CancerEpiSys – Integrative analysis of epigenetic networks that determine the chronic lymphocytic leukemia disease state

A public repository of data processed for Mallm, Iskar, Ishaque et. al. 2018 Linking aberrant chromatin features in chronic lymphocytic leukemia to deregulated transcription factor networks

Website: http://www.cancerepisys.org/cancerepisys/index.html

Github: https://github.com/CancerEpiSys/Mallm-et-al-processing-scripts

Research mission

CancerEpiSys is a BMBF funded research project with the CancerSys program that dissects the epigenetic networks associated with chronic lymphocytic leukemia (CLL) to develop novel diagnostic and therapeutic approaches for the disease. It has been initiated based on the emerging view that signals encoded in the DNA sequence, epigenetic modifications (e.g. DNA methylation, post-translational histone modifications), non-coding RNAs and nucleosome positioning are not independently regulated properties. Rather, these chromatin features are governed by an interconnected network of molecular processes that determine the cellular gene expression program. Any errors that occur in the interplay of these factors can lead to aberrant gene regulation associated with cancer. To rationalize the mode of action of novel ‘epigenetic’ drugs in cancer therapy that change properties of this network, we will dissect experimentally and mathematically the interdependence of these processes, focusing on CLL.

The main objectives of CancerEpiSys are: (i) deciphering the relation of DNA sequence, epigenetic modifications, nucleosome positioning and aberrant gene expression in CLL, (ii) the identification of epigenetic network morphologies that describe the response to the epigenetic drugs panobinostat and 3-deazaneplanocin (DZNep) that inhibit histone deacetylases and methyltransferases, (iii) the characterization of epigenetic markers and chromatin features of CLL patient subgroups, and (iv) the integration of results into an analysis scheme for the epigenetic aberrations most relevant for prognostication, prediction of treatment relapse and stratification of patients with respect to therapeutic options. Moreover, our results will inform novel therapeutic approaches that target gene-expression programs at the epigenetic level to sensitize cancer cells towards apoptosis and anti-growth signals.