Pieter Mestdagh

A novel and universal method for microRNA RT-qPCR data normalization

Gene expression analysis of microRNA molecules is becoming increasingly important. In this study we assess the use of the mean expression value of all expressed microRNAs in a given sample as a normalization factor for microRNA real-time quantitative PCR data and compare its performance to the currently adopted approach. We demonstrate that the mean expression value outperforms the current normalization strategy in terms of better reduction of technical variation and more accurate appreciation of biological changes.

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 impact of disparate isolation methods for extracellular vesicles on downstream RNA profiling

Despite an enormous interest in the role of extracellular vesicles, including exosomes, in cancer and their use as biomarkers for diagnosis, prognosis, drug response and recurrence, there is no consensus on dependable isolation protocols. We provide a comparative evaluation of 4 exosome isolation protocols for their usability, yield and purity, and their impact on downstream omics approaches for biomarker discovery. OptiPrep density gradient centrifugation outperforms ultracentrifugation and ExoQuick and Total Exosome Isolation precipitation in terms of purity, as illustrated by the highest number of CD63-positive nanovesicles, the highest enrichment in exosomal marker proteins and a lack of contaminating proteins such as extracellular Argonaute-2 complexes. The purest exosome fractions reveal a unique mRNA profile enriched for translation, ribosome, mitochondrion and nuclear lumen function. Our results demonstrate that implementation of high purification techniques is a prerequisite to obtain reliable omics data and identify exosome-specific functions and biomarkers.

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.

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.

MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer.

BackgroundAdvances in high-throughput technologies and bioinformatics have transformed gene expression profiling methodologies. The results of microarray experiments are often validated using reverse transcription quantitative PCR (RT-qPCR), which is the most sensitive and reproducible method to quantify gene expression. Appropriate normalisation of RT-qPCR data using stably expressed reference genes is critical to ensure accurate and reliable results. Mi(cro)RNA expression profiles have been shown to be more accurate in disease classification than mRNA expression profiles. However, few reports detailed a robust identification and validation strategy for suitable reference genes for normalisation in miRNA RT-qPCR studies.MethodsWe adopt and report a systematic approach to identify the most stable reference genes for miRNA expression studies by RT-qPCR in colorectal cancer (CRC). High-throughput miRNA profiling was performed on ten pairs of CRC and normal tissues. By using the mean expression value of all expressed miRNAs, we identified the most stable candidate reference genes for subsequent validation. As such the stability of a panel of miRNAs was examined on 35 tumour and 39 normal tissues. The effects of normalisers on the relative quantity of established oncogenic (miR-21 and miR-31) and tumour suppressor (miR-143 and miR-145) target miRNAs were assessed.ResultsIn the array experiment, miR-26a, miR-345, miR-425 and miR-454 were identified as having expression profiles closest to the global mean. From a panel of six miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) and two small nucleolar RNA genes (RNU48 and Z30), miR-16 and miR-345 were identified as the most stably expressed reference genes. The combined use of miR-16 and miR-345 to normalise expression data enabled detection of a significant dysregulation of all four target miRNAs between tumour and normal colorectal tissue.ConclusionsOur study demonstrates that the top six most stably expressed miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) described herein should be validated as suitable reference genes in both high-throughput and lower throughput RT-qPCR colorectal miRNA studies.

An update on LNCipedia: a database for annotated human lncRNA sequences

The human genome is pervasively transcribed, producing thousands of non-coding RNA transcripts. The majority of these transcripts are long non-coding RNAs (lncRNAs) and novel lncRNA genes are being identified at rapid pace. To streamline these efforts, we created LNCipedia, an online repository of lncRNA transcripts and annotation. Here, we present LNCipedia 3.0 (http://www.lncipedia.org), the latest version of the publicly available human lncRNA database. Compared to the previous version of LNCipedia, the database grew over five times in size, gaining over 90 000 new lncRNA transcripts. Assessment of the protein-coding potential of LNCipedia entries is improved with state-of-the art methods that include large-scale reprocessing of publicly available proteomics data. As a result, a high-confidence set of lncRNA transcripts with low coding potential is defined and made available for download. In addition, a tool to assess lncRNA gene conservation between human, mouse and zebrafish has been implemented.

Deep sequencing reveals differential expression of microRNAs in favorable versus unfavorable neuroblastoma

Small non-coding RNAs, in particular microRNAs(miRNAs), regulate fine-tuning of gene expression and can act as oncogenes or tumor suppressor genes. Differential miRNA expression has been reported to be of functional relevance for tumor biology. Using next-generation sequencing, the unbiased and absolute quantification of the small RNA transcriptome is now feasible. Neuroblastoma(NB) is an embryonal tumor with highly variable clinical course. We analyzed the small RNA transcriptomes of five favorable and five unfavorable NBs using SOLiD next-generation sequencing, generating a total of >188 000 000 reads. MiRNA expression profiles obtained by deep sequencing correlated well with real-time PCR data. Cluster analysis differentiated between favorable and unfavorable NBs, and the miRNA transcriptomes of these two groups were significantly different. Oncogenic miRNAs of the miR17-92 cluster and the miR-181 family were overexpressed in unfavorable NBs. In contrast, the putative tumor suppressive microRNAs, miR-542-5p and miR-628, were expressed in favorable NBs and virtually absent in unfavorable NBs. In-depth sequence analysis revealed extensive post-transcriptional miRNA editing. Of 13 identified novel miRNAs, three were further analyzed, and expression could be confirmed in a cohort of 70 NBs.

MicroRNA Expression in Induced Sputum of Smokers and Patients with Chronic Obstructive Pulmonary Disease

RATIONALE Chronic obstructive pulmonary disease (COPD) is characterized by progressive inflammation in the airways and lungs combined with disturbed homeostatic functions of pulmonary cells. MicroRNAs (miRNAs) have the ability to regulate these processes by interfering with gene transcription and translation. OBJECTIVES We aimed to identify miRNA expression in induced sputum and examined whether the expression of miRNAs differed between patients with COPD and subjects without airflow limitation. METHODS Expression of 627 miRNAs was evaluated in induced sputum supernatant of 32 subjects by stem-loop reverse transcription-quantitative polymerase chain reaction. Differentially expressed miRNAs were validated in an independent replication cohort of 41 subjects. Enrichment of miRNA target genes was identified by in silico analysis. Protein expression of target genes was determined by ELISA. MEASUREMENTS AND MAIN RESULTS Thirty-four miRNAs were differentially expressed between never-smokers and current smokers without airflow limitation in the screening cohort. Eight miRNAs were expressed at a significantly lower level in current-smoking patients with COPD compared with never-smokers without airflow limitation. Reduced expression of let-7c and miR-125b in patients with COPD compared with healthy subjects was confirmed in the validation cohort. Target genes of let-7c were significantly enriched in the sputum of patients with severe COPD. The concentration of tumor necrosis factor receptor type II (TNFR-II, implicated in COPD pathogenesis and a predicted target gene of let-7c) was inversely correlated with the sputum levels of let-7c . CONCLUSIONS let-7c is significantly reduced in the sputum of currently smoking patients with COPD and is associated with increased expression of TNFR-II.

Monoallelic but not biallelic loss of Dicer1 promotes tumorigenesis in vivo

Human tumors are characterized by widespread reduction in microRNA (miRNA) expression, although it is unclear how such changes come about and whether they have an etiological role in the disease. Importantly, miRNA knockdown has been shown to enhance the tumorigenic potential of human lung adenocarcinoma cells. A defect in miRNA processing is one possible mechanism for global downregulation. To explore this possibility in more detail in vivo, we have manipulated Dicer1 gene dosage in a mouse model of retinoblastoma. We show that although monoallelic loss of Dicer1 does not affect normal retinal development, it dramatically accelerates tumor formation on a retinoblastoma-sensitized background. Importantly, these tumors retain one wild-type Dicer1 allele and exhibit only a partial decrease in miRNA processing. Accordingly, in silico analysis of human cancer genome data reveals frequent hemizygous, but not homozygous, deletions of DICER1. Strikingly, complete loss of Dicer1 function in mice did not accelerate retinoblastoma formation. miRNA profiling of these tumors identified members of the let-7 and miR-34 families as candidate tumor suppressors in retinoblastoma. We conclude that Dicer1 functions as a haploinsufficient tumor suppressor. This finding has implications for cancer etiology and cancer therapy.