Antitumor activities of cyclopamine and γ-secretase inhibitor against HEKTER-LUK and HEKTER-ST cell lines

<p><b>Copyright information:</b></p><p>Taken from "Cross-platform expression profiling demonstrates that SV40 small tumor antigen activates Notch, Hedgehog, and Wnt signaling in human cells"</p><p>BMC Cancer 2006;6():54-54.</p><p>Published online 7 Mar 2006</p><p>PMCID:PMC1420312.</p><p>Copyright © 2006 Ali-Seyed et al; licensee BioMed Central Ltd.</p> Survival of HEK-TERV and HEK-TERST cells determined by MTT assay after treatment with vehicle, 2.4μM Cyclopamine or 1 nM γ-secretase inhibitor for 72 hrs. Mean and standard error are shown for each treatment. Percent cell survival was computed relative to untreated cells. Survival of HEK-TERST cells determined by Trypan Blue exclusion assay after treatment of 1 × 10cells with vehicle, 2.4μM Cyclopamine or 1 nM γ-secretase inhibitor for 72 hrs

Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays-3

<p><b>Copyright information:</b></p><p>Taken from "Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays"</p><p>BMC Genomics 2006;7():59-59.</p><p>Published online 21 Mar 2006</p><p>PMCID:PMC1435885.</p><p>Copyright © 2006 Wang et al; licensee BioMed Central Ltd.</p>rm (y-axis) were plotted aganinst those determined by TaqMan Assays (x-axis). Genes were filtered based on real-time PCR detection thresholds (detectable in at least 3 out of 4 technical replicates in at least one of the three tissues). The lines represent lowess smoothing fitting curves to 3,105 data points (sum of all three pair-wise tissues) in each platform

Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays-5

<p><b>Copyright information:</b></p><p>Taken from "Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays"</p><p>BMC Genomics 2006;7():59-59.</p><p>Published online 21 Mar 2006</p><p>PMCID:PMC1435885.</p><p>Copyright © 2006 Wang et al; licensee BioMed Central Ltd.</p> 0.05 using a student t-test (Panel A), using -value adjusted according to Benjamini Horschberg multiple testing to control FDR at 5% (Panel B), or using a fold change cutoff (> 1.2-fold) for the TaqMan reference data sets while using a fold change cutoff (> 1.2-fold) and -value < 0.05 based on t-test for microarray platforms (Panel C). Composite results for all three pairs of tissues (Brain vs. Liver, Brain vs. Lung, and Liver vs. Lung) were plotted. Gene expression levels are ordered according to TaqManGene Expression Assay measurements (average Ct between the three tissues, only genes detected in both tissues by TaqMan assays were analyzed). A sliding window containing 100 consecutive genes was constructed and moved one gene at a time to cover the whole range of Ct values. Within each sliding window, the True Positive Rate (upper panel) and False Discovery Rate (lower panel) of each microarray platform was computed and plotted as a function of gene expression level

Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays-2

<p><b>Copyright information:</b></p><p>Taken from "Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays"</p><p>BMC Genomics 2006;7():59-59.</p><p>Published online 21 Mar 2006</p><p>PMCID:PMC1435885.</p><p>Copyright © 2006 Wang et al; licensee BioMed Central Ltd.</p>e1/MedianSignal_tissue2); for Agilent arrays, log2(MedianSignal_tissue1/MedianSignal_UHR)- log2(medianSignal_tissue2/MedianSignal_UHR); x-axis, fold change determined by real-time PCR, which is defined as ΔΔCt = (Ct_tissue2-Ct_PPIA)-(Ct_tissue1-Ct_PPIA). For each pair-wise comparison, genes were filtered based on real-time PCR detection thresholds (detectable in at least 3 out of 4 technical replicates in each tissue and detectable in both tissues, the number of genes are shown in the parentheses). A robust linear regression fitting and the corresponding Rvalue are presented in each plot

Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays-1

<p><b>Copyright information:</b></p><p>Taken from "Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays"</p><p>BMC Genomics 2006;7():59-59.</p><p>Published online 21 Mar 2006</p><p>PMCID:PMC1435885.</p><p>Copyright © 2006 Wang et al; licensee BioMed Central Ltd.</p>nt lowess smoothing fitting curves to the 5,500 data points in each platform

Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays-4

<p><b>Copyright information:</b></p><p>Taken from "Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays"</p><p>BMC Genomics 2006;7():59-59.</p><p>Published online 21 Mar 2006</p><p>PMCID:PMC1435885.</p><p>Copyright © 2006 Wang et al; licensee BioMed Central Ltd.</p>qMan Gene Expression Assay based real-time PCR. The gene expression profile for each gene across the three tissues was determined using the median expression level of the four technical replicates followed by a z-score transformation across the three tissues for each of platforms as described in Methods. (B). Distribution of the Spearman rank-order correlation coefficients () of profiles determined by each microarray platform vs. real-time PCR

Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays-6

<p><b>Copyright information:</b></p><p>Taken from "Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays"</p><p>BMC Genomics 2006;7():59-59.</p><p>Published online 21 Mar 2006</p><p>PMCID:PMC1435885.</p><p>Copyright © 2006 Wang et al; licensee BioMed Central Ltd.</p>t at 95% significance level (-value = 0.05). Using one-sample z-test, genes showing "at least F fold change" with 95% confidence are grouped based on TaqManGene Expression Assays data set. True Positive Rates of each microarray platform was plotted as a function of Fold Change cut-off (range from 1.2 – 10) for each pair-wise tissues

Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays-7

<p><b>Copyright information:</b></p><p>Taken from "Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays"</p><p>BMC Genomics 2006;7():59-59.</p><p>Published online 21 Mar 2006</p><p>PMCID:PMC1435885.</p><p>Copyright © 2006 Wang et al; licensee BioMed Central Ltd.</p>et as a reference. For each microarray platform, on top of the p-value criteria (p < 0.05 in student t-test), a series of FDR (0–20%) were also applied to achieve increasing stringency. Each point on the ROC curve of a given microarray platform represents the sensitivity (true positive rate) and 1- specificity (false positive rate) at a given FDR level (labeled on dashed lines)