2 resultados para Heterogeneous information network
em Glasgow Theses Service
Resumo:
Acute myeloid leukemia (AML) involves the proliferation, abnormal survival and arrest of cells at a very early stage of myeloid cell differentiation. The biological and clinical heterogeneity of this disease complicates treatment and highlights the significance of understanding the underlying causes of AML, which may constitute potential therapeutic targets, as well as offer prognostic information. Tribbles homolog 2 (Trib2) is a potent murine oncogene capable of inducing transplantable AML with complete penetrance. The pathogenicity of Trib2 is attributed to its ability to induce proteasomal degradation of the full length isoform of the transcription factor CCAAT/enhancer-binding protein alpha (C/EBPα p42). The role of TRIB2 in human AML cells, however, has not been systematically investigated or targeted. Across human cancers, TRIB2 oncogenic activity was found to be associated with its elevated expression. In the context of AML, TRIB2 overexpression was suggested to be associated with the large and heterogeneous subset of cytogenetically normal AML patients. Based upon the observation that overexpression of TRIB2 has a role in cellular transformation, the effect of modulating its expression in human AML was examined in a human AML cell line that expresses high levels of TRIB2, U937 cells. Specific suppression of TRIB2 led to impaired cell growth, as a consequence of both an increase in apoptosis and a decrease in cell proliferation. Consistent with these in vitro results, TRIB2 silencing strongly reduced progression of the U937 in vivo xenografts, accompanied by detection of a lower spleen weight when compared with mice transplanted with TRIB2- expressing control cells. Gene expression analysis suggested that TRIB2 modulates apoptosis and cell-cycle sensitivity by influencing the expression of a subset of genes known to have implications on these phenotypes. Furthermore, TRIB2 was found to be expressed in a significant subset of AML patient samples analysed. To investigate whether increased expression of this gene could be afforded prognostic significance, primary AML cells with dichotomized levels of TRIB2 transcripts were evaluated in terms of their xenoengraftment potential, an assay reported to correlate with disease aggressiveness observed in humans. A small cohort of analysed samples with higher TRIB2 expression did not associate with preferential leukaemic cell engraftment in highly immune-deficient mice, hence, not predicting for an adverse prognosis. However, further experiments including a larger cohort of well characterized AML patients would be needed to clarify TRIB2 significance in the diagnostic setting. Collectively, these data support a functional role for TRIB2 in the maintenance of the oncogenic properties of human AML cells and suggest TRIB2 can be considered a rational therapeutic target. Proteasome inhibition has emerged as an attractive target for the development of novel anti-cancer therapies and results from translational research and clinical trials support the idea that proteasome inhibitors should be considered in the treatment of AML. The present study argued that proteasome inhibition would effectively inhibit the function of TRIB2 by abrogating C/EBPα p42 protein degradation and that it would be an effective pharmacological targeting strategy in TRIB2-positive AMLs. Here, a number of cell models expressing high levels of TRIB2 were successfully targeted by treatment with proteasome inhibitors, as demonstrated by multiple measurements that included increased cytotoxicity, inhibition of clonogenic growth and anti-AML activity in vivo. Mechanistically, it was shown that block of the TRIB2 degradative function led to an increase of C/EBPα p42 and that response was specific to the TRIB2-C/EBPα axis. Specificity was addressed by a panel of experiments showing that U937 cells (express detectable levels of endogenous TRIB2 and C/EBPα) treated with the proteasome inhibitor bortezomib (Brtz) displayed a higher cytotoxic response upon TRIB2 overexpression and that ectopic expression of C/EBPα rescued cell death. Additionally, in C/EBPα-negative leukaemia cells, K562 and Kasumi 1, Brtz-induced toxicity was not increased following TRIB2 overexpression supporting the specificity of the compound on the TRIB2-C/EBPα axis. Together these findings provide pre-clinical evidence that TRIB2- expressing AML cells can be pharmacologically targeted with proteasome inhibition due, in part, to blockage of the TRIB2 proteolytic function on C/EBPα p42. A large body of evidence indicates that AML arises through the stepwise acquisition of genetic and epigenetic changes. Mass spectrometry data has identified an interaction between TRIB2 and the epigenetic regulator Protein Arginine Methyltransferase 5 (PRMT5). Following assessment of TRIB2‟s role in AML cell survival and effective targeting of the TRIB2-C/EBPα degradation pathway, a putative TRIB2/PRMT5 cooperation was investigated in order to gain a deeper understanding of the molecular network in which TRIB2 acts as a potent myeloid oncogene. First, a microarray data set was interrogated for PRMT5 expression levels and the primary enzyme responsible for symmetric dimethylation was found to be transcribed at significantly higher levels in AML patients when compared to healthy controls. Next, depletion of PRMT5 in the U937 cell line was shown to reduce the transformative phenotype in the high expressing TRIB2 AML cells, which suggests that PRMT5 and TRIB2 may cooperate to maintain the leukaemogenic potential. Importantly, PRMT5 was identified as a TRIB2-interacting protein by means of a protein tagging approach to purify TRIB2 complexes from 293T cells. These findings trigger further research aimed at understanding the underlying mechanism and the functional significance of this interplay. In summary, the present study provides experimental evidence that TRIB2 has an important oncogenic role in human AML maintenance and, importantly in such a molecularly heterogeneous disease, provides the rational basis to consider proteasome inhibition as an effective targeting strategy for AML patients with high TRIB2 expression. Finally, the identification of PRMT5 as a TRIB2-interacting protein opens a new level of regulation to consider in AML. This work may contribute to our further understanding and therapeutic strategies in acute leukaemias.
Resumo:
Conventional web search engines are centralised in that a single entity crawls and indexes the documents selected for future retrieval, and the relevance models used to determine which documents are relevant to a given user query. As a result, these search engines suffer from several technical drawbacks such as handling scale, timeliness and reliability, in addition to ethical concerns such as commercial manipulation and information censorship. Alleviating the need to rely entirely on a single entity, Peer-to-Peer (P2P) Information Retrieval (IR) has been proposed as a solution, as it distributes the functional components of a web search engine – from crawling and indexing documents, to query processing – across the network of users (or, peers) who use the search engine. This strategy for constructing an IR system poses several efficiency and effectiveness challenges which have been identified in past work. Accordingly, this thesis makes several contributions towards advancing the state of the art in P2P-IR effectiveness by improving the query processing and relevance scoring aspects of a P2P web search. Federated search systems are a form of distributed information retrieval model that route the user’s information need, formulated as a query, to distributed resources and merge the retrieved result lists into a final list. P2P-IR networks are one form of federated search in routing queries and merging result among participating peers. The query is propagated through disseminated nodes to hit the peers that are most likely to contain relevant documents, then the retrieved result lists are merged at different points along the path from the relevant peers to the query initializer (or namely, customer). However, query routing in P2P-IR networks is considered as one of the major challenges and critical part in P2P-IR networks; as the relevant peers might be lost in low-quality peer selection while executing the query routing, and inevitably lead to less effective retrieval results. This motivates this thesis to study and propose query routing techniques to improve retrieval quality in such networks. Cluster-based semi-structured P2P-IR networks exploit the cluster hypothesis to organise the peers into similar semantic clusters where each such semantic cluster is managed by super-peers. In this thesis, I construct three semi-structured P2P-IR models and examine their retrieval effectiveness. I also leverage the cluster centroids at the super-peer level as content representations gathered from cooperative peers to propose a query routing approach called Inverted PeerCluster Index (IPI) that simulates the conventional inverted index of the centralised corpus to organise the statistics of peers’ terms. The results show a competitive retrieval quality in comparison to baseline approaches. Furthermore, I study the applicability of using the conventional Information Retrieval models as peer selection approaches where each peer can be considered as a big document of documents. The experimental evaluation shows comparative and significant results and explains that document retrieval methods are very effective for peer selection that brings back the analogy between documents and peers. Additionally, Learning to Rank (LtR) algorithms are exploited to build a learned classifier for peer ranking at the super-peer level. The experiments show significant results with state-of-the-art resource selection methods and competitive results to corresponding classification-based approaches. Finally, I propose reputation-based query routing approaches that exploit the idea of providing feedback on a specific item in the social community networks and manage it for future decision-making. The system monitors users’ behaviours when they click or download documents from the final ranked list as implicit feedback and mines the given information to build a reputation-based data structure. The data structure is used to score peers and then rank them for query routing. I conduct a set of experiments to cover various scenarios including noisy feedback information (i.e, providing positive feedback on non-relevant documents) to examine the robustness of reputation-based approaches. The empirical evaluation shows significant results in almost all measurement metrics with approximate improvement more than 56% compared to baseline approaches. Thus, based on the results, if one were to choose one technique, reputation-based approaches are clearly the natural choices which also can be deployed on any P2P network.