Franki Speleman

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.

qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data.

Although quantitative PCR (qPCR) is becoming the method of choice for expression profiling of selected genes, accurate and straightforward processing of the raw measurements remains a major hurdle. Here we outline advanced and universally applicable models for relative quantification and inter-run calibration with proper error propagation along the entire calculation track. These models and algorithms are implemented in qBase, a free program for the management and automated analysis of qPCR data.

RTPrimerDB: the Real-Time PCR primer and probe database

The real-time polymerase chain reaction (PCR) methodology has become increasingly popular for nucleic acids detection and/or quantification. As primer/probe design and experimental evaluation is time-consuming, we developed a public database application for the storage and retrieval of validated real-time PCR primer and probe sequence records. The integrity and accuracy of the data are maintained by linking to and querying other reference databases. RTPrimerDB provides free public access through the Web to perform queries and submit user based information. Primer/probe records can be searched for by official gene symbol, nucleotide sequence, type of application, detection chemistry, LocusLink or Single Nucleotide Polymorphism (SNP) identifier, and submitters name. Each record is directly linked to LocusLink, dbSNP and/or PubMed to retrieve additional information on the gene/SNP for which the primers/probes are designed. Currently, the database contains primer/probe records for human, mouse, rat, fruit fly and zebrafish, and all current detection chemistries such as intercalating dyes (SYBR Green I), hydrolysis probes (Taqman), adjacent hybridizations probes and molecular beacons. Real-time PCR primer/probe records are available at http://www.realtimeprimerdatabase.ht.st.

High-throughput stem-loop RT-qPCR miRNA expression profiling using minute amounts of input RNA

MicroRNAs (miRNAs) are an emerging class of small non-coding RNAs implicated in a wide variety of cellular processes. Research in this field is accelerating, and the growing number of miRNAs emphasizes the need for high-throughput and sensitive detection methods. Here we present the successful evaluation of the Megaplex reverse transcription format of the stem-loop primer-based real-time quantitative polymerase chain reaction (RT-qPCR) approach to quantify miRNA expression. The Megaplex reaction provides simultaneous reverse transcription of 450 mature miRNAs, ensuring high-throughput detection. Further, the introduction of a complementary DNA pre-amplification step significantly reduces the amount of input RNA needed, even down to single-cell level. To evaluate possible pre-amplification bias, we compared the expression of 384 miRNAs in three different cancer cell lines with Megaplex RT, with or without an additional pre-amplification step. The normalized Cq values of all three sample pairs showed a good correlation with maintenance of differential miRNA expression between the cell lines. Moreover, pre-amplification using 10 ng of input RNA enabled the detection of miRNAs that were undetectable when using Megaplex alone with 400 ng of input RNA. The high specificity of RT-qPCR together with a superior sensitivity makes this approach the method of choice for high-throughput miRNA expression profiling.

The miR-17-92 microRNA cluster regulates multiple components of the TGF-β pathway in neuroblastoma.

The miR-17-92 microRNA cluster is often activated in cancer cells, but the identity of its targets remains elusive. Using SILAC and quantitative mass spectrometry, we examined the effects of activation of the miR-17-92 cluster on global protein expression in neuroblastoma (NB) cells. Our results reveal cooperation between individual miR-17-92 miRNAs and implicate miR-17-92 in multiple hallmarks of cancer, including proliferation and cell adhesion. Most importantly, we show that miR-17-92 is a potent inhibitor of TGF-β signaling. By functioning both upstream and downstream of pSMAD2, miR-17-92 activation triggers downregulation of multiple key effectors along the TGF-β signaling cascade as well as direct inhibition of TGF-β-responsive genes.

Further delineation of the 15q13 microdeletion and duplication syndromes: a clinical spectrum varying from non-pathogenic to a severe outcome

Background: Recurrent 15q13.3 microdeletions were recently identified with identical proximal (BP4) and distal (BP5) breakpoints and associated with mild to moderate mental retardation and epilepsy. Methods: To assess further the clinical implications of this novel 15q13.3 microdeletion syndrome, 18 new probands with a deletion were molecularly and clinically characterised. In addition, we evaluated the characteristics of a family with a more proximal deletion between BP3 and BP4. Finally, four patients with a duplication in the BP3–BP4–BP5 region were included in this study to ascertain the clinical significance of duplications in this region. Results: The 15q13.3 microdeletion in our series was associated with a highly variable intra- and inter-familial phenotype. At least 11 of the 18 deletions identified were inherited. Moreover, 7 of 10 siblings from four different families also had this deletion: one had a mild developmental delay, four had only learning problems during childhood, but functioned well in daily life as adults, whereas the other two had no learning problems at all. In contrast to previous findings, seizures were not a common feature in our series (only 2 of 17 living probands). Three patients with deletions had cardiac defects and deletion of the KLF13 gene, located in the critical region, may contribute to these abnormalities. The limited data from the single family with the more proximal BP3–BP4 deletion suggest this deletion may have little clinical significance. Patients with duplications of the BP3–BP4–BP5 region did not share a recognisable phenotype, but psychiatric disease was noted in 2 of 4 patients. Conclusions: Overall, our findings broaden the phenotypic spectrum associated with 15q13.3 deletions and suggest that, in some individuals, deletion of 15q13.3 is not sufficient to cause disease. The existence of microdeletion syndromes, associated with an unpredictable and variable phenotypic outcome, will pose the clinician with diagnostic difficulties and challenge the commonly used paradigm in the diagnostic setting that aberrations inherited from a phenotypically normal parent are usually without clinical consequences.

LIN28B induces neuroblastoma and enhances MYCN levels via let-7 suppression

LIN28B regulates developmental processes by modulating microRNAs (miRNAs) of the let-7 family. A role for LIN28B in cancer has been proposed but has not been established in vivo. Here, we report that LIN28B showed genomic aberrations and extensive overexpression in high-risk neuroblastoma compared to several other tumor entities and normal tissues. High LIN28B expression was an independent risk factor for adverse outcome in neuroblastoma. LIN28B signaled through repression of the let-7 miRNAs and consequently resulted in elevated MYCN protein expression in neuroblastoma cells. LIN28B–let-7–MYCN signaling blocked differentiation of normal neuroblasts and neuroblastoma cells. These findings were fully recapitulated in a mouse model in which LIN28B expression in the sympathetic adrenergic lineage induced development of neuroblastomas marked by low let-7 miRNA levels and high MYCN protein expression. Interference with this pathway might offer therapeutic perspectives.

International consensus for neuroblastoma molecular diagnostics: report from the International Neuroblastoma Risk Group (INRG) Biology Committee.

Neuroblastoma serves as a paradigm for utilising tumour genomic data for determining patient prognosis and treatment allocation. However, before the establishment of the International Neuroblastoma Risk Group (INRG) Task Force in 2004, international consensus on markers, methodology, and data interpretation did not exist, compromising the reliability of decisive genetic markers and inhibiting translational research efforts. The objectives of the INRG Biology Committee were to identify highly prognostic genetic aberrations to be included in the new INRG risk classification schema and to develop precise definitions, decisive biomarkers, and technique standardisation. The review of the INRG database (n=8800 patients) by the INRG Task Force finally enabled the identification of the most significant neuroblastoma biomarkers. In addition, the Biology Committee compared the standard operating procedures of different cooperative groups to arrive at international consensus for methodology, nomenclature, and future directions. Consensus was reached to include MYCN status, 11q23 allelic status, and ploidy in the INRG classification system on the basis of an evidence-based review of the INRG database. Standardised operating procedures for analysing these genetic factors were adopted, and criteria for proper nomenclature were developed. Neuroblastoma treatment planning is highly dependant on tumour cell genomic features, and it is likely that a comprehensive panel of DNA-based biomarkers will be used in future risk assignment algorithms applying genome-wide techniques. Consensus on methodology and interpretation is essential for uniform INRG classification and will greatly facilitate international and cooperative clinical and translational research studies.

A cooperative microRNA-tumor suppressor gene network in acute T-cell lymphoblastic leukemia (T-ALL)

The importance of individual microRNAs (miRNAs) has been established in specific cancers. However, a comprehensive analysis of the contribution of miRNAs to the pathogenesis of any specific cancer is lacking. Here we show that in T-cell acute lymphoblastic leukemia (T-ALL), a small set of miRNAs is responsible for the cooperative suppression of several tumor suppressor genes. Cross-comparison of miRNA expression profiles in human T-ALL with the results of an unbiased miRNA library screen allowed us to identify five miRNAs (miR-19b, miR-20a, miR-26a, miR-92 and miR-223) that are capable of promoting T-ALL development in a mouse model and which account for the majority of miRNA expression in human T-ALL. Moreover, these miRNAs produce overlapping and cooperative effects on tumor suppressor genes implicated in the pathogenesis of T-ALL, including IKAROS (also known as IKZF1), PTEN, BIM, PHF6, NF1 and FBXW7. Thus, a comprehensive and unbiased analysis of miRNA action in T-ALL reveals a striking pattern of miRNA-tumor suppressor gene interactions in this cancer.

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.