1. Hauptnavigation
  2. Navigation des Hauptbereiches
  3. Inhalt der Seite

Division of Functional Genome Analysis

Dr. Jörg D. Hoheisel

Visualisation of the degree of methylation in breast samples. Each sample is depicted as a coloured square and differentially methylated CpG sites are represented as black dots. All co-localise with the cancer samples at the right side, indicating that the highest methylation level is found in cancer. In contrast, healthy samples are located to the left, in the opposite direction off the centroid, indicating the lowest level of methylation. Likewise, based on the localisation of normal-appearing tissues from cancer patients and samples of benign tumours along the horizontal axis (first principal component), it can be seen that an intermediate methylation load existed in these samples.
Vergrößerte Ansicht Visualisation of the degree of methylation in breast samples. Each sample is depicted as a coloured square and differentially methylated CpG sites are represented as black dots. All co-localise with the cancer samples at the right side, indicating that the highest methylation level is found in cancer. In contrast, healthy samples are located to the left, in the opposite direction off the centroid, indicating the lowest level of methylation. Likewise, based on the localisation of normal-appearing tissues from cancer patients and samples of benign tumours along the horizontal axis (first principal component), it can be seen that an intermediate methylation load existed in these samples.

Research at the Division of Functional Genome Analysis focuses on the development and immediate application of new technologies for an assessment and description of both the realisation and regulation of cellular function from genetic information.

Analyses of tumour material are at the centre of attention, with an emphasis on pancreatic cancer and personalised approaches. Studies are under way about the effect of DNA sequence variations and the epigenetic modulation of the genome. Measurements are performed on variations in transcription factor binding and changes in transcript levels of coding and non-coding RNAs. Concomitantly, the actual protein expression is analysed, mostly by means of affinity-based assay formats. Beside the creation of knowledge, we aim at the establishment of means for reliable, potentially early and non-invasive diagnosis, accurate prognosis and patient stratification, monitoring of treatment results and the establishment of new therapeutic approaches. Particularly for the last objective, we complement the molecular analyses with functional studies for the elucidation of relevant cellular mechanisms.

A particular focus are developments and applications in the field of affinity-based proteome analysis, since analytical processes in this area are still inadequate for many, in particular biomedical purposes. We have established affinity-based processes that permit analyses with a robustness and reproducibility that meet the requirements of clinical applications. One aim is the identification of disease-relevant protein isoforms, since structural variation is often an immediate indicator for different functional activity. Quantitative measurements of protein interactions are performed, in particular for the identification of variations that occur at a personal level. Another activity is the creation of a map of protein-mediated communication between the different cell types of the tumour microenvironment.

Another line of work aims at the fully synthetic, in vitro implementation of complex biological processes. Motivation is their utilisation for the production of biomedically active molecules, such as non-immunogenic agents, and the establishment of entirely artificial molecular systems. Cell-free biosynthetic production will be crucial for mastering many biotechnological and pharmacochemical challenges. Artificial experimental systems will complement current systems biology by evaluating biological models experimentally. Similar to physics, insight into cellular function will be gained by an iterative processing of information by experimental and theoretical systems biology. Eventually, this may lead to the establishment of a fully synthetic self-replicating system and, ultimately, an archetypical model of a cell.

Website of the Division

Selected Publications

Srinivasan H. et al. (2014). Prediction of recurrence of non muscle-invasive bladder cancer by means of a protein signature identified by antibody microarray analyses. Proteomics 14, 1333-1342.

Wolf J. et al. (2014). SALL1 acts as tumor suppressor and regulator of CDH1. Oncogene 33, 4273-4278.

Keller et al. (2014). miRNAs can be generally associated with human pathologies as exemplified for miR-144*. BMC Med. 12, 224.

Moskalev E.A. et al. (2015). GHSR DNA hypermethylation is a common epigenetic alteration of high diagnostic value in a broad spectrum of cancers. Oncotarget 6, 4418-4427.

last update: 19/05/2015 back to top