miRandola 2017: a curated knowledge base of non-invasive biomarkers

miRandola (http://mirandola.iit.cnr.it/) is a database of extracellular non-coding RNAs (ncRNAs) that was initially published in 2012, foreseeing the relevance of ncRNAs as non-invasive biomarkers. An increasing amount of experimental evidence shows that ncRNAs are frequently dysregulated in diseases. Further, ncRNAs have been discovered in different extracellular forms, such as exosomes, which circulate in human body fluids. Thus, miRandola 2017 is an effort to update and collect the accumulating information on extracellular ncRNAs that is spread across scientific publications and different databases. Data are manually curated from 314 articles that describe miRNAs, long non-coding RNAs and circular RNAs. Fourteen organisms are now included in the database, and associations of ncRNAs with 25 drugs, 47 sample types and 197 diseases. miRandola also classifies extracellular RNAs based on their extracellular form: Argonaute2 protein, exosome, microvesicle, microparticle, membrane vesicle, high density lipoprotein and circulating. We also implemented a new web interface to improve the user experience

EBF1, MYO6 and CALR expression levels predict therapeutic response in diffuse large B-cell lymphomas

BackgroundDiffuse large B-cell lymphoma (DLBCL) is a hematological malignancy representing one-third of non-Hodgkin’s lymphoma cases. Notwithstanding immunotherapy in combination with chemotherapy (R-CHOP) is an effective therapeutic approach for DLBCL, a subset of patients encounters treatment resistance, leading to low survival rates. Thus, there is an urgent need to identify predictive biomarkers for DLBCL including the elderly population, which represents the fastest-growing segment of the population in Western countries.MethodsGene expression profiles of n=414 DLBCL biopsies were retrieved from the public dataset GSE10846. Differentially expressed genes (DEGs) (fold change >1.4, p-value <0.05, n=387) have been clustered in responder and non-responder patient cohorts. An enrichment analysis has been performed on the top 30 up-regulated genes of responder and non-responder patients to identify the signatures involved in gene ontology (MSigDB). The more significantly up-regulated DEGs have been validated in our independent collection of formalin-fixed paraffin-embedded (FFPE) biopsy samples of elderly DLBCL patients, treated with R-CHOP as first-line therapy.ResultsFrom the analysis of two independent cohorts of DLBCL patients emerged a gene signature able to predict the response to R-CHOP therapy. In detail, expression levels of EBF1, MYO6, CALR are associated with a significant worse overall survival.ConclusionsThese results pave the way for a novel characterization of DLBCL biomarkers, aiding the stratification of responder versus non-responder patients

RNA-interference e Farmacogenomica: dall'analisi dell'RNA agli effetti dei farmaci

Le interazioni tra i geni insieme con i loro livelli di espressione determinano un fenotipo in un dato organismo. Tuttavia pochi sforzi sono stati fatti per usare i dati fenotipici che capire le singole relazioni genotipo-fenotipo. L'origine genetica di una malattia è spesso scoperta una volta che il suo fenotipo è stato chiaramente definito, in aggiunta i tratti complessi delle malattie comprendono una varietà di fenotipi e meccanismi biologici, tali da rendere difficile determinare i geni da studiare. Per molto tempo, i fenotipi sono stati visti unicamente come indicatori di cambi nei genotipi o nelle malattie. L'abilità di interferire in maniera sistematica nei componenti genetici ha aumentato l'importanza dei fenotipi come tool per comprendere i processi biologici a livello molecolare. A livello qualitativo il data set di mutazione umana supera quella di qualsiasi altra specie poichè i fenotipi umani possono essere facilmente individuati e descritti dalle loro caratteristiche osservabili e l'esistenza di specifici gruppi di fenotipi di malattie suggerisce che la fenomica è possibile negli umani. Molti fenotipi umani possono essere trovati nel database OMIM (Online Mendelian Inheritance in Man), in cui sono espressi in linguaggio naturale, ma che non contiene un sistema standardizzato per lo scoring dei fenotipi. Un particolare problema con l'analisi dei fenotipi è la mancanza di un comune vocabolario per descriverli, a causa di questa eterogeneità l'analisi dei fenotipi è scoraggiante ed ancora un processo relativamente inesplorato. Un altro ostacolo deriva dalla scarsa disponibilità di data set di phenotipi con i rispettivi geni. Eshmun è un web tool che integra informazioni eterogenee il cui scopo è quello di annotare un set di geni tramite l'uso di network, basandosi sulle rappresentazioni dei fenotipi, microRNA, grug, proteine, effetti collraterali e fattori di trascrizione. Tale ricchezza di informazioni è una valida risorsa per i ricercatori biomedici

A knowledge base for the discovery of function, diagnostic potential and drug effects on cellular and extracellular miRNAs

Background: MicroRNAs (miRNAs) are small noncoding RNAs that play an important role in the regulation ofvarious biological processes through their interaction with cellular mRNAs. A significant amount of miRNAs hasbeen found in extracellular human body fluids (e.g. plasma and serum) and some circulating miRNAs in the bloodhave been successfully revealed as biomarkers for diseases including cardiovascular diseases and cancer. ReleasedmiRNAs do not necessarily reflect the abundance of miRNAs in the cell of origin. It is claimed that release ofmiRNAs from cells into blood and ductal fluids is selective and that the selection of released miRNAs may correlatewith malignancy. Moreover, miRNAs play a significant role in pharmacogenomics by down-regulating genes thatare important for drug function. In particular, the use of drugs should be taken into consideration while analyzingplasma miRNA levels as drug treatment. This may impair their employment as biomarkers.Description: We enriched our manually curated extracellular/circulating microRNAs database, miRandola, byproviding (i) a systematic comparison of expression profiles of cellular and extracellular miRNAs, (ii) a miRNA targetsenrichment analysis procedure, (iii) information on drugs and their effect on miRNA expression, obtained byapplying a natural language processing algorithm to abstracts obtained from PubMed.Conclusions: This allows users to improve the knowledge about the function, diagnostic potential, and the drugeffects on cellular and circulating miRNAs

A knowledge base for the discovery of function, diagnostic potential and drug effects on cellular and extracellular miRNAs

Background: MicroRNAs (miRNAs) are small noncoding RNAs that play an important role in the regulation ofvarious biological processes through their interaction with cellular mRNAs. A significant amount of miRNAs hasbeen found in extracellular human body fluids (e.g. plasma and serum) and some circulating miRNAs in the bloodhave been successfully revealed as biomarkers for diseases including cardiovascular diseases and cancer. ReleasedmiRNAs do not necessarily reflect the abundance of miRNAs in the cell of origin. It is claimed that release ofmiRNAs from cells into blood and ductal fluids is selective and that the selection of released miRNAs may correlatewith malignancy. Moreover, miRNAs play a significant role in pharmacogenomics by down-regulating genes thatare important for drug function. In particular, the use of drugs should be taken into consideration while analyzingplasma miRNA levels as drug treatment. This may impair their employment as biomarkers.Description: We enriched our manually curated extracellular/circulating microRNAs database, miRandola, byproviding (i) a systematic comparison of expression profiles of cellular and extracellular miRNAs, (ii) a miRNA targetsenrichment analysis procedure, (iii) information on drugs and their effect on miRNA expression, obtained byapplying a natural language processing algorithm to abstracts obtained from PubMed.Conclusions: This allows users to improve the knowledge about the function, diagnostic potential, and the drugeffects on cellular and circulating miRNAs

Additional file 1: of KAOS: a new automated computational method for the identification of overexpressed genes

Protein expression of ZAP70 in DU4475 breast cancer cell line. Characterization by Western Blot analysis of ZAP-70 protein. Total cell lysated were subjected to Western Blot analysis using anti-ZAP70 (sc-1526) goat polyclonal antibody raised against a peptide mapping at the C-terminus of ZAP-70. 1) DU4475 (20 ng); 2) MCF7 (20 ng); 3) HisGST-ZAP70 recombinant protein (15 ng), positive control. (PNG 68 kb

Comprehensive kinome NGS targeted expression profiling by KING-REX

Abstract Background Protein kinases are enzymes controlling different cellular functions. Genetic alterations often result in kinase dysregulation, making kinases a very attractive class of druggable targets in several human diseases. Existing approved drugs still target a very limited portion of the human ‘kinome’, demanding a broader functional knowledge of individual and co-expressed kinase patterns in physiologic and pathologic settings. The development of novel rapid and cost-effective methods for kinome screening is therefore highly desirable, potentially leading to the identification of novel kinase drug targets. Results In this work, we describe the development of KING-REX (KINase Gene RNA EXpression), a comprehensive kinome RNA targeted custom assay-based panel designed for Next Generation Sequencing analysis, coupled with a dedicated data analysis pipeline. We have conceived KING-REX for the gene expression analysis of 512 human kinases; for 319 kinases, paired assays and custom analysis pipeline features allow the evaluation of 3′- and 5′-end transcript imbalances as readout for the prediction of gene rearrangements. Validation tests on cell line models harboring known gene fusions demonstrated a comparable accuracy of KING-REX gene expression assessment as in whole transcriptome analyses, together with a robust detection of transcript portion imbalances in rearranged kinases, even in complex RNA mixtures or in degraded RNA. Conclusions These results support the use of KING-REX as a rapid and cost effective kinome investigation tool in the field of kinase target identification for applications in cancer biology and other human diseases