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Durchdewald et al., 2008 Supplemental Material and Methods Microarrays. Global gene expression profiling was accomplished on self-printed microarrays employing a set of 35,852 oligomeres representing approximately 25,000 genes (Mouse Oligo Set Version 4.0; Operon, Cologne, Germany) as described in NCBIs Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) and accessible through GEO Series accession number GPL6015. Sample preparation and hybridization. Prior to all experiments total RNA isolated from tumor samples and commercially available mouse universal reference RNA (Stratagene, La Jolla, CA) was examined for integrity and purity using an Agilent RNA 6000 Series II Nano kit on a 2100 Bioanalyzer (Agilent, Santa Clara, CA). Targeted mRNA was amplified in an in vitro transcription-based protocol (34) and subsequently labeled with cyanine-3 and cyanine-5 in separate reactions. Each tumor sample was then hybridized against universal reference on one array, having different fluorescent labels in a color switch experiment. Hybridization processes and following washing procedures were automatically conducted in a GeneTac chamber (Genomic Solutions, Ann Arbor, Michigan, USA) as described previously (34) with expanded hybridization time to 23 h in order to increase signal intensity. RQ-PCR analysis. Total RNA extraction was performed according the manufacturer’s instructions using peqGOLD RNAPure (Peqlab Biotechnologie, Erlangen, Germany) and cDNA synthesis was performed as described elsewhere (28). RQ-PCR was performed using a MyiQ Single-Color Real-Time PCR Detection System (Bio-Rad, Munich, Germany) according to the manufacturer’s instructions. The Absolute SYBR Green Fluorescein Kit (ABgene, Surrey, UK) was used according to the manufacturers instructions. All RQ-PCR experiments were done in triplicates and normalized onto Hprt control. Sequences of all primers used for RQ-PCR analysis are listed in Supplemental Table 3. Data processing. Microarray read out was accomplished in a two-color Agilent Scanner G25505B (Agilent, Santa Clara, CA) with 5μm resolution and automatically adjusting PMT Durchdewald et al., 2008 voltages according to manufacturer’s specification. Recorded images were analyzed using GenePix Pro 6.0 software. Raw intensity tables were further processed within the analysis platform ChipYard (http://www.dkfz.de/genetics/ChipYard/), which applied the variance stabilization normalization algorithm (39), implemented data filtering based on mean to median ratio, minimal raw intensity, user flags and averaged signal values between color switch experiments. Differential gene expression was assessed using the Limma package for the R computing environment (40). A gene was considered significant for a Benjamini & Hochberg-corrected p-value of <0.05 in a moderated t-statistic that shrinks the standard deviation of individual genes to a common value according to a Bayesian model. In addition, we applied a threshold of at least 50% probability for a concurrent B-statistic that calculated the posterior odds of differential expression using an empirical Bayesian approach. A total portion of differentially expressed genes of 1% was assumed to adjust for multiple testing. The fold change in gene expression was indicated as linear ratio of Fosep SOS+ to Fosf/f SOS+. For means of result visualization, significant genes were grouped according to their biological processes by the use of Ingenuity Pathway Analysis (Ingenuity® Systems, www.ingenuity.com) and depicted in a heat map utilizing MultiExperiment Viewer v4.0 (41). The expression values represented in the map were calculated out of the difference between the log (log2) ratio of each gene in a sample (sample against reference) and the mean log (log2) ratio of all samples. The data discussed in this publication have been deposited in NCBIs Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) and are accessible through GEO Series accession number GSE10218.