MicroRNAs (miRNAs) are a class of short non-coding RNAs involved in the regulation of gene expression and the control of several cellular processes at physiological and pathological levels. Furthermore, extracellular vesicles (EV), which are small membrane-bound vesicles secreted by cells in the extracellular environment, contain functional miRNAs. The remarkable deregulation of many miRNAs has been demonstrated in respiratory diseases. Among them, miR-206, miR-133a-5p, and miR-133a-3p are striated muscle-specific miRNAs (myo-miRNA), related to skeletal muscle dysfunction, one of the commonest systemic manifestations in patients with chronic obstructive pulmonary disease (COPD). Nevertheless, their circulating expression in COPD patients is not demonstrated. For these reasons, we performed a pilot study to analyze the expression profiles of myo-miRNAs in plasma-derived EV from patients with COPD. We analyzed the expression profiles of selected myo-miRNAs in plasma-derived EV from COPD. Receiver operating characteristic analyses were carried out to evaluate whether selected plasma miRNAs were able to discriminate between different groups of COPD patients. We found EV-embedded myo-miRNAs in the bloodstream of COPD patients. Specifically, miR-206, miR-133a-5p and miR-133a-3p were significantly upregulated in group B patients. Receiver operating characteristic analyses of the combination of these selected miRNAs showed their high capacity to discriminate group B from other COPD patients. Our data provide evidence that myo-miRNA are present in EV in the plasma of COPD patients and their expression (miR-206, miR-133a-5p, and miR-133a-3p) can discriminate group B from group C patients. The future analysis of a larger number of patients should allow us to obtain more refined correlations.

Extracellular vesicles (EVs) play a pivotal role in a variety of physiologically relevant processes, including lung inflammation. Recent attention has been directed toward EV-derived microRNAs (miRNAs), such as miR-191-5p, particularly in the context of inflammation. Here, we investigated the impact of miR-191-5p-enriched EVs on the activation of NF-κB and the expression of molecules associated with inflammation such as interleukin-8 (IL-8). To this aim, cells of bronchial epithelial origin, 16HBE, were transfected with miR-191-5p mimic and inhibitor and subsequently subjected to stimulations to generate EVs. Then, bronchial epithelial cells were exposed to the obtained EVs to evaluate the activation of NF-κB and IL-8 levels. Additionally, we conducted a preliminary investigation to analyze the expression profiles of miR-191-5p in EVs isolated from the plasma of patients diagnosed with chronic obstructive pulmonary disease (COPD). Our initial findings revealed two significant observations. First, the exposure of bronchial epithelial cells to miR-191-5p-enriched EVs activated the NF-kB signaling and increased the synthesis of IL-8. Second, we discovered the presence of miR-191-5p in peripheral blood-derived EVs from COPD patients and noted a correlation between miR-191-5p levels and inflammatory and functional parameters. Collectively, these data corroborate and further expand the proinflammatory role of EVs, with a specific emphasis on miR-191-5p as a key cargo involved in this process. Consequently, we propose a model in which miR-191-5p, carried by EVs, plays a role in airway inflammation and may contribute to the pathogenesis of COPD.

Cancer is characterized by chronic inflammation and hypercoagulability, with an excess of venous thromboembolism (VTE). Tissue factor, the initiator of blood coagulation, circulates associated with extracellular vesicles (EV-TF). Studies investigating EV-TF between cancer-associated and non-cancer-associated VTE are lacking. We therefore compared EV-TF in unprovoked VTE (U-VTE), cancer-associated VTE (C-VTE), and cancer without VTE (C-w/o VTE). We also investigated interleukin-6 (IL-6) levels between the same groups. The final population included 68 patients (U-VTE: n = 15; C-VTE: n = 24; C-w/o VTE: n = 29). All patients with VTE were enrolled within 48 h of diagnosis; non-VTE patients were recruited in the oncologic outpatient services. EV were isolated by differential centrifugation from 4 mL of peripheral blood; the final EV pellet (16,000× g for 45 min) was resuspended in 100 μL saline and tested for TF using a one-step clotting assay. There was a statistically significant difference for higher EV-TF in C-VTE and C-w/o VTE compared to U-VTE (p = 0.024; Kruskal–Wallis test). There was no significant difference between C-VTE and C-w/o VTE. Moreover, we did not find any difference in IL-6 levels. These preliminary data suggest that cancer represents, per se, a strong driver of EV-TF generation.

Introduction: Triple therapy with two bronchodilators (LABA plus LAMA) and an inhaled corticosteroid (ICS) is recommended for patients suffering from severe chronic obstructive pulmonary disease (COPD). Areas covered: All 12-52 week-long studies comparing triple therapy with umeclidinium (UM) added to either fluticasone furoate/vilanterol (FF/VI) or fluticasone propionate/salmeterol (FP/SAL) versus other comparators in COPD patients of group B or D (2011 GOLD classification) were considered. When UM was added to ICS/LABA with separate devices or within a single device, triple combination was more effective than comparators (usually, ICS/LABA combinations) regarding improvements to pulmonary function, symptoms, quality of life and, in the longer studies, rate of moderate-severe exacerbations. The IMPACT study (a large trial comparing UM/FF/VI with both FF/VI and UM/VI combinations) showed that triple therapy had a greater effect compared to dual therapies in reducing the rate of moderate-severe exacerbations, improving trough FEV1 and improving quality of life. The safety profile was good, without excess cardiovascular effects or pneumonia, however, the presence of comorbidities was frequent. Expert Commentary: UM/FF/VI combination represents a good option for severe COPD patients who remain symptomatic and/or with frequent exacerbations despite dual therapies. Once daily administration with a simple and effective device may increase adherence and efficacy of the treatment.

Calling copy number alterations (CNAs) from RNA-Seq is challenging, because differences in gene expression mean that read depth across genes varies by several orders of magnitude and there is a paucity of informative single nucleotide polymorphisms (SNPs). We previously developed SuperFreq to analyse exome data of tumours by combining variant calling and copy number estimation in an integrated pipeline. Here we have used the SuperFreq framework for the analysis of RNA sequencing (RNA-Seq) data, which allows for the detection of absolute and allele sensitive CNAs. SuperFreq uses an error-propagation framework to combine and maximise the information available in the read depth and B-allele frequencies of SNPs (BAFs) to make CNA calls on RNA-seq data. We used data from The Cancer Genome Atlas (TCGA) to evaluate the CNA called from RNA-Seq with those generated from SNP-arrays. When ploidy estimates were consistent, we found excellent agreement with CNAs called from DNA of over 98% of the genome for acute myeloid leukaemia (TCGA-AML, n=116) and 87% for colorectal cancer (TCGA-CRC, n=377), which has a much higher CNA burden. As expected, the sensitivity of CNA calling from RNA-Seq was dependent on gene density. Nonetheless, using RNA-Seq SuperFreq detected 78% of CNA calls covering 100 or more genes with a precision of 94%. Recall dropped markedly for focal events, but this also depended on the signal intensity. For example, in the CRC cohort SuperFreq identified 100% (7/7) of cases with high-level amplification of ERBB2, where the copy number was typically >20, but identified only 6% (1/17) of cases with moderate amplification of IGF2, typically 4 or 5 copies over a smaller region (median 5 flanking genes for IGF2, compared to 20 for ERBB2). We were able to reproduce the relationship between mutational load and CNA profile in CRC using RNA-Seq alone. SuperFreq offers an integrated platform for identification of CNAs and point mutations from RNA-seq in cancer transcriptomes.