The supportive data for this hypothesis includes the in vitro observations that these are genes induced when an EGFR http://www.selleckchem.com/Wnt.html dependent cell line is freed from growth inhibition via EGFR inhibitors and the in vivo associations between the high expression of these signa tures and genes including HRAS, KRAS and EGFR itself. Regardless of the classical markers of activation of the selleck chemicals EGFR RAS MEK pathway, the strong associations between these expression profiles and patient outcomes in two dif ferent data sets suggest that they are important profiles. Currently, we have chosen only to validate our profiles using additional microarray etc data sets, as opposed to using western blots or quantitative PCR of the training set, since each of these signatures represents a large number of genesproteins. Two to four microar rays per experimental cell line condition were performed, including a dye flip replicate for gefitinib and cetuximab treated samples. Microarrays were scanned on an Axon GenePix 4000B microarray scanner and analyzed using GenePix Pro 5. 1 software. Microarray raw data were uploaded into the UNC Microarray Database and Lowess normalization was performed on the Cy3 and Cy5 chan nels.
The microarray and patient clinical data are available at UNC Microarray Database and have been depos ited in the Gene Expression Omnibus under the accession number GSE6128. Statistical analyses Intra class correlations between cell line microarray exper iments were performed to judge the degree of concord ance between experimentssamples as described in Hu et al. Unsupervised analyses of the cell line samples were performed by selecting genes with an absolute signal intensity of at least 30 units in both channels in at least 70% of the samples tested and that also showed a Log2 RG Lowess normalized ratio of two on at least two arrays. The pro gram Cluster was used to hierarchically cluster samples and genes, and Treeview was used to view the data. Using the SUM102 treated cells, a one class Sig nificance Analysis of Microarrays was used to iden tify significantly induced genes in all the post treatment experiments. Gene ontology enrichment was assessed using EASE. Analyses of the primary tumor data used the top 500 induced genes from the cell line SAM analysis described above, after filtering for 30 units in both channels in at least 70% of the tumor samples. These genes were exam ined in a two way hierarchical clustering analysis with the 248 UNC tumor sample set. Three distinct expression pat terns were observed and labeled as Clusters 13. Next, the genes in each of these three tumor defined clusters were identified in the NKI295 patient data set, and a mean expression value for each cluster for each patient was determined. The NKI295 patients were then rank ordered and separated into two equal groups rep resenting low and high, or three equal groups repre senting low, medium, and high average expression for each cluster. In addition, similar gene based rank order patient stratifications were performed for individual genes that included EGFR, HER2, HER4, EGF, TGFA, AREG, CRYAB, KRAS, KRAS amplicon profile, HRAS, NRAS, PIK3CA, PIK3R1, AKT1, AKT2, AKT3, MEK1, MEK2, ERK1, and ERK2.