The Medical Epigenomics Laboratory studies the role of the epigenome in cancer, which provides a new perspective for understanding how cancer develops and how it can be diagnosed and treated. We combine both wet-lab and computational methods in order to explore opportunities for epigenetic combination therapies against cancer.
The epigenome strikes a balance between the relatively static genome and highly volatile gene expression patterns, making it an important mechanism by which cell states are controlled during embryonic development and cellular differentiation. Given that cancer can be seen as a disease of messed-up cell states, it is not surprising that epigenetic mechanisms feature prominently in cancer development. We study the underlying epigenome dynamics in the lab and in clinical patient samples.
The lab’s long-term goal is to improve cancer therapy through interdisciplinary research at the interface of high-throughput biology, bioinformatics and biomedicine, and we work closely with clinical researchers at the Medical University of Vienna. In particular, we study the role of the epigenome in leukemia, and develop methods for rational design of epigenetic cancer therapies.
We develop experimental and computational methods to gain a unique perspective. For example, we combine next generation sequencing with biochemical tricks that help us map various types of epigenetic modifications, and develop bioinformatic algorithms for inferring relevant cancer biology from such high-throughput data.
The following two projects are examples of research currently being carried out by the Bock group.
Modeling epigenome dynamics in leukemia and in the hematopoietic system
The epigenetic alterations that are frequently observed in hematopoietic malignancies emerge from a complex interplay between cell-type specific variation, genetically determined variation, and disease-specific variation. High-throughput and computational methods are needed to disentangle these complex networks and to predict which mechanisms provide promising drug targets.
The lab uses the hematopoietic system and the development of leukemia as a model for dissecting the interplay of genetic, epigenetic and transcriptional mechanisms in the course of cellular differentiation and in leukemia. This work will give rise to a dynamic and potentially predictive computational model of the deregulation of cell states when cells become malignant.
Development of epigenetic biomarkers for cancer diagnostics and personalized therapy
All cancers exhibit widespread epigenetic alterations, and epigenetic regulator proteins are frequently mutated in a broad range of tumor types. Because epigenetic defects tend to occur early during carcinogenesis and correlate with important clinical phenotypes, they are promising targets for biomarker development.
The lab has established an epigenetic biomarker platform for systematically deriving, prioritizing and validating DNA methylation biomarkers in cancer. This work is performed in the context of the European BLUEPRINT project and the International Human Epigenome Consortium, and it provides a framework for collaborating with clinical researchers aiming to characterize the genomes, epigenomes and/or transcriptomes in large patient cohorts.
Next Generation Sequencing and Whole Genome Medicine
The Biomedical Sequencing Facility (BSF) is Austria’s first technology platform dedicated to next generation sequencing in biomedicine and is thus expected to play a catalyzing role in the country’s development of genomic medicine.
The BSF not only operates next generation sequencing for Vienna’s medical campus (and beyond), but it also provides technological expertise and bioinformatic services for basic researchers and clinicians. Furthermore, it contributes to several flagship projects aimed at establishing proof-of-concept for genomic medicine in Austria.
Christoph Bock joined CeMM as principal investigator in 2012. He is also a professor of Medical Informatics at the Medical University of Vienna (MedUni Vienna), where he leads the Institute of Artificial Intelligence at the Center for Medical Data Science. His research combines experimental biology (high-throughput sequencing, epigenetics, CRISPR screening, synthetic biology) with computational methods (bioinformatics, machine learning, artificial intelligence) for cancer, immunology, and precision medicine. Before coming to Vienna, he was a postdoc at the Broad Institute of MIT and Harvard (2008–2011) and a PhD student at the Max Planck Institute for Informatics (2004–2008). Christoph Bock also acts as the scientific coordinator of the Biomedical Sequencing Facility of CeMM and MedUni Vienna. He is a fellow of the European Lab for Learning and Intelligent Systems (ELLIS) and an elected member of the Young Academy of the Austrian Academy of Sciences. He has received major research awards, including an ERC Starting Grant (2016-2021), an ERC Consolidator Grant (2021-2026), the Otto Hahn Medal of the Max Planck Society (2009), the Overton Prize of the International Society for Computational Biology (2017), and the Erwin Schrödinger Prize of the Austrian Academy of Sciences (2022). He has been included in the global list of “Highly Cited Researchers” by Clarivate Analytics each year since 2019.
Klughammer J, Romanovskaia D, et al. Comparative analysis of genome-scale, base-resolution DNA methylation profiles across 580 animal species. Nat Commun. 2023 Jan 16;14(1):232. (abstract)
Bock C et al. High-content CRISPR screening. Nat Rev Methods Primers. 2022 2, 8. (abstract)
Datlinger P, Rendeiro AF, et al. Ultra-high-throughput single-cell RNA sequencing and perturbation screening with combinatorial fluidic indexing. Nat Methods. 2021 Jun;18(6):635-642. (abstract)
Bock C et al. The Organoid Cell Atlas. Nat Biotechnol. 2021 Jan;39(1):13-17. (abstract)
Krausgruber T, Fortelny N, et al. Structural cells are key regulators of organ-specific immune response. Nature. 2020 Jul;583(7815):296-302. (abstract)
Rendeiro AF*, Krausgruber T* et al. Chromatin mapping and single-cell immune profiling defines the temporal dynamics of ibrutinib drug response in chronic lymphocytic leukemia. Nature Communications. 2020;11:577. (abstract)
Schmidl C*, Vladimer GI*, Rendeiro AF*, Schnabl S* et al. Combined chemosensitivity and chromatin profiling prioritizes drug combinations in CLL. Nature Chemical Biology. 2019;15:232-240. (abstract)
Halbritter F*, Farlik M* et al. Epigenomics and single-cell sequencing define a developmental hierarchy in Langerhans cell histiocytosis. Cancer Discovery. 2019;9:1406-1421. (abstract)
Klughammer J*, Kiesel B* et al. The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space. Nature Medicine. 2018;24:1611-1624. (abstract)
Datlinger P, et al. Pooled CRISPR screening with single-cell transcriptome read out. Nature Methods. 2017;14:297-301. (abstract)
Bock C. Analysing and interpreting DNA methylation data. Nat Rev Genet. 2012 Oct;13(10):705-19. (abstract)
Bock C, Lengauer T. Managing drug resistance in cancer: lessons from HIV therapy. Nat Rev Cancer. 2012 Jun 7;12(7):494-501. (abstract)
Bock C, Beerman I, Lien WH, Smith ZD, Gu H, Boyle P, Gnirke A, Fuchs E, Rossi DJ, Meissner A. DNA methylation dynamics during in vivo differentiation of blood and skin stem cells. Mol Cell. 2012 Aug 24;47(4):633-47. (abstract)
Bock C, Kiskinis E, Verstappen G, Gu H, Boulting G, Smith ZD, Ziller M, Croft GF, Amoroso MW, Oakley DH, Gnirke A, Eggan K, Meissner A. Reference Maps of human ES and iPS cell variation enable high-throughput characterization of pluripotent cell lines. Cell. 2011 Feb 4;144(3):439-52. (abstract)