Reliable Transcript Quantification by Real-Time Reverse Transcriptase-Polymerase Chain Reaction in Primary Neuroblastoma Using Normalization to Averaged Expression Levels of the Control Genes HPRT1 and SDHA
2005; Elsevier BV; Volume: 7; Issue: 1 Linguagem: Inglês
10.1016/s1525-1578(10)60013-x
ISSN1943-7811
AutoresMatthias Fischer, Matthias Skowron, Frank Berthold,
Tópico(s)Ubiquitin and proteasome pathways
ResumoReal-time reverse transcriptase-polymerase chain reaction (RT-PCR) represents a sensitive and efficient technique to determine expression levels of target genes in multiple samples and is increasingly used in clinical oncology to evaluate the patient's outcome or to detect minimal residual disease. Normalization of raw data are required to obtain comparable results between different specimens and is usually achieved by correlating transcript abundances of target genes with those of a single control gene with putatively stable expression levels. In this study, expression stability of six supposed control genes was evaluated in 64 samples of primary neuroblastoma and HPRT1 and SDHA mRNA levels were shown to exhibit the least expression variability among the samples. Because application of more than one control gene may enhance reliability of real-time RT-PCR results, various normalization factors consisting of the geometrical mean of multiple control gene expression values were calculated and evaluated by mRNA quantification of 14 target genes. Comparison with transcript levels determined by oligonucleotide-array expression analysis revealed that target gene mRNA quantification became most consistent after normalization to averaged expression levels of HPRT1 and SDHA. This normalization factor was in addition demonstrated to be not associated with stage of disease or MYCN amplification status of the tumor. Thus, these data indicate that the geometrical mean of HPRT1 and SDHA transcript levels represents a suitable internal control for biological and clinical studies investigating differential gene expression in primary neuroblastoma by real-time RT-PCR. Real-time reverse transcriptase-polymerase chain reaction (RT-PCR) represents a sensitive and efficient technique to determine expression levels of target genes in multiple samples and is increasingly used in clinical oncology to evaluate the patient's outcome or to detect minimal residual disease. Normalization of raw data are required to obtain comparable results between different specimens and is usually achieved by correlating transcript abundances of target genes with those of a single control gene with putatively stable expression levels. In this study, expression stability of six supposed control genes was evaluated in 64 samples of primary neuroblastoma and HPRT1 and SDHA mRNA levels were shown to exhibit the least expression variability among the samples. Because application of more than one control gene may enhance reliability of real-time RT-PCR results, various normalization factors consisting of the geometrical mean of multiple control gene expression values were calculated and evaluated by mRNA quantification of 14 target genes. Comparison with transcript levels determined by oligonucleotide-array expression analysis revealed that target gene mRNA quantification became most consistent after normalization to averaged expression levels of HPRT1 and SDHA. This normalization factor was in addition demonstrated to be not associated with stage of disease or MYCN amplification status of the tumor. Thus, these data indicate that the geometrical mean of HPRT1 and SDHA transcript levels represents a suitable internal control for biological and clinical studies investigating differential gene expression in primary neuroblastoma by real-time RT-PCR. Quantification of target gene expression levels by real-time reverse transcriptase-polymerase chain reaction (RT-PCR)1Heid CA Stevens J Livak KJ Williams PM Real time quantitative PCR.Genome Res. 1996; 6: 986-994Crossref PubMed Scopus (4966) Google Scholar, 2Bustin SA Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays.J Mol Endocrinol. 2000; 25: 169-193Crossref PubMed Scopus (3030) Google Scholar is becoming increasingly significant in neuroblastoma as in other human malignancies to gain insight into the molecular pathology of the tumor, to identify novel prognostic markers, or to evaluate minimal residual disease response.3Krams M Parwaresch R Sipos B Heidorn K Harms D Rudolph P Expression of the c-kit receptor characterizes a subset of neuroblastomas with favorable prognosis.Oncogene. 2004; 23: 588-595Crossref PubMed Scopus (46) Google Scholar, 4Tajiri T Liu X Thompson PM Tanaka S Suita S Zhao H Maris JM Prendergast GC Hogarty MD Expression of a MYCN-interacting isoform of the tumor suppressor BIN1 is reduced in neuroblastomas with unfavorable biological features.Clin Cancer Res. 2003; 9: 3345-3355PubMed Google Scholar, 5Poremba C Hero B Heine B Scheel C Schaefer KL Christiansen H Berthold F Kneif S Stein H Juergens H Boecker W Dockhorn-Dworniczak B Telomerase is a strong indicator for assessing the proneness to progression in neuroblastomas.Med Pediatr Oncol. 2000; 35: 651-655Crossref PubMed Scopus (22) Google Scholar, 6Cheung IY Lo Piccolo MS Kushner BH Kramer K Cheung NK Quantitation of GD2 synthase mRNA by real-time reverse transcriptase polymerase chain reaction: clinical utility in evaluating adjuvant therapy in neuroblastoma.J Clin Oncol. 2003; 21: 1087-1093Crossref PubMed Scopus (46) Google Scholar, 7Cohn SL London WB Huang D Katzenstein HM Salwen HR Reinhart T Madafiglio J Marshall GM Norris MD Haber M MYCN expression is not prognostic of adverse outcome in advanced-stage neuroblastoma with nonamplified MYCN.J Clin Oncol. 2000; 18: 3604-3613Crossref PubMed Scopus (99) Google Scholar, 8Lambooy LH Gidding CE van den Heuvel LP Hulsbergen-van de Kaa CA Ligtenberg M Bokkerink JP De Abreu RA Real-time analysis of tyrosine hydroxylase gene expression: a sensitive and semiquantitative marker for minimal residual disease detection of neuroblastoma.Clin Cancer Res. 2003; 9: 812-819PubMed Google Scholar, 9Dotsch J Harmjanz A Christiansen H Hanze J Lampert F Rascher W Gene expression of neuronal nitric oxide synthase and adrenomedullin in human neuroblastoma using real-time PCR.Int J Cancer. 2000; 88: 172-175Crossref PubMed Scopus (25) Google Scholar A common feature of most transcript quantification techniques is the requirement for normalization, because a number of variables may influence the results.2Bustin SA Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays.J Mol Endocrinol. 2000; 25: 169-193Crossref PubMed Scopus (3030) Google Scholar, 10Lion T Current recommendations for positive controls in RT-PCR assays.Leukemia. 2001; 15: 1033-1037Crossref PubMed Scopus (63) Google Scholar Ideally, abundances of mRNA levels are determined as transcript copies per cell.2Bustin SA Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays.J Mol Endocrinol. 2000; 25: 169-193Crossref PubMed Scopus (3030) Google Scholar, 11Vandesompele J De Preter K Pattyn F Poppe B Van Roy N De Paepe A Speleman F Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.Genome Biol. 2002; 3: 0034.1-0034.12Crossref Google Scholar However, this approach is not feasible in many studies, in particular if samples of solid tissues are analyzed. As a surrogate, the amount of total RNA is often used to receive comparable results of expression levels between different samples, assuming that the cells under investigation contain approximately equal amounts of total RNA and mRNA. This assumption, however, does not hold true in many cases because it has been shown that even a particular cell type may contain different quantities of total RNA and/or mRNA under various physiological conditions.12Boon K Caron HN van Asperen R Valentijn L Hermus MC van Sluis P Roobeek I Weis I Voute PA Schwab M Versteeg R N-myc enhances the expression of a large set of genes functioning in ribosome biogenesis and protein synthesis.EMBO J. 2001; 20: 1383-1393Crossref PubMed Scopus (336) Google Scholar, 13Schmittgen TD Zakrajsek BA Effect of experimental treatment on housekeeping gene expression: validation by real-time, quantitative RT-PCR.J Biochem Biophys Methods. 2000; 46: 69-81Crossref PubMed Scopus (1000) Google Scholar In addition, determination of the cell count or total RNA amount does not take varying RNA quality or enzymatic efficiencies into account, which may have a significant impact on the results in RT-PCR reactions.10Lion T Current recommendations for positive controls in RT-PCR assays.Leukemia. 2001; 15: 1033-1037Crossref PubMed Scopus (63) Google Scholar, 14Bishop GA Rokahr KL Lowes M McGuinness PH Napoli J DeCruz DJ Wong WY McCaughan GW Quantitative reverse transcriptase-PCR amplification of cytokine mRNA in liver biopsy specimens using a non-competitive method.Immunol Cell Biol. 1997; 75: 142-147Crossref PubMed Scopus (27) Google Scholar Thus, expression levels of target genes are usually normalized to expression levels of internal control genes that are supposed to show stable expression in the tissues of interest. However, it has been demonstrated by a number of studies that frequently used control genes such as β-actin and GAPDH exhibit considerably varying transcript levels in cells of different histological origin and under various physiological or experimental conditions.2Bustin SA Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays.J Mol Endocrinol. 2000; 25: 169-193Crossref PubMed Scopus (3030) Google Scholar, 11Vandesompele J De Preter K Pattyn F Poppe B Van Roy N De Paepe A Speleman F Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.Genome Biol. 2002; 3: 0034.1-0034.12Crossref Google Scholar, 13Schmittgen TD Zakrajsek BA Effect of experimental treatment on housekeeping gene expression: validation by real-time, quantitative RT-PCR.J Biochem Biophys Methods. 2000; 46: 69-81Crossref PubMed Scopus (1000) Google Scholar, 15Suzuki T Higgins PJ Crawford DR Control selection for RNA quantitation.Biotechniques. 2000; 29: 332-337Crossref PubMed Scopus (704) Google Scholar, 16Hamalainen HK Tubman JC Vikman S Kyrola T Ylikoski E Warrington JA Lahesmaa R Identification and validation of endogenous reference genes for expression profiling of T helper cell differentiation by quantitative real-time RT-PCR.Anal Biochem. 2001; 299: 63-70Crossref PubMed Scopus (216) Google Scholar, 17Tricarico C Pinzani P Bianchi S Paglierani M Distante V Pazzagli M Bustin SA Orlando C Quantitative real-time reverse transcription polymerase chain reaction: normalization to rRNA or single housekeeping genes is inappropriate for human tissue biopsies.Anal Biochem. 2002; 309: 293-300Crossref PubMed Scopus (489) Google Scholar The finding that a universal control gene does apparently not exist led to the conclusion that putative reference genes have to be evaluated carefully for every individual cell type separately.2Bustin SA Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays.J Mol Endocrinol. 2000; 25: 169-193Crossref PubMed Scopus (3030) Google Scholar, 10Lion T Current recommendations for positive controls in RT-PCR assays.Leukemia. 2001; 15: 1033-1037Crossref PubMed Scopus (63) Google Scholar, 11Vandesompele J De Preter K Pattyn F Poppe B Van Roy N De Paepe A Speleman F Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.Genome Biol. 2002; 3: 0034.1-0034.12Crossref Google Scholar, 16Hamalainen HK Tubman JC Vikman S Kyrola T Ylikoski E Warrington JA Lahesmaa R Identification and validation of endogenous reference genes for expression profiling of T helper cell differentiation by quantitative real-time RT-PCR.Anal Biochem. 2001; 299: 63-70Crossref PubMed Scopus (216) Google Scholar, 18Livak KJ Schmittgen TD Analysis of relative gene expression data using real-time quantitative PCR and the 2(-delta delta C(T)) method.Methods. 2001; 25: 402-408Crossref PubMed Scopus (119102) Google ScholarThe present study evaluates the stability of expression levels of six putative control genes in primary tissue samples of the pediatric tumor neuroblastoma and establishes a hierarchy of the control genes according to their degree of regulation among the samples. It furthermore shows that normalization to more than one control gene considerably reduces the influence of varying expression levels of single control genes on target gene mRNA quantification. Finally, it reveals that a normalization factor consisting of the geometrical mean of HPRT1 and SDHA expression levels is not associated with stage or MYCN amplification status of primary neuroblastoma.Materials and MethodsSample Preparation and cDNA SynthesisNeuroblastoma cell lines IMR-5, IMR-32, and CHP-134 were grown to subconfluency in RPMI 1640 medium (Biochrom, Berlin, Germany) supplemented with 10% fetal calf serum and 0.1% Plasmocin (InvivoGen, San Diego, CA). Cells were harvested, washed once with phosphate-buffered saline, and subsequently used for RNA isolation. Approximately 40 mg of snap-frozen tissue samples of 64 primary neuroblastomas were cryosliced into 20-μm-thick tissue sections and transferred into 2-ml reaction tubes. After samples were homogenized by the FastPrep FP120 cell disrupter (Qbiogene Inc., Carlsbad, CA), total RNA was prepared using the TRIzol reagent following the instructions of the supplier (Invitrogen, Karlsruhe, Germany). RNA concentrations were quantified by spectrophotometric OD260 measurement and integrity of RNA was checked by agarose gel electrophoresis. First strand cDNA was synthesized in a total volume of 21 μl using 2 μg of total RNA each, 500 ng of oligo-(dT12–18)-primers (Invitrogen) and SuperScript II reverse transcriptase according to the manufacturer's protocol (Invitrogen).Real-Time RT-PCRReal-time RT-PCR was performed using the SYBR Green I reagent on the ABI PRISM 7700 sequence detection system (Applied Biosystems, Foster City, CA). PCR reactions were performed in a total volume of 30 μl containing 26.8 μl of 1× SYBR Green PCR master mix (Applied Biosystems), 0.4 μl undiluted first strand cDNA, and 1.4 μl of 2.5 μmol/L forward and reverse primer (Eurogentec, Seraing, Belgium) each. To enable calculation of relative expression levels, serial dilutions (undiluted, 1:3, 1:9, and 1:27) of cDNA of the cell lines IMR-32 or CHP-134 (for assessment of interassay variance and comparison of real-time RT-PCR results to oligonucleotide array data) were used for the generation of standard curves of each gene separately. Oligonucleotides hybridizing specifically to corresponding sequences of control genes PBGD, PPIA, PGK1, HPRT1, SDHA, and LMNB1 as well as target genes PCBP4, SNAP91, BASP1, DBH, IGFBP7, HSPA5, STMN4, TUBA3, IFI27, PRAME, ROBO1, CLSTN3, CADPS, and EVL served as primers in PCR reactions (Tables 1and 2). Oligonucleotides were selected in successive exons (intron-spanning) for each gene except for TUBA3 to avoid amplification of contaminating genomic DNA. PCR reactions were performed in duplicates using 96-well optical reaction plates with optical caps (Applied Biosystems). Cycling conditions consisted of a single incubation step at 50°C for 2 minutes and a subsequent heating to 95°C for 10 minutes, followed by 40 cycles of 15 seconds at 95°C and 60 seconds at 60°C. To evaluate amplification of genomic DNA or nonspecific products, aliquots of each reaction mixture were analyzed by agarose gel electrophoresis.Table 1Control Genes Evaluated in This Study and Oligonucleotide Sequences Used as Primers for AmplificationSymbolGene nameSequenceAccession no.LMNB1 forLamin B15′-GCTGCTCCTCAACTATGCTAAGAA-3′NM_005573LMNB1 rev5′-TCTTTCGAATTCAGTGCTGCTTC-3′PBGD forPorphobilinogen-deaminase (Hydroxymethylbilane synthase)5′-CTACTTTCCAAGCGGAGCCAT-3′NM_000190PBGD rev5′-CCACGCGAATCACTCTCATCT-3′PPIA forPeptidylprolyl isomerase A5′-GCTCGTGCCGTTTTGCA-3′NM_021130PPIA rev5′-GCAAACAGCTCAAAGGAGACG-3′PGK1 forPhosphoglycerate kinase 15′-AGGGAAAAGATGCTTCTGGG-3′NM_000291PGK1 rev5′-AAGTGAAGCTCGGAAAGCTTCTAT-3′SDHA forSuccinate dehydrogenase complex, subunit A, flavoprotein (Fp)5′-TGGGAACAAGAGGGCATCTG-3′NM_004168SDHA rev5′-CCACCACTGCATCAAATTCATG-3′HPRT1 forHypoxanthine phosphoribosyltransferase 15′-TGACACTGGCAAAACAATGCA-3′NM_000194HPRT1 rev5′-GGTCCTTTTCACCAGCAAGCT-3′Forward and reverse primers are indicated by "for" and "rev", respectively, following the gene symbol. Open table in a new tab Table 2Target Genes Evaluated in This Study and Oligonucleotide Sequences Used as Primers for AmplificationSymbolGene nameSequenceAccession no.TUBA3 forTubulin, alpha 35′-CATTGAAAAGTTGTGGTCTGATCA-3′NM_006009TUBA3 rev5′-GCTTGGGTCTGTAACAAAGCAT-3′STMN4 forStathmin-like 45′-GGCCCAGAAGATGGAATCCAA-3′NM_030795STMN4 rev5′-GCACCTCCTCGGCGTGCTT-3′IGFBP7 forInsulin-like growth factor binding protein 75′-CCAGGTCAGCAAGGGCACCT-3′NM_001553IGFBP7 rev5′-CAGTGACATTCCAGATGTCCTT-3′HSPA5 forHeat shock 70-kd protein 55′-CTACAGCTTCTGATAATCAACCA-3′NM_005347HSPA5 rev5′-CCACGAGGAGCAGGAGGAAT-3′DBH forDopamine beta-hydroxylase5′-CAGAAGTACTTCCACCTCATCA-3′NM_000787DBH rev5′-GTCGCGGTTGAAGGAGTTCCA-3′BASP1 forBrain abundant, membrane attached signal protein 15′-GAAAGCCAAGGAGAAAGACAAGA-3′NM_006317BASP1 rev5′-CGGCCTTGCCCTCGGCGT-3′EVL forEnah/Vasp-like5′-CCTGCTGGGAGCGTGAATGA-3′NM_016337EVL rev5′-CCTCCTTCACCTTGTGGAGC-3′PCBP4 forPoly(rC) binding protein 45′-CCTGAACGCATCACCACCAT-3′NM_020418PCBP4 rev5′-CTGACTGGCAGGGATGACAA-3′IFI27 forInterferon, alpha-inducible protein 275′-GAGTTGCCTCGGGCAGCCT-3′NM_005532IFI27 rev5′-GCCCAGGATGAACTTGGTCAA-3′SNAP91 forSynaptosomal-associated protein5′-GCGGATCTTAACATCAAGGATTT-3′BC060818SNAP91 rev91-kd homolog (mouse)5′-GTACTGGTGGCTCCCTTTGA-3′PRAME forPreferentially expressed antigen in melanoma5′-TGCAGGCTCTCTATGTGGACT-3′NM_006115PRAME rev5′-ATGCACATGCCCTTCCATTCCGA-3′ROBO1 forRoundabout, axon guidance receptor, homolog 1 (Drosophila)5′-GCGTGCAGTACTAAGGGAACA-3′NM_002941ROBO1 rev5′-GGCTTCTTACATGAACATAATGAA-3′CADPS forCa2+-dependent activator protein for secretion5′-CAGCTTCCAAATATGTGGATGTA-3′NM_003716CADPS rev5′-CATCTCCTCATTGACCTTATCA-3′CLSTN3 forCalsyntenin 35′-GTTATCGGCTGCGACACGGA-3′NM_014718CLSTN3 rev5′-GGTTCATGCTGTGCAGGACATT-3′Forward and reverse primers are indicated by "for" and "rev," respectively, following the gene symbol. Open table in a new tab Oligonucleotide Array AnalysisGene expression profiles of seven primary neuroblastoma samples (three tumors of stage 4 and four tumors of stage 4S) were generated using Agilent Human 1A and 1B oligonucleotide microarrays (Agilent Technologies, Palo Alto, CA). For each tumor sample, 2 μg of total RNA were linear amplified and aliquots were labeled with either Cy5 or Cy3 dyes (Perkin Elmer, Rodgau, Germany) using Agilent's Low RNA Input Fluor Linear Amp kit according to the manufacturer's protocol. One μg of Cy-labeled cRNA samples of each tumor specimen was hybridized along with the same amount of reverse-color Cy-labeled product from a pool consisting of equal amounts of cRNA from all tumor samples analyzed. After dye correction, target gene expression levels were normalized to the global mean array intensity of the respective sample. Data analysis was performed using the Luminator Gene Expression Data Analysis System, version 2.0 (Rosetta Inpharmatics, Seattle, WA).Data AnalysisAfter averaging duplicate Ct measurements, relative expression levels were calculated according to the standard curve method as described by the user bulletin 2 of the ABI Prism 7700 sequence detection system (Applied Biosystems). Calculation of the control gene stability measure M was performed according to Vandesompele and colleagues.11Vandesompele J De Preter K Pattyn F Poppe B Van Roy N De Paepe A Speleman F Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.Genome Biol. 2002; 3: 0034.1-0034.12Crossref Google Scholar In brief, real-time RT-PCR expression levels aij of n internal control genes are determined in m tissue samples. An array Ajk of m elements is calculated for every combination of two internal control genes j and k, consisting of the log2-transformed expression ratios aij/aik (Equation 1). The pairwise variation Vjk for the control genes j and k represents the SD of Ajk elements (Equation 2). The gene stability measure Mj for control gene j is the arithmetic mean of all pairwise variations Vjk (Equation 3).(∀ j,k ∈ [1,n] and j ≠ k): Ajk={log2(aijaik)}i=1→m(1) Vjk=st.dev.(Ajk)(2) Mj=∑k=1nVjkn-1(3) Normalization factors NF2 to NF6 were determined for each sample by calculating the geometrical mean of expression levels of the two best performing control genes (NF2) and stepwise inclusion of additional control genes in the order of their expression stability (NF3 to NF6).11Vandesompele J De Preter K Pattyn F Poppe B Van Roy N De Paepe A Speleman F Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.Genome Biol. 2002; 3: 0034.1-0034.12Crossref Google Scholar To analyze independence of the proposed normalization factor of stage and MYCN status of the tumor, distributions of normalization factor values within each subgroup were compared to one another and statistically evaluated using the Kruskal-Wallis and Mann-Whitney U-tests. Comparison of target gene expression levels determined by real-time RT-PCR and oligonucleotide array was enabled by calibrating transcript abundances measured by either method to the minimal expression value of the respective gene within the set of tumors analyzed.ResultsRelative expression levels of the putative control genes porphobilinogen-deaminase (PBGD),19Westerman BA Neijenhuis S Poutsma A Steenbergen RD Breuer RH Egging M van Wijk IJ Oudejans CB Quantitative reverse transcription-polymerase chain reaction measurement of HASH1 (ASCL1), a marker for small cell lung carcinomas with neuroendocrine features.Clin Cancer Res. 2002; 8: 1082-1086PubMed Google Scholar cyclophilin A (PPIA),20Korz C Pscherer A Benner A Mertens D Schaffner C Leupolt E Dohner H Stilgenbauer S Lichter P Evidence for distinct pathomechanisms in B-cell chronic lymphocytic leukemia and mantle cell lymphoma by quantitative expression analysis of cell cycle and apoptosis-associated genes.Blood. 2002; 99: 4554-4561Crossref PubMed Scopus (122) Google Scholar, 21Feroze-Merzoug F Berquin IM Dey J Chen YQ Peptidylprolyl isomerase A (PPIA) as a preferred internal control over GAPDH and beta-actin in quantitative RNA analyses.Biotechniques. 2002; 32: 776-782Crossref PubMed Scopus (58) Google Scholar phosphoglycerate kinase (PGK1),20Korz C Pscherer A Benner A Mertens D Schaffner C Leupolt E Dohner H Stilgenbauer S Lichter P Evidence for distinct pathomechanisms in B-cell chronic lymphocytic leukemia and mantle cell lymphoma by quantitative expression analysis of cell cycle and apoptosis-associated genes.Blood. 2002; 99: 4554-4561Crossref PubMed Scopus (122) Google Scholar lamin B1 (LMNB1),20Korz C Pscherer A Benner A Mertens D Schaffner C Leupolt E Dohner H Stilgenbauer S Lichter P Evidence for distinct pathomechanisms in B-cell chronic lymphocytic leukemia and mantle cell lymphoma by quantitative expression analysis of cell cycle and apoptosis-associated genes.Blood. 2002; 99: 4554-4561Crossref PubMed Scopus (122) Google Scholar hypoxanthine phosphoribosyltransferase 1 (HPRT1),11Vandesompele J De Preter K Pattyn F Poppe B Van Roy N De Paepe A Speleman F Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.Genome Biol. 2002; 3: 0034.1-0034.12Crossref Google Scholar and succinate dehydrogenase complex subunit A (SDHA)11Vandesompele J De Preter K Pattyn F Poppe B Van Roy N De Paepe A Speleman F Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.Genome Biol. 2002; 3: 0034.1-0034.12Crossref Google Scholar were determined in 64 primary neuroblastoma samples by real-time RT-PCR using SYBR Green 1 dye detection. Aliquots of the reactions were analyzed by agarose gel electrophoresis to evaluate PCR specificity. Detection of a single specific amplification product of the expected length and absence of visible primer dimers demonstrated a high PCR specificity in all cases. Amplification efficiencies of real-time RT-PCR reactions were compared by plotting the ΔCt values of different primer combinations of serial dilutions against the LOG of starting template concentrations. Resulting slopes ranged from −0.84 to 1.18 for different reactions (data not shown), which indicates significantly varying amplification efficiencies.18Livak KJ Schmittgen TD Analysis of relative gene expression data using real-time quantitative PCR and the 2(-delta delta C(T)) method.Methods. 2001; 25: 402-408Crossref PubMed Scopus (119102) Google Scholar Thus, amplification results of the various genes investigated in this project are not directly comparable to one another. Relative expression levels were therefore determined by adjusting Ct values of the samples to standard curves derived from serial cDNA dilutions of neuroblastoma cell lines IMR-32 or CHP-134, which were generated for each gene in every run separately.To determine the interassay variation of the real-time polymerase-chain reaction, expression levels of four selected genes (PBGD, PPIA, PGK1, and LMNB1) were analyzed in two samples (patient 587 and neuroblastoma cell line IMR-5) in 10 independent PCR runs. After adjustment of the Ct values of each gene to their respective standard curve, the resulting relative expression levels varied from 1.3-fold to 2.4-fold between minimum and maximum values with coefficients of variation ranging from 9 to 25% (Table 3), which is in the range of results that have been reported previously.16Hamalainen HK Tubman JC Vikman S Kyrola T Ylikoski E Warrington JA Lahesmaa R Identification and validation of endogenous reference genes for expression profiling of T helper cell differentiation by quantitative real-time RT-PCR.Anal Biochem. 2001; 299: 63-70Crossref PubMed Scopus (216) Google Scholar, 18Livak KJ Schmittgen TD Analysis of relative gene expression data using real-time quantitative PCR and the 2(-delta delta C(T)) method.Methods. 2001; 25: 402-408Crossref PubMed Scopus (119102) Google Scholar, 22Schmittgen TD Zakrajsek BA Mills AG Gorn V Singer MJ Reed MW Quantitative reverse transcription-polymerase chain reaction to study mRNA decay: comparison of endpoint and real-time methods.Anal Biochem. 2000; 285: 194-204Crossref PubMed Scopus (843) Google Scholar These data, however, indicate that expression values of distinct samples differing less than twofold cannot reliably be assigned to distinct transcript abundances, because they might result from variations of the experimental procedure.Table 3Determination of the Interassay Variance of RealTime RT-PCR ExperimentsPBGDLMNB1PPIAPGK1Max/min IMR-51.71.82.22.1Coefficient of variation (%)15.917.622.217.8Max/min patient 5872.01.32.42.0Coefficient of variation (%)22.58.925.020.2Control gene expression levels of two samples (neuroblastoma cell line IMR-5 and patient 587) were analyzed in 10 independent PCR runs. Indicated are the fold-differences between maximum and minimum values and the coefficient of variation of each control gene. Open table in a new tab Expression stability of the six control genes was assessed in primary neuroblastoma using a calculation termed as "internal control gene-stability measure M" that was recently published by Vandesompele and colleagues.11Vandesompele J De Preter K Pattyn F Poppe B Van Roy N De Paepe A Speleman F Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.Genome Biol. 2002; 3: 0034.1-0034.12Crossref Google Scholar In this calculation, the pairwise variation of every control gene with all other control genes is determined as the SD of the logarithmically transformed expression ratios. The internal control gene stability measure M is defined as the average pairwise variation of a particular gene with all other genes (see Material and Methods). Low M values correspond to stable expression levels and vice versa. Stepwise exclusion of the gene with the highest M value thus results in a ranking of the genes in order of their expression stability, which ends up with the two housekeeping genes showing the most stable expression among the samples. Calculation of M values for the control genes examined in this project identified HPRT1 and SDHA as the most stably expressed control genes, followed by PPIA, PBGD, and PGK1, whereas LMNB1 turned out to be the strongest regulated gene (Figure 1 and Table 4).Table 4Order of Expression Stability of Control Genes in Primary NeuroblastomaGene rankingDistance (bp)*Nucleotide distances of the PCR amplicons to the 3′ end of the respective transcript.LMNB12077PGK11807PBGD1315PPIA1503HPRT1/SDHA1331/2054Control genes are ranked in order of increasing variability from bottom to the top. The two most stable control genes HPRT1 and SDHA cannot be ranked because of the requirement of gene ratios for gene stability measure M calculation.* Nucleotide distances of the PCR amplicons to the 3′ end of the respective transcript. Open table in a new tab Although RNA quality of each sample had been carefully assessed, it cannot be ruled out that small amounts of RNA degradation might have contributed to sample-to-sample variability of measured expression values. Because oligo(dT) primers were used for mRNA conversion into cDNA, RNA degradation is expected to result in increased variations of RT-PCR results corresponding to the distance of the PCR amplicon to the poly(A) tail of the transcript. Thus, th
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