Glucocorticoids (GCs) selectively trigger cell death in the multiple myeloma cell line MM1S which express NR3C1/Glucocorticoid Receptor (GR) protein, but fail to kill MM1R cells which lack GR protein. Given recent demonstrations of altered microRNA profiles in a diverse range of haematological malignancies and drug resistance, we characterized GC inducible mRNA and microRNA transcription profiles in GC sensitive MM1S as compared to GC resistant MM1R cells. Transcriptome analysis revealed that GCs regulate expression of multiple genes involved in cell cycle control, cell organization, cell death and immunological disease in MM1S cells, which remain unaffected in MM1R cells. With respect to microRNAs, mir-150-5p was identified as the most time persistent GC regulated microRNA, out of 5 QPCR validated microRNAs (mir-26b, mir-125a-5p, mir-146-5p, mir-150-5p, and mir-184), which are GC inducible in MM1S but not in MM1R cells. Functional studies further revealed that ectopic transfection of a synthetic mir-150-5p mimics GR dependent gene expression changes involved in cell death and cell proliferation pathways. Remarkably, despite the gene expression changes observed, overexpression of mir-150-5p in absence of GCs did not trigger significant cytotoxicity in MM1S or MM1R cells. This suggests the requirement of additional steps in GC induced cell death, which can not be mimicked by mir-150-5p overexpression alone. Interestingly, a combination of mir-150-5p transfection with low doses GC in MM1S cells was found to sensitize therapy response, whereas opposite effects could be observed with a mir-150-5p specific antagomir. Although mir-150-5p overexpression did not substantially change GR expression levels, it was found that mir-150-5p evokes GR specific effects through indirect mRNA regulation of GR interacting transcription factors and hormone receptors, GR chaperones, as well as various effectors of unfolded protein stress and chemokine signalling. Altogether GC-inducible mir-150-5p adds another level of regulation to GC specific therapeutic responses in multiple myeloma.
Identifying relevant signatures for clinical patient outcome is a fundamental task in high-throughput studies. Signatures, composed of features such as mRNAs, miRNAs, SNPs or other molecular variables, are often non-overlapping, even though they have been identified from similar experiments considering samples with the same type of disease. The lack of a consensus is mostly due to the fact that sample sizes are far smaller than the numbers of candidate features to be considered, and therefore signature selection suffers from large variation. We propose a robust signature selection method that enhances the selection stability of penalized regression algorithms for predicting survival risk. Our method is based on an aggregation of multiple, possibly unstable, signatures obtained with the preconditioned lasso algorithm applied to random (internal) subsamples of a given cohort data, where the aggregated signature is shrunken by a simple thresholding strategy. The resulting method, RS-PL, is conceptually simple and easy to apply, relying on parameters automatically tuned by cross validation. Robust signature selection using RS-PL operates within an (external) subsampling framework to estimate the selection probabilities of features in multiple trials of RS-PL. These probabilities are used for identifying reliable features to be included in a signature. Our method was evaluated on microarray data sets from neuroblastoma, lung adenocarcinoma, and breast cancer patients, extracting robust and relevant signatures for predicting survival risk. Signatures obtained by our method achieved high prediction performance and robustness, consistently over the three data sets. Genes with high selection probability in our robust signatures have been reported as cancer-relevant. The ordering of predictor coefficients associated with signatures was well-preserved across multiple trials of RS-PL, demonstrating the capability of our method for identifying a transferable consensus signature. The software is available as an R package rsig at CRAN (http://cran.r-project.org).
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.
exosomes; extracellular vesicles; ultracentrifugation; ExoQuick; OptiPrep; omics
Since 2002, information on individual microRNAs (miRNAs), such as reference names and sequences, has been stored in miRBase, the reference database for miRNA annotation. As a result of progressive insights into the miRNome and its complexity, miRBase underwent addition and deletion of miRNA records, changes in annotated miRNA sequences and adoption of more complex naming schemes over time. Unfortunately, miRBase does not allow straightforward assessment of these ongoing miRNA annotation changes, which has resulted in substantial ambiguity regarding miRNA identity and sequence in public literature, in target prediction databases and in content on various commercially available analytical platforms. As a result, correct interpretation, comparison and integration of miRNA study results are compromised, which we demonstrate here by assessing the impact of ignoring sequence annotation changes. To address this problem, we developed miRBase Tracker (www.mirbasetracker.org), an easy-to-use online database that keeps track of all historical and current miRNA annotation present in the miRBase database. Three basic functionalities allow researchers to keep their miRNA annotation up-to-date, reannotate analytical miRNA platforms and link published results with outdated annotation to the latest miRBase release. We expect miRBase Tracker to increase the transparency and annotation accuracy in the field of miRNA research.
Mammalian blastocyst formation is characterized by two lineage segregations resulting in the formation of the trophectoderm, the hypoblast, and the epiblast cell lineages. Cell fate determination during these early lineage segregations is associated with changes in the expression of specific transcription factors. In addition to the transcription factor-based control, it has become clear that also microRNAs (miRNAs) play an important role in the post-transcriptional regulation of pluripotency and differentiation. To elucidate the role of miRNAs in early lineage segregation, we compared the miRNA expression in early bovine blastocysts with the more advanced stage of hatched blastocysts. Reverse transcription–quantitative PCR-based miRNA expression profiling revealed eight upregulated miRNAs (miR-127, miR-130a, miR-155, miR-196a, miR-203, miR-28, miR-29c, and miR-376a) and four downregulated miRNAs (miR-135a, miR-218, miR-335, and miR-449b) in hatched blastocysts. Through an integrative analysis of matching miRNA and mRNA expression data, candidate miRNA-mRNA interaction pairs were prioritized for validation. Using an in vitro luciferase reporter assay, we confirmed a direct interaction between miR-218 and CDH2, miR-218 and NANOG, and miR-449b and NOTCH1. By interfering with the FGF signaling pathway, we found functional evidence that miR-218, mainly expressed in the inner cell mass, regulates the NANOG expression in the bovine blastocyst in response to FGF signaling. The results of this study expand our knowledge about the miRNA signature of the bovine blastocyst and of the interactions between miRNAs and cell fate regulating transcription factors.
More accurate assessment of prognosis is important to further improve the choice of risk-related therapy in neuroblastoma (NB) patients. In this study, we aimed to establish and validate a prognostic miRNA signature for children with NB and tested it in both fresh frozen and archived formalin-fixed paraffin-embedded (FFPE) samples.
Four hundred-thirty human mature miRNAs were profiled in two patient subgroups with maximally divergent clinical courses. Univariate logistic regression analysis was used to select miRNAs correlating with NB patient survival. A 25-miRNA gene signature was built using 51 training samples, tested on 179 test samples, and validated on an independent set of 304 fresh frozen tumor samples and 75 archived FFPE samples.
The 25-miRNA signature significantly discriminates the test patients with respect to progression-free and overall survival (P < 0.0001), both in the overall population and in the cohort of high-risk patients. Multivariate analysis indicates that the miRNA signature is an independent predictor of patient survival after controlling for current risk factors. The results were confirmed in an external validation set. In contrast to a previously published mRNA classifier, the 25-miRNA signature was found to be predictive for patient survival in a set of 75 FFPE neuroblastoma samples.
In this study, we present the largest NB miRNA expression study so far, including more than 500 NB patients. We established and validated a robust miRNA classifier, able to identify a cohort of high-risk NB patients at greater risk for adverse outcome using both fresh frozen and archived material.
Measuring messenger RNA (mRNA) levels using the reverse transcription quantitative polymerase chain reaction (RT-qPCR) is common practice in many laboratories. A specific set of mRNAs as internal control reference genes is considered as the preferred strategy to normalize RT-qPCR data. Proper selection of reference genes is a critical issue, especially in cancer cells that are subjected to different in vitro manipulations. These manipulations may result in dramatic alterations in gene expression levels, even of assumed reference genes. In this study, we evaluated the expression levels of 11 commonly used reference genes as internal controls for normalization of 19 experiments that include neuroblastoma, T-ALL, melanoma, breast cancer, non small cell lung cancer (NSCL), acute myeloid leukemia (AML), prostate cancer, colorectal cancer, and cervical cancer cell lines subjected to various perturbations.
The geNorm algorithm in the software package qbase+ was used to rank the candidate reference genes according to their expression stability. We observed that the stability of most of the candidate reference genes varies greatly in perturbation experiments. Expressed Alu repeats show relatively stable expression regardless of experimental condition. These Alu repeats are ranked among the best reference assays in all perturbation experiments and display acceptable average expression stability values (M<0.5).
We propose the use of Alu repeats as a reference assay when performing cancer cell perturbation experiments.
Several microRNAs (miRNAs) that are either specifically enriched or highly expressed in neurons and glia have been described, but the identification of miRNAs modulating neural stem cell (NSC) biology remains elusive. In this study, we exploited high throughput miRNA expression profiling to identify candidate miRNAs enriched in NSC/early progenitors derived from the murine subventricular zone (SVZ). Then, we used lentiviral miRNA sensor vectors (LV.miRT) to monitor the activity of shortlisted miRNAs with cellular and temporal resolution during NSC differentiation, taking advantage of in vitro and in vivo models that recapitulate physiological neurogenesis and gliogenesis and using known neuronal- and glial-specific miRNAs as reference. The LV.miRT platform allowed us monitoring endogenous miRNA activity in low represented cell populations within a bulk culture or within the complexity of CNS tissue, with high sensitivity and specificity. In this way we validated and extended previous results on the neuronal-specific miR-124 and the astroglial-specific miR-23a. Importantly, we describe for the first time a cell type- and differentiation stage-specific modulation of miR-93 and miR-125b in SVZ-derived NSC cultures and in the SVZ neurogenic niche in vivo, suggesting key roles of these miRNAs in regulating NSC function.
Chronic lymphocytic leukemia (CLL) is a disease with variable clinical outcome. Several prognostic factors such as the immunoglobulin heavy chain variable genes (IGHV) mutation status are linked to the B-cell receptor (BCR) complex, supporting a role for triggering the BCR in vivo in the pathogenesis. The miRNA profile upon stimulation and correlation with IGHV mutation status is however unknown. To evaluate the transcriptional response of peripheral blood CLL cells upon BCR stimulation in vitro, miRNA and mRNA expression was measured using hybridization arrays and qPCR. We found both IGHV mutated and unmutated CLL cells to respond with increased expression of MYC and other genes associated with BCR activation, and a phenotype of cell cycle progression. Genome-wide expression studies showed hsa-miR-132-3p/hsa-miR-212 miRNA cluster induction associated with a set of downregulated genes, enriched for genes modulated by BCR activation and amplified by Myc. We conclude that BCR triggering of CLL cells induces a transcriptional response of genes associated with BCR activation, enhanced cell cycle entry and progression and suggest that part of the transcriptional profiles linked to IGHV mutation status observed in isolated peripheral blood are not cell intrinsic but rather secondary to in vivo BCR stimulation.
Neuroblastoma is an embryonic tumor arising from immature sympathetic nervous system cells. Recurrent genomic alterations include MYCN and ALK amplification as well as recurrent patterns of gains and losses of whole or large partial chromosome segments. A recent whole genome sequencing effort yielded no frequently recurring mutations in genes other than those affecting ALK. However, the study further stresses the importance of DNA copy number alterations in this disease, in particular for genes implicated in neuritogenesis. Here we provide additional evidence for the importance of focal DNA copy number gains and losses, which are predominantly observed in MYCN amplified tumors. A focal 5 kb gain encompassing the MYCN regulated miR-17∼92 cluster as sole gene was detected in a neuroblastoma cell line and further analyses of the array CGH data set demonstrated enrichment for other MYCN target genes in focal gains and amplifications. Next we applied an integrated genomics analysis to prioritize MYCN down regulated genes mediated by MYCN driven miRNAs within regions of focal heterozygous or homozygous deletion. We identified RGS5, a negative regulator of G-protein signaling implicated in vascular normalization, invasion and metastasis, targeted by a focal homozygous deletion, as a new MYCN target gene, down regulated through MYCN activated miRNAs. In addition, we expand the miR-17∼92 regulatory network controlling TGFß signaling in neuroblastoma with the ring finger protein 11 encoding gene RNF11, which was previously shown to be targeted by the miR-17∼92 member miR-19b. Taken together, our data indicate that focal DNA copy number imbalances in neuroblastoma (1) target genes that are implicated in MYCN signaling, possibly selected to reinforce MYCN oncogene addiction and (2) serve as a resource for identifying new molecular targets for treatment.
Here, we present LNCipedia (http://www.lncipedia.org), a novel database for human long non-coding RNA (lncRNA) transcripts and genes. LncRNAs constitute a large and diverse class of non-coding RNA genes. Although several lncRNAs have been functionally annotated, the majority remains to be characterized. Different high-throughput methods to identify new lncRNAs (including RNA sequencing and annotation of chromatin-state maps) have been applied in various studies resulting in multiple unrelated lncRNA data sets. LNCipedia offers 21 488 annotated human lncRNA transcripts obtained from different sources. In addition to basic transcript information and gene structure, several statistics are determined for each entry in the database, such as secondary structure information, protein coding potential and microRNA binding sites. Our analyses suggest that, much like microRNAs, many lncRNAs have a significant secondary structure, in-line with their presumed association with proteins or protein complexes. Available literature on specific lncRNAs is linked, and users or authors can submit articles through a web interface. Protein coding potential is assessed by two different prediction algorithms: Coding Potential Calculator and HMMER. In addition, a novel strategy has been integrated for detecting potentially coding lncRNAs by automatically re-analysing the large body of publicly available mass spectrometry data in the PRIDE database. LNCipedia is publicly available and allows users to query and download lncRNA sequences and structures based on different search criteria. The database may serve as a resource to initiate small- and large-scale lncRNA studies. As an example, the LNCipedia content was used to develop a custom microarray for expression profiling of all available lncRNAs.
Gene expression quantification on cultured cells using the reverse transcription quantitative polymerase chain reaction (RT-qPCR) typically involves an RNA purification step that limits sample processing throughput and precludes parallel analysis of large numbers of samples. An approach in which cDNA synthesis is carried out on crude cell lysates instead of on purified RNA samples can offer a fast and straightforward alternative. Here, we evaluate such an approach, benchmarking Ambion's Cells-to-CT kit with the classic workflow of RNA purification and cDNA synthesis, and demonstrate its good accuracy and superior sensitivity.
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 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 TGFβ-signaling. By functioning both upstream and downstream of pSMAD2, miR-17-92 activation triggers downregulation of multiple key effectors along the TGFβ-signaling cascade as well as through direct inhibition of TGFβ-responsive genes.
While a growing body of evidence implicates regulatory miRNA modules in various aspects of human disease and development, insights into specific miRNA function remain limited. Here, we present an innovative approach to elucidate tissue-specific miRNA functions that goes beyond miRNA target prediction and expression correlation. This approach is based on a multi-level integration of corresponding miRNA and mRNA gene expression levels, miRNA target prediction, transcription factor target prediction and mechanistic models of gene network regulation. Predicted miRNA functions were either validated experimentally or compared to published data. The predicted miRNA functions are accessible in the miRNA bodymap, an interactive online compendium and mining tool of high-dimensional newly generated and published miRNA expression profiles. The miRNA bodymap enables prioritization of candidate miRNAs based on their expression pattern or functional annotation across tissue or disease subgroup. The miRNA bodymap project provides users with a single one-stop data-mining solution and has great potential to become a community resource.
The purpose of this study was to further define the biology of the 11q− neuroblastoma tumor subgroup by the integration of aCGH with miRNA expression profiling data to determine if improved patient stratification is possible.
A set of primary neuroblastoma (n=160) which was broadly representative of all genetic subtypes was analyzed by aCGH and for the expression of 430 miRNAs. A 15 miRNA expression signature previously demonstrated to be predictive of clinical outcome was used to analyze an independent cohort of 11q− tumors (n=37).
Loss of 4p and gain of 7q occurred at a significantly higher frequency in the 11q−tumors, further defining the genetic characteristics of this subtype. The 11q− tumors could be split into two subgroups using a miRNA expression survival signature which differed significantly in both clinical outcome and the overall frequency of large scale genomic imbalances, with the poor survival subgroup having significantly more imbalances. MiRNAs from the expression signature which were up-regulated in unfavorable tumors were predicted to target down-regulated genes from a published mRNA expression classifier of clinical outcome at a higher than expected frequency, indicating the miRNAs might contribute to the regulation of genes within the signature.
We demonstrate that two distinct biological subtypes of neuroblastoma with loss of 11q occur which differ in their miRNA expression profiles, frequency of segmental imbalances and clinical outcome. A miRNA expression signature, combined with an analysis of segmental imbalances, provides greater prediction of EFS and OS outcomes than 11q status by itself, improving patient stratification.
aCGH; MYCN; neuroblastoma; miRNA
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 the global down-regulation. To explore this possibility in more detail in vivo we have manipulated Dicer1 gene dosage in a mouse model of retinoblastoma. We show that while 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 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 aetiology and cancer therapy.
Dicer; microRNA; retinoblastoma; tumor suppressor; haploinsufficiency
MicroRNAs (miRNAs) are increasingly implicated in regulating the malignant progression of cancer. Here we show that miR-9, the level of which is upregulated in breast cancer cells, directly targets CDH1, the E-cadherin-encoding mRNA, leading to increased cell motility and invasiveness. miR-9-mediated E-cadherin downregulation results in the activation of β-catenin signaling, which contributes to upregulated expression of the gene encoding vascular endothelial growth factor (VEGF); this leads, in turn, to increased tumor angiogenesis. Overexpression of miR-9 in otherwise-non-metastatic breast tumor cells enables these cells to form pulmonary micrometastases in mice. Conversely, inhibiting miR-9 using a ‘miRNA sponge’ in highly malignant cells inhibits metastasis formation. Expression of miR-9 is activated by MYC and MYCN, both of which directly bind to the mir-9-3 locus. Significantly, in human cancers, miR-9 levels correlate with MYCN amplification, tumor grade, and metastatic status. These findings uncover a regulatory and signaling pathway involving a metastasis-promoting miRNA that is predicted to directly target expression of the key metastasis-suppressing protein E-cadherin.
Neuroblastoma is one of the most common solid tumors of childhood, arising from immature sympathetic nervous system cells. The clinical course of patients with neuroblastoma is highly variable, ranging from spontaneous regression to widespread metastatic disease. Although the outcome for children with cancer has improved considerably during the past decades, the prognosis of children with aggressive neuroblastoma remains dismal. The clinical heterogeneity of neuroblastoma mirrors the biological and genetic heterogeneity of these tumors. Ploidy and MYCN amplification have been used as genetic markers for risk stratification and therapeutic decision making, and, more recently, gene expression profiling and genome-wide DNA copy number analysis have come into the picture as sensitive and specific tools for assessing prognosis. The applica tion of new genetic tools also led to the discovery of an important familial neuroblastoma cancer gene, ALK, which is mutated in approximately 8% of sporadic tumors, and genome-wide association studies have unveiled loci with risk alleles for neuroblastoma development. For some of the genomic regions that are deleted in some neuroblastomas, on 1p, 3p and 11q, candidate tumor suppressor genes have been identified. In addition, evidence has emerged for the contribution of epigenetic disturbances in neuroblastoma oncogenesis. As in other cancer entities, altered microRNA expression is also being recognized as an important player in neuroblastoma. The recent successes in unraveling the genetic basis of neuroblastoma are now opening opportunities for development of targeted therapies.
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.
Advances 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.
We 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.
In 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.
Our 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.
MiRNAs regulate gene expression at a post-transcriptional level and their dysregulation can play major roles in the pathogenesis of many different forms of cancer, including neuroblastoma, an often fatal paediatric cancer originating from precursor cells of the sympathetic nervous system. We have analyzed a set of neuroblastoma (n = 145) that is broadly representative of the genetic subtypes of this disease for miRNA expression (430 loci by stem-loop RT qPCR) and for DNA copy number alterations (array CGH) to assess miRNA involvement in disease pathogenesis. The tumors were stratified and then randomly split into a training set (n = 96) and a validation set (n = 49) for data analysis. Thirty-seven miRNAs were significantly over- or under-expressed in MYCN amplified tumors relative to MYCN single copy tumors, indicating a potential role for the MYCN transcription factor in either the direct or indirect dysregulation of these loci. In addition, we also determined that there was a highly significant correlation between miRNA expression levels and DNA copy number, indicating a role for large-scale genomic imbalances in the dysregulation of miRNA expression. In order to directly assess whether miRNA expression was predictive of clinical outcome, we used the Random Forest classifier to identify miRNAs that were most significantly associated with poor overall patient survival and developed a 15 miRNA signature that was predictive of overall survival with 72.7% sensitivity and 86.5% specificity in the validation set of tumors. We conclude that there is widespread dysregulation of miRNA expression in neuroblastoma tumors caused by both over-expression of the MYCN transcription factor and by large-scale chromosomal imbalances. MiRNA expression patterns are also predicative of clinical outcome, highlighting the potential for miRNA mediated diagnostics and therapeutics.
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.
The mean expression value: a new method for accurate and reliable normalization of microRNA expression data from RT-qPCR experiments.
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.
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.