gms | German Medical Science

Breast cancer is one of the most common malignant diseases in females. Tumors can be divided into estrogen-receptor positive and estrogen-receptor negative tissues which show distinct clinical behaviours. To understand the regulatory processes of gene expression networks in cancer diseases, single genes with relevance in cancer are silenced using chemically synthesised siRNA. The main focus of this project is on the analysis of estrogen receptor (ESR) signalling in breast cancer, using different breast cell-lines (ESR-positive and negative) as model organisms. To establish the experimental conditions, the TP53 gene was used: Human cells were grown for 24h before transfection in 96 well-plates and transfected with two different siRNA against TP53 using the HiPerFect transfection reagent. The transfection reaction was stopped after 42h of incubation by lysing the cells. RNA was extracted, and the silencing efficiency of TP53 was measured using qRT-PCR. The RNA samples with best silencing efficiency were amplified and used for hybridisation on human whole genome cDNA microarrays containing 37,500 clones (RZPD Unigene Set 3.1). The gene expression patterns were used to analyse the downstream effects of the cellular perturbance. By using the microarray data, network models are designed to account the hierarchial organisation of transcriptional regulation among cancer-relevant genes related to the estrogen-receptor pathway in breast cancer. In the future we will set up a screening-procedure for gene silencing in breast-cancer related cell lines (MCF7, SKBR3, BT474) to be able to construct hierarchial networks. By the support of our bioinformatic resource, we will try to calculated regulatory dependencies among the subset of silenced genes in order to find unknown interactions between cancer relevant genes.