013, 15(4):373-IN375.

Lin P-C, Chiu Y-L, Banerjee S, Park K, Mosquera JM, Giannopoulou E, Alves P, Tewari AK, Gerstein MB, Beltran H: Epigenetic repression of miR-31 disrupts androgen receptor homeostasis and contributes to prostate cancer progression. Cancer research 2013, 73(3):1232-1244.

Hatzi K, Jiang Y, Huang C, Garrett-Bakelman F, Gearhart MD, Giannopoulou EG, Zumbo P, Kirouac K, Bhaskara S, Polo JM: A hybrid mechanism of action for BCL6 in B cells defined by formation of functionally distinct complexes at enhancers and promoters. Cell reports 2013, 4(3):578-588.

Giannopoulou EG, Elemento O: Inferring chromatin-bound protein complexes from genome-wide binding assays. Genome research 2013, 23(8):1295-1306.

Chang C-Y, Pasolli HA, Giannopoulou EG, Guasch G, Gronostajski RM, Elemento O, Fuchs E: NFIB is a governor of epithelial-melanocyte stem cell behaviour in a shared niche. Nature 2013.

Giannopoulou EG, Lepouras G, Manolakos ES: Visualizing Meta-Features in Proteomic Maps. BMC bioinformatics 2011, 12(1):308.

Giannopoulou EG, Elemento O: An integrated ChIP-seq analysis platform with customizable workflows. BMC bioinformatics 2011, 12(1):277.

Giannopoulou EG, Garbis SD, Vlahou A, Kossida S, Lepouras G, Manolakos ES: Proteomic feature maps: a new visualization approach in proteomics analysis. Journal of biomedical informatics 2009, 42(4):644-653.

Google Scholar Listing

For more publications, please see the PubMed listing.

Research Description

Focusing in the areas of genomics, epigenomics, computational biology and applied bioinformatics. Developing software and tools for the analysis of next-generation sequencing data. Involved in high-throughput data analysis and biologically-driven projects related to rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and other autoimmune and inflammatory diseases.

Building an online database of epigenomic signatures for autoimmune rheumatic diseases

Epigenetics is the study of heritable, non DNA-based but DNA-associated mechanisms that influence gene expression and phenotypes, such as histone modifications (i.e., post-translational modifications of certain amino acids of histone tails), and DNA methylation (i.e., addition of methyl groups to cytosines at CG dinucleotides). Nowadays, in the high-throughput “–omics” era, epigenomics refers to the global analyses of epigenetic changes across the entire genome. Disruption of epigenetic marks has been associated with a number of autoimmune diseases, such as Rheumatoid Arthritis (RA), Scleroderma and Systemic Sclerosis (SSc) and Systemic Lupus Erythematosus (SLE). In particular, abnormal DNA methylation in CD4+ T and B cells has been associated with SLE and SSc. In this project we study the relevant literature in order to extract DNA methylation signatures from patients with RA, SLE or SSc, and build an online repository of epigenomic signatures for autoimmune rheumatic diseases.

Modeling chromatin-bound protein complexes.

Transcription factors rarely bind chromatin alone, but instead frequently bind to cis-regulatory elements (CREs) together with other factors thus forming protein complexes. We have developed a computational methodology to systematically capture protein complexes and infer their impact on gene expression. We applied our method to ENCODE ChIP-seq datasets from three human cell types (GM12878, H1 Esc, K562), identified thousands of CREs, inferred known and undescribed complexes recruited to these CREs, determined the role of the complexes as activators or repressors, and found that the predicted complexes have a higher number of physical interactions between their members than expected by chance. This work provides a mechanism for developing hypotheses about gene regulation via binding partners, and deciphering the interplay between combinatorial binding and gene expression.

ChIPseeqer: A comprehensive framework for the analysis of ChIP-seq data.

To address the ChIP-seq peak interpretation challenge, we have developed ChIPseeqer, an integrative, comprehensive, fast and user-friendly computational framework for in-depth analysis of ChIP-seq datasets. The novelty of ChIPseeqer is the capability to combine several computational tools in order to create easily customized workflows that can be adapted to the user’s needs and objectives. The framework is freely available as a user-friendly GUI application, but all programs are also executable from the command line.


Contact Information

Office Locations

Caspary Research Building
541 East 71st Street
New York, NY 10021
Tel: 212.774.7262


Mailing Address

Hospital for Special Surgery
535 East 70th Street
New York, New York 10021

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