Characterization and discovery of novel miRNAs and moRNAs in JAK2V617F-mutated SET2 cells.

To gain insights into a possible role of microRNAs in myeloproliferative neoplasms, we performed short RNA massive sequencing and extensive bioinformatic analysis in the JAK2V617F-mutated SET2 cell line. Overall, 652 known mature miRNAs were detected, of which 21 were highly expressed, thus being responsible of most of miRNA-mediated gene repression. microRNA putative targets were enriched in specific signaling pathways, providing information about cell activities under massive posttranscriptional regulation. The majority of miRNAs were mixtures of sequence variants, called isomiRs, mainly because of alternative, noncanonical processing of hairpin precursors. We also identified 78 novel miRNAs (miRNA*) derived from known hairpin precursors. Both major and minor (*) forms of miRNAs were expressed concurrently from half of expressed hairpins, highlighting the relevance of miRNA* and the complexity of strand selection bias regulation. Finally, we discovered that SET2 cells express a number of miRNA-offset RNAs (moRNAs), short RNAs derived from genomic regions flanking mature miRNAs. We provide novel data about the possible origin of moRNAs, although their functional role remains to be elucidated. Overall, this study shed light on the complexity of microRNA-mediated gene regulation in SET2 cells and represents the basis for future studies in JAK2V617F-mutated cellular models.

Impact of microRNAs on regulatory networks and pathways in human colorectal carcinogenesis and development of metastasis.

BACKGROUND: Qualitative alterations or abnormal expression of microRNAs (miRNAs) in colon cancer have mainly been demonstrated in primary tumors. Poorly overlapping sets of oncomiRs, tumor suppressor miRNAs and metastamiRs have been linked with distinct stages in the progression of colorectal cancer. To identify changes in both miRNA and gene expression levels among normal colon mucosa, primary tumor and liver metastasis samples, and to classify miRNAs into functional networks, in this work miRNA and gene expression profiles in 158 samples from 46 patients were analysed. RESULTS: Most changes in miRNA and gene expression levels had already manifested in the primary tumors while these levels were almost stably maintained in the subsequent primary tumor-to-metastasis transition. In addition, comparing normal tissue, tumor and metastasis, we did not observe general impairment or any rise in miRNA biogenesis. While only few mRNAs were found to be differentially expressed between primary colorectal carcinoma and liver metastases, miRNA expression profiles can classify primary tumors and metastases well, including differential expression of miR-10b, miR-210 and miR-708. Of 82 miRNAs that were modulated during tumor progression, 22 were involved in EMT. qRT-PCR confirmed the down-regulation of miR-150 and miR-10b in both primary tumor and metastasis compared to normal mucosa and of miR-146a in metastases compared to primary tumor. The upregulation of miR-201 in metastasis compared both with normal and primary tumour was also confirmed. A preliminary survival analysis considering differentially expressed miRNAs suggested a possible link between miR-10b expression in metastasis and patient survival. By integrating miRNA and target gene expression data, we identified a combination of interconnected miRNAs, which are organized into sub-networks, including several regulatory relationships with differentially expressed genes. Key regulatory interactions were validated experimentally. Specific mixed circuits involving miRNAs and transcription factors were identified and deserve further investigation. The suppressor activity of miR-182 on ENTPD5 gene was identified for the first time and confirmed in an independent set of samples. CONCLUSIONS: Using a large dataset of CRC miRNA and gene expression profiles, we describe the interplay of miRNA groups in regulating gene expression, which in turn affects modulated pathways that are important for tumor development.

MAGIA, a web-based tool for miRNA and Genes Integrated Analysis.

MAGIA (miRNA and genes integrated analysis) is a novel web tool for the integrative analysis of target predictions, miRNA and gene expression data. MAGIA is divided into two parts: the query section allows the user to retrieve and browse updated miRNA target predictions computed with a number of different algorithms (PITA, miRanda and Target Scan) and Boolean combinations thereof. The analysis section comprises a multistep procedure for (i) direct integration through different functional measures (parametric and non-parametric correlation indexes, a variational Bayesian model, mutual information and a meta-analysis approach based on P-value combination) of mRNA and miRNA expression data, (ii) construction of bipartite regulatory network of the best miRNA and mRNA putative interactions and (iii) retrieval of information available in several public databases of genes, miRNAs and diseases and via scientific literature text-mining. MAGIA is freely available for Academic users at http://gencomp.bio.unipd.it/magia.

Identification of microRNA expression patterns and definition of a microRNA/mRNA regulatory network in distinct molecular groups of multiple myeloma.

To date, little evidence of miRNA expression/deregulation in multiple myeloma has been reported. To characterize miRNA in the context of the major multiple myeloma molecular types, we generated miRNA expression profiles of highly purified malignant plasma cells from 40 primary tumors. Furthermore, transcriptional profiles, available for all patients, were used to investigate the occurrence of miRNA/predicted target mRNA pair anticorrelations, and the miRNA and genome-wide DNA data were integrated in a subset of patients to evaluate the influence of allelic imbalances on miRNA expression. Differential miRNA expression patterns were identified, which were mainly associated with the major IGH translocations; particularly, t(4;14) patients showed specific overexpression of let-7e, miR-125a-5p, and miR-99b belonging to a cluster at 19q13.33. The occurrence of other lesions (ie, 1q gain, 13q and 17p deletions, and hyperdiploidy) was slightly characterized by specific miRNA signatures. Furthermore, the occurrence of several allelic imbalances or loss of heterozygosity was found significantly associated with the altered expression of miRNAs located in the involved regions, such as let-7b at 22q13.31 or miR-140-3p at 16q22. Finally, the integrative analysis based on computational target prediction and miRNA/mRNA profiling defined a network of putative functional miRNA-target regulatory relations supported by expression data.

Human miRNome profiling in colorectal cancer and liver metastasis development.

Qualitative alterations or abnormal expression of microRNAs (miRNAs) in colorectal cancer has mainly been demonstrated in primary tumors. The miRNA expression profiles in 78 samples from 46 patients were analyzed to identify changes in miRNA expression level among normal colon mucosa, primary tumor and liver metastasis samples. Using this dataset, we describe the interplay of miRNA groups in regulating pathways that are important for tumor development. Here we describe in details the contents and quality controls for the miRNA expression and clinical data associated with the study published by Pizzini and colleagues in the BMC Genomics in 2013 (Pizzini et al., 2013). Data are deposited in GEO database as GSE35834 series.

Impact of host genes and strand selection on miRNA and miRNA* expression.

Dysregulation of miRNAs expression plays a critical role in the pathogenesis of genetic, multifactorial disorders and in human cancers. We exploited sequence, genomic and expression information to investigate two main aspects of post-transcriptional regulation in miRNA biogenesis, namely strand selection regulation and expression relationships between intragenic miRNAs and host genes. We considered miRNAs expression profiles, measured in five sizeable microarray datasets, including samples from different normal cell types and tissues, as well as different tumours and disease states. First, the study of expression profiles of "sister" miRNA pairs (miRNA/miRNA*, 5' and 3' strands of the same hairpin precursor) showed that the strand selection is highly regulated since it shows tissue-/cell-/condition-specific modulation. We used information about the direction and the strength of the strand selection bias to perform an unsupervised cluster analysis for the sample classification evidencing that is able to distinguish among different tissues, and sometimes between normal and malignant cells. Then, considering a minimum expression threshold, in few miRNA pairs only one mature miRNA is always present in all considered cell types, whereas the majority of pairs were concurrently expressed in some cell types and alternatively in others. In a significant fraction of concurrently expressed pairs, the major and the minor forms found at comparable levels may contribute to post-transcriptional gene silencing, possibly in a coordinate way. In the second part of the study, the behaved tendency to co-expression of intragenic miRNAs and their "host" mRNA genes was confuted by expression profiles examination, suggesting that the expression profile of a given host gene can hardly be a good estimator of co-transcribed miRNA(s) for post-transcriptional regulatory networks inference. Our results point out the regulatory importance of post-transcriptional phases of miRNAs biogenesis, reinforcing the role of such layer of miRNA biogenesis in miRNA-based regulation of cell activities.

Critical analysis of transcriptional and post-transcriptional regulatory networks in multiple myeloma.

Network analysis has emerged as a powerful approach to understand complex phenomena and organization in social, technological and biological systems. In particular, it is increasingly recognized the role played by the topology of cellular networks, the intricate web of interactions among genes, proteins and other molecules regulating cell activity, in unveiling the biological mechanisms underlying the physiological states of living organisms. In this study, critical analysis of network components has been applied to inspect the transcriptional and post-transcriptional regulatory networks reconstructed from mRNA and microRNA expression data of multiple myeloma (MM) samples. Specifically, the importance of a gene as a putative regulatory element has been assessed calculating the drop in the network performance caused by its deactivation instead of quantifying its degree of connectivity. The application of critical analysis to transcriptional and post-transcriptional regulatory networks allowed inferring novel regulatory relations potentially functional in multiple myeloma.