Explore the vast range of titles available.

The increasing number of biomedical and translational applications in mass spectrometry-based proteomics poses new analytical challenges and raises the need for automated quality control systems. Despite previous efforts to set standard file formats, data processing workflows and key evaluation parameters for quality control, automated quality control systems are not yet widespread among proteomics laboratories, which limits the acquisition of high-quality results, inter-laboratory comparisons and the assessment of variability of instrumental platforms. Here we present QCloud, a cloud-based system to support proteomics laboratories in daily quality assessment using a user-friendly interface, easy setup, automated data processing and archiving, and unbiased instrument evaluation. QCloud supports the most common targeted and untargeted proteomics workflows, it accepts data formats from different vendors and it enables the annotation of acquired data and reporting incidences. A complete version of the QCloud system has successfully been developed and it is now open to the proteomics community (http://qcloud.crg.eu). QCloud system is an open source project, publicly available under a Creative Commons License Attribution-ShareAlike 4.0.

Despite recent advances in the management of BRCA1 mutated high-grade serous ovarian cancer (HGSC), the physiology of these tumors remains poorly understood. Here we provide a comprehensive molecular understanding of the signaling processes that drive HGSC pathogenesis with the addition of valuable ubiquitination profiling, and their dependency on BRCA1 mutation-state directly in patient-derived tissues. Using a multilayered proteomic approach, we show the tight coordination between the ubiquitination and phosphorylation regulatory layers and their role in key cellular processes related to BRCA1-dependent HGSC pathogenesis. In addition, we identify key bridging proteins, kinase activity, and post-translational modifications responsible for molding distinct cancer phenotypes, thus providing new opportunities for therapeutic intervention, and ultimately advance towards a more personalized patient care.

Hepatitis A is an acute disease of the liver caused by the hepatitis A virus (HAV). Chronic liver disease, other viral hepatitis coinfections, and age over 50 years are the main host factors associated with an increased risk of complications. We investigated the evolution of hepatitis A hospitalizations and in-hospital deaths during 2000-2021 in Spain according to demographic characteristics, presence of other sexually transmitted infections, and vaccination strategy (universal or risk-group vaccination). Using data from the Spanish National Health System's Minimum Basic Data Set, we calculated age-standardized cumulative hospitalization incidence and 95% confidence interval (CI), factors associated with hospital stay, and hospitalization deaths. Adjusted OR (aOR) values were calculated using a multivariate logistic regression model. The Spanish cumulative hospitalization incidence for hepatitis A over the 22-year period was 8.84 per 1 000 000 globally and 12.54 and 5.26 per 1 000 000 for men and women, respectively (RR = 2.38; 95% CI: 2.28-2.50). Median length of stay was 4 days (range 0-85). Factors associated with hospitalization >7 days were age groups 40-59 and ≥60 years (aOR 1.58; 95% CI: 1.37-1.82 and aOR 5.09; 95% CI: 4.01-6.47, respectively), cirrhosis (aOR 6.11; 95% CI: 2.59-14.43), and presence of HIV and HBV (aOR 1.65; 95% CI: 1.15-2.38 and 2.01; 95% CI: 1.03-3.63, respectively). In-hospital deaths were associated with age ≥ 60 years (aOR 35.23; 95% CI: 11.12-111.58), hospitalization >7 days (aOR 4.37; 95% CI: 1.80-10.58), cirrhosis (aOR 8.84; 95% CI: 2.37-32.99), and HCV infection (aOR 8.66; 95% CI: 1.57-47.87). The cumulative hospitalization incidence was lower in regions implementing universal vaccination (RR 0.79; 95% CI: 0.75-0.84). Results of studies based on characteristics of hospitalized hepatitis A cases taking into account the existing prevention policies can be useful to have a better knowledge about its evolving epidemiology and to improve the prevention and control of the disease.

Background High-grade serous carcinoma (HGSC) is the most common and deadly subtype of ovarian cancer. Although most patients will initially respond to first-line treatment with a combination of surgery and platinum-based chemotherapy, up to a quarter will be resistant to treatment. We aimed to identify a new strategy to improve HGSC patient management at the time of cancer diagnosis (HGSC-1LTR). Methods A total of 109 ready-available formalin-fixed paraffin-embedded HGSC tissues obtained at the time of HGSC diagnosis were selected for proteomic analysis. Clinical data, treatment approach and outcomes were collected for all patients. An initial discovery cohort (n = 21) were divided into chemoresistant and chemosensitive groups and evaluated using discovery mass-spectrometry (MS)-based proteomics. Proteins showing differential abundance between groups were verified in a verification cohort (n = 88) using targeted MS-based proteomics. A logistic regression model was used to select those proteins able to correctly classify patients into chemoresistant and chemosensitive. The classification performance of the protein and clinical data combinations were assessed through the generation of receiver operating characteristic (ROC) curves. Results Using the HGSC-1LTR strategy we have identified a molecular signature (TKT, LAMC1 and FUCO) that combined with ready available clinical data (patients’ age, menopausal status, serum CA125 levels, and treatment approach) is able to predict patient response to first-line treatment with an AUC: 0.82 (95% CI 0.72–0.92). Conclusions We have established a new strategy that combines molecular and clinical parameters to predict the response to first-line treatment in HGSC patients (HGSC-1LTR). This strategy can allow the identification of chemoresistance at the time of diagnosis providing the optimization of therapeutic decision making and the evaluation of alternative treatment strategies. Thus, advancing towards the improvement of patient outcome and the individualization of HGSC patients’ care.

Little is known about the molecular profiling associated with the effect of cladribine in patients with multiple sclerosis (MS). Here, we aimed first to characterize the transcriptomic and proteomic profiles induced by cladribine in blood cells, and second to identify potential treatment response biomarkers to cladribine in patients with MS. Gene, protein and microRNA (miRNA) expression profiles were determined by microarrays (genes, miRNAs) and mass spectrometry (proteins) in peripheral blood mononuclear cells (PBMCs) from MS patients after treatment with cladribine in its active and inactive forms. Two bioinformatics approaches to integrate the three obtained datasets were applied: (i) a multiomics discriminant analysis (DIABLO - Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies); and (ii) a multi-stage integration of features selected in differential expression analysis on each dataset and then merged. Selected molecules from the study were quantified by qPCR in PBMCs from MS patients receiving cladribine. PBMCs treated with cladribine were characterized by a major downregulation of gene, protein, and miRNA expression compared with the untreated cells. An intermediate pattern between the cladribine-treated and untreated conditions was observed in PBMCs treated with cladribine in its inactive form. The differential expression analysis of each dataset led to the identification of four genes and their encoded proteins, and twenty-two miRNAs regulating their expression, that were associated with cladribine treatment. Two of these genes (PPIF and NHLRC2), and three miRNAs (miR-21-5p, miR-30b-5p, and miR-30e-5p) were validated in MS patients treated with cladribine. By using a combination of omics data and bioinformatics approaches we were able to identify a multiomics molecular profile induced by cladribine in PBMCs. We also identified a number of biomarkers that were validated in PBMCs from patients with MS treated with cladribine that have the potential to become treatment response biomarkers to this drug.

Background: The main consequences of chronic hepatitis B virus (HBV) infections are cirrhosis and hepatocellular carcinoma (HCC), both associated with frequent hospitalization. The aim of this study was to analyze the impact of universal HBV vaccination in Spain on chronic HBV-related hospital discharges from 2005 to 2021. Methods: Using data from the Minimum Basic Data Set of the Spanish National Health System, we calculated the hospital discharge rate ratio (HDRR) and 95% confidence interval (CI) values for chronic HBV-related discharges between 2005 and 2021. For comparative purposes, we calculated the HDRR and 95% confidence interval (CI) values for the early (2005–2013) and later (2014–2021) periods and the vaccinated compared with unvaccinated cohorts for the 20–39 age group. Results: The hospital discharge rate per 1,000,000 people was 3.08 in 2005 and 4.50 in 2021 for HCC, and 4.81 in 2005 and 1.92 in 2021 for cirrhosis. Comparing the early and later periods, values were higher for HCC (HDRR 1.13; 95% CI: 1.06–1.20) and lower for cirrhosis (HDRR 0.56; 95% CI: 0.51–0.60). The rate for the 20–39 age group was lower for the vaccinated compared with the unvaccinated cohorts overall (HDRR 0.53; 95% CI: 0.45–0.62), for HCC (HDRR 0.66; 95% CI: 0.53–0.82), and for cirrhosis (HDRR 0.41; 95% CI: 0.33–0.53). Conclusions: This study describes the important impact, after 25 years, of universal HBV vaccination in Spain: cirrhosis hospital discharge rate was reduced, and the vaccinated cohorts, compared with the unvaccinated cohorts in the 20–39 age group, had a lower hospital discharge rate of both HCC and cirrhosis.

Background Huntington’s disease (HD) is the most frequent autosomal dominant neurodegenerative disorder, which is caused by a CAG repeat expansion in the HTT gene. Despite its well-defined genetic origin, there is currently no cure, and reliable biomarkers for disease progression and pathophysiology remain limited. Mutant huntingtin protein accumulates in endosomal compartments, disrupting endosomal trafficking and potentially affecting the biogenesis, release, and cargo of exosomes–extracellular vesicles (EVs) derived from the endosomal pathway. However, the role of exosomes in HD pathogenesis and their potential as biomarkers has been underexplored. In this work, we investigated whether the levels and content of small EV subpopulations, including exosomes, are altered in the brains of HD patients. Methods We analyzed two distinct subpopulations of small EVs from the striatum and cortex of postmortem HD brains at early and advanced neuropathological stages, as well as from age-matched controls. EVs were isolated by differential ultracentrifugation and high-resolution iodixanol density gradient centrifugation, and analyzed by Western blotting, electron microscopy, NTA, and proteomics using mass spectrometry. EV secretion was also analyzed in primary fibroblasts derived from HD patients and healthy controls. Results Mass spectrometry data revealed HD-associated alterations in EV protein content, particularly proteins related to the endosomal system. Our data also indicate that the level of ectosomes increased in the HD cortex, whereas exosomes were reduced in the HD striatum compared to controls. In terms of EV content, EVs from HD brains showed increased levels of Annexin A2 and decreased levels of Alix, a key component of the endosomal sorting complex required for transport (ESCRT). Alix depletion in EVs mirrored a progressive reduction of Alix in brain tissue, correlating with disease severity based on Vonsattel staging. In vitro, HD fibroblasts secreted EVs with reduced Alix content, despite no significant difference in cellular Alix levels compared to controls. Conclusions These findings highlight disease-specific changes in EV populations and cargo in HD, and identify Alix as a potential neuropathological marker. This study advances our understanding of the role of brain-derived EVs in HD and underscores their potential utility in biomarker discovery.

Objective α-Synuclein has been studied as a potential biomarker for Parkinson’s disease (PD) with no concluding results. Accordingly, there is an urgent need to find out reliable specific biomarkers for PD. GPR37 is an orphan G protein-coupled receptor that toxically accumulates in autosomal recessive juvenile parkinsonism. Here, we investigated whether GPR37 is upregulated in sporadic PD, and thus a suitable potential biomarker for PD. Methods GPR37 protein density and mRNA expression in postmortem substantia nigra (SN) from PD patients were analysed by immunoblot and RT-qPCR, respectively. The presence of peptides from the N-terminus-cleaved domain of GPR37 (i.e. ecto-GPR37) in human cerebrospinal fluid (CSF) was determined by liquid chromatography-mass spectrometric analysis. An engineered in-house nanoluciferase-based immunoassay was used to quantify ecto-GPR37 in CSF samples from neurological control (NC) subjects, PD patients and Alzheimer’s disease (AD) patients. Results GPR37 protein density and mRNA expression were significantly augmented in sporadic PD. Increased amounts of ecto-GPR37 peptides in the CSF samples from PD patients were identified by mass spectrometry and quantified by the in-house ELISA method. However, the CSF total α-synuclein level in PD patients did not differ from that in NC subjects. Similarly, the cortical GPR37 mRNA expression and CSF ecto-GPR37 levels in AD patients were also unaltered. Conclusion GPR37 expression is increased in SN of sporadic PD patients. The ecto-GPR37 peptides are significantly increased in the CSF of PD patients, but not in AD patients. These results open perspectives and encourage further clinical studies to confirm the validity and utility of ecto-GPR37 as a potential PD biomarker.

Abstract Motivation In mass spectrometry-based proteomics, the availability of peptide prior knowledge has improved our ability to assign fragmentation spectra to specific peptide sequences. However, some peptides exhibit similar analytical values and fragmentation patterns, which makes them nearly indistinguishable with current data analysis tools. Results Here we developed the Mass Spectrometry Content Information (MSCI) Python package to tackle the challenges of peptide identification in mass spectrometry-based proteomics, particularly regarding indistinguishable peptides. MSCI provides a comprehensive toolset that streamlines the workflow from data import to spectral analysis, enabling researchers to effectively evaluate fragmentation similarity scores among peptide sequences and pinpoint indistinguishable peptide pairs in a given proteome. Availability and implementation MSCI is implemented in Python and it is released under a permissive MIT license. The source code and the installers are available on GitHub at https://github.com/proteomicsunitcrg/MSCI.

The aim of this study was to analyse the impact of the introduction of universal adolescent HBV vaccination on the incidence of acute hepatitis B virus (HBV) infections. Acute HBV cases reported to the Spanish National Epidemiological Surveillance Network between 2005 and 2021 were included. For regions starting adolescent vaccination in 1991–1993 and in 1994–1996, HBV incidence rates were compared by calculating the incidence rate ratio (IRR) and 95% confidence interval (CI). We also analysed the 2017 Spanish national seroprevalence survey data. The overall acute HBV incidence per 100,000 persons was 1.54 in 2005 and 0.64 in 2021 (p < 0.001). The incidence in 2014–2021 was lower for regions that started adolescent vaccination in 1991–1993 rather than in 1994–1996 (IRR 0.76; 95% CI 0.72–0.83; p < 0.001). In the 20–29 age group, incidence in regions that started adolescent vaccination in 1991–1993 was also lower (IRR 0.87; 95% CI 0.77–0.98; p = 0.02 in 2005–2013 and IRR 0.71; 95% CI 0.56–0·90; p < 0.001 in 2014–2021). Anti-HBc prevalence in the 35–39 age group was lower in the regions that started vaccination earlier, although the difference was not statistically significant (p = 0.09). Acute HBV incidence decreased more in the young adult population in regions that began adolescent vaccination earlier. Maintaining high universal vaccination coverage in the first year of life and in at-risk groups is necessary to achieve HBV elimination by 2030.