Signature optimisation and validation

Coordinator:		Prof. Jan G. Hengstler
Institution:		IfADo - Leibniz Research Centre
Homepage:		www.ifado.de/

A reliable diagnostic tool should not exclusively rely on gene chip data but should be confirmed by quantitative analysis. Therefore expression of all genes within the signatures identified by our partner Dr. Gehrmann will be confirmed by quantitative real time PCR. We will analyze whether introduction of quantitative aspects (such as thresholds for resistance associated genes) will improve the predictive power of the model. A large amount of literature has been published showing that protein/phosphoprotein expression and SNPs may be associated with chemosensitivity and prognosis. Therefore, we will analyze expression of beta-tubulin III, microtubule associate protein tau, Mad2 and BubR1 (the latter factors are known to be associated with paclitaxel resistance), erbB2, P-erbB2, ERK1/2, P-ERK1/2, AKT/PKB, P-AKT/PKB and SNPs by a 500 Kb SNP chip. Using multivariate analysis we will figure out, whether these parameters can be covered by RNA expression signatures or whether they add independent information.