ch as transcription factors and co activators that affect gene expression at promoter regions, in the radiation response is well known. However, selleck kinase inhibitor the potential contri butions of DNA topology changes and other epigenetic effects exerted by non coding RNA, DNA methylation and histone modification are not as well studied in the radiation response. There is some evidence Inhibitors,Modulators,Libraries for epige netic mechanisms such as DNA hypo methylation after radiation exposure but little is known about target genes and their dynamics, except Inhibitors,Modulators,Libraries in the case of the INK4A locus. Our study, by clustering genes with similar time course responses after radiation and bystander treatments, suggested a possible role for epi genetic regulation of metallothionein levels.
Inhibitors,Modulators,Libraries Network and ontology analysis in bystander gene response STEM clustering of the bystander data for the 238 genes yielded 6 significant clusters with uni form cardinality as seen in the case of irradiation. Using the same approach as before, we applied gene ontology methods using the PANTHER web based tool to assess the biological relevance of these six clusters. First, we mapped the genes in each cluster to see if any of the statistically significant clusters had largely unmapped genes. We found that the mapping of each cluster, once again, was randomly spread from 67% mapped genes in Clus ter 3 to 90% in Cluster 5. Gene ontology analyses of these clusters showed that Cluster 1 had over represented categories related to signaling and defense. Cell cycle processes were not significantly enriched in any bystander clusters as they were after direct irradiation, but apoptosis was significantly enriched in Cluster 2.
FAS, TNFRSF10C, TNFRSF10B, MYBL1 and Inhibitors,Modulators,Libraries MDM2 were gene members in this cate gory. STEM clustering in bystanders suggested only one biologically significant cluster with minimal biolo gical findings in other clusters. This suggests that although this method can group genes into visually tight patterns, the algorithm is blind to functionally Anacetrapib related genes that could be clustered together with more descriptive features, such as those used in FBPA. Network analysis of the six clusters confirmed that p53 and NF B family members were potential upstream regulators of gene expression in most of the STEM bystander clusters. We also applied the same analyses to the FBPA clusters of the 238 bystander gene profiles.
Again we observed no significant trend of mapping across clusters and the largest cluster, Clus ter 1 with 107 genes, showed 28% of genes were unmapped in PANTHER. A surprising result of gene ontology analysis was that there were no significantly enriched biological processes in Clus ter 1, which grouped the most genes. However, significant enrichment of biological processes was identified sellckchem in Clusters 2, 3 and 4. Cluster 2 shared categories in common with Clusters 3 and 4, the most significant process in Cluster 2 was the NF B cascade. In Cluster 2, which was visually a tight cluster by pattern and magni tude of change,