Marta Milo

Distinct MicroRNA Alterations Characterize High- and Low-Grade Bladder Cancer

Urothelial carcinoma of the bladder (UCC) is a common disease that arises by at least two different molecular pathways. The biology of UCC is incompletely understood, making the management of this disease difficult. Recent evidence implicates a regulatory role for microRNA in cancer. We hypothesized that altered microRNA expression contributes to UCC carcinogenesis. To test this hypothesis, we examined the expression of 322 microRNAs and their processing machinery in 78 normal and malignant urothelial samples using real-time rtPCR. Genes targeted by differentially expressed microRNA were investigated using real-time quantification and microRNA knockdown. We also examined the role of aberrant DNA hypermethylation in microRNA downregulation. We found that altered microRNA expression is common in UCC and occurs early in tumorogenesis. In normal urothelium from patients with UCC, 11% of microRNAs had altered expression when compared with disease-free controls. This was associated with upregulation of Dicer, Drosha, and Exportin 5. In UCC, microRNA alterations occur in a tumor phenotype-specific manner and can predict disease progression. High-grade UCC were characterized by microRNA upregulation, including microRNA-21 that suppresses p53 function. In low-grade UCC, there was downregulation of many microRNA molecules. In particular, loss of microRNAs-99a/100 leads to upregulation of FGFR3 before its mutation. Promoter hypermethylation is partly responsible for microRNA downregulation. In conclusion, distinct microRNA alterations characterize UCC and target genes in a pathway-specific manner. These data reveal new insights into the disease biology and have implications regarding tumor diagnosis, prognosis and therapy.

Restoration of auditory evoked responses by human ES-cell-derived otic progenitors

Deafness is a condition with a high prevalence worldwide, produced primarily by the loss of the sensory hair cells and their associated spiral ganglion neurons (SGNs). Of all the forms of deafness, auditory neuropathy is of particular concern. This condition, defined primarily by damage to the SGNs with relative preservation of the hair cells, is responsible for a substantial proportion of patients with hearing impairment. Although the loss of hair cells can be circumvented partially by a cochlear implant, no routine treatment is available for sensory neuron loss, as poor innervation limits the prospective performance of an implant. Using stem cells to recover the damaged sensory circuitry is a potential therapeutic strategy. Here we present a protocol to induce differentiation from human embryonic stem cells (hESCs) using signals involved in the initial specification of the otic placode. We obtained two types of otic progenitors able to differentiate in vitro into hair-cell-like cells and auditory neurons that display expected electrophysiological properties. Moreover, when transplanted into an auditory neuropathy model, otic neuroprogenitors engraft, differentiate and significantly improve auditory-evoked response thresholds. These results should stimulate further research into the development of a cell-based therapy for deafness.

Prolyl hydroxylase 3 (PHD3) is essential for hypoxic regulation of neutrophilic inflammation in humans and mice

The regulation of neutrophil lifespan by induction of apoptosis is critical for maintaining an effective host response and preventing excessive inflammation. The hypoxia-inducible factor (HIF) oxygen-sensing pathway has a major effect on the susceptibility of neutrophils to apoptosis, with a marked delay in cell death observed under hypoxic conditions. HIF expression and transcriptional activity are regulated by the oxygen-sensitive prolyl hydroxylases (PHD1-3), but the role of PHDs in neutrophil survival is unclear. We examined PHD expression in human neutrophils and found that PHD3 was strongly induced in response to hypoxia and inflammatory stimuli in vitro and in vivo. Using neutrophils from mice deficient in Phd3, we demonstrated a unique role for Phd3 in prolonging neutrophil survival during hypoxia, distinct from other hypoxia-associated changes in neutrophil function and metabolic activity. Moreover, this selective defect in neutrophil survival occurred in the presence of preserved HIF transcriptional activity but was associated with upregulation of the proapoptotic mediator Siva1 and loss of its binding target Bcl-xL. In vivo, using an acute lung injury model, we observed increased levels of neutrophil apoptosis and clearance in Phd3-deficient mice compared with WT controls. We also observed reduced neutrophilic inflammation in an acute mouse model of colitis. These data support what we believe to be a novel function for PHD3 in regulating neutrophil survival in hypoxia and may enable the development of new therapeutics for inflammatory disease.

Drosha regulates neurogenesis by controlling Neurogenin 2 expression independent of microRNAs

Temporal regulation of embryonic neurogenesis is controlled by hypostable transcription factors. The mechanism of the process is unclear. Here we show that the RNase III Drosha and DGCR8 (also known as Pasha), key components of the microRNA (miRNA) microprocessor, have important functions in mouse neurogenesis. Loss of microprocessor in forebrain neural progenitors resulted in a loss of stem cell character and precocious differentiation whereas Dicer deficiency did not. Drosha negatively regulated expression of the transcription factors Neurogenin 2 (Ngn2) and NeuroD1 whereas forced Ngn2 expression phenocopied the loss of Drosha. Neurog2 mRNA contains evolutionarily conserved hairpins with similarities to pri-miRNAs, and associates with the microprocessor in neural progenitors. We uncovered a Drosha-dependent destabilization of Neurog2 mRNAs consistent with microprocessor cleavage at hairpins. Our findings implicate direct and miRNA-independent destabilization of proneural mRNAs by the microprocessor, which facilitates neural stem cell (NSC) maintenance by blocking accumulation of differentiation and determination factors.

A tractable probabilistic model for Affymetrix probe-level analysis across multiple chips

MOTIVATION Affymetrix GeneChip arrays are currently the most widely used microarray technology. Many summarization methods have been developed to provide gene expression levels from Affymetrix probe-level data. Most of the currently popular methods do not provide a measure of uncertainty for the expression level of each gene. The use of probabilistic models can overcome this limitation. A full hierarchical Bayesian approach requires the use of computationally intensive MCMC methods that are impractical for large datasets. An alternative computationally efficient probabilistic model, mgMOS, uses Gamma distributions to model specific and non-specific binding with a latent variable to capture variations in probe affinity. Although promising, the main limitations of this model are that it does not use information from multiple chips and does not account for specific binding to the mismatch (MM) probes. RESULTS We extend mgMOS to model the binding affinity of probe-pairs across multiple chips and to capture the effect of specific binding to MM probes. The new model, multi-mgMOS, provides improved accuracy, as demonstrated on some bench-mark datasets and a real time-course dataset, and is much more computationally efficient than a competing hierarchical Bayesian approach that requires MCMC sampling. We demonstrate how the probabilistic model can be used to estimate credibility intervals for expression levels and their log-ratios between conditions. AVAILABILITY Both mgMOS and the new model multi-mgMOS have been implemented in an R package, which is available at http://www.bioinf.man.ac.uk/resources/puma.

Probe-level measurement error improves accuracy in detecting differential gene expression

MOTIVATION Finding differentially expressed genes is a fundamental objective of a microarray experiment. Numerous methods have been proposed to perform this task. Existing methods are based on point estimates of gene expression level obtained from each microarray experiment. This approach discards potentially useful information about measurement error that can be obtained from an appropriate probe-level analysis. Probabilistic probe-level models can be used to measure gene expression and also provide a level of uncertainty in this measurement. This probe-level measurement error provides useful information which can help in the identification of differentially expressed genes. RESULTS We propose a Bayesian method to include probe-level measurement error into the detection of differentially expressed genes from replicated experiments. A variational approximation is used for efficient parameter estimation. We compare this approximation with MAP and MCMC parameter estimation in terms of computational efficiency and accuracy. The method is used to calculate the probability of positive log-ratio (PPLR) of expression levels between conditions. Using the measurements from a recently developed Affymetrix probe-level model, multi-mgMOS, we test PPLR on a spike-in dataset and a mouse time-course dataset. Results show that the inclusion of probe-level measurement error improves accuracy in detecting differential gene expression. AVAILABILITY The MAP approximation and variational inference described in this paper have been implemented in an R package pplr. The MCMC method is implemented in Matlab. Both software are available from http://umber.sbs.man.ac.uk/resources/puma.

puma: a Bioconductor package for propagating uncertainty in microarray analysis

BackgroundMost analyses of microarray data are based on point estimates of expression levels and ignore the uncertainty of such estimates. By determining uncertainties from Affymetrix GeneChip data and propagating these uncertainties to downstream analyses it has been shown that we can improve results of differential expression detection, principal component analysis and clustering. Previously, implementations of these uncertainty propagation methods have only been available as separate packages, written in different languages. Previous implementations have also suffered from being very costly to compute, and in the case of differential expression detection, have been limited in the experimental designs to which they can be applied.Resultspuma is a Bioconductor package incorporating a suite of analysis methods for use on Affymetrix GeneChip data. puma extends the differential expression detection methods of previous work from the 2-class case to the multi-factorial case. puma can be used to automatically create design and contrast matrices for typical experimental designs, which can be used both within the package itself but also in other Bioconductor packages. The implementation of differential expression detection methods has been parallelised leading to significant decreases in processing time on a range of computer architectures. puma incorporates the first R implementation of an uncertainty propagation version of principal component analysis, and an implementation of a clustering method based on uncertainty propagation. All of these techniques are brought together in a single, easy-to-use package with clear, task-based documentation.ConclusionFor the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. These methods can be used to improve results from more traditional analyses of microarray data. puma also offers improvements in terms of scope and speed of execution over previously available methods. puma is recommended for anyone working with the Affymetrix GeneChip platform for gene expression analysis and can also be applied more generally.

RNA microarray analysis in prenatal mouse cochlea reveals novel IGF-I target genes: implication of MEF2 and FOXM1 transcription factors

Background Insulin-like growth factor-I (IGF-I) provides pivotal cell survival and differentiation signals during inner ear development throughout evolution. Homozygous mutations of human IGF1 cause syndromic sensorineural deafness, decreased intrauterine and postnatal growth rates, and mental retardation. In the mouse, deficits in IGF-I result in profound hearing loss associated with reduced survival, differentiation and maturation of auditory neurons. Nevertheless, little is known about the molecular basis of IGF-I activity in hearing and deafness. Methodology/Principal Findings A combination of quantitative RT-PCR, subcellular fractionation and Western blotting, along with in situ hybridization studies show IGF-I and its high affinity receptor to be strongly expressed in the embryonic and postnatal mouse cochlea. The expression of both proteins decreases after birth and in the cochlea of E18.5 embryonic Igf1−/− null mice, the balance of the main IGF related signalling pathways is altered, with lower activation of Akt and ERK1/2 and stronger activation of p38 kinase. By comparing the Igf1−/− and Igf1+/+ transcriptomes in E18.5 mouse cochleae using RNA microchips and validating their results, we demonstrate the up-regulation of the FoxM1 transcription factor and the misexpression of the neural progenitor transcription factors Six6 and Mash1 associated with the loss of IGF-I. Parallel, in silico promoter analysis of the genes modulated in conjunction with the loss of IGF-I revealed the possible involvement of MEF2 in cochlear development. E18.5 Igf1+/+ mouse auditory ganglion neurons showed intense MEF2A and MEF2D nuclear staining and MEF2A was also evident in the organ of Corti. At P15, MEF2A and MEF2D expression were shown in neurons and sensory cells. In the absence of IGF-I, nuclear levels of MEF2 were diminished, indicating less transcriptional MEF2 activity. By contrast, there was an increase in the nuclear accumulation of FoxM1 and a corresponding decrease in the nuclear cyclin-dependent kinase inhibitor p27Kip1. Conclusions/Significance We have defined the spatiotemporal expression of elements involved in IGF signalling during inner ear development and reveal novel regulatory mechanisms that are modulated by IGF-I in promoting sensory cell and neural survival and differentiation. These data will help us to understand the molecular bases of human sensorineural deafness associated to deficits in IGF-I.

Genomic Analysis of the Function of the Transcription Factor gata3 during Development of the Mammalian Inner Ear

We have studied the function of the zinc finger transcription factor gata3 in auditory system development by analysing temporal profiles of gene expression during differentiation of conditionally immortal cell lines derived to model specific auditory cell types and developmental stages. We tested and applied a novel probabilistic method called the gamma Model for Oligonucleotide Signals to analyse hybridization signals from Affymetrix oligonucleotide arrays. Expression levels estimated by this method correlated closely (p<0.0001) across a 10-fold range with those measured by quantitative RT-PCR for a sample of 61 different genes. In an unbiased list of 26 genes whose temporal profiles clustered most closely with that of gata3 in all cell lines, 10 were linked to Insulin-like Growth Factor signalling, including the serine/threonine kinase Akt/PKB. Knock-down of gata3 in vitro was associated with a decrease in expression of genes linked to IGF-signalling, including IGF1, IGF2 and several IGF-binding proteins. It also led to a small decrease in protein levels of the serine-threonine kinase Akt2/PKBβ, a dramatic increase in Akt1/PKBα protein and relocation of Akt1/PKBα from the nucleus to the cytoplasm. The cyclin-dependent kinase inhibitor p27kip1, a known target of PKB/Akt, simultaneously decreased. In heterozygous gata3 null mice the expression of gata3 correlated with high levels of activated Akt/PKB. This functional relationship could explain the diverse function of gata3 during development, the hearing loss associated with gata3 heterozygous null mice and the broader symptoms of human patients with Hearing-Deafness-Renal anomaly syndrome.

Transcriptional targets of Drosophila JAK/STAT pathway signalling as effectors of haematopoietic tumour formation.

Although many signal transduction pathways have been implicated in the development of human disease, the identification of pathway targets and the biological processes that mediate disease progression remains challenging. One such disease‐related pathway is the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) cascade whose constitutive misactivation by the JAK2 V617F mutation underlies most human myeloproliferative disorders. Here, we use transcript profiling of Drosophila haemocyte‐like cells to identify JAK/STAT target genes, combined with an in vivo model for JAK‐induced blood cell overproliferation, to identify the main effectors required for haematopoietic tumour development. The identified human homologues of the Drosophila effectors were tested for potential V617F‐mediated transcriptional regulation in human HeLa cells and compared with small interfering RNA‐derived data, quantify their role in regulating the proliferation of cancer‐derived cell lines. Such an inter‐species approach is an effective way to identify factors with conserved functions that might be central to human disease.