FOXO3A has been shown to down regulate CCND1 during cell cycle inhibition

Results Unsupervised co inertia analysis identifies Amuvatinib MP-470 prominent trends in the BT474 and SKBR3 cell lines For each cell line we used CIA to simultaneously analyse mRNA expression levels and TFBS information in the promoters of the same genes. Unsupervised CIA was applied to the 48 microarrays for each of the BT474 and SKBR3 cell lines and the asso ciated geneTFBS frequency tables to identify underlying trends in the data in each of the cell lines. The ultimate goal was to identify the TFs responsible for these trends and the differentially regulated genes they were pre dicted to target. The unsupervised CIA of the BT474 and SKBR3 cell lines are shown in Figures 1 and 2 re spectively and are described in the following sections.

Unsupervised co inertia analysis of the BT474 cell line identifies a separation of 6 and 12 hour 1 um lapatinib treatment samples Axes one and three of the CIA for BT474 are plotted in Figure 1a, for data exploration purposes. This allows us to estimate the response to lapatinib in the BT474 cell line. Axes one and three were chosen as they represent the dominant Afatinib 価格 split within the data. The samples are la belled based on time and treatment. The samples at 6 hours and 12 hours post treatment with 1 uM lapatinib clearly separated from those treated with 0. 1% DMSO, with 0. 1 uM lapatinib and 2 hours post treatment with 1 uM lapatinib, demonstrating a clear separ ation in the data between 1 uM lapatinib treated cells and the other samples. However, there was no difference between 0. 1 uM lapatinib treated and 0.

1% DMSO treated cells, suggesting that this is a dosage dependent response in that a separation only occurred between the control samples and the high dose lapatinib samples, with the exception of one outlier on the far right of the plot. The lack of separation AG-1478 ic50 at 2 hours post treatment with 1 uM lapatinib suggests that the gene expression effects of the drug are not yet apparent at this time point. These observations guided our choice of compari sons for both the supervised CIA and the differential gene expression analysis which are summarised in Table 1. Figure 1b shows the motifs associated with this trend. The most extreme motifs along each axis are labelled and named. Those motifs furthest from the origin in the same orientation as the split of interest are most associated with that split. In this case V. AHRARNT.

02 was the motif most associated with the separation of 1 uM lapatinib treated cells from the other samples and therefore is the motif most associated with the response to lapatinib. This is the motif for the agonist activated heterodimer AHR ARNTwhich directly associates with the es trogen receptors ER alpha and ER beta in ER positive breast cancer, although its function in HER2 positive breast cancers is not well characterised. Unsupervised co inertia analysis of the SKBR3 cell line identifies a separation of 6 and 12 hour 0. 1 uM and 1 um lapatinib treatment samples Figure 2a shows axes one and two of the CIA for SKBR3. The samples are labelled as before based on time and treatment. There was a clear split between the 0. 1 uM and 1 uM lapatinib treated cells at 6 and 12 hours post treatment from the 0. 1% DMSO treated con trols, with the exception of one out lier.