Dynamic Changes in miRNA Expression during the Generation of Expanded and Activated NK Cells.

Therapies based on allogenic Natural Killer (NK) cells are becoming increasingly relevant, and our laboratory has produced expanded and activated NK (eNK) cells that are highly cytotoxic against several hematological cancers when used alone or in combination with currently approved therapeutic monoclonal antibodies. In order to produce eNK cells, healthy human donor NK cells undergo a 20-day expansion protocol with IL-2, IL-15 and Epstein-Barr virus (EBV)-transformed lymphoblastoid feeder cells. In order to produce an even more potent eNK-based therapy, we must elucidate the changes our protocol produces within healthy NK cells. To understand the post-transcriptional changes responsible for the increased cytolytic abilities of eNK cells, we performed microRNA (miRNA) expression analysis on purified NK cells from day 0 and day 20 of the protocol using quantitative reverse transcription PCR (RT-qPCR). Of the 384 miRNAs profiled, we observed changes in the expression of 64 miRNAs, with especially significant changes in 7 of them. The up-regulated miRNAs of note were miRs-146a, -124, -34a, and -10a, which are key in the regulation of cell survival through the modulation of pro-apoptotic genes such as PUMA. The down-regulation of miRs-199a, -223, and -340 was also detected and is associated with the promotion of NK cell cytotoxicity. We validated our analysis using immunoblot and flow cytometry studies on specific downstream targets of both up- and down-regulated miRNAs such as PUMA and Granzyme B. These results corroborate the functional importance of the described miRNA expression patterns and show the wide variety of changes that occur in eNK cells at day 20.

Molecular diagnosis of polycystic ovary syndrome in obese and non-obese women by targeted plasma miRNA profiling.

OBJECTIVE: Polycystic ovary syndrome (PCOS) is diagnosed based on the clinical signs, but its presentation is heterogeneous and potentially confounded by concurrent conditions, such as obesity and insulin resistance. miRNA have recently emerged as putative pathophysiological and diagnostic factors in PCOS. However, no reliable miRNA-based method for molecular diagnosis of PCOS has been reported. The aim of this study was to develop a tool for accurate diagnosis of PCOS by targeted miRNA profiling of plasma samples, defined on the basis of unbiased biomarker-finding analyses and biostatistical tools. METHODS: A case-control PCOS cohort was cross-sectionally studied, including 170 women classified into four groups: non-PCOS/lean, non-PCOS/obese, PCOS/lean, and PCOS/obese women. High-throughput miRNA analyses were performed in plasma, using NanoString technology and a 800 human miRNA panel, followed by targeted quantitative real-timePCR validation. Statistics were applied to define optimal normalization methods, identify deregulated biomarker miRNAs, and build classification algorithms, considering PCOS and obesity as major categories. RESULTS: The geometric mean of circulating hsa-miR-103a-3p, hsa-miR-125a-5p, and hsa-miR-1976, selected among 125 unchanged miRNAs, was defined as optimal reference for internal normalization (named mR3-method). Ten miRNAs were identified and validated after mR3-normalization as differentially expressed across the groups. Multinomial least absolute shrinkage and selection operator regression and decision-tree models were built to reliably discriminate PCOS vs non-PCOS, either in obese or non-obese women, using subsets of these miRNAs as performers. CONCLUSIONS: We define herein a robust method for molecular classification of PCOS based on unbiased identification of miRNA biomarkers and decision-tree protocols. This method allows not only reliable diagnosis of non-obese women with PCOS but also discrimination between PCOS and obesity. CAPSULE: We define a novel protocol, based on plasma miRNA profiling, for molecular diagnosis of PCOS. This tool not only allows proper discrimination of the condition in non-obese women but also permits distinction between PCOS and obesity, which often display overlapping clinical presentations.

The PRoteomics IDEntifications (PRIDE) database and associated tools: status in 2013.

The PRoteomics IDEntifications (PRIDE, http://www.ebi.ac.uk/pride) database at the European Bioinformatics Institute is one of the most prominent data repositories of mass spectrometry (MS)-based proteomics data. Here, we summarize recent developments in the PRIDE database and related tools. First, we provide up-to-date statistics in data content, splitting the figures by groups of organisms and species, including peptide and protein identifications, and post-translational modifications. We then describe the tools that are part of the PRIDE submission pipeline, especially the recently developed PRIDE Converter 2 (new submission tool) and PRIDE Inspector (visualization and analysis tool). We also give an update about the integration of PRIDE with other MS proteomics resources in the context of the ProteomeXchange consortium. Finally, we briefly review the quality control efforts that are ongoing at present and outline our future plans.

Critical amino acid residues in proteins: a BioMart integration of Reactome protein annotations with PRIDE mass spectrometry data and COSMIC somatic mutations.

The reversible phosphorylation of serine, threonine and tyrosine hydroxyl groups is an especially prominent form of post-translational modification (PTM) of proteins. It plays critical roles in the regulation of diverse processes, and mutations that directly or indirectly affect these phosphorylation events have been associated with many cancers and other pathologies. Here, we describe the development of a new BioMart tool that gathers data from three different biological resources to provide the user with an integrated view of phosphorylation events associated with a human protein of interest, the complexes of which the protein (modified or not) is a part, the reactions in which the protein and its complexes participate and the somatic mutations that might be expected to perturb those functions. The three resources used are the Reactome, PRIDE and COSMIC databases. The Reactome knowledgebase contains annotations of phosphorylated human proteins linked to the reactions in which they are phosphorylated and dephosphorylated, to the complexes of which they are parts and to the reactions in which the phosphorylated proteins participate as substrates, catalysts and regulators. The PRIDE database holds extensive mass spectrometry data from which protein phosphorylation patterns can be inferred, and the COSMIC database holds records of somatic mutations found in human cancer cells. This tool supports both flexible, user-specified queries and standard ('canned') queries to retrieve frequently used combinations of data for user-specified proteins and reactions. We demonstrate using the Wnt signaling pathway and the human c-SRC protein how the tool can be used to place somatic mutation data into a functional perspective by changing critical residues involved in pathway modulation, and where available, check for mass spectrometry evidence in PRIDE supporting identification of the critical residue.

Phosphorylation analysis of primary human T lymphocytes using sequential IMAC and titanium oxide enrichment.

T lymphocytes mediate cellular and humoral defense against foreign bodies or autoantigens. An understanding of T-cell information processing furthers studies of the immunological response. We describe a large-scale phosphorylation analysis of primary T cells using a multidimensional separation strategy, involving preparative SDS-PAGE for prefractionation, in-gel digestion and sequential phosphopeptide enrichment using IMAC and TiO2. A total of 281 phosphorylation sites (197 of high confidence, Ascore > 15), mapping to 204 human gene sequences, were identified by LC-MS(n) analysis in an LTQ linear ion trap. Subsequently, we created the LymPHOS database (http://lymphos.org), which links mass spectrometric peptide information to phosphorylation sites and phosphoprotein sequences.