Dr. Lars Kaderali

Dr. Lars Kaderali - BioQuant, Heidelberg University

While both gene expression data and global chromosomal aberration profiles have been used for survival prediction, only few studies have so far attempted an integrated analysis of these types of data. In my talk, I will present results of an integrated analysis of microarray gene expression data and array CGH data. The focus of our work was to predict patient overall and / or event-free survival in years and months, comparing the effectiveness of the different platforms, and combining their predictive power by using data from both platforms simultaneously. For this purpose, we adapted the CASPAR algorithm to handle this integrative data analysis task, and we evaluated several different methods of preprocessing the experimental data.

I will show results on two tumor datasets. I will first present data from 128 patients with Neuroblastoma, a cancer of the neuronal crest cells. For these patients, both gene expression and aCGH data was acquired. I will discuss different methods of analysing this data set, and will show prediction results based on gene expression data only, array CGH data only, and the combined data. I will then show a second example of 81 previously published breast cancer patients, for which again both gene expression and aCGH data are available, essentially reconfirming the findings from the Neuroblastoma patients in a second, different tumor entity.