Computational Cancer Epigenomics
Overview
Recent advances in microarray and sequencing technologies made the genome-wide profiling of DNA methylation and histone modifications feasible and scalable to cohorts containing hundreds or even thousands of samples. Large international consortia, such as the Encylopedia of DNA Elements, The Cancer Genome Atlas Project, the International Cancer Genome Consortium and the International Human Epigenome Consortium have systematically generated comprehensive epigenome-wide datasets on tissue samples and cell lines in human. These vast cohorts open unprecedented opportunities to study the genetic regulation, intracellular heterogeneity and disease progression at the molecular level, but they also bring up enormous challenges in data processing and analysis.
Major Research Directions
Our major goal is to improve the knowledge about the role of epigenetic processes by designing and using novel, integrative analysis techniques and advanced visualization approaches to map the complex interplay between genome, epigenome and transcriptome in the initiation and progression of cardiovascular diseases and cancer.
We also design custom strategies for biomarker prioritization and validation for various purposes, including therapy suggestions in early onset prostate cancer, classification of rare tumors and non-invasive diagnosis of cardiovascular diseases. We also study the predictive potential of DNA methylation and the applicability of methylation-based prediction models in clinical settings.
To improve the reproducibility and comparability of the currently used genome-wide technologies in detecting local and global changes in DNA methylation and histone marks, we investigate the strengths and limitations of these methods and their processing pipelines.
Selected Ongoing Projects
BMBF Computational Life Sciences Project "BSmadeEZ - Standardizing and scaling bisulfite sequencing data processing using EpiCWL" (2019-2021)
BMBF de.NBI Partner project de.NBI-Epi/DKFZ (with Prof. B. Brors, 2020-2021)
Helmholtz AMPro, subproject Lutsik (2020)
Deutsche Krebshilfe Project "CO-CLL: Epigenomes in the Cells of Origin of Chronic Lymphocytic Leukemia
- Implications for disease progression and potential as biomarker" (with Prof. C. Plass, 2020-2023)
Selected Recent Publications
- Lutsik P, Baude A, Mancarella D, Öz S, Kühn A, Toth R, Hey J, Toprak U, Lim J, Nguyen V, Jiang C, Mayakonda A, Hartmann M, Rosemann F, Breuer K, Vonficht D, Grünschläger F, Lee S, Schuhmacher M, Kusevic D, Jauch A, Weichenhan D, Zustin J, Schlesner M, Haas S, Park J, Park Y, Oppermann U, Jeltsch A, Haller F, Fellenberg J, Lindroth A, Plass C. Globally altered epigenetic landscape and delayed osteogenic differentiation in H3.3-G34W-mutant giant cell tumor of bone. Nature Communications 11, 5414 (2020)
- Schönung M, Hess J, Bawidamann P, Stäble S, Hey J, Langstein J, Assenov Y, Weichenhan D, Lutsik P, Lipka DB. AmpliconDesign - an interactive web server for the design of high-throughput targeted DNA methylation assays. Epigenetics, Oct 24:1-7, 2020.
- Mayakonda A, Schönung M, Hey J, Batra RN, Feuerstein-Akgoz C, Köhler K, Lipka DB, Sotillo R, Plass C, Lutsik P, Toth R. Methrix: an R/bioconductor package for systematic aggregation and analysis of bisulfite sequencing data. Bioinformatics, Dec21:btaa1048, 2020
- Scherer M, Nazarov PV, Toth R, Sahay S, Kaoma T, Maurer V, Vedeneev N, Plass C, Lengauer T, Walter J, Lutsik P. Reference-free deconvolution, visualization and interpretation of complex DNA methylation data using DecompPipeline, MeDeCom and FactorViz. Nature Protocols,15(10): 3240-3263, 2020
- Toth R, Schiffmann H, Hube-Magg C, Büscheck F, Höflmayer D, Weidemann S, Lebok P, Fraune C, Minner S, Schlomm T, Sauter G, Plass C, Assenov Y, Simon R, Meiners J, Gerhäuser C. Random forest-based modelling to detect biomarkers for prostate cancer progression. Clinical Epigenetics 11(1): 148, 2019
- Lutsik P, Slawski M, Gasparoni G, Vedeneev N, Hein M, Walter J. MeDeCom: discovery and quantification of latent components of heterogeneous methylomes. Genome Biology 18(1): 55, 2017
- Assenov Y, Müller F, Lutsik P, Walter J, Lengauer T, Bock C. Comprehensive analysis of DNA methylation data with RnBeads. Nature Methods, 11(11):1138-1140, 2014
The full list of publications is available as a this Pubmed query.
Furthermore, the publication lists of individual members can be seen on their Google Profiles: