NGFN-TRANSFER

Identification of gene signatures predicting drug efficacy

Coordinator:    Dr. Christoph Kneip
Institution: TheraCode GmbH, Molecular Diagnostics
Homepage: http://theracode.de/

With > 70.000 cases per year in Germany breast cancer breast cancer is the most frequent cancer in women. In the last few years it was determined that breast cancer should not longer be considered as a single disease, as breast tumors can be divided into several subtypes. Tumors of different subtypes differ with regard to disease prognosis and response to local or systemic therapy. The subtypes are defined by differences in the expression profile of certain genes, resulting in different protein levels. Today, several genes/gene products serve as molecular biomarkers for subtyping of breast tumors. A biomarker is defined as a measurable characteristic, which is specific for a certain physiological or pathological state. A molecular biomarker is defined as a characteristic which can be determined on the genomic level (DNA) and/or genetic/biochemical level (e.g. gene expression = RNA and proteins). While prognostic markers are used to identify the risk with regard to disease progression and outcome, predictive biomarkers allow for prediction of a tumors response to a certain therapeutic intervention.

The main goal of our subproject was the identification of novel molecular biomarkers for better prognostic and/or predictive diagnosis in breast cancer. In course of the project, we analyzed and evaluated genomewide gene expression signatures of tumor and normal samples utilizing the state-of-the-art technology of next generation sequencing (NGS). NGS is a highly sensitive and specific method for identification of unknown biomarkers. For this purpose we established and optimized methods for preanalytical processing of clinical sample material to allow for a sensitive and reproducible expression analysis. Using adopted bioinformatic algorithms we analyzed and validated tumor specific gene expression signatures for subsequent identification of novel prognostic and/or predictive biomarker candidates. These candidates are the basis for the development of new diagnostic test systems to determine the best therapeutic treatments options for patients diagnosed with breast cancer.


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