Integrative molecular bioinformatics study of human adrenocortical tumors : microRNA, tissue-specific target prediction, and pathway analysis.

MicroRNAs (miRs) are involved in the pathogenesis of several neoplasms; however, there are no data on their expression patterns and possible roles in adrenocortical tumors. Our objective was to study adrenocortical tumors by an integrative bioinformatics analysis involving miR and transcriptomics profiling, pathway analysis, and a novel, tissue-specific miR target prediction approach. Thirty-six tissue samples including normal adrenocortical tissues, benign adenomas, and adrenocortical carcinomas (ACC) were studied by simultaneous miR and mRNA profiling. A novel data-processing software was used to identify all predicted miR-mRNA interactions retrieved from PicTar, TargetScan, and miRBase. Tissue-specific target prediction was achieved by filtering out mRNAs with undetectable expression and searching for mRNA targets with inverse expression alterations as their regulatory miRs. Target sets and significant microarray data were subjected to Ingenuity Pathway Analysis. Six miRs with significantly different expression were found. miR-184 and miR-503 showed significantly higher, whereas miR-511 and miR-214 showed significantly lower expression in ACCs than in other groups. Expression of miR-210 was significantly lower in cortisol-secreting adenomas than in ACCs. By calculating the difference between dCT(miR-511) and dCT(miR-503) (delta cycle threshold), ACCs could be distinguished from benign adenomas with high sensitivity and specificity. Pathway analysis revealed the possible involvement of G2/M checkpoint damage in ACC pathogenesis. To our knowledge, this is the first report describing miR expression patterns and pathway analysis in sporadic adrenocortical tumors. miR biomarkers may be helpful for the diagnosis of adrenocortical malignancy. This tissue-specific target prediction approach may be used in other tumors too.

SwissTargetPrediction: a web server for target prediction of bioactive small molecules.

Bioactive small molecules, such as drugs or metabolites, bind to proteins or other macro-molecular targets to modulate their activity, which in turn results in the observed phenotypic effects. For this reason, mapping the targets of bioactive small molecules is a key step toward unraveling the molecular mechanisms underlying their bioactivity and predicting potential side effects or cross-reactivity. Recently, large datasets of protein-small molecule interactions have become available, providing a unique source of information for the development of knowledge-based approaches to computationally identify new targets for uncharacterized molecules or secondary targets for known molecules. Here, we introduce SwissTargetPrediction, a web server to accurately predict the targets of bioactive molecules based on a combination of 2D and 3D similarity measures with known ligands. Predictions can be carried out in five different organisms, and mapping predictions by homology within and between different species is enabled for close paralogs and orthologs. SwissTargetPrediction is accessible free of charge and without login requirement at http://www.swisstargetprediction.ch.

Allele variants in functional MicroRNA target sites of the neurotrophin-3 receptor gene (NTRK3) as susceptibility factors for anxiety disorders

Genetic and functional data indicate that variation in the expression of the neurotrophin-3 receptor gene (NTRK3) may have an impact on neuronal plasticity, suggesting a role for NTRK3 in the pathophysiology of anxiety disorders. MicroRNA (miRNA) posttranscriptional gene regulators act by base-pairing to specific sequence sites, usually at the 3'UTR of the target mRNA. Variants at these sites might result in gene expression changes contributing to disease susceptibility. We investigated genetic variation in two different isoforms of NTRK3 as candidate susceptibility factors for anxiety by resequencing their 3'UTRs in patients with panic disorder (PD), obsessive-compulsive disorder (OCD), and in controls. We have found the C allele of rs28521337, located in a functional target site for miR-485-3p in the truncated isoform of NTRK3, to be significantly associated with the hoarding phenotype of OCD. We have also identified two new rare variants in the 3'UTR of NTRK3, ss102661458 and ss102661460, each present only in one chromosome of a patient with PD. The ss102661458 variant is located in a functional target site for miR-765, and the ss102661460 in functional target sites for two miRNAs, miR-509 and miR-128, the latter being a brain-enriched miRNA involved in neuronal differentiation and synaptic processing. Interestingly, these two variants significantly alter the miRNA-mediated regulation of NTRK3, resulting in recovery of gene expression. These data implicate miRNAs as key posttranscriptional regulators of NTRK3 and provide a framework for allele-specific miRNA regulation of NTRK3 in anxiety disorders.

Modélisation de réseaux d'interactions des microARN et analyse et validation expérimentale de leurs boucles minimales avec des facteurs de transcription

Les microARN (miARN) sont de petits ARN non-codants qui répriment la traduction de leurs gènes cibles par hybridation à leur ARN messager (ARNm). L'identification de cibles biologiquement actives de miARN est cruciale afin de mieux comprendre leurs rôles. Ce problème est cependant difficile parce que leurs sites ne sont définis que par sept nucléotides. Dans cette thèse je montre qu'il est possible de modéliser certains aspects des miARN afin d'identifier leurs cibles biologiquement actives à travers deux modélisations d'un aspect des miARN. La première modélisation s'intéresse aux aspects de la régulation des miARN par l'identification de boucles de régulation entre des miARN et des facteurs de transcription (FT). Cette modélisation a permis, notamment, d'identifier plus de 700 boucles de régulation miARN/FT, conservées entre l'humain et la souris. Les résultats de cette modélisation ont permis, en particulier, d'identifier deux boucles d'auto-régulation entre LMO2 et les miARN miR-223 et miR-363. Des expériences de transplantation de cellules souches hématopoïétiques et de progéniteurs hématopoïétiques ont ensuite permis d'assigner à ces deux miARN un rôle dans la détermination du destin cellulaire hématopoïétique. La deuxième modélisation s'intéresse directement aux interactions des miARN avec les ARNm afin de déterminer les cibles des miARN. Ces travaux ont permis la mise au point d'une méthode simple de prédiction de cibles de miARN dont les performances sont meilleures que les outils courant. Cette modélisation a aussi permis de mettre en lumière certaines conséquences insoupçonnées de l'effet des miARN, telle que la spécificité des cibles de miARN au contexte cellulaire et l'effet de saturation de certains ARNm par les miARN. Cette méthode peut également être utilisée pour identifier des ARNm dont la surexpression fait augmenter un autre ARNm par l'entremise de miARN partagés et dont les effets sur les ARNm non ciblés seraient minimaux.

Identification of HMX1 target genes: a predictive promoter model approach.

PURPOSE: A homozygous mutation in the H6 family homeobox 1 (HMX1) gene is responsible for a new oculoauricular defect leading to eye and auricular developmental abnormalities as well as early retinal degeneration (MIM 612109). However, the HMX1 pathway remains poorly understood, and in the first approach to better understand the pathway's function, we sought to identify the target genes. METHODS: We developed a predictive promoter model (PPM) approach using a comparative transcriptomic analysis in the retina at P15 of a mouse model lacking functional Hmx1 (dmbo mouse) and its respective wild-type. This PPM was based on the hypothesis that HMX1 binding site (HMX1-BS) clusters should be more represented in promoters of HMX1 target genes. The most differentially expressed genes in the microarray experiment that contained HMX1-BS clusters were used to generate the PPM, which was then statistically validated. Finally, we developed two genome-wide target prediction methods: one that focused on conserving PPM features in human and mouse and one that was based on the co-occurrence of HMX1-BS pairs fitting the PPM, in human or in mouse, independently. RESULTS: The PPM construction revealed that sarcoglycan, gamma (35kDa dystrophin-associated glycoprotein) (Sgcg), teashirt zinc finger homeobox 2 (Tshz2), and solute carrier family 6 (neurotransmitter transporter, glycine) (Slc6a9) genes represented Hmx1 targets in the mouse retina at P15. Moreover, the genome-wide target prediction revealed that mouse genes belonging to the retinal axon guidance pathway were targeted by Hmx1. Expression of these three genes was experimentally validated using a quantitative reverse transcription PCR approach. The inhibitory activity of Hmx1 on Sgcg, as well as protein tyrosine phosphatase, receptor type, O (Ptpro) and Sema3f, two targets identified by the PPM, were validated with luciferase assay. CONCLUSIONS: Gene expression analysis between wild-type and dmbo mice allowed us to develop a PPM that identified the first target genes of Hmx1.

Prédiction de boucles de régulation associant microARN et gènes régulés par le récepteur de l'acide rétinoïque dans le cancer du sein

Le récepteur de l'acide rétinoïque RAR est une protéine de la superfamille des récepteurs nucléaires liant le ligand acide rétinoïque (AR). En présence de son ligand, RAR induit la transcription de ses gènes cibles alors qu'en son absence la transcription est inhibée. Le mécanisme de régulation de RAR est altéré dans les lignées cellulaires humaines de carcinome mammaire dû à une baisse de capacité de synthèse de l'AR. Aussi, l'expression des microARN (miR) est perturbée dans le cancer du sein et un grand nombre de gènes ont été identifiés, après une analyse in-silico, comme des cibles prédites des miRs. Ces derniers peuvent être régulés pas des facteurs de transcription et ils sont capables d'inhiber la prolifération cellulaire et d'induire l'apoptose via la régulation de leurs cibles. Ainsi, les miRs peuvent jouer un rôle dans le mécanisme de régulation de RAR et être impliqués dans des boucles de régulation avec ce récepteur. Dans le cadre de ce travail, nous décrivons une approche développée pour prédire et caractériser des circuits de régulation au niveau transcriptionnel et post-transcriptionnel dans le cancer du sein. Nous nous sommes intéressés aux boucles de régulation de type feed-forward où RAR régule un miR et en commun ils régulent un ensemble de gènes codants pour des protéines dans les cellules tumorales mammaires MCF7 et SKBR3. Ces circuits ont été construits en combinant des données de ChIP-chip de RAR et des données de micro-puces d'ADN tout en utilisant des outils in-silico de prédiction des gènes cibles de miRs. Afin de proposer le modèle approprié de régulation, une analyse in-silico des éléments de réponse de l'AR (RARE) dans les promoteurs des miRs est réalisée. Cette étape permet de prédire si la régulation par RAR est directe ou indirecte. Les boucles ainsi prédites sont filtrées en se basant sur des données d'expression de miR existantes dans des bases de données et dans différentes lignées cellulaires, en vue d'éliminer les faux positifs. De plus, seuls les circuits pertinents sur le plan biologique et trouvés enrichis dans Gene Ontology sont retenus. Nous proposons également d'inférer l'activité des miRs afin d'orienter leur régulation par RAR. L'approche a réussi à identifier des boucles validées expérimentalement. Plusieurs circuits de régulation prédits semblent être impliqués dans divers aspects du développement de l'organisme, de la prolifération et de la différenciation cellulaire. De plus, nous avons pu valider que let-7a peut être induit par l'AR dans les MCF7.

miRNApath: A database of miRNAs, target genes and metabolic pathways

MicroRNAs (miRNAs) are small non-coding RNAs that regulate target gene expression and hence play important roles in metabolic pathways. Recent studies have evidenced the interrelation of miRNAs with cell proliferation, differentiation, development, and diseases. Since they are involved in gene regulation, they are intrinsically related to metabolic pathways. This leads to questions that are particularly interesting for investigating medical and laboratorial applications. We developed an miRNApath online database that uses miRNA target genes to link miRNAs to metabolic pathways. Currently, databases about miRNA target genes (DIANA miRGen), genomic maps (miRNAMap) and sequences (miRBase) do not provide such correlations. Additionally, miRNApath offers five search services and a download area. For each search, there is a specific type of input, which can be a list of target genes, miRNAs, or metabolic pathways, which results in different views, depending upon the input data, concerning relationships between the target genes, miRNAs and metabolic pathways. There are also internal links that lead to a deeper analysis and cross-links to other databases with more detailed information. miRNApath is being continually updated and is available at http://lgmb.fmrp.usp.br/mirnapath. ©FUNPEC-RP.

Shaping the interaction landscape of bioactive molecules.

MOTIVATION: Most bioactive molecules perform their action by interacting with proteins or other macromolecules. However, for a significant fraction of them, the primary target remains unknown. In addition, the majority of bioactive molecules have more than one target, many of which are poorly characterized. Computational predictions of bioactive molecule targets based on similarity with known ligands are powerful to narrow down the number of potential targets and to rationalize side effects of known molecules. RESULTS: Using a reference set of 224 412 molecules active on 1700 human proteins, we show that accurate target prediction can be achieved by combining different measures of chemical similarity based on both chemical structure and molecular shape. Our results indicate that the combined approach is especially efficient when no ligand with the same scaffold or from the same chemical series has yet been discovered. We also observe that different combinations of similarity measures are optimal for different molecular properties, such as the number of heavy atoms. This further highlights the importance of considering different classes of similarity measures between new molecules and known ligands to accurately predict their targets. CONTACT: olivier.michielin@unil.ch or vincent.zoete@unil.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A pilot study identifying a set of microRNAs as precise diagnostic biomarkers of acute kidney injury

In the last decade, Acute Kidney Injury (AKI) diagnosis and therapy have not notably improved probably due to delay in the diagnosis, among other issues. Precocity and accuracy should be critical parameters in novel AKI biomarker discovery. microRNAs are key regulators of cell responses to many stimuli and they can be secreted to the extracellular environment. Therefore, they can be detected in body fluids and are emerging as novel disease biomarkers. We aimed to identify and validate serum miRNAs useful for AKI diagnosis and management. Using qRT-PCR arrays in serum samples, we determined miRNAs differentially expressed between AKI patients and healthy controls. Statistical and target prediction analysis allowed us to identify a panel of 10 serum miRNAs. This set was further validated, by qRT-PCR, in two independent cohorts of patients with relevant morbi-mortality related to AKI: Intensive Care Units (ICU) and Cardiac Surgery (CS). Statistical correlations with patient clinical parameter were performed. Our results demonstrated that the 10 selected miRNAs (miR-101-3p, miR-127-3p, miR-210-3p, miR-126-3p, miR-26b-5p, miR-29a-3p, miR-146a-5p, miR-27a-3p, miR-93-3p and miR-10a-5p) were diagnostic biomarkers of AKI in ICU patients, exhibiting areas under the curve close to 1 in ROC analysis. Outstandingly, serum miRNAs estimated before CS predicted AKI development later on, thus becoming biomarkers to predict AKI predisposition. Moreover, after surgery, the expression of the miRNAs was modulated days before serum creatinine increased, demonstrating early diagnostic value. In summary, we have identified a set of serum miRNAs as AKI biomarkers useful in clinical practice, since they demonstrate early detection and high diagnostic value and they recognize patients at risk.

Gene transfer engineering for astrocyte-specific silencing in the CNS.

Cell-type-specific gene silencing is critical to understand cell functions in normal and pathological conditions, in particular in the brain where strong cellular heterogeneity exists. Molecular engineering of lentiviral vectors has been widely used to express genes of interest specifically in neurons or astrocytes. However, we show that these strategies are not suitable for astrocyte-specific gene silencing due to the processing of small hairpin RNA (shRNA) in a cell. Here we develop an indirect method based on a tetracycline-regulated system to fully restrict shRNA expression to astrocytes. The combination of Mokola-G envelope pseudotyping, glutamine synthetase promoter and two distinct microRNA target sequences provides a powerful tool for efficient and cell-type-specific gene silencing in the central nervous system. We anticipate our vector will be a potent and versatile system to improve the targeting of cell populations for fundamental as well as therapeutic applications.

miR-21 functionally interacts with the 3'UTR of chemokine CCL20 and down-regulates CCL20 expression in miR-21 transfected colorectal cancer cells

As deregulation of miRNAs and chemokine CCL20 was shown to play a role in colorectal cancer (CRC) pathogenesis, we analyzed the functional interactions of candidate miRNAs with CCL20 mRNA. After target prediction software programs indicated a role for miR-21 in CCL20 regulation, we applied the luciferase reporter assay system to demonstrate that miR-21 functionally interacts with the 3'UTR of CCL20 mRNA and down-regulates CCL20 in miR-21 mimic transfected CRC cell lines (Caco-2, SW480 and SW620). Thus, regulation of CCL20 expression by miR-21 might be a regulatory mechanism involved in progression of CRC.

Saccadic eye movement changes in Parkinson's disease dementia and dementia with Lewy bodies.

Neurodegeneration in Parkinson's disease dementia (PDD) and dementia with Lewy bodies (DLB) affect cortical and subcortical networks involved in saccade generation. We therefore expected impairments in saccade performance in both disorders. In order to improve the pathophysiological understanding and to investigate the usefulness of saccades for differential diagnosis, saccades were tested in age- and education-matched patients with PDD (n = 20) and DLB (n = 20), Alzheimer's disease (n = 22) and Parkinson's disease (n = 24), and controls (n = 24). Reflexive (gap, overlap) and complex saccades (prediction, decision and antisaccade) were tested with electro-oculography. PDD and DLB patients had similar impairment in all tasks (P > 0.05, not significant). Compared with controls, they were impaired in both reflexive saccade execution (gap and overlap latencies, P < 0.0001; gains, P < 0.004) and complex saccade performance (target prediction, P < 0.0001; error decisions, P < 0.003; error antisaccades: P < 0.0001). Patients with Alzheimer's disease were only impaired in complex saccade performance (Alzheimer's disease versus controls, target prediction P < 0.001, error decisions P < 0.0001, error antisaccades P < 0.0001), but not reflexive saccade execution (for all, P > 0.05). Patients with Parkinson's disease had, compared with controls, similar complex saccade performance (for all, P > 0.05) and only minimal impairment in reflexive tasks, i.e. hypometric gain in the gap task (P = 0.04). Impaired saccade execution in reflexive tasks allowed discrimination between DLB versus Alzheimer's disease (sensitivity > or =60%, specificity > or =77%) and between PDD versus Parkinson's disease (sensitivity > or =60%, specificity > or =88%) when +/-1.5 standard deviations was used for group discrimination. We conclude that impairments in reflexive saccades may be helpful for differential diagnosis and are minimal when either cortical (Alzheimer's disease) or nigrostriatal neurodegeneration (Parkinson's disease) exists solely; however, they become prominent with combined cortical and subcortical neurodegeneration in PDD and DLB. The similarities in saccade performance in PDD and DLB underline the overlap between these conditions and underscore differences from Alzheimer's disease and Parkinson's disease.

Identification of micro-RNAs targeting genes of PI3K/AKT pathway in ovarian cancer

Ovarian cancer is the leading cause of cancer-related death for females due to lack of specific early detection method. It is of great interest to find molecular-based biomarkers which are sensitive and specific to ovarian cancer for early diagnosis, prognosis and therapeutics. miRNAs have been proposed to be potential biomarkers that could be used in cancer prevention and therapeutics. The current study analyzed the miRNA and mRNA expression data extracted from the Cancer Genome Atlas (TCGA) database. Using simple linear regression and multiple regression models, we found 71 miRNA-mRNA pairs which were negatively associated between 56 miRNAs and 24 genes of PI3K/AKT pathway. Among these miRNA and mRNA target pairs, 9 of them were in agreement with the predictions from the most commonly used target prediction programs including miRGen, miRDB, miRTarbase and miR2Disease. These shared miRNA-mRNA pairs were considered to be the most potential genes that were involved in ovarian cancer. Furthermore, 4 of the 9 target genes encode cell cycle or apoptosis related proteins including Cyclin D1, p21, FOXO1 and Bcl2, suggesting that their regulator miRNAs including miR-16, miR-96 and miR-21 most likely played important roles in promoting tumor growth through dysregulated cell cycle or apoptosis. miR-96 was also found to directly target IRS-1. In addition, the results showed that miR-17 and miR-9 may be involved in ovarian cancer through targeting JAK1. This study might provide evidence for using miRNA or miRNA profile as biomarker.^

Systems Biology Approaches to Probe Gene Regulation in Bacteria

Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb). First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses and survive within resting macrophages. As a result, the method unveiled transcriptional regulators and associated regulons utilized by Mtb to establish a successful infection of macrophages throughout the first 14 days of infection. Additionally, this network-based analysis identified the production of Fe-S proteins coupled to lipid metabolism through the alkane hydroxylase complex as a possible strategy employed by Mtb to survive in the host. Second, I developed a network inference method to infer the small non-coding RNA (sRNA) regulatory network in Mtb. The method identifies sRNA-mRNA interactions by integrating a priori knowledge of possible binding sites with structure-driven identification of binding sites. The reconstructed network was useful to predict functional roles for the multitude of sRNAs recently discovered in the pathogen, being that several sRNAs were postulated to be involved in virulence-related processes. Finally, I applied a combined experimental and computational approach to study post-transcriptional repression mediated by small non-coding RNAs in bacteria. Specifically, a probabilistic ranking methodology termed rank-conciliation was developed to infer sRNA-mRNA interactions based on multiple types of data. The method was shown to improve target prediction in Escherichia coli, and therefore is useful to prioritize candidate targets for experimental validation.

Estudos sobre a organização genômica, evolução e expressão de microRNAs

Os microRNAs (miRNAs) são pequenos RNAs não codificadores de proteínas presentes na maioria dos eucariotos. Esses RNAs regulam a expressão gênica em nível pós-transcricional através do silenciamento de mRNAs-alvo que possuem sítios complementares às suas sequências, atuando em praticamente todos os processos celulares. Embora a estrutura e função dos miRNAs estejam bem caracterizadas, aspectos relacionados à sua organização genômica, evolução e atuação em doenças são tópicos que apresentam enormes lacunas. Nesta tese, utilizamos abordagens computacionais para investigar estes temas em três trabalhos. No primeiro, processamos e integramos um vasto volume de dados publicamente disponíveis referentes aos miRNAs e genes codificadores de proteínas para cinco espécies de vertebrados. Com isso, construimos uma ferramenta web que permite a fácil inspeção da organização genômica dos miRNAs em regiões inter e intragênicas, o acesso a dados de expressão de miRNAs e de genes codificadores de proteínas (classificados em genes hospedeiros e não hospedeiros de miRNAs), além de outras informações pertinentes. Verificamos que a ferramenta tem sido amplamente utilizada pela comunidade científica e acreditamos que ela possa facilitar a geração de hipóteses associadas à regulação dos miRNAs, principalmente quando estão inseridos em genes hospedeiros. No segundo estudo, buscamos compreender como o contexto genômico e a origem evolutiva dos genes hospedeiros influenciam a expressão e evolução dos miRNAs humanos. Nossos achados mostraram que os miRNAs intragênicos surgem preferencialmente em genes antigos (origem anterior à divergência de vertebrados). Observamos que os miRNAs inseridos em genes antigos têm maior abrangência de expressão do que os inseridos em genes novos. Surpreendentemente, miRNAs jovens localizados em genes antigos são expressos em um maior número de tecidos do que os intergênicos de mesma idade, sugerindo uma vantagem adaptativa inicial que pode estar relacionada com o controle da expressão dos genes hospedeiros, e como consequência, expondo-os a contextos celulares e conjuntos de alvos diversos. Na evolução a longo prazo, vimos que genes antigos conferem maior restrição nos padrões de expressão (menor divergência de expressão) para miRNAs intragênicos, quando comparados aos intergênicos. Também mostramos possíveis associações funcionais relacionadas ao contexto genômico, tais como o enriquecimento da expressão de miRNAs intergênicos em testículo e dos intragênicos em tecidos neurais. Propomos que o contexto genômico e a idade dos genes hospedeiros são fatores-chave para a evolução e expressão dos miRNAs. Por fim, buscamos estabelecer associações entre a expressão diferencial de miRNAs e a quimioresistência em câncer colorretal utilizando linhagens celulares sensíveis e resistentes às drogas 5-Fluoruracil e Oxaliplatina. Dentre os miRNAs identificados, o miR-342 apresentou níveis elevados de expressão nas linhagens sensíveis à Oxaliplatina. Com base na análise dos alvos preditos, detectamos uma significativa associação de miR-342 com a apoptose. A superexpressão de miR-342 na linhagem resistente SW620 evidenciou alterações na expressão de genes da via apoptótica, notavelmente a diminuição da expressão do fator de crescimento PDGFB, um alvo predito possivelmente sujeito à regulação direta pelo miR-342.