Dysregulated placental microRNAs in Early and Late onset Preeclampsia

Copyright © 2017. Published by Elsevier Ltd.INTRODUCTION: To determine the miRNA expression profile in placentas complicated by Preeclampsia (PE) and compare it to uncomplicated pregnancies. METHODS: Sixteen placentas from women with PE, [11 with early onset PE (EOPE) and 5 with late onset PE (LOPE)], as well as 8 placentas from uncomplicated pregnancies were analyzed using miRNA microarrays. For statistical analyses the MATLAB® simulation environment was applied. The over-expression of miR-518a-5p was verified using Quantitative Real-Time Polymerase Chain Reaction. RESULTS: Forty four miRNAs were found dysregulated in PE complicated placentas. Statistical analysis revealed that miR-431, miR-518a-5p and miR-124* were over-expressed in EOPE complicated placentas as compared to controls, whereas miR-544 and miR-3942 were down-regulated in EOPE. When comparing the miRNA expression profile in cases with PE and PE-growth restricted fetuses (FGR), miR-431 and miR-518a-5p were found over-expressed in pregnancies complicated by FGR. DISCUSSION: Since specific miRNAs can differentiate EOPE and LOPE from uncomplicated placentas, they may be considered as putative PE-specific biomarkers. MiR-518a-5p emerged as a potential diagnostic indicator for EOPE cases as well as for PE-FGR complicated placentas, indicating a potential link to the severity of the disease.Peer reviewe

Involvement of microRNAs in physiological and pathological processes in the lung

To date, at least 900 different microRNA (miRNA) genes have been discovered in the human genome. These short, single-stranded RNA molecules originate from larger precursor molecules that fold to produce hairpin structures, which are subsequently processed by ribonucleases Drosha/Pasha and Dicer to form mature miRNAs. MiRNAs play role in the posttranscriptional regulation of about one third of human genes, mainly via degradation of target mRNAs. Whereas the target mRNAs are often involved in the regulation of diverse physiological processes ranging from developmental timing to apoptosis, miRNAs have a strong potential to regulate fundamental biological processes also in the lung compartment. However, the knowledge of the role of miRNAs in physiological and pathological conditions in the lung is still limited. This review, therefore, summarizes current knowledge of the mechanism, function of miRNAs and their contribution to lung development and homeostasis. Besides the involvement of miRNAs in pulmonary physiological conditions, there is evidence that abnormal miRNA expression may lead to pathological processes and development of various pulmonary diseases. Next, the review describes current state-of-art on the miRNA expression profiles in smoking-related diseases including lung cancerogenesis, in immune system mediated pulmonary diseases and fibrotic processes in the lung. From the current research it is evident that miRNAs may play role in the posttranscriptional regulation of key genes in human pulmonary diseases. Further studies are, therefore, necessary to explore miRNA expression profiles and their association with target mRNAs in human pulmonary diseases

The 20th anniversary of EMBnet: 20 years of bioinformatics for the Life Sciences community

The EMBnet Conference 2008, focusing on 'Leading Applications and Technologies in Bioinformatics', was organized by the European Molecular Biology network (EMBnet) to celebrate its 20th anniversary. Since its foundation in 1988, EMBnet has been working to promote collaborative development of bioinformatics services and tools to serve the European community of molecular biology laboratories. This conference was the first meeting organized by the network that was open to the international scientific community outside EMBnet. The conference covered a broad range of research topics in bioinformatics with a main focus on new achievements and trends in emerging technologies supporting genomics, transcriptomics and proteomics analyses such as high-throughput sequencing and data managing, text and data-mining, ontologies and Grid technologies. Papers selected for publication, in this supplement to BMC Bioinformatics, cover a broad range of the topics treated, providing also an overview of the main bioinformatics research fields that the EMBnet community is involved in

miRTar: an integrated system for identifying miRNA-target interactions in human

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are small non-coding RNA molecules that are ~22-nt-long sequences capable of suppressing protein synthesis. Previous research has suggested that miRNAs regulate 30% or more of the human protein-coding genes. The aim of this work is to consider various analyzing scenarios in the identification of miRNA-target interactions, as well as to provide an integrated system that will aid in facilitating investigation on the influence of miRNA targets by alternative splicing and the biological function of miRNAs in biological pathways.</p> <p>Results</p> <p>This work presents an integrated system, miRTar, which adopts various analyzing scenarios to identify putative miRNA target sites of the gene transcripts and elucidates the biological functions of miRNAs toward their targets in biological pathways. The system has three major features. First, the prediction system is able to consider various analyzing scenarios (1 miRNA:1 gene, 1:N, N:1, N:M, all miRNAs:N genes, and N miRNAs: genes involved in a pathway) to easily identify the regulatory relationships between interesting miRNAs and their targets, in 3'UTR, 5'UTR and coding regions. Second, miRTar can analyze and highlight a group of miRNA-regulated genes that participate in particular KEGG pathways to elucidate the biological roles of miRNAs in biological pathways. Third, miRTar can provide further information for elucidating the miRNA regulation, i.e., miRNA-target interactions, affected by alternative splicing.</p> <p>Conclusions</p> <p>In this work, we developed an integrated resource, miRTar, to enable biologists to easily identify the biological functions and regulatory relationships between a group of known/putative miRNAs and protein coding genes. miRTar is now available at <url>http://miRTar.mbc.nctu.edu.tw/</url>.</p

Novel Regulators of Pancreatic Cancer Cell Growth and Mobility

Haimasyöpä on harvinainen mutta erittäin aggressiivinen syöpätyyppi, johon sairastuu Suomessa vuosittain noin tuhat henkilöä. Vaikka haimasyövän osuus uusista syöpätapauksista on vain muutama prosentti, se on kolmanneksi yleisin syöpäkuolemien syy niin miehillä kuin naisillakin. Haimasyövän ennuste on erittäin huono: keskimääräinen elinaika diagnoosista on vain noin puoli vuotta. Suurin syy tähän on se, että keinoja taudin diagnosointiin ja hoitoon on todella vähän, ja hoidot ovat usein tehottomia. Diagnoosi tehdään yleensä vasta vaiheessa, jossa sairaus on edennyt niin pitkälle, ettei sitä pystytä enää parantamaan. Väitöskirjatyön tarkoituksena oli tutkia haimasyövässä toistuvasti monistuvia kromosomialueita sekä kartoittaa geenien toimintaa säätelevien mikroRNA:iden ilmenemismuutoksia ja siten löytää uusia mahdollisia kohdegeenejä niin diagnostisiin kuin hoidollisiinkin tarkoituksiin. Laajat kromosomimuutokset ovat tyypillisiä haimasyövälle kuten suurimmalle osalle muitakin kiinteitä syöpäkasvaimia. Toistuvasti monistuvilla kromosomialueilla sijaitsee suurella todennäköisyydellä geenejä, joilla on vaikutusta sairauden syntyyn, ja jotka siten voisivat toimia myös ns. kohdegeeneinä syövän diagnoosissa tai hoidossa. Tässä työssä tutkittiin 7q21-q22 kromosomialueen monistumaa haimasyövässä ja pyrittiin siten löytämään uusia kohdegeenejä. Kyseistä monistumaa todettiin esiintyvän noin joka neljännessä haimasyöpäsolulinjassa ja yhtä usein myös haiman primäärikasvaimissa. Monistuman todettiin johtavan useiden geenien yli-ilmentymiseen. Jatkotutkimukset kohdistuivat kolmeen monistuneeseen geeniin, ARPC1A, ARPC1B ja KPNA7, ja osoittivat, että näiden toiminta vaikuttaa haimasyövän ominaisuuksiin. ARPC1A ja ARPC1B kuuluvat proteiinikompleksiin, joka säätelee muun muassa solujen liikkumista. Näiden kahden geenin hiljentäminen haimasyöpäsoluissa vähensi huomattavasti solujen liikkumiskykyä, mikä on merkittävä syövän leviämiseen liittyvä ominaisuus. KPNA7 puolestaan osallistuu proteiinien kuljetukseen solun sytoplasmasta tumaan. Sen ilmentymisen hiljentäminen vähensi dramaattisesti haimasyöpäsolujen kasvua. Kasvun hidastuminen johtui p21-proteiinin ilmentymistason kohoamisesta ja siitä seuranneesta solusyklin osittaisesta pysähtymisestä. Kaiken kaikkiaan nämä tulokset viittaavat siihen, että 7q21-q22 monistuma-alueella ei olisi yhtä ainoaa kohdegeeniä, vaan ennemmin useamman geenin joukko, jotka kaikki ovat monistuneita ja yli-ilmentyneitä ja yhdessä vaikuttavat syöpäsolujen eri ominaisuuksiin. Sekä ARPC1A, ARPC1B että KPNA7 toimivat tärkeissä solun toimintaan vaikuttavissa tehtävissä, ja ovat siten potentiaalisia uusien syöpähoitojen kohteita. MikroRNA:t ovat lyhyitä yksijuosteisia RNA-molekyylejä, joilla on tärkeä tehtävä geenien ilmentymisen säätelyssä. Myös niiden ilmentyminen on usein häiriintynyt syövässä. Mikro-RNA:iden ilmentymistä tutkittiin haimasyöpäsolulinjoissa sekä normaalista haimasta peräisin olevissa näytteissä, ja tarkoituksena oli tunnistaa sellaiset mikro-RNA:t, joiden ilmentyminen oli muuttunut syövässä. Työssä löydettiin 72 mikro-RNA:ta, joiden muuttuneen ilmentymisen perusteella voitiin erottaa syöpänäytteet normaaleista näytteistä. Näiden joukosta valittiin miR-31 tarkempiin tutkimuksiin sen erityisen mielenkiintoisen ilmentymistavan vuoksi. Yllättäen sekä miR-31:n ilmentymisen estäminen että lisääminen johtivat haimasyöpäsolujen liikkumisen selkeään vähenemiseen. Useissa tutkimuksissa miR-31:n on todettu olevan tärkeä solujen liikkumisen säätelijä haimasyövän lisäksi myös muissa syövissä. Tämä tekee siitä erityisen houkuttelevan kohteen syövän etäpesäkkeisiin kohdistuville hoitomuodoille. Yhteenvetona voidaan todeta, että tässä tutkimuksessa osoitettiin kolmella 7q21-q22 monistuman kohdegeenillä olevan onkogeenisiä eli syöpää edistäviä ominaisuuksia haimasyövässä. Kaikki nämä kolme geeniä, ARPC1A, ARPC1B ja KPNA7, olivat yli-ilmentyneitä haimasyöpäsoluissa ja niiden toiminta osaltaan vahvisti näiden solujen pahanlaatuisia ominaispiirteitä. Lisäksi miR-31:n todettiin yli-ilmentyvän osassa haimasyövistä, ja sen osoitettiin olevan tärkeä syöpäsolujen liikkumisen säätelijä. Tämä tutkimus tuo uutta tietoa haimasyövän geneettisestä taustasta ja tarjoaa mielenkiintoisia lähtökohtia tämän taudin diagnosointi- ja hoitomenetelmien kehittämiseen.Pancreatic cancer is a rare but very aggressive malignancy affecting yearly approximately 1,000 individuals in Finland. Although it accounts only for a little over 3% of all new cancer cases, it is the third leading cause of cancer deaths for both genders. The main cause for the poor prognosis is the fact that the diagnostic and therapeutic tools for pancreatic cancer are truly limited and inefficient. This study aimed to characterize both recurrently amplified chromosomal regions as well as microRNA expression patterns in pancreatic cancer and thus to identify novel putative targets for diagnostic and therapeutic purposes. Large chromosomal aberrations are typical for most solid tumors, including pancreatic cancer. Recurrently amplified regions are likely to contain genes which contribute to the development of the disease and might thus serve as targets for early detection or treatment of the disease. Here, a detailed characterization of the 7q21 q22 amplicon in pancreatic cancer was performed in order to identify novel target genes. The amplification was found to exist in 25% of both pancreatic cancer cell lines and primary tumors and to result in overexpression of several genes within the amplicon core. Further functional studies on three of the amplified genes, ARPC1A, ARPC1B, and KPNA7 confirmed that these genes do contribute to the pathogenesis of pancreatic cancer. ARPC1A and ARPC1B both encode for the ARPC1 subunit of the ARP2/3 protein complex which participates in actin polymerization and thus regulates cell mobility. Silencing of these two genes in pancreatic cancer cells resulted in a significant reduction of cell migration and invasion, presumably due to defective function of the ARP2/3 complex. KPNA7 belongs to the karyopherin alpha protein family of nuclear import receptors. Silencing of KPNA7 expression dramatically decreased the growth of pancreatic cancer cell lines via a p21 induced G1 arrest. These data suggest that rather than a single target gene, the 7q21-q22 amplicon contains a set of genes which are all amplified and overexpressed and together contribute to different features of the cancer cells. Both ARPC1 and KPNA7 have important cellular functions and might serve as potential novel therapeutic targets. MicroRNAs are short single-stranded RNA molecules which have a crucial role in regulating gene expression, and are also widely misregulated in cancer. The expression levels of miRNAs in a panel of pancreatic cancer cell lines and normal samples were screened to identify miRNAs that are aberrantly expressed in pancreatic cancer. A set of 72 differentially expressed miRNAs was found to provide a molecular signature discriminating the cancer and normal samples. Of these, miR-31 was further functionally studied based on its unique on-off expression pattern. Interestingly, both inhibiting and inducing miR-31 expression decreased the migration of pancreatic cancer cells, indicating that not only the presence but also the amount of miR-31 is important for its function. The role of miR-31 as a regulator of cancer cell mobility has also been established in various other cancers, making it a tempting target for anti-metastasis therapy. To conclude, three target genes of the 7q21-q22 amplicon, ARPC1A, ARPC1B, and KPNA7 were shown to have oncogenic properties in pancreatic cancer, as they were all overexpressed and promoted the malignant properties of the disease. Furthermore, miR-31 was shown to be overexpressed in a subset of pancreatic cancers and to regulate cancer cell mobility. Overall, this study provides novel information on the genetic background of pancreatic cancer pathogenesis

Validierung und Target-Identifizierung deregulierter microRNAs in Metastasen des klarzelligen Nierenzellkarzinom

Die Prognose der Patienten mit einem klarzelligen Nierenzellkarzinom verschlechtert sich bei vorliegender Metastasierung drastisch. Auch neuartige zielgerichtete Systemtherapien und Immuntherapien führen äußerst selten zu einer kompletten Remission. Um neue effektive Therapieansätze und neue Prognoseparameter zu entwickeln, ist es notwendig, die molekularbiologischen Mechanismen der Metastasierung im klarzelligen Nierenzellkarzinom besser zu verstehen. MicroRNAs sind entscheidende Regulatoren diverser molekularbiologischer Prozesse. Vorrangegangene Untersuchungen konnten Expressionsunterschiede der microRNAs zwischen Primärtumoren und dem umliegenden Normalgewebe bestätigen. Mithilfe der Expressionsunterschiede und funktioneller Analysen konnte die Beteiligung von microRNAs an der Tumorgenese belegt werden. Wenig untersucht ist die microRNA Expression in den Metastasen. Die Vorergebnisse von Heinzelmann, Unrein et al. konnten diesbezüglich Unterschiede zwischen Primärtumoren und Lungen-, Knochen- und Gehirnmetastasen zeigen. Mittels Microarrayanalysen wurden microRNAs (insbesondere miR-30a-3p, miR-24-1-5p) identifiziert, welche an den Hauptmetastasierungsorten im Vergleich zu den Primärtumoren verändert exprimiert waren. Zusätzlich wurden an einzelnen Metastasierungsorten spezifische microRNA-Änderungen (unter anderem miR-200a-3p-Deregulation in Gehirnmetastasen) detektiert. Um die Metastasierungsprozesse besser zu verstehen, ist es das Ziel dieser Arbeit, auf Basis der Vorergebnisse die Genexpressionsunterschiede von miR-30a-3p, miR-24-1-5p und der miR-200a-3p in weiteren Tumor- und Metastasengeweben mittels quantitative reverse transcription-polymerase chain reaction (qRT-PCR) zu validieren. Am Beispiel einer ausgewählten microRNA soll die Bedeutung für die Metastasierung mithilfe der Targetidentifizierung untersucht werden. Total-RNA wurde aus formalin-fixed paraffin-embedded (FFPE) Proben von metastasierten und nicht-metastasierten Primärtumoren des klarzelligen Nierenzellkarzinoms (n=28) und Fernmetastasen (n=29) aus Lunge, Gehirn und Knochen isoliert. Mittels qRT-PCR wurde die relative Genexpression der miR-30a-3p, miR-24-1-5p und miR-200a-3p ermittelt. Nach der Transienten Transfektion von miR-30a-3p in die Zelllinie 786-O wurden die potentiellen microRNA-Targets mittels Zwei-Dimensionaler-Gelelektrophorese identifiziert. Mithilfe des computerbasierten Vorhersage-Programmes GOmir und miRWalk wurden die komplementären Nukleotidsequenzen der potentiellen Targets für miR-30a-3p zusätzlich abgeglichen. Zunächst beinhaltet die vorliegende Arbeit den Nachweis einer spezifischen microRNA-Änderung an einem einzelnen Metastasierungsort. Die Expression der miR-200a-3p war reduziert in Gehirnmetastasen im Vergleich zu den nicht-metastasierten und metastasierten Primärtumoren (5,38-fach (p= 0,00024) /4,9-fach (p= 0,003)). MiR-200a-3p wurde in Gehirnmetastasen gegenüber der Knochenmetastasen um das 2,92-fache (p=0,003) und gegenüber der Lungenmetastasen um das 4,33-fache (p=0,003) reduziert exprimiert. Übereinstimmend mit dem Vorarbeiten war eine spezifische miRNA-Expressionsänderung für miR-200a-3p in Gehirnmetastasen reproduzierbar. Die ortsspezifische Expressionsänderung deutet auf Prozesse hin, die sich in den verschiedenen Metastasierungsorten unterscheiden. Weiterhin war eine generelle Expressionsveränderung von miR-30a-3p und miR-24-1-5p an den Hauptmetastasierungsorten zu überprüfen. Eine Expressionsänderung von miR-24-1-5p an den Hauptmetastasierungsorten (Gehirn, Lunge und Knochen) konnte mittels qRT-PCR nur teilweise bestätigt werden. Nur in Gehirnmetastasen zeigte sich ein deutlicher Expressionsunterschied im Vergleich zu den Primärtumoren und den Lungenmetastasen. Damit ist miR-24-1-5p am ehesten als eine microRNA anzusehen, die nicht in allen Hauptmetastasierungsorten verändert ist, sondern nur im Gehirn. Hingegen zeigte miR-30a-3p eine generelle Expressionsveränderung an den Hauptmetastasierungsorten. Die relative Genexpression von miR-30a-3p nahm im Vergleich zu den nicht-metastasierten klarzelligen Nierenzellkarzinom in dem metastasierten klarzelligen Nierenzellkarzinom um ein 1,99-faches (p=0,028), in den Knochenmetastasen um ein 4,08-faches (p=0,0005), in den Gehirnmetastasen um ein 8,13-faches (p=0,00005) und in den Lungenmetastasen um ein 2,62-faches (p=0,002) ab. Die generelle Expressionsänderung in den Hauptmetastasierungsorten im Vergleich zum Primärtumor deutet auf eine Beteiligung am Metastasierungsprozess hin. Die zusätzlich nachgewiesene Verminderung der miR-30a-3p im metastasierten Primärtumor lässt schlussfolgern, dass miR-30a-3p schon an den initialen Prozessen der Metastasierung beteiligt ist. Die identifizierten potentiellen miRNA-Targets der miR-30a-3p sprechen ebenfalls für diese These. Mithilfe der Zwei-dimensionalen Gelelektrophorese wurden die potentiellen Targets Alpha-Enolase, Galectin-1, Cofilin und Nukleosid-Diphosphat-kinase B identifiziert. Alpha-Enolase ist ein Enzym der Glykolyse und Glukoneogenese und dient als Energiequelle für Tumorzellen (WARBURG, 1956a). Die Ziel-mRNA, Galectin-1 ist in verschiedenen Signalwegen beschrieben, unter anderem in der Zelladhäsion und der Metastasierung. Cofilin und Nukleosid-Diphosphat-kinase B, sind am Signalweg des Aktinzytoskelettumbaus beteiligt und tragen zur Mobilität der Zellen bei. Die Mobilität von Tumorzellen ist ein essentieller Vorgang in der Metastasierung. Die vorliegenden Ergebnisse deuten erstmalig auf eine regulierende Funktion der miR-30a-3p an dem Signalweg des Cofilins hin. Damit scheint miR-30a-3p über Cofilin an der Metastasierung des klarzelligen Nierenzellkarzinoms beteiligt zu sein. Zusammenfassend leisten die verifizierten microRNA Expressionen und die identifizierten Targets einen Beitrag zum besseren Verständnis der Metastasierung des klarzelligen NZK. In Zukunft sollte geprüft werden, ob sich die untersuchten microRNAs als biologische Marker für den individuellen Krankheitsverlauf und die prognosebestimmende Metastasierung eignenThe prognosis of patients with a clear cell renal cell carcinoma drastically deteriorates due to metastasis. Even novel targeted therapy and immune therapy rarely achieves a complete remission. To develop new effective therapies and new prognostic factors, a better understanding of molecular mechanism of metastasis is necessary. MicroRNAs (miRNAs) are regulators of diverse molecular processes. Previous analyses could confirm alterations in miRNA expression between primary tumors und normal kidney tissue. MiRNA expression alterations and functional analyses confirmed a participation of miRNAs in tumorigenesis. Little is known about miRNA expression levels in metastases. Regarding to these preceding studies by Heinzelmann, Unrein et al. found miRNA alterations between primary tumors and of lung, bone and brain metastases. By microarray analyses, miRNAs (in particular miR-30a-3p, miR-24-1-5p) were identified, which were differentially expressed in metastases in comparison with primary tumors. Additionally there were specific miRNA alterations found at some metastasis locations (for example the dysregulation of miR-200a-3p in brain metastases). For a better understanding of metastasis processes, the aim of this study is to validate on the basis of the preceding study the gene expression alterations of miR-30a-3p, miR-24-1-5p and miR-200a-3p in other tissues of primary tumors and metastases by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). For one selected miRNA the correlation to the metastasis process shall be investigated by target identification. Total-RNA samples of metastatic and non-metastatic primary clear cell renal cell carcinoma (n=28) and metastases from lung, brain, bone (n=29) were isolated from formalin-fixed paraffin-embedded (FFPE) samples. The relative gene expression of miR-30a-3p, miR-24-1-5p and miR-200a-3p was investigated by qRT-PCR. After transient transfection of miR-30a-3p in cell line 786-O, targets were identified by two-dimensional gel electrophoresis. The nucleotide sequences of the potential targets of miR-30a-3p were compared by the computer-based prediction programs GOmir and miRWalk. At first this study treats the verification of a differently expressed miRNA in a single metastatic location. The gene expression of miR-200a-3p was found to be reduced in brain metastases compared to non-metastatic and metastatic primary tumors (5,38-fold (p= 0,00024) /4,9-fold (p= 0,003)). Furthermore miR-200a-3p was reduced expressed in brain metastasis compared to bone (2,92-fold (p=0,003)) and lung metastases (4,33-fold (p=0,003)). Concordantly to the preceding studies a specific miRNA expression alteration was confirmed. The specific local expression alterations indicate differences in the processes at different metastases locations. Furthermore a general expression alteration of miR-30a-3p and miR-24-1-5p in the distant metastases should be verified. An expression alteration of miR-24-1-5p in distant metastases (brain, lung and bones) could be partially confirmed by qRT-PCR. But in brain metastasis the expression is reduced compared to primary tumors and lung metastases. Therefore miR-24-1-5p is not regarded to be generally dysregulated miRNA in distant metastases, but rather as a dysregulated miRNA just in brain metastases. However, miR-30a-3p showed a general decrease of the expression in distant metastases. The relative gene expression of miR-30a-3p was found reduced in metastatic primary tumors (1,99-fold (p=0,028)), in brain metastases (8,13-faches (p=0,00005)), in lung metastases (2,62-faches (p=0,002)) and in bone metastases (4,08-faches (p=0,0005)) compared to non-metastatic primary tumor. The general expression alteration in the distant metastases shows that different processes between primary tumor and distant metastasis occur. These processes are supposed to be involved in the metastasis. Additionally the decrease of miR-30a-3p expression in metastatic primary tumor shows which miR-30a-3p is involved in the early steps of metastasis. The identified potential targets of miR-30a-3p support this thesis. By two-dimensional gel electrophoresis four targets, alpha-enolase, galectin-1 cofilin and nucleosid-diphosphate-kinase B were identified. Alpha-enolase is an enzyme of the glycolysis and gluconeogenesis and serves as energy source for tumor cells. The target galectin-1 is described in several signal pathways, amongst other in cell adhesion and in the metastasis. Two more microRNA-targets, cofilin and nucleosid-diphosphate-kinase B are involved in the signal pathway of actin cytoskeleton organization and contribute to cell mobility. Cell mobility is an essential event in metastasis. For the first time, the present study suggests a regulatory function of miR-30a-3p in the cofilin pathway. The verified miRNA expression alterations and the identified targets contribute to a better understanding of metastasis. In the future the investigated microRNAs shell be proved as biological markers for the individual follow-up prediction and for the metastasis prognosis

Investigating “Gene Ontology”- based semantic similarity in the context of functional genomics

Gene functional annotations are an essential part of knowledge discovery in the analysis of large datasets, with the Gene Ontology [Ashburner et al., 2000] as the de facto standard for such annotations. A considerable number of approaches for quantifying functional similarity between gene products based on the semantic similarity between their annotations have been developed, but little guidance exists as to which of these measures are the most appropriate for different purposes. This was addressed here by comparing the performances of a number of similarity measures and associated parameters. This comparison provided some interesting new insights as well as confirming emerging trends from the literature. There is also a pressing need for novel ways of applying these measures to facilitate the functional analysis of lists of gene products. We developed a novel algorithm, FuSiGroups, to group GO terms based on their semantic similarity and genes based on their functional similarity. This two-fold grouping results in groups of not only functionally similar genes but also an associated set of related GO terms that characterise a single functional aspect relating the genes in the group, which facilitates analysis by creating more coherent groups. Each gene can belong to multiple groups, so the groups more accurately reflect the complexity of biological reality than clusters generated using traditional approaches. FuSiGroups was tested on a number of scenarios and in each case, successfully generated biologically relevant groups, identifying the key functional aspects of the dataset. The algorithm also managed to eliminate genes that were functionally unrelated to the bulk of the dataset and distinguish between different biological pathways. Although dataset size is currently a limiting factor, with smaller datasets performing the best, FuSiGroups has been demonstrated as a promising approach for the functional analysis of gene products

Investigating “Gene Ontology”- based semantic similarity in the context of functional genomics

Gene functional annotations are an essential part of knowledge discovery in the analysis of large datasets, with the Gene Ontology [Ashburner et al., 2000] as the de facto standard for such annotations. A considerable number of approaches for quantifying functional similarity between gene products based on the semantic similarity between their annotations have been developed, but little guidance exists as to which of these measures are the most appropriate for different purposes. This was addressed here by comparing the performances of a number of similarity measures and associated parameters. This comparison provided some interesting new insights as well as confirming emerging trends from the literature. There is also a pressing need for novel ways of applying these measures to facilitate the functional analysis of lists of gene products. We developed a novel algorithm, FuSiGroups, to group GO terms based on their semantic similarity and genes based on their functional similarity. This two-fold grouping results in groups of not only functionally similar genes but also an associated set of related GO terms that characterise a single functional aspect relating the genes in the group, which facilitates analysis by creating more coherent groups. Each gene can belong to multiple groups, so the groups more accurately reflect the complexity of biological reality than clusters generated using traditional approaches. FuSiGroups was tested on a number of scenarios and in each case, successfully generated biologically relevant groups, identifying the key functional aspects of the dataset. The algorithm also managed to eliminate genes that were functionally unrelated to the bulk of the dataset and distinguish between different biological pathways. Although dataset size is currently a limiting factor, with smaller datasets performing the best, FuSiGroups has been demonstrated as a promising approach for the functional analysis of gene products.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Human microRNA target analysis and gene ontology clustering by GOmir, a novel stand-alone application

Background: microRNAs (miRNAs) are single-stranded RNA molecules of about 20–23 nucleotides length found in a wide variety of organisms. miRNAs regulate gene expression, by interacting with target mRNAs at specific sites in order to induce cleavage of the message or inhibit translation. Predicting or verifying mRNA targets of specific miRNAs is a difficult process of great importance. Results: GOmir is a novel stand-alone application consisting of two separate tools: JTarget and TAGGO. JTarget integrates miRNA target prediction and functional analysis by combining the predicted target genes from TargetScan, miRanda, RNAhybrid and PicTar computational tools as well as the experimentally supported targets from TarBase and also providing a full gene description and functional analysis for each target gene. On the other hand, TAGGO application is designed to automatically group gene ontology annotations, taking advantage of the Gene Ontology (GO), in order to extract the main attributes of sets of proteins. GOmir represents a new tool incorporating two separate Java applications integrated into one stand-alone Java application. Conclusion: GOmir (by using up to five different databases) introduces miRNA predicted targets accompanied by (a) full gene description, (b) functional analysis and (c) detailed gene ontology clustering. Additionally, a reverse search initiated by a potential target can also be conducted. GOmir can freely be downloaded BRFAA