Taqman PCR analysis confirms a consistent dysregulation of 5 of the 19 addition

Taqman PCR analysis confirms a consistent buy Amuvatinib dysregulation of 5 of the 19 additional genes selected for validation, following lapatinib exposure A panel of 19 genes was selected from the list of 421 candidate genes as described. As with the TFs, the 19 genes were first analysed for differential expres sion in BT474 and SKBR3 cells that had been treated with 1 uM lapatinib for 12 hours using untreated cells as a control. Of the 19 genes 5 were found to be differen tially expressed with an RQ value of2 in both the BT474 and SKBR3 cell lines. Of the remaining 14 genes, some were found to be differentially expressed, however, this alter ation in expression did not occur in both of the cell lines and they were therefore excluded from further analysis.<br><br> For further validation expression of, CCND1, ERBB3, FOXO3, NR3C1 and RB1CC1, was analysed in two add itional lapatinib sensitive purchase AT-406 cell lines EFM192A and HCC1954. Both of these cell lines are HER2 positive and have varying sensitivities to lapatinib, with IC50 values of 0. 193 uM 0. 0665 uM and 0. 4166 uM 0. 18 uM, re spectively. Two lapatinib insensitive cell lines were also analysed, MDAMB453 and MDAMB231. MDAMB453 is a HER2 positive breast cancer cell line that is innately insensitive to lapatinib and MDAMB231 is a triple nega tive breast cancer cell line that has an IC50 value of 7. 46 0. 102 uM In the lapatinib sensitive cell lines, the 5 genes showed differen tial gene expression levels proportional to the degree of sensitivity of the cells to lapatinib and are highlighted in bold in Table 3.<br><br> Figure 4 shows the expression profiles of RB1CC1, FOXO3A, NR3C1 and ERBB3 in the four lapatinib sensitive cell lines and clearly demonstrates a correlation between the degree of sensitivity of the cell line to lapa tinib and the magnitude of differential gene expression. BT474 was the buy AG-490 most lapatinib sensitive cell line and dis played the highest differential expression values for the four upregulated genes. As the cell lines became less sensitive to lapatinib, the magnitude of differential gene expression decreases. In the lapatinib insensitive cell lines, MDAMB453 and MDAMB231, the expression of these genes switched from up regulation following lapatinib exposure to down regulation. In the case of CCND1, the differential gene expression pattern followed a largely proportional response and not a switching response which was evident with the other genes.<br><br> In the lapatinib sensitive cell lines the gene was found to be strongly down regulated following the 12 hr treatment. The magnitude of this down regulation was reduced as the cells became more lapatinib insensitive. Discussion In this paper, we describe the application of a method for inferring the action of TFs by integrating the information provided by TFBS target prediction with mRNA gene expression data to identify possible markers for early lapatinib response. This is the first time this approach has been used to analyse an array data set derived from breast cancer cells treated with a targeted therapeutic. This multivariate statistical tech nique was applied to gene expression data incorporating time series data post treatment with high and low dose lapatinib in lapatinib sensitive, HER2 positive cell lines.