Cancer Biology Group

Scientific overview

According to the world health organization (WHO), malignant neoplasms are the most common cause of death worldwide. Despite intensive research on carcinogenesis this frightening scenario will persist mainly due to the overall increase of lifetime expectancy. Furthermore, most cancers are only diagnosed in an advanced stage, which prohibits curative treatment and a large proportion of patients do not respond to their chemotherapy. In a concerted action, based on the recent improvements of methodological techniques, we develop strategies for the identification of patients at risk and tumors and we intend to identify prognostic and predictive biomarkers as guides for patient’s successful treatment at different stages of the disease. These goals are approached by means of newest high-throughput technologies combined with computational analyses. On the other side, and at least of similar importance, we perform functional experiments to identify pathomechanisms underlying tumor development, progression and latency.

DNA Methylation analyses in prostate cancer

Prostate cancer (PC) accounts for more than 900,000 cases per year and is the second most common cancer among men worldwide. The clinical course of PC is heterogeneous, ranging from indolent tumours requiring no therapy during lifetime to highly aggressive PC developing into a metastatic disease. Despite its high prevalence, the clinical management of PC is limited by the low specificity of the existing diagnostic and prognostic tools and the lack of effective systemic therapeutic strategies

A large proportion of PCs harbor gene fusions involving members of the ETS family and the androgen regulated transmembrane protease serine 2 (TMPRSS2) gene, most commonly involving the v-ets erythroblastosis virus E26 oncogene homolog ERG that is observed in approximately 50% of all PC cases. The overexpression of ERG is thought to be sufficient for the initiation of PIN (prostate intraepithelial neoplasia) lesions, a precursor of PC. Other rearrangements are less frequent and tend to be present in PCs already harboring the TMPRSS2:ERG gene fusion (FUS+). This suggests that other molecular mechanisms than trans- locations like alterations in the methylation or gene expression pattern must play a driving role in the TMPRSS2:ERG negative (FUS-) subclass.

Using a MeDIP-Seq approach on 51 tumor (20 TMPRSS2:ERG fusion negative (FUS-); 17 TMPRSS2:ERG fusion positive (FUS+)) and 53 normal samples we identified 147.000 differentially methylated regions comparing tumour and normal samples of which marker sets for future prostate cancer detection could be derived and successfully tested in independent sample sets. Most importantly, comparing FUS+ and FUS- samples revealed a significantly altered methylation pattern in FUS- cancers, while FUS+ samples were more equal to normal samples. Interestingly, we found EZH2 (enhancer of zeste homolog 2) – a polycomb group gene – significantly up-regulated in tumour samples. Increased expression can be explained by ERG in FUS+ samples while in FUS-samples we found mi- R26a – a suppressor of EZH2 - significantly down-regulated. We could show that hypermethylation of a 2kb region near miR26a is causative for miR26a supppression in FUS-samples. Thus, we developed a model for prostate tumour formation: In FUS+ cells, ERG overexpression results in overexpression of oncogenes like MYC, and EZH2 causing hypermethylation of homeobox genes leading to a reversion of differentiation and tumour formation. On the other hand FUS-samples exhibit a methylator phenotype accompagnied by hypermethylation of regulatory microRNA genes like miR26a (suppressing EZH2) or miR34 (suppressing MYC). Suppression of the regulatory microRNAs results in overexpression of MYC and EZH2, the latter augmenting aberrations in the DNA methylation pat- tern. Next steps are now to identify causes and consequences of the differential methylation patterns in FUS-samples. Our goal is to identify modifier enzymes responsible for the aberrant methylation pattern and to investigate mechanisms reverting the observed phenotype.

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