The association of different genes with the three EGFR associated signa tures is likely reflective of the complexity of signaling in this pathway acro

Multivariate Cox proportional hazards analysis was performed in SAS v9. 0 to estimate the hazard AG 013736 price ratio associated with cluster expression in the three groups after controlling for stand ard clinical predictors. Chi Square tests were used to examine correlations between cluster groups, individual genes, and tumor selleck chem subtype. The pathway was built de novo based on information from KEGG, BioCarta, and a review HDAC pathway inhibitor by Yarden and Silowkoski with a focus on the RAS MEK and PI3K AKT components. To date, most information has been obtained through genome wide association studies using microarray technol ogy, providing information only on common SNVs. The current generation of GWA studies typically include several thousand individuals with the disease of interest and a similar number of control individuals without the dis ease. These studies and meta analyses combining data from multiple studies have now found more than 1600 loci where variants are associated with complex traits, including many diseases. There have been a number of discussions on the effi cacy of GWA studies. In spite of the success in disco vering disease associations, it is becoming clear that many disease mechanism genes with the highest effect on disease phenotypes are not discovered by GWAS. We compiled a list of disease related traits in the GWAS catalog and extracted the reported genes for each of them. The disease list includes a number of cancers, a variety of complex trait diseases, and disease predisposition traits such as obesity and hypertension. We then found the drugs used in treat ment of each of these traits in Drugbank, and extracted the drug target genes for each drug. Thus, for each trait, we have a list of GWAS reported genes and a list of drug targets. For the 88 GWAS diseases that have drugs in Drugbank, there are on average 29. 2 GWAS reported genes and 24. 0 drug targets for 19. 9 drugs. There are a total 23 instances of GWAS genes that are also drug targets for the same disease. Three of these genes are each drug targets for two different diseases, so that only 20 of the 856 drug target genes have been dis covered in GWA studies of the corresponding traits. This is slightly larger than the overlap of approximately 5 from a completely random model, but is a very low number considering that altered activity of most drug target genes will influence the disease phenotype. Possible data related reasons for low overlap One possible cause of lower overlap is that in Drugbank, some drug targets do not have a known mechanism and are probably predicted targets based on sequence simi larity to other verified drug targets, and thus may be incorrect. We therefore compiled a list of verified drug targets, all of which have known drug action mechanisms documented in Drugbank. We find similar results with this set to those for the complete list of drug targets. For those 353 drug targets for 81 diseases with known mechanisms and with corresponding GWAS studies, only 12 are discovered by GWAS.