miR-10a is aberrantly overexpressed in Nucleophosmin1 mutated acute myeloid leukaemia and its suppression induces cell death

<p>Abstract</p> <p>Background</p> <p>Acute myeloid leukaemia (AML) with nucleophosmin-1 (<it>NPM1</it>) mutation is a major subtype of AML. The <it>NPM1 </it>mutation induces a myeloproliferative disorder, but evidence indicates that other insults are necessary for the development of AML. We utilised microRNA microarrays and functional assays to determine if microRNA dysregulation could be involved in the pathogenesis of in <it>NPM1 </it>mutated (<it>NPM1^mut</it>)-AML.</p> <p>Results</p> <p>We used a stringent locked nucleic acid (LNA) based microRNA microarray platform to profile bone marrow samples of patients with normal karyotype AML. A panel of five microRNAs dichotomised AML patients according to their <it>NPM1 </it>mutational status. miR-10a, let-7b and let-7c were significantly over-expressed, while miR-130a and miR-335 were under-expressed in <it>NPM1^mut</it>-AML when compared to <it>NPM1^wildtype</it>-AML. Of these, miR-10a is the most differentially expressed in <it>NPM1^mut</it>-AML versus <it>NPM1^wildtype</it>-AML (> 10 fold higher as confirmed by qRT-PCR). To investigate the functions of miR-10a, the OCI-AML3 cell line was utilised, which is the only commercially available cell line bearing <it>NPM1^mut</it>. OCI-AML3 cells were firstly demonstrated to have a similarly high miR-10a expression to primary <it>NPM1^mut</it>-AML patient samples. Inhibition of miR-10a expression by miRCURY LNA Inhibitors (Exiqon) in these cells resulted in increased cell death as assessed by MTS, cell cycle and Annexin-V assays and reduced clonogenic capacity, indicative of an involvement in leukaemic cell survival. <it>In silico </it>filtering of bioinformatically predicted targets of miR-10a identified a number of potential mRNA targets with annotated functions in haematopoiesis, cell growth and apoptosis. Lucferase reporter assays confirmed a number of these putative tumorogenic genes that are miR-10a suppressible including <it>KLF4 </it>and <it>RB1CC1</it>. This provides a potential mechanism for the pathogenic role of miR-10a in <it>NPM1^mut</it>-AML.</p> <p>Conclusions</p> <p>This study provides, for the first time, <it>in vitro </it>evidence of a pro-survival role of miR-10a in <it>NPM1^mut</it>-AML, that it may contribute to the pathogenesis of <it>NPM1^mut</it>-AML and identifies putative tumorogenic targets.</p

Measures of Association for Identifying MicroRNA-mRNA Pairs of Biological Interest

MicroRNAs are a class of small non-protein coding RNAs that play an important role in the regulation of gene expression. Most studies on the identification of microRNA-mRNA pairs utilize the correlation coefficient as a measure of association. The use of correlation coefficient is appropriate if the expression data are available for several conditions and, for a given condition, both microRNA and mRNA expression profiles are obtained from the same set of individuals. However, there are many instances where one of the requirements is not satisfied. Therefore, there is a need for new measures of association to identify the microRNA-mRNA pairs of interest and we present two such measures. The first measure requires expression data for multiple conditions but, for a given condition, the microRNA and mRNA expression may be obtained from different individuals. The new measure, unlike the correlation coefficient, is suitable for analyzing large data sets which are obtained by combining several independent studies on microRNAs and mRNAs. Our second measure is able to handle expression data that correspond to just two conditions but, for a given condition, the microRNA and mRNA expression must be obtained from the same set of individuals. This measure, unlike the correlation coefficient, is appropriate for analyzing data sets with a small number of conditions. We apply our new measures of association to multiple myeloma data sets, which cannot be analyzed using the correlation coefficient, and identify several microRNA-mRNA pairs involved in apoptosis and cell proliferation

Discriminating lymphomas and reactive lymphadenopathy in lymph node biopsies by gene expression profiling

<p>Abstract</p> <p>Background</p> <p>Diagnostic accuracy of lymphoma, a heterogeneous cancer, is essential for patient management. Several ancillary tests including immunophenotyping, and sometimes cytogenetics and PCR are required to aid histological diagnosis. In this proof of principle study, gene expression microarray was evaluated as a single platform test in the differential diagnosis of common lymphoma subtypes and reactive lymphadenopathy (RL) in lymph node biopsies.</p> <p>Methods</p> <p>116 lymph node biopsies diagnosed as RL, classical Hodgkin lymphoma (cHL), diffuse large B cell lymphoma (DLBCL) or follicular lymphoma (FL) were assayed by mRNA microarray. Three supervised classification strategies (global multi-class, local binary-class and global binary-class classifications) using diagonal linear discriminant analysis was performed on training sets of array data and the classification error rates calculated by leave one out cross-validation. The independent error rate was then evaluated by testing the identified gene classifiers on an independent (test) set of array data.</p> <p>Results</p> <p>The binary classifications provided prediction accuracies, between a subtype of interest and the remaining samples, of 88.5%, 82.8%, 82.8% and 80.0% for FL, cHL, DLBCL, and RL respectively. Identified gene classifiers include LIM domain only-2 (<it>LMO2</it>), Chemokine (C-C motif) ligand 22 (<it>CCL22</it>) and Cyclin-dependent kinase inhibitor-3 (<it>CDK3</it>) specifically for FL, cHL and DLBCL subtypes respectively.</p> <p>Conclusions</p> <p>This study highlights the ability of gene expression profiling to distinguish lymphoma from reactive conditions and classify the major subtypes of lymphoma in a diagnostic setting. A cost-effective single platform "mini-chip" assay could, in principle, be developed to aid the quick diagnosis of lymph node biopsies with the potential to incorporate other pathological entities into such an assay.</p

Identification of microRNA-mRNA modules using microarray data

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are post-transcriptional regulators of mRNA expression and are involved in numerous cellular processes. Consequently, miRNAs are an important component of gene regulatory networks and an improved understanding of miRNAs will further our knowledge of these networks. There is a many-to-many relationship between miRNAs and mRNAs because a single miRNA targets multiple mRNAs and a single mRNA is targeted by multiple miRNAs. However, most of the current methods for the identification of regulatory miRNAs and their target mRNAs ignore this biological observation and focus on miRNA-mRNA pairs.</p> <p>Results</p> <p>We propose a two-step method for the identification of many-to-many relationships between miRNAs and mRNAs. In the first step, we obtain miRNA and mRNA clusters using a combination of miRNA-target mRNA prediction algorithms and microarray expression data. In the second step, we determine the associations between miRNA clusters and mRNA clusters based on changes in miRNA and mRNA expression profiles. We consider the miRNA-mRNA clusters with statistically significant associations to be potentially regulatory and, therefore, of biological interest.</p> <p>Conclusions</p> <p>Our method reduces the interactions between several hundred miRNAs and several thousand mRNAs to a few miRNA-mRNA groups, thereby facilitating a more meaningful biological analysis and a more targeted experimental validation.</p

Molecular events surrounding secretory granule biogenesis in transgenic hormone producing liver cell lines

Secretory granule biogenesis describes the events leading up to the budding of a nascent granule from the trans Golgi network. Literature surrounding secretory granule biogenesis is conflicting and has generated much debate. This thesis aims to address the important issues of this debate by utilizing the insulin-producing liver cell line HUH7-ins. This cell line has been shown to synthesize, store and secrete mature insulin in response to glucose via the possession of secretory granules. Using microarraytechnology the gene expression profile of HUH7-ins cells was compared with parental HUH7 cells, hoping to identify possible candidate genes contributing to secretory granule biogenesis. 164 genes were shown to be differentially expressed although no known granulogenic protein exhibited a change in expression. The data did suggest anervous system differentiation event and implicates myosin Vc in the regulated secretion of insulin. HUH7-ins cells express a number of granulogenic protein mRNAs and while chromogranin B (CgB) protein level remained constant upon insulin expression, a significant increase in the level of chromogranin A (CgA) was observed,though the significance of this increase in expression is unknown. The over-expression of CgA in a clone of HUH7-ins that did not possess the regulated secretory pathway was unable to rescue the regulated secretory pathway, suggesting that CgA expression alone is unable to form secretory granules in our model. To determine if the secretory granule biogenesis seen in HUH7-ins cells was specific to insulin, three prohormones of different neuroendocrine origin were over-expressed in HUH7 cells; amylin ( cell),pancreatic polypeptide (pancreatic islet) and proopiomelanocortin (pituitary). None of these prohormones were able to form structures in the cytoplasm that resembled secretory granules by immunofluorescent microscopy, nor did they induce the expression of CgA. No prohormone was detected in cell lysates or conditioned media, raising the possibility that these exogenous prohormone aggregates are trafficked to the lysosomal/endosomal system for degradation. This study provides significant information regarding the genome-wide expression changes induced upon secretory granule biogenesis in a liver cell line, describes the lack of effect of CgA in this eventand suggests that secretory granule biogenesis in this liver cell line is specific to insulin

Identification of significant miRNA-mRNA pairs using association measures based on unmatched and matched data.

<p>Identification of significant miRNA-mRNA pairs using association measures based on unmatched and matched data.</p

Association measures for co-analysis of miRNA and mRNA expression profiles.

<p>Association measures for co-analysis of miRNA and mRNA expression profiles.</p

Number of mRNAs associated with different biological processes in the RB deletion group.

<p>Number of mRNAs associated with different biological processes in the RB deletion group.</p

Relative expression levels of hsa-miR-320 and two of its predicted targets in samples with RB deletion.

<p>Relative expression levels of hsa-miR-320 and two of its predicted targets in samples with RB deletion.</p