N7-methylguanosine methylation of tRNAs regulates survival to stress in cancer

Tumour progression and therapy tolerance are highly regulated and complex processes largely dependent on the plasticity of cancer cells and their capacity to respond to stress. The higher plasticity of cancer cells highlights the need for identifying targetable molecular pathways that challenge cancer cell survival. Here, we show that

miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments

Next-generation sequencing allows now the sequencing of small RNA molecules and the estimation of their expression levels. Consequently, there will be a high demand of bioinformatics tools to cope with the several gigabytes of sequence data generated in each single deep-sequencing experiment. Given this scene, we developed miRanalyzer, a web server tool for the analysis of deep-sequencing experiments for small RNAs. The web server tool requires a simple input file containing a list of unique reads and its copy numbers (expression levels). Using these data, miRanalyzer (i) detects all known microRNA sequences annotated in miRBase, (ii) finds all perfect matches against other libraries of transcribed sequences and (iii) predicts new microRNAs. The prediction of new microRNAs is an especially important point as there are many species with very few known microRNAs. Therefore, we implemented a highly accurate machine learning algorithm for the prediction of new microRNAs that reaches AUC values of 97.9% and recall values of up to 75% on unseen data. The web tool summarizes all the described steps in a single output page, which provides a comprehensive overview of the analysis, adding links to more detailed output pages for each analysis module. miRanalyzer is available at http://web.bioinformatics.cicbiogune.es/microRNA/

Extracellular Vesicles From Liver Progenitor Cells Downregulates Fibroblast Metabolic Activity and Increase the Expression of Immune-Response Related Molecules

Extracellular vesicles (EVs) mediate cell-to-cell crosstalk whose content can induce changes in acceptor cells and their microenvironment. MLP29 cells are mouse liver progenitor cells that release EVs loaded with signaling cues that could affect cell fate. In the current work, we incubated 3T3-L1 mouse fibroblasts with MLP29-derived EVs, and then analyzed changes by proteomics and transcriptomics. Results showed a general downregulation of protein and transcript expression related to proliferative and metabolic routes dependent on TGF-beta. We also observed an increase in the ERBB2 interacting protein (ERBIN) and Cxcl2, together with an induction of ribosome biogenesis and interferon-related response molecules, suggesting the activation of immune system signaling

Signal integration and transcriptional regulation of the inflammatory response mediated by the GM-/MCSF signaling axis in human monocytes

In recent years, the macrophage colony-stimulating factor (M-CSF) and granulocyte-macrophage CSF (GM-CSF) cytokines have been identified as opposing regulators of the inflammatory program. However, the two cytokines are simultaneously present in the inflammatory milieu, and it is not clear how cells integrate these signals. In order to understand the regulatory networks associated with the GM/M-CSF signaling axis, we analyzed DNA methylation in human monocytes. Our results indicate that GM-CSF induces activation of the inflammatory program and extensive DNA methylation changes, while M-CSF-polarized cells are in a less differentiated state. This inflammatory program is mediated via JAK2 associated with the GM-CSF receptor and the downstream extracellular signal-regulated (ERK) signaling. However, PI3K signaling is associated with a negative regulatory loop of the inflammatory program and M-CSF autocrine signaling in GM-CSF-polarized monocytes. Our findings describe the regulatory networks associated with the GM/M-CSF signaling axis and how they contribute to the establishment of the inflammatory program associated with monocyte activation.This work was supported by grants from the Plan Nacional de I+D+I 2013– 2016 ISCIII (Institute of Health Carlos III; PI16/01318, PI17/01244, PI17/ 0119, PI16/1900, and PI19/00184); the Gobierno del Principado de Asturias; the PCTI-Plan de Ciencia, Tecnologı´a e Innovacio´ n 2013-2017 (grant IDI/ 2018/144); FEDER ‘‘Funding Program of the European Union’’; the Red Española de Investigación Renal (REDinREN) (RD16/0009/0020, RD016/0009/002, and RD016/0009/001); the Agencia Estatal de Investigación (AEI) (ayuda Juan de la Cierva-Incorporaciόn; IJCI-2017-33347 to R.M.R.); and the Instituto de Salud Carlos III (Contratos Sara Borrell; CD16/00033 to C.H.). CIC bioGUNE support was provided by the Basque Department of Industry, Tourism and Trade (Etortek and Elkartek programs), the Innovation Technology Department of Bizkaia County, the CIBERehd Network, and Spanish MINECO, the Severo Ochoa Excellence Accreditation (SEV-2016-0644

Integrative analysis of transcriptomics and clinical data uncovers the tumor- suppressive activity of MITF in prostate cancer

The dysregulation of gene expression is an enabling hallmark of cancer. Computational analysis of transcriptomics data from human cancer specimens, complemented with exhaustive clinical annotation, provides an opportunity to identify core regulators of the tumorigenic process. Here we exploit well-annotated clinical datasets of prostate cancer for the discovery of transcriptional regulators relevant to prostate cancer. Following this rationale, we identify Microphthalmia-associated transcription factor (MITF) as a prostate tumor suppressor among a subset of transcription factors. Importantly, we further interrogate transcriptomics and clinical data to refine MITF perturbation-based empirical assays and unveil Crystallin Alpha B (CRYAB) as an unprecedented direct target of the transcription factor that is, at least in part, responsible for its tumor-suppressive activity in prostate cancer. This evidence was supported by the enhanced prognostic potential of a signature based on the concomitant alteration of MITF and CRYAB in prostate cancer patients. In sum, our study provides proof-of-concept evidence of the potential of the bioinformatics screen of publicly available cancer patient databases as discovery platforms, and demonstrates that the MITF-CRYAB axis controls prostate cancer biology

CANCERTOOL: A Visualization and Representation Interface to Exploit Cancer Datasets

[EN] With the advent of OMICs technologies, both individual research groups and consortia have spear-headed the characterization of human samples of multiple pathophysiologic origins, resulting in thousands of archived genomes and transcriptomes. Although a variety of web tools are now available to extract information from OMICs data, their utility has been limited by the capacity of nonbioinformatician researchers to exploit the information. To address this problem, we have developed CANCERTOOL, a web-based interface that aims to overcome the major limitations of public transcriptomics dataset analysis for highly prevalent types of cancer (breast, prostate, lung, and colorectal). CANCERTOOL provides rapid and comprehensive visualization of gene expression data for the gene(s) of interest in well-annotated cancer datasets. This visualization is accompanied by generation of reports customized to the interest of the researcher (e.g., editable figures, detailed statistical analyses, and access to raw data for reanalysis). It also carries out gene-to-gene correlations in multiple datasets at the same time or using preset patient groups. Finally, this new tool solves the time-consuming task of performing functional enrichment analysis with gene sets of interest using up to 11 different databases at the same time. Collectively, CANCERTOOL represents a simple and freely accessible interface to interrogate well-annotated datasets and obtain publishable representations that can contribute to refinement and guidance of cancer-related investigations at all levels of hypotheses and design. Significance: In order to facilitate access of research groups without bioinformatics support to public transcriptomics data, we have developed a free online tool with an easy-to-use interface that allows researchers to obtain quality information in a readily publishable forma

Low-dose statin treatment increases prostate cancer aggressiveness

Altres ajuts: NM-M was supported by the Spanish Association Against Cancer (AECC), AECC JP Vizcaya. VT is supported by Fundación Vasca de Innovación e Investigación Sanitarias, BIOEF (BIO15/CA/052), the department of health of the Basque Government (2016111109) and the 2016 grant of the AECC (Junta provincial de Bizkaia). LA, AA-A and LV-J were supported by the Basque Government of education. The work of A.C. is supported by the Ramón y Cajal award, the Basque Department of Industry, Tourism and Trade (Etortek) and the department of education (IKERTALDE IT1106-16), FERO VIII Fellowship, the BBVA foundation, Severo Ochoa. Excellence Accreditation SEV-2016-0644) and the European Research Council (Starting Grant 336343; Proof of Concept 754627). The participation of AC, VT, NM-M, SF and AZ as part of CIBERONC was co-funded with FEDER funds.Prostate cancer is diagnosed late in life, when co-morbidities are frequent. Among them, hypertension, hypercholesterolemia, diabetes or metabolic syndrome exhibit an elevated incidence. In turn, prostate cancer patients frequently undergo chronic pharmacological treatments that could alter disease initiation, progression and therapy response. Here we show that treatment with anti-cholesterolemic drugs, statins, at doses achieved in patients, enhance the pro-tumorigenic activity of obesogenic diets. In addition, the use of a mouse model of prostate cancer and human prostate cancer xenografts revealed that in vivo simvastatin administration alone increases prostate cancer aggressiveness. In vitro cell line systems supported the notion that this phenomenon occurs, at least in part, through the direct action on cancer cells of low doses of statins, in range of what is observed in human plasma. In sum, our results reveal a prostate cancer experimental system where statins exhibit an undesirable effect, and warrant further research to address the relevance and implications of this observation in human prostate cancer