Katleen De Preter

Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes

BackgroundGene-expression analysis is increasingly important in biological research, with real-time reverse transcription PCR (RT-PCR) becoming the method of choice for high-throughput and accurate expression profiling of selected genes. Given the increased sensitivity, reproducibility and large dynamic range of this methodology, the requirements for a proper internal control gene for normalization have become increasingly stringent. Although housekeeping gene expression has been reported to vary considerably, no systematic survey has properly determined the errors related to the common practice of using only one control gene, nor presented an adequate way of working around this problem.ResultsWe outline a robust and innovative strategy to identify the most stably expressed control genes in a given set of tissues, and to determine the minimum number of genes required to calculate a reliable normalization factor. We have evaluated ten housekeeping genes from different abundance and functional classes in various human tissues, and demonstrated that the conventional use of a single gene for normalization leads to relatively large errors in a significant proportion of samples tested. The geometric mean of multiple carefully selected housekeeping genes was validated as an accurate normalization factor by analyzing publicly available microarray data.ConclusionsThe normalization strategy presented here is a prerequisite for accurate RT-PCR expression profiling, which, among other things, opens up the possibility of studying the biological relevance of small expression differences.

Quantification of MYCN, DDX1, and NAG gene copy number in neuroblastoma using a real-time quantitative PCR assay.

Amplification of the proto-oncogene MYCN is a strong adverse prognostic factor in neuroblastoma patients in all tumor stages. The status of the MYCN gene has become an important factor in clinical decision making and therapy stratification. Consequently, fast and accurate assessment of MYCN gene copy number is of the utmost importance and the use of two independent methods to determine MYCN status is recommended. For these reasons we have developed and evaluated a real-time quantitative PCR (Q-PCR) assay as an alternative for time-consuming Southern blot analysis (SB), and as a second independent technique in parallel with fluorescence in situ hybridization (FISH) analysis. Advantages of Q-PCR are a large dynamic range of quantification, no requirement for post-PCR sample handling and the need for very small amounts of starting material. The accuracy of the assay was illustrated by measurement of MYCN single gene copy changes in DNA samples of two patients with 2p deletion and duplication, respectively. Two different detection chemistries i.e., a sequence specific TaqMan probe and a generic DNA binding dye SYBR Green I were evaluated and shown to yield similar results. Also, two different calculation methods for copy number determination were used i.e., the kinetic method and the comparative CT method, and shown to be equivalent. In total, 175 neuroblastoma samples with known MYCN status, as determined by FISH and/or SB, were examined. Q-PCR data were highly concordant with FISH and SB data. In addition to MYCN copy number evaluation, DDX1 and NAG gene copy numbers were determined using a similar Q-PCR strategy. Survival analysis pointed out that DDX1 and/or NAG amplification has no additional adverse effect on prognosis.

Meta-analysis of Neuroblastomas Reveals a Skewed ALK Mutation Spectrum in Tumors with MYCN Amplification

Purpose: Activating mutations of the anaplastic lymphoma kinase (ALK) were recently described in neuroblastoma. We carried out a meta-analysis of 709 neuroblastoma tumors to determine their frequency and mutation spectrum in relation to genomic and clinical parameters, and studied the prognostic significance of ALK copy number and expression. Experimental Design: The frequency and type of ALK mutations, copy number gain, and expression were analyzed in a new series of 254 neuroblastoma tumors. Data from 455 published cases were used for further in-depth analysis. Results: ALK mutations were present in 6.9% of 709 investigated tumors, and mutations were found in similar frequencies in favorable [International Neuroblastoma Staging System (INSS) 1, 2, and 4S; 5.7%] and unfavorable (INSS 3 and 4; 7.5%) neuroblastomas (P = 0.087). Two hotspot mutations, at positions R1275 and F1174, were observed (49% and 34.7% of the mutated cases, respectively). Interestingly, the F1174 mutations occurred in a high proportion of MYCN-amplified cases (P = 0.001), and this combined occurrence was associated with a particular poor outcome, suggesting a positive cooperative effect between both aberrations. Furthermore, the F1174L mutant was characterized by a higher degree of autophosphorylation and a more potent transforming capacity as compared with the R1275Q mutant. Chromosome 2p gains, including the ALK locus (91.8%), were associated with a significantly increased ALK expression, which was also correlated with poor survival. Conclusions: ALK mutations occur in equal frequencies across all genomic subtypes, but F1174L mutants are observed in a higher frequency of MYCN-amplified tumors and show increased transforming capacity as compared with the R1275Q mutants. Clin Cancer Res; 16(17); 4353–62. ©2010 AACR.

Unequivocal Delineation of Clinicogenetic Subgroups and Development of a New Model for Improved Outcome Prediction in Neuroblastoma

PURPOSE Neuroblastoma is a genetically heterogeneous pediatric tumor with a remarkably variable clinical behavior ranging from widely disseminated disease to spontaneous regression. In this study, we aimed for comprehensive genetic subgroup discovery and assessment of independent prognostic markers based on genome-wide aberrations detected by comparative genomic hybridization (CGH). MATERIALS AND METHODS Published CGH data from 231 primary untreated neuroblastomas were converted to a digitized format suitable for global data mining, subgroup discovery, and multivariate survival analyses. RESULTS In contrast to previous reports, which included only a few genetic parameters, we present here for the first time a strategy that allows unbiased evaluation of all genetic imbalances detected by CGH. The presented approach firmly established the existence of three different clinicogenetic subgroups and indicated that chromosome 17 status and tumor stage were the only independent significant predictors for patient outcome. Important new findings were: (1) a normal chromosome 17 status as a delineator of a subgroup of presumed favorable-stage tumors with highly increased risk; (2) the recognition of a survivor signature conferring 100% 5-year survival for stage 1, 2, and 4S tumors presenting with whole chromosome 17 gain; and (3) the identification of 3p deletion as a hallmark of older age at diagnosis. CONCLUSION We propose a new regression model for improved patient outcome prediction, incorporating tumor stage, chromosome 17, and amplification/deletion status. These findings may prove highly valuable with respect to more reliable risk assessment, evaluation of clinical results, and optimization of current treatment protocols.

Human fetal neuroblast and neuroblastoma transcriptome analysis confirms neuroblast origin and highlights neuroblastoma candidate genes.

BackgroundNeuroblastoma tumor cells are assumed to originate from primitive neuroblasts giving rise to the sympathetic nervous system. Because these precursor cells are not detectable in postnatal life, their transcription profile has remained inaccessible for comparative data mining strategies in neuroblastoma. This study provides the first genome-wide mRNA expression profile of these human fetal sympathetic neuroblasts. To this purpose, small islets of normal neuroblasts were isolated by laser microdissection from human fetal adrenal glands.ResultsExpression of catecholamine metabolism genes, and neuronal and neuroendocrine markers in the neuroblasts indicated that the proper cells were microdissected. The similarities in expression profile between normal neuroblasts and malignant neuroblastomas provided strong evidence for the neuroblast origin hypothesis of neuroblastoma. Next, supervised feature selection was used to identify the genes that are differentially expressed in normal neuroblasts versus neuroblastoma tumors. This approach efficiently sifted out genes previously reported in neuroblastoma expression profiling studies; most importantly, it also highlighted a series of genes and pathways previously not mentioned in neuroblastoma biology but that were assumed to be involved in neuroblastoma pathogenesis.ConclusionThis unique dataset adds power to ongoing and future gene expression studies in neuroblastoma and will facilitate the identification of molecular targets for novel therapies. In addition, this neuroblast transcriptome resource could prove useful for the further study of human sympathoadrenal biogenesis.

Measurable impact of RNA quality on gene expression results from quantitative PCR

Compromised RNA quality is suggested to lead to unreliable results in gene expression studies. Therefore, assessment of RNA integrity and purity is deemed essential prior to including samples in the analytical pipeline. This may be of particular importance when diagnostic, prognostic or therapeutic conclusions depend on such analyses. In this study, the comparative value of six RNA quality parameters was determined using a large panel of 740 primary tumour samples for which real-time quantitative PCR gene expression results were available. The tested parameters comprise of microfluidic capillary electrophoresis based 18S/28S rRNA ratio and RNA Quality Index value, HPRT1 5′–3′ difference in quantification cycle (Cq) and HPRT1 3′ Cq value based on a 5′/3′ ratio mRNA integrity assay, the Cq value of expressed Alu repeat sequences and a normalization factor based on the mean expression level of four reference genes. Upon establishment of an innovative analytical framework to assess impact of RNA quality, we observed a measurable impact of RNA quality on the variation of the reference genes, on the significance of differential expression of prognostic marker genes between two cancer patient risk groups, and on risk classification performance using a multigene signature. This study forms the basis for further rational assessment of reverse transcription quantitative PCR based results in relation to RNA quality.

Mutational dynamics between primary and relapse neuroblastomas

Neuroblastoma is a malignancy of the developing sympathetic nervous system that is often lethal when relapse occurs. We here used whole-exome sequencing, mRNA expression profiling, array CGH and DNA methylation analysis to characterize 16 paired samples at diagnosis and relapse from individuals with neuroblastoma. The mutational burden significantly increased in relapsing tumors, accompanied by altered mutational signatures and reduced subclonal heterogeneity. Global allele frequencies at relapse indicated clonal mutation selection during disease progression. Promoter methylation patterns were consistent over disease course and were patient specific. Recurrent alterations at relapse included mutations in the putative CHD5 neuroblastoma tumor suppressor, chromosome 9p losses, DOCK8 mutations, inactivating mutations in PTPN14 and a relapse-specific activity pattern for the PTPN14 target YAP. Recurrent new mutations in HRAS, KRAS and genes mediating cell-cell interaction in 13 of 16 relapse tumors indicate disturbances in signaling pathways mediating mesenchymal transition. Our data shed light on genetic alteration frequency, identity and evolution in neuroblastoma.

Targeted Expression of Mutated ALK Induces Neuroblastoma in Transgenic Mice

ALK inhibitors induce complete tumor regression in a mouse model of ALK-driven neuroblastoma. Driving Neuroblastoma: A wALK in the Park Correlation doesn’t prove causation. For example, even though you may always see your neighbors walking their dog right before you find that odiferous pile of unscooped pooh, unless you directly witness a walkaway or use DNA testing to trace the culprit, you can’t prove that they did it. Demonstrating causation is even more important in cancer biology—just finding a prevalent mutation in people with a particular type of cancer isn’t enough to show that mutation is actually relevant to disease. Heukamp et al. now address the potential causative role of anaplastic lymphoma kinase (ALK) mutations in neuroblastoma. ALK mutations are found in most familial and some sporadic cases of neuroblastoma, a malignant tumor that affects children. To determine whether ALK mutations can drive the development of neuroblastoma, the authors introduced the most common ALK mutation into neural crest stem cells in mice. Tumors driven by this mutation resembled human neuroblastomas physiologically and mimicked the genetic structure of the disease. Mutated ALK and MYCN, another driver mutation for neuroblastoma, combined synergistically for tumor development. Heukamp et al. then used their new model to demonstrate that an ALK inhibitor currently in preclinical testing induced complete tumor regression in these mice; however, it remains to be seen whether these inhibitors will be useful in treating neuroblastoma in people. Activating anaplastic lymphoma kinase (ALK) mutations were recently detected in most familial and 10% of sporadic neuroblastomas. However, the role of mutated ALK in tumorigenesis remains elusive. We demonstrate that targeted expression of the most frequent and aggressive variant, ALKF1174L, is tumorigenic in mice. Tumors resembled human neuroblastomas in morphology, metastasis pattern, gene expression, and the presence of neurosecretory vesicles as well as synaptic structures. This ALK-driven neuroblastoma mouse model precisely recapitulated the genetic spectrum of the disease. Chromosomal aberrations were syntenic to those in human neuroblastoma, including 17q gain and MYCN oncogene amplification. Targeted ALKF1174L and MYCN coexpression revealed a strong synergism in inducing neuroblastoma with minimal chromosomal aberrations, suggesting that fewer secondary hits are required for tumor induction if both oncoproteins are targeted. Treatment of ALKF1174L transgenic mice with the ALK inhibitor TAE-684 induced complete tumor regression, indicating that tumor cells were addicted to ALKF1174L activity. We conclude that an activating mutation within the ALK kinase domain is sufficient to induce neuroblastoma development, and ALK inhibitors show promise for treating human neuroblastomas harboring ALK mutations.

arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays.

BackgroundThe availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH). One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment.ResultsWe have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment) supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser.ConclusionArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at http://medgen.ugent.be/arrayCGHbase/.

Accurate prediction of neuroblastoma outcome based on miRNA expression profiles.

For neuroblastoma, the most common extracranial tumour of childhood, identification of new biomarkers and potential therapeutic targets is mandatory to improve risk stratification and survival rates. MicroRNAs are deregulated in most cancers, including neuroblastoma. In this study, we analysed 430 miRNAs in 69 neuroblastomas by stem‐loop RT‐qPCR. Prediction of event‐free survival (EFS) with support vector machines (SVM) and actual survival times with Cox regression‐based models (CASPAR) were highly accurate and were independently validated. SVM‐accuracy for prediction of EFS was 88.7% (95% CI: 88.5–88.8%). For CASPAR‐based predictions, 5y‐EFS probability was 0.19% (95% CI: 0–38%) in the CASPAR‐predicted short survival group compared with 0.78% (95%CI: 64–93%) in the CASPAR‐predicted long survival group. Both classifiers were validated on an independent test set yielding accuracies of 94.74% (SVM) and 5y‐EFS probabilities as 0.25 (95% CI: 0.0–0.55) for short versus 1 ± 0.0 for long survival (CASPAR), respectively. Amplification of the MYCN oncogene was highly correlated with deregulation of miRNA expression. In addition, 37 miRNAs correlated with TrkA expression, a marker of excellent outcome, and 6 miRNAs further analysed in vitro were regulated upon TrkA transfection, suggesting a functional relationship. Expression of the most significant TrkA‐correlated miRNA, miR‐542‐5p, also discriminated between local and metastatic disease and was inversely correlated with MYCN amplification and event‐free survival. We conclude that neuroblastoma patient outcome prediction using miRNA expression is feasible and effective. Studies testing miRNA‐based predictors in comparison to and in combination with mRNA and aCGH information should be initiated. Specific miRNAs (e.g., miR‐542‐5p) might be important in neuroblastoma tumour biology, and qualify as potential therapeutic targets.