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47 IPA was then used to predict upstream regulators and downstream effects based on the observed patterns of pairwise differential expression. 3-mercaptopyruvate sulfurtransferase For the technical and biological validation and replication of gene expression levels generated in the microarray expression profiling assay, RT-qPCR was used to measure gene expression levels for six genes. These genes were chosen because they were either differentially expressed between the different treatment conditions (ATL3, CCL20, IL24, and PTGS2 from 438 DEGs) or represented a stable gene across our various?experimental?conditions (TERF2IP). In addition, a reference gene (GAPDH) was used to normalize mRNA expression levels. In brief, validation RT-qPCR was performed on the same samples that were used in the microarray assays and on the samples from repeated experiments. The?cDNA was prepared from 1 ��g of untreated total RNA using an Applied Biosystems high-capacity cDNA reverse transcription kit (Life Technologies). qPCR was performed for the seven genes using TaqMan gene expression assays and TaqMan universal PCR master mix with the recommended thermal profiles on a 7900HT fast real-time PCR system (Life Technologies). Relative normalized expression levels between samples were calculated using the 2(?����CT) method. IPA was used to predict the likely upstream transcription Selinexor solubility dmso factors (TFs) for a given set of DEGs (for here, 438 DEGs) in terms of activation z-score and number of downstream targets that are also DEGs. For a given TF, the direction of change of each target in our set of DEGs was compared with the predicted effect based on the current literature to arrive at a z-score that implies activation or?inactivation of the TF of interest. If the change in expression across all target genes is positively correlated with prediction, then the TF is viewed as relatively more activated in the treated samples, compared with the controls. If the target genes are negatively correlated with prediction, then the learn more TF is viewed as less activated, compared with the controls. The intersection P value measures the probability that an observed number of downstream targets in the data are due to chance. A given TF is significant if it has a z-score of >2 in absolute value and has an intersection P value of
