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JMD 2005, Vol. 7, No. 1
Copyright © 2005 American Society for Investigative Pathology & Association for Molecular Pathology

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

Matthias Fischer, Matthias Skowron and Frank Berthold

From the Department of Pediatric Oncology, University Children’s Hospital Cologne, Cologne, Germany


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
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.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Quantification of target gene expression levels by real-time reverse transcriptase-polymerase chain reaction (RT-PCR)1, 2 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.3, 4, 5, 6, 7, 8, 9 A common feature of most transcript quantification techniques is the requirement for normalization, because a number of variables may influence the results.2, 10 Ideally, abundances of mRNA levels are determined as transcript copies per cell.2, 11 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.12, 13 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.10, 14 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 ß-actin and GAPDH exhibit considerably varying transcript levels in cells of different histological origin and under various physiological or experimental conditions.2, 11, 13, 15, 16, 17 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.2, 10, 11, 16, 18

The 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 Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Sample Preparation and cDNA Synthesis
Neuroblastoma 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-PCR
Real-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 1x 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 1Go and 2)Go . 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.


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  		Table 1. Control Genes Evaluated in This Study and Oligonucleotide Sequences Used as Primers for Amplification

 

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  		Table 2. Target Genes Evaluated in This Study and Oligonucleotide Sequences Used as Primers for Amplification

 
Oligonucleotide Array Analysis
Gene 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 Analysis
After 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.11 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) .

({forall} j,k [1,n] and j != k):

(1)

(2)

(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).11 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.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Relative expression levels of the putative control genes porphobilinogen-deaminase (PBGD),19 cyclophilin A (PPIA),20, 21 phosphoglycerate kinase (PGK1),20 lamin B1 (LMNB1),20 hypoxanthine phosphoribosyltransferase 1 (HPRT1),11 and succinate dehydrogenase complex subunit A (SDHA)11 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 {Delta}Ct 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.18 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)Go , which is in the range of results that have been reported previously.16, 18, 22 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.


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  		Table 3. Determination of the Interassay Variance of Real-Time RT-PCR Experiments

 
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.11 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 (FigureGo 1and Table 4Go ).



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  		Figure 1. Average expression stability values M of remaining control genes during stepwise exclusion of the least stable reference genes. Calculations were performed according to Vandesompele and colleagues11 (see text).

 

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  		Table 4. Order of Expression Stability of Control Genes in Primary Neuroblastoma

 
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, the proximity of PCR amplicons to the poly(A) tail of control gene mRNAs were compared to the M values determined for the respective gene. Table 4Go shows that distances of PCR amplicons to the poly(A) tail of the transcripts did not correlate with measured expression stabilities, which suggests that inconsistencies of RNA integrity did not contribute considerably to sample-to-sample variations of control gene mRNA levels.

The use of averaged expression levels of multiple control genes that are not co-regulated has been suggested to enhance reliability of normalization of real-time RT-PCR data,11 because individual outlying values of single control genes might be compensated by expression levels of additional genes. To test whether normalization to averaged expression levels of multiple control genes results in more accurate determination of target gene transcript abundances, the geometrical mean of the two best-performing control genes SDHA and HPRT1 was calculated for each sample and denoted as normalization factor 2 (NF2). Likewise, normalization factors NF3 to NF6 were calculated by stepwise inclusion of additional control genes in the order of their expression stability. Expression levels of 14 target genes (PCBP4, DBH, SNAP91, HSPA5, BASP1, IGFBP7, STMN4, TUBA3, IFI27, PRAME, ROBO1, CLSTN3, CADPS, and EVL) were measured by real-time RT-PCR in seven primary neuroblastoma samples and normalized to SDHA, HPRT1, and NF2 to NF6 separately, and were then compared to their transcript abundances determined by oligonucleotide array analysis of the same samples. Correlation of relative expression levels determined by the two methods was assessed by calculating Pearson’s correlation coefficient r for each gene. In three cases (EVL, TUBA3, and CLSTN3), no or very poor correlation (r < 0.5) of real-time RT-PCR and array data were observed irrespective of the normalization strategy applied (Table 5)Go . The remaining 11 genes correlated best after normalization to NF2 (Table 5)Go , with nine genes showing a high correlation (r ≥ 0.8) of relative expression levels. Inclusion of additional genes did not further improve but rather resulted in a slightly impaired overall correlation suggesting that normalization of target gene mRNA levels to the geometrical mean of HPRT1 and SDHA transcript abundances yields the most reliable results.


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  		Table 5. Correlation of Expression Data Determined by Real-Time RT-PCR after Normalization to Various Normalization Factors and Oligonucleotide-Array Analysis

 
Because identification of differentially expressed genes in the various subtypes of neuroblastoma is a major goal of current neuroblastoma research, a normalization factor serving as an internal control should be not associated with particular biological phenotypes of this malignancy. The panel of tumors analyzed in this study comprised 26 samples derived from localized disease (stage 1 to 3), 19 samples of stage 4S disease that usually shows spontaneous regression and 19 samples of stage 4 neuroblastoma. Nine samples derived from tumors of various stages contained an amplification of the oncogene MYCN, which is associated with an unfavorable prognosis. To ascertain independence of the normalization factor from stage or MYCN amplification status of the tumor, geometrical means of HPRT1 and SDHA expression levels were calculated for each sample and distributions of the resulting values were compared between the groups. No correlation was observed for either stage (P = 0.985) or MYCN amplification (P = 0.664), indicating that the proposed normalization factor is not associated with the major biological phenotypes of this malignancy (Figure 2)Go .



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  		Figure 2. Distribution of normalization factor NF2 values among the samples with regard to stage (A) and MYCN amplification status (B) of the tumor. The number of tumor samples of each category is indicated by (n). NF2 values are depicted in arbitrary units.

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Expression levels of target genes measured by real-time RT-PCR are usually normalized by comparison with transcript abundances of reference genes. However, evaluation of expression stability of well established and frequently used control genes such as ß-actin and GAPDH revealed that expression levels of control genes may vary considerably in the samples of interest,2, 11, 13, 15, 16, 17 which may lead to a serious distortion of experimental results. It has been shown by gene expression profiling using serial analysis of gene expression,23 for example, that induction of expression of the oncogene MYCN in a neuroblastoma cell line results in up-regulation of the putative control gene GAPDH,12 which has been used in many studies for normalization.4, 5, 6, 8, 9 If GAPDH is used as an internal control for experiments investigating differential gene expression between MYCN-amplified tumors that usually show enhanced MYCN expression24 and nonamplified neuroblastomas, which is a major topic of current neuroblastoma research,12, 25 genes that are up-regulated in MYCN-amplified tumors might be missed and genes that are stably expressed might be classified as down-regulated by mistake because of the co-regulation of MYCN and GAPDH expression levels. This example illustrates the necessity for validation of control genes for every single cell type. Accordingly, evaluation of expression stability of control genes for each individual experiment has been claimed in a number of previous publications.2, 10, 11, 16, 18 In the present study, the six putative control genes PPIA, PGK1, LMNB1, HPRT1, SDHA, and PBGD were evaluated regarding their expression stability in various subtypes of primary neuroblastoma. Calculation of the internal control gene stability measure M11 revealed that SDHA and HPRT1 exhibit the most constant expression levels among the samples, followed by PPIA, PBGD, PGK1, and LMNB1.

It has been suggested previously, that normalization to the geometrical mean of more than one control gene compensates for outlying values of single reference genes in individual samples and may therefore more accurately reflect transcript abundances of target genes.11 In the present study, this hypothesis was tested by comparison of expression values of 14 target genes determined by real-time RT-PCR and by oligonucleotide array expression profiling in seven primary tumor samples. Normalization to the geometrical mean of mRNA levels of the two best-performing control genes SDHA and HPRT1 improved correlation of results as compared to normalization to expression values of each of these genes alone. Inclusion of additional genes into the normalization factor did not further enhance correlation of transcript abundances, indicating that normalization to averaged expression levels of SDHA and HPRT1 reveals reliable results. Expression levels of three target genes did not correlate irrespective of the normalization factor used, which might in part be because of distinct splice variants measured by either method. This suggestion is supported by the observation that expression levels of EVL and CLSTN3 determined by real-time RT-PCR correlated well with transcript abundances obtained by serial analysis of gene expression (r = 0.77 and 0.82, respectively, data not shown).

The pediatric tumor neuroblastoma shows remarkable heterogeneity in its biological and clinical behavior.26 Some tumors regress spontaneously, in particular those of children that have been classified as stage 4S disease. In contrast, many other patients show an adverse outcome despite intensive therapy. Tumors of these children usually present as stage 4 disease and frequently harbor a genomic amplification of the oncogene MYCN. The underlying molecular mechanisms of these completely different biological subtypes are still to be characterized. A major goal of current neuroblastoma research is the identification of genes that are responsible for either spontaneous regression or fatal progression of the disease,12, 25, 27, 28 and quantitative PCR is increasingly used to evaluate correlation of marker gene expression levels with the biological phenotype of the tumor or outcome of disease.3, 4, 5, 6, 7, 9 Comparison of expression levels of candidate genes by real-time RT-PCR experiments therefore requires a normalization factor that is supposed to show no considerable variation between the different subtypes. In the present study, no significant difference was observed for distributions of normalization factor values with regard to stage and MYCN amplification status (Figure 2)Go , which suggests that the normalization factor is not associated with the major biological and clinical subtypes of neuroblastoma and that it therefore represents a suitable control for real-time RT-PCR experiments in this malignancy.

In a recent study by Vandesompele and colleagues,11 expression stability of 10 putative control genes including PBGD (denoted as HMBS in that study), SDHA, and HPRT1 was investigated in 34 neuroblastoma cell lines using real-time RT-PCR. Although overall expression stability of reference genes appeared to be slightly lower in the cell lines in comparison to primary tumors analyzed in the present work as indicated by higher M values, both SDHA and HPRT1 were shown to exhibit rather constant expression levels and were ranked among the three most stable control genes. Thus, normalization of target gene expression levels to a normalization factor consisting of HPRT1 and SDHA might be suitable for both primary neuroblastoma and neuroblastoma cell lines.

In conclusion, this study provides additional evidence to previous suggestions that control genes in real-time RT-PCR experiments analyzing transcript abundances have to be evaluated for each individual cell type. Furthermore, it is demonstrated that normalization to the geometrical mean of more than one control gene may reduce the impact of varying control gene expression levels by compensating single outlying values. Finally, we propose that mRNA levels of target genes in primary neuroblastoma determined by real-time RT-PCR are appropriately normalized using the geometrical mean of expression levels of the control genes HPRT1 and SDHA, which may result in an enhanced reliability of studies investigating correlation of marker gene expression levels with clinical and biological characteristics of the tumor.


   Acknowledgments
 
We thank Yvonne Kahlert for excellent technical assistance; Dr. André Oberthür for providing expression data determined by oligonucleotide array analysis; Dr. Barbara Hero, Tom Christiansen, and Dr. Christoph Fischer for lessons in statistical analysis; Hichem Gallala for helpful discussions; Dr. Rüdiger Spitz and Dr. Ralf Küppers for critical reading of the manuscript; and the Competence Network Pediatric Oncology and Hematology (KPOH, supported by the Bundesministerum für Bildung und Forschung) for providing tumor samples.


   Footnotes
 
Address reprint requests to Dr. Matthias Fischer, University Children’s Hospital Cologne, Department of Pediatric Oncology, Joseph-Stelzmann-Str. 9, 50924 Cologne, Germany. E-mail: matthias.fischer{at}medizin.uni-koeln.de

Supported by the Fördergesellschaft Kinderkrebs-Neuroblastom-Forschung e.V. and Kind-Philipp-Stiftung (to M.S.).

M.F. and M.S. contributed equally to this work.

Accepted for publication July 16, 2004.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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F. Westermann, K.-O. Henrich, J. S. Wei, W. Lutz, M. Fischer, R. Konig, R. Wiedemeyer, V. Ehemann, B. Brors, K. Ernestus, et al.
High Skp2 Expression Characterizes High-Risk Neuroblastomas Independent of MYCN Status
Clin. Cancer Res., August 15, 2007; 13(16): 4695 - 4703.
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G. Michels, F. Er, M. Eicks, S. Herzig, and U. C. Hoppe
Long-Term and Immediate Effect of Testosterone on Single T-Type Calcium Channel in Neonatal Rat Cardiomyocytes
Endocrinology, November 1, 2006; 147(11): 5160 - 5169.
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M. Fischer, A. Oberthuer, B. Brors, Y. Kahlert, M. Skowron, H. Voth, P. Warnat, K. Ernestus, B. Hero, and F. Berthold
Differential Expression of Neuronal Genes Defines Subtypes of Disseminated Neuroblastoma with Favorable and Unfavorable Outcome
Clin. Cancer Res., September 1, 2006; 12(17): 5118 - 5128.
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K.-O. Henrich, M. Fischer, D. Mertens, A. Benner, R. Wiedemeyer, B. Brors, A. Oberthuer, F. Berthold, J. S. Wei, J. Khan, et al.
Reduced Expression of CAMTA1 Correlates with Adverse Outcome in Neuroblastoma Patients
Clin. Cancer Res., January 1, 2006; 12(1): 131 - 138.
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