Stefaan Derveaux

How to do successful gene expression analysis using real-time PCR

Reverse transcription quantitative PCR (RT-qPCR) is considered today as the gold standard for accurate, sensitive and fast measurement of gene expression. Unfortunately, what many users fail to appreciate is that numerous critical issues in the workflow need to be addressed before biologically meaningful and trustworthy conclusions can be drawn. Here, we review the entire workflow from the planning and preparation phase, over the actual real-time PCR cycling experiments to data-analysis and reporting steps. This process can be captured with the appropriate acronym PCR: plan/prepare, cycle and report. The key message is that quality assurance and quality control are essential throughout the entire RT-qPCR workflow; from living cells, over extraction of nucleic acids, storage, various enzymatic steps such as DNase treatment, reverse transcription and PCR amplification, to data-analysis and finally reporting.

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.

Synergism between particle-based multiplexing and microfluidics technologies may bring diagnostics closer to the patient

In the field of medical diagnostics there is a growing need for inexpensive, accurate, and quick high-throughput assays. On the one hand, recent progress in microfluidics technologies is expected to strongly support the development of miniaturized analytical devices, which will speed up (bio)analytical assays. On the other hand, a higher throughput can be obtained by the simultaneous screening of one sample for multiple targets (multiplexing) by means of encoded particle-based assays. Multiplexing at the macro level is now common in research labs and is expected to become part of clinical diagnostics. This review aims to debate on the “added value” we can expect from (bio)analysis with particles in microfluidic devices. Technologies to (a) decode, (b) analyze, and (c) manipulate the particles are described. Special emphasis is placed on the challenges of integrating currently existing detection platforms for encoded microparticles into microdevices and on promising microtechnologies that could be used to down-scale the detection units in order to obtain compact miniaturized particle-based multiplexing platforms.

RNA pre-amplification enables large-scale RT-qPCR gene-expression studies on limiting sample amounts.

BackgroundThe quantitative polymerase chain reaction (qPCR) is a widely utilized method for gene-expression analysis. However, insufficient material often compromises large-scale gene-expression studies. The aim of this study is to evaluate an RNA pre-amplification method to produce micrograms of cDNA as input for qPCR.FindingsThe linear isothermal Ribo-SPIA pre-amplification method (WT-Ovation; NuGEN) was first evaluated by measuring the expression of 20 genes in RNA samples from six neuroblastoma cell lines and of 194 genes in two commercially available reference RNA samples before and after pre-amplification, and subsequently applied on a large panel of 738 RNA samples extracted from neuroblastoma tumours. All RNA samples were evaluated for RNA integrity and purity. Starting from 5 to 50 nanograms of total RNA the sample pre-amplification method was applied, generating approximately 5 microgams of cDNA, sufficient to measure more than 1000 target genes. The results obtained from this study show a constant yield of pre-amplified cDNA independent of the amount of input RNA; preservation of differential gene-expression after pre-amplification without introduction of substantial bias; no co-amplification of contaminating genomic DNA; no necessity to purify the pre-amplified material; and finally the importance of good RNA quality to enable pre-amplification.ConclusionApplication of this unbiased and easy to use sample pre-amplification technology offers great advantage to generate sufficient material for diagnostic and prognostic work-up and enables large-scale qPCR gene-expression studies using limited amounts of sample material.

External oligonucleotide standards enable cross laboratory comparison and exchange of real-time quantitative PCR data

The quantitative polymerase chain reaction (qPCR) is widely utilized for gene expression analysis. However, the lack of robust strategies for cross laboratory data comparison hinders the ability to collaborate or perform large multicentre studies conducted at different sites. In this study we introduced and validated a workflow that employs universally applicable, quantifiable external oligonucleotide standards to address this question. Using the proposed standards and data-analysis procedure, we obtained a perfect concordance between expression values from eight different genes in 366 patient samples measured on three different qPCR instruments and matching software, reagents, plates and seals, demonstrating the power of this strategy to detect and correct inter-run variation and to enable exchange of data between different laboratories, even when not using the same qPCR platform.

Target enrichment using parallel nanoliter quantitative PCR amplification

BackgroundNext generation targeted resequencing is replacing Sanger sequencing at high pace in routine genetic diagnosis. The need for well validated, high quality enrichment platforms to complement the bench-top next generation sequencing devices is high.ResultsWe used the WaferGen Smartchip platform to perform highly parallelized PCR based target enrichment for a set of known cancer genes in a well characterized set of cancer cell lines from the NCI60 panel. Optimization of PCR assay design and cycling conditions resulted in a high enrichment efficiency. We provide proof of a high mutation rediscovery rate and have included technical replicates to enable SNP calling validation demonstrating the high reproducibility of our enrichment platform.ConclusionsHere we present our custom developed quantitative PCR based target enrichment platform. Using highly parallel nanoliter singleplex PCR reactions makes this a flexible and efficient platform. The high mutation validation rate shows this platform’s promise as a targeted resequencing method for multi-gene routine sequencing diagnostics.

Whole-Genome RT-qPCR MicroRNA Expression Profiling

MicroRNAs (miRNAs) are small noncoding RNA molecules that function as negative regulators of gene expression. They are essential components of virtually every biological process and deregulated miRNA expression has been reported in a multitude of human diseases including cancer. Owing to their small size (20-22 nucleotides), accurate quantification of miRNA expression is particularly challenging. In this chapter, we present different RT-qPCR technologies that enable whole genome miRNA expression quantification.

Long non-coding RNA expression profiling in the NCI60 cancer cell line panel using high-throughput RT-qPCR

Long non-coding RNAs (lncRNAs) form a new class of RNA molecules implicated in various aspects of protein coding gene expression regulation. To study lncRNAs in cancer, we generated expression profiles for 1707 human lncRNAs in the NCI60 cancer cell line panel using a high-throughput nanowell RT-qPCR platform. We describe how qPCR assays were designed and validated and provide processed and normalized expression data for further analysis. Data quality is demonstrated by matching the lncRNA expression profiles with phenotypic and genomic characteristics of the cancer cell lines. This data set can be integrated with publicly available omics and pharmacological data sets to uncover novel associations between lncRNA expression and mRNA expression, miRNA expression, DNA copy number, protein coding gene mutation status or drug response

Abstract 2987: Regulatory network discovery using 3-way integration of high-dimensional mRNA, miRNA and lncRNA expression data from the entire NCI60 cancer cell line panel

Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL With the discovery of different non-coding RNA species, the complexity of the transcriptome and its regulation has increased dramatically. Next to the well-studied small non-coding miRNAs, several thousands of long non-coding RNAs (lncRNAs) have recently been described. Like miRNAs, lncRNAs appear to predominantly function as regulators of gene expression and are implicated in various regulatory networks involving both miRNAs and protein-coding genes. In order to facilitate the search for miRNA-lncRNA-mRNA regulatory networks in cancer we have profiled the expression of each of these RNA information layers using the high-throughput SmartChip RT-qPCR technology on the entire NCI60 cancer cell line panel. In total, three SmartChip Panels with 1050 miRNAs, 1250 cancer-focused mRNAs, and 1718 lncRNAs, respectively, were quantified with a minimum of 3 technical replicates against each cell line. Here, we present the results of an unprecedented integrated analysis aimed at identifying networks of highly co-regulated miRNA-lncRNA-mRNA clusters. In brief, individual clusters are annotated using a pathway enrichment approach whereby network edges are evaluated using miRNA target, lncRNA target, and transcription factor target predictions. MiRNA-lncRNA-mRNA clusters centered around key cancer genes are annotated and the complex interplay is described. This unique and extensive high quality dataset, comprised of three major information layers of the NCI60 cell line transcriptome offers numerous opportunities towards a better understanding of complex regulatory networks in cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2987. doi:1538-7445.AM2012-2987