Tfpcr array poster


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Tfpcr array poster

  1. 1. Multi-Gene Validation of Differential Gene Expression Using the RT2Profiler™ PCR Array, a Low-Density qPCR Array Ray Blanchard; Hongguang Pan; Yanyang Sun; Jie Wang; Siulan Lee; Xiaomei Bao; Savita Prabhakar; Bill Wang; Jingping Yang SuperArray Bioscience Corporation, Frederick, MD Using the RT²Profiler™ PCR Array to Identify Tumor-Specific Genes Performance of RT²Profiler™ PCR Array 2 Figure 1: The RT Profiler™ PCR Array Shows High Reproducibility of Ct Profiler™ Values on Replicate Plates Ct Value 10-25 25-30 30-35 =>35 Not Detectable Total 40 30 0.24 Figure 4: Identify Differentially Expressed Genes Between Breast Tumor and Normal Breast Using the Cancer PathwayFinder™ RT2Profiler™ PCR Array Profiler™ PathwayFinder™ Frequency 47 36 14 3 1 100 15 15 20 35 40 6% 5% 6 7 8 9 10 11 12 G1 G2 G3 G4 G5 G6 G7 G8 G9 G10 G11 G12 B G13 G14 G15 G16 G17 G18 G19 G20 G21 G22 G23 G24 C G25 G26 G27 G28 G29 G30 G31 G32 G33 G34 G35 G36 D G37 G38 G39 G40 G41 G42 G43 G44 G45 G46 G47 G48 E G49 G50 G51 G52 G53 G54 G55 G56 G57 G58 G59 G60 F G61 G62 G63 G64 G65 G66 G67 G68 G69 G70 G71 G G73 G74 G75 G76 G77 G78 G79 G80 G81 G82 G83 G84 H HK1 HK2 HK3 HK4 HK5 GDC RTC RTC RTC PPC PPC 1.E-06 TIGA4 1% 0% 10 20 Average Ct 30 40 ∆∆Ct (GOI) = average ∆Ct (Expt) – average ∆Ct (Cntrl) The GOI fold-change from control to experimental group = 2 ^ (-∆∆Ct). The significance of the fold-change in gene expression between the two groups is evaluated by the student t-test and displayed on a volcano plot. 1.E-08 -7 -5 Breast Tumor 2-4% 4-6% C Coefficiency of Variation Rang -3 -1 1 3 5 7 Log2(Fold Change) ITGA2 ITGA2 ITGA2 MCAM MCAM MCAM MMP9 MMP9 MMP9 ITGB3 ITGB3 ITGB3 ITGA4 ITGA4 ITGA4 TGFB1 TGFB1 TGFB1 TNF TNF TNF TIMP3 TIMP3 TIMP3 CCNE1 CCNE1 CCNE1 CDKN2A CDKN2A CDKN2A FGFR2 FGFR2 FGFR2 Figure 2: Validation of Ct reproducibility Across Time and Investigator Experiment 1 9 Fold change Tumor/Normal 542.45 39.85 35.51 27.54 15.10 12.27 9.74 9.30 6.88 6.88 5.34 5.34 5.34 5.34 4.65 4.44 4.14 3.61 3.44 3.36 3.36 3.29 3.07 3.07 -3.29 -3.78 -4.65 -5.34 -7.73 -8.48 -9.08 -26.91 -41.74 T-TEST p value 0.0000 0.0000 0.0000 0.0001 0.0000 0.0012 0.0003 0.0003 0.0003 0.0008 0.0018 0.0001 0.0042 0.0001 0.0003 0.0007 0.0000 0.0132 0.0015 0.0028 0.0031 0.0314 0.0068 0.0019 0.0000 0.0000 0.0003 0.0004 0.0000 0.0000 0.0026 0.0000 0.0007 Ave Raw Ct Tumor Normal 21.8 30.0 30.5 35.0 25.2 29.5 31.1 35.0 21.1 24.1 24.6 27.4 20.1 22.5 25.5 27.9 27.7 29.7 22.3 24.2 23.8 25.4 19.9 21.5 26.8 28.4 21.3 22.9 22.5 23.9 26.4 27.7 28.2 29.4 27.8 28.8 23.5 24.4 31.3 32.2 24.7 25.6 34.1 35.0 22.9 23.6 24.1 24.9 25.9 23.3 23.9 21.1 26.6 23.5 25.7 22.4 26.0 22.2 27.6 23.7 33.3 29.3 29.4 23.8 31.5 25.2 Experiment 2 To identify breast tumor specific genes, total RNA from normal breast tissue and the first of two unmatched breast tumor samples (BioChain Institute, Inc.) were characterized on the RT2Profiler™ Cancer PathwayFinder™ PCR Array (APH-033A). The scatter plot (Panel A) depicts a log transformation plot of the relative expression level of each gene (2^(-∆Ct)) between breast tumor and normal breast. The pink lines indicate the 3-fold change in gene expression threshold. The volcano plot (panel B) depicts the fold changes versus the p-values from the t-test. Panel C plots the fold changes of each gene as a z-axis displacement from the xy-plane representing the 96-well layout of the PCR Array. A total of 33 genes in the Cancer PathwayFinder™ PCR Array demonstrate at least a three-fold difference in gene expression between normal breast tissue and the breast tumor, as listed in panel D. Seven of these genes (colored red in panel A) represent cellular adhesion molecules. The results suggest that changes in the expression of genes involved in cellular interactions played an important role in the transformation of this and perhaps other breast tumors. To further confirm this hypothesis and to analyze the expression of other adhesion-related genes, a second breast tumor sample was characterized on the Extracellular Matrix and Adhesion Molecules PCR Array (APH-013A) and comparable results were obtained (data not shown). 20050825_1 20050825_2 20050825_3 20050825_4 20050825 20050825 20050825 20050825 _1 _2 _3 _4 1 0.995 1 0.997 0.994 1 0.995 0.994 0.996 1 20060111_1 20060111_2 20060111_3 20060111_4 20060111 20060111 20060111 20060111 _1 _2 _3 _4 1 0.998 1 0.998 0.998 1 0.998 0.998 0.998 1 Validation of RT2Profiler™ PCR array reproducibility at different times and in the hands of different investigators is demonstrated by the high level of correlation between replicate plate Ct values. The MAQC brain reference RNA sample was reverse transcribed and run on four replicate APH-002 (Human Drug Metabolism PCR Array) plates three months apart and by different investigators. The average correlation coefficient for Ct values between replicate runs was 0.995 ± 0.001 and 0.998 ± 0.000 for experiment 1 and 2, respectively. Figure 3: Cross Instrument Platform Validation of the RT2Profiler™ PCR Array Profiler™ A. Sample A ave Ct B. Sample B ave Ct C. B/A Fold change (log2) RT²Profiler™ PCR array is easy-to-use and requires minimal hands-on time. The protocol takes only two hours per sample to perform from start to finish (from cDNA to raw data). With its combination of pathway-specific gene lists, gene-specific PCR primers, and master mixes specific for individual instrumentation, the PCR Array system delivers superior system convenience and cost effectiveness. Data Analysis Method Fold-changes in gene expression are calculated using the ∆∆Ct method. For each gene of interest (GOI): ∆Ct (Cntrl Rep 1) = Ct (GOI) – avg Ct (HK genes) ∆Ct (Cntrl Rep 2) = Ct (GOI) – avg Ct (HK genes) ∆Ct (Cntrl Rep 3) = Ct (GOI) – avg Ct (HK genes)… ∆Ct (Expt Rep 1) = Ct (GOI) – avg Ct (HK genes) ∆Ct (Expt Rep 2) = Ct (GOI) – avg Ct (HK genes) ∆Ct (Expt Rep 3) = Ct (GOI) – avg Ct (HK genes)… 1.E-07 TIMP3 1.E-06 Two different RNA samples were each characterized in technical triplicates on a PCR Array. Panel A plots the average Ct values for each gene in each sample. The y-axis bars in the plot depict one average standard deviation about each calculated average Ct value. The table in Panel B summarizes the results in Panel A by listing the average standard deviation for different Ct value ranges as well as the percentage of genes in each group (percent frequency). Panel C charts the frequency of genes exhibiting a coefficient of variation in Ct value determination within a given range while the insert shows the %CV for each individual assay on the plate. RT²Profiler™ PCR array is a 96-well plate containing gene-specific primer sets for a thoroughly researched set of 84 genes relevant to a specific biological pathway or disease state plus five housekeeping genes and technical controls. A single sample is applied to all the wells of each plate so that replicates have their own plate. RT²Profiler™ PCR array control elements include: 1) A panel of 5 common housekeeping genes (HK1-HK5) The Cts for all 5 are averaged to produce a plate normalizing factor 2) A genomic DNA contamination control (GDC) Primers detect a region of non-mRNA coding gDNA 3) Triplicate reverse transcription control (RTC) elements Primers detect an external RNA control sequence from SuperArray’s RT2 PCR Array First Strand Kit (C-02) 4) Triplicate positive PCR control (PPC) elements The pre-dispensed external DNA template and primers in these wells produce a defined Ct under proper PCR conditions MMP9 1.E-05 2% 0 0-2% PPC G72 1.E-04 1.E-05 TNF 3% 1.E+00 5 A BCL2 GZMA 4% 1.E-01 4 PLAUR ITGA2 MCAM TEK ITGB3 1.E-04 MMP9 TIMP3 TNF ITGA4 TGFB1 BCL2 FOS GZMA TEK JUN APAF1 ATM ITGA2 PIK3R1 SYK PLAUR MCAM PLAU ETS2 ANGPT1 FAS TERT NFKB1 NME4 ERBB2 ITGA3 UCC1 MYC SNCG CCNE1 ITGB3 CDKN2A FGFR2 1.E-03 APAF1 1.E-02 3 FGFR2 1.E-03 2 FOS PIK3R1 SYK Jun TGFB1 CCNE1 UCC1 Gene 1.E-02 ATM MYC 1.E-03 1.E-04 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% CDKN2A 1.E-05 25 30 Average Ct value Frequency 20 C D 1.E-01 1.E-02 25 B 1.E+00 1.E-01 What is the RT²Profiler™ PCR Array? 1 A 1.E+00 SNCG Coefficiency of Variation Average Ct value 35 Ave SD 0.17 0.26 0.39 0.39 1.E-06 Validation of the RT²Profiler™ PCR Array platform can be demonstrated by its high level of reproducibility on several levels. SuperArray’s experimentally verified primer design algorithm and specially formulated master mix of the RT² SYBR® Green PCR system insure uniform annealing temperatures and high amplification efficiencies for optimal performance of every assay on the array plate. The individual PCR assays, which generate gene expression data using ∆∆Ct calculations, produce a standard deviation of 0.24 cycles and a CV of 0.92% between Ct values in replicate runs on the same cDNA. Collectively, the correlation coefficient for Ct values between replicate runs was 0.995 ± 0.001 (n=6) and 0.998 ± 0.000 (n=6) on two separate tests. Further tests provide cross-platform validation on three different real-time thermal cyclers with correlation coefficients averaging 0.991. A biological demonstration of the PCR Arrays’ performance identifies human breast tumor-specific genes from cancerous and normal tissues using the Cancer PathwayFinder™ RT²Profiler™ PCR Array. These results identified 33 genes with a statistically significant 3-fold or greater change in mRNA levels and indicated that cell adhesion molecules are the most dramatically affected pathway. B A Breast Normal Biological validation of gene expression results from high-density microarrays is an essential part of any expression profiling experiment and reverse transcription, real-time PCR (RTqPCR) has become the standard for this process. Unfortunately, the speed of this process has been hindered by the low throughput of traditional RT-qPCR using individual gene assays and standard curves. Additionally, the use of RT-qPCR multi-gene panels to achieve higher throughput has been hampered by the requirement for very tight control of assay reaction conditions across a wide range of genes in order to produce consistent results across expression system and instrument platforms. The SuperArray RT²Profiler™ PCR Array accelerates microarray validation by RT-qPCR through the combination of optimized and validated SYBR® Green PCR assays in a multi-gene array plate format. P Value Abstract Conclusions Overall, the RT²Profiler™ PCR Array provides the high reproducibility, specificity, sensitivity and wide linear dynamic range expected of real-time PCR with the multi-gene advantages of a low-density array. As demonstrated by the validation data in this report, the RT²Profiler™ PCR Array provides highly reliable SYBR® Green qPCR gene expression analysis. In both preand custom designed options the RT²Profiler™ PCR Array offers a powerful solution for accelerating the pace of microarray data validation. Wide linear dynamic range, high amplification efficiency, reproducibility and specificity expected of real-time PCR Replicate Ct value measurements within 0.24 cycle average standard deviation High degree of correlation, R2 ≥ 0.995, between Ct values obtained months apart by different investigators High degree of correlation, R2 ≥ 0.988, between Ct values obtained on different models of real-time PCR instruments 7500Fast MX3000P iCycler 7500Fast MX3000P 1 0.992 1 0.991 0.995 iCycler 1 7500Fast MX3000P iCycler 7500Fast MX3000P 1 0.989 1 0.990 0.988 iCycler 1 7500Fast MX3000P iCycler 7500Fast MX3000P 1 0.980 1 0.981 0.973 High degree of correlation, R2 ≥ 0.973 between fold-changes results obtained from different real-time PCR instruments iCycler 1 Cross platform validation of measurements and results were performed using the two MAQC reference RNAs analyzed on the Human Drug Metabolism RT2Profiler™ PCR array (APH-002) using three different real-time PCR thermal cycler models. Five replicate arrays were run for each sample on each model instrument and the average Ct value for each assay is compared in panels A and B. The results show a high correlation across instruments at the level of instrument measurement values. Panel C shows the cross platform comparison of fold change results obtained from these data with an average correlation coefficient of 0.991. Thirty-three genes from the Cancer PathwayFinder™ PCR Array demonstrated at least a 3-fold change in gene expression between a human breast tumor and normal breast tissue Pathway-focused PCR arrays offer a simple and reliable method to identify and monitor gene expression changes within a defined group of genes