A quality control portal for sequencing data deposited at the European genome-phenome archive.

Since its launch in 2008, the European Genome-Phenome Archive (EGA) has been leading the archiving and distribution of human identifiable genomic data. In this regard, one of the community concerns is the potential usability of the stored data, as of now, data submitters are not mandated to perform any quality control (QC) before uploading their data and associated metadata information. Here, we present a new File QC Portal developed at EGA, along with QC reports performed and created for 1 694 442 files [Fastq, sequence alignment map (SAM)/binary alignment map (BAM)/CRAM and variant call format (VCF)] submitted at EGA. QC reports allow anonymous EGA users to view summary-level information regarding the files within a specific dataset, such as quality of reads, alignment quality, number and type of variants and other features. Researchers benefit from being able to assess the quality of data prior to the data access decision and thereby, increasing the reusability of data (https://ega-archive.org/blog/data-upcycling-powered-by-ega/).

The European Genome-phenome Archive in 2021.

The European Genome-phenome Archive (EGA - https://ega-archive.org/) is a resource for long term secure archiving of all types of potentially identifiable genetic, phenotypic, and clinical data resulting from biomedical research projects. Its mission is to foster hosted data reuse, enable reproducibility, and accelerate biomedical and translational research in line with the FAIR principles. Launched in 2008, the EGA has grown quickly, currently archiving over 4,500 studies from nearly one thousand institutions. The EGA operates a distributed data access model in which requests are made to the data controller, not to the EGA, therefore, the submitter keeps control on who has access to the data and under which conditions. Given the size and value of data hosted, the EGA is constantly improving its value chain, that is, how the EGA can contribute to enhancing the value of human health data by facilitating its submission, discovery, access, and distribution, as well as leading the design and implementation of standards and methods necessary to deliver the value chain. The EGA has become a key GA4GH Driver Project, leading multiple development efforts and implementing new standards and tools, and has been appointed as an ELIXIR Core Data Resource.

Beacon v2 and Beacon networks: A "lingua franca" for federated data discovery in biomedical genomics, and beyond.

Beacon is a basic data discovery protocol issued by the Global Alliance for Genomics and Health (GA4GH). The main goal addressed by version 1 of the Beacon protocol was to test the feasibility of broadly sharing human genomic data, through providing simple "yes" or "no" responses to queries about the presence of a given variant in datasets hosted by Beacon providers. The popularity of this concept has fostered the design of a version 2, that better serves real-world requirements and addresses the needs of clinical genomics research and healthcare, as assessed by several contributing projects and organizations. Particularly, rare disease genetics and cancer research will benefit from new case level and genomic variant level requests and the enabling of richer phenotype and clinical queries as well as support for fuzzy searches. Beacon is designed as a "lingua franca" to bridge data collections hosted in software solutions with different and rich interfaces. Beacon version 2 works alongside popular standards like Phenopackets, OMOP, or FHIR, allowing implementing consortia to return matches in beacon responses and provide a handover to their preferred data exchange format. The protocol is being explored by other research domains and is being tested in several international projects.

Every which way? On predicting tumor evolution using cancer progression models.

Successful prediction of the likely paths of tumor progression is valuable for diagnostic, prognostic, and treatment purposes. Cancer progression models (CPMs) use cross-sectional samples to identify restrictions in the order of accumulation of driver mutations and thus CPMs encode the paths of tumor progression. Here we analyze the performance of four CPMs to examine whether they can be used to predict the true distribution of paths of tumor progression and to estimate evolutionary unpredictability. Employing simulations we show that if fitness landscapes are single peaked (have a single fitness maximum) there is good agreement between true and predicted distributions of paths of tumor progression when sample sizes are large, but performance is poor with the currently common much smaller sample sizes. Under multi-peaked fitness landscapes (i.e., those with multiple fitness maxima), performance is poor and improves only slightly with sample size. In all cases, detection regime (when tumors are sampled) is a key determinant of performance. Estimates of evolutionary unpredictability from the best performing CPM, among the four examined, tend to overestimate the true unpredictability and the bias is affected by detection regime; CPMs could be useful for estimating upper bounds to the true evolutionary unpredictability. Analysis of twenty-two cancer data sets shows low evolutionary unpredictability for several of the data sets. But most of the predictions of paths of tumor progression are very unreliable, and unreliability increases with the number of features analyzed. Our results indicate that CPMs could be valuable tools for predicting cancer progression but that, currently, obtaining useful predictions of paths of tumor progression from CPMs is dubious, and emphasize the need for methodological work that can account for the probably multi-peaked fitness landscapes in cancer.

Cellular stress responses in hepatitis C virus infection: Mastering a two-edged sword.

Hepatitis C virus (HCV) infection affects chronically more than 150 million humans worldwide. Chronic HCV infection causes severe liver disease and hepatocellular carcinoma. While immune response-mediated events are major players in HCV pathogenesis, the impact that viral replication has on cellular homeostasis is increasingly recognized as a necessary contributor to pathological manifestations of HCV infection such as steatosis, insulin-resistance or liver cancer. In this review, we will briefly overview the different cellular stress pathways that are induced by hepatitis C virus infection, the response that the cell promotes to attempt regaining homeostasis or to induce dysfunctional cell death, and how the virus co-opts these response mechanisms to promote both viral replication and survival of the infected cell. We will review the role of unfolded protein and oxidative stress responses as well as the role of auto- and mitophagy in HCV infection. Finally, we will discuss the recent discovery of a cellular chaperone involved in stress responses, the sigma-1 receptor, as a cellular factor required at the onset of HCV infection and the potential molecular events underlying the proviral role of this cellular factor in HCV infection.

HCV-specific immune responses induced by CIGB-230 in combination with IFN-α plus ribavirin.

AIM: To analyze hepatitis C virus (HCV)-specific immune responses in chronically infected patients under triple therapy with interferon-α (IFN-α) plus ribavirin and CIGB-230. METHODS: CIGB-230 was administered in different schedules with respect to IFN-α plus ribavirin therapy. Paired serum and peripheral blood mononuclear cells (PBMC) samples from baseline and end of treatment were analyzed. The HCV-specific humoral response was tested by enzyme-linked immunosorbent assay, neutralizing antibodies were evaluated by cell culture HCV neutralization assays, PBMC proliferation was assayed by carboxyfluorescein succinimidyl ester staining and IFN-γ secretion was assessed by enzyme-linked immunospot. Data on virological and histological response and their association with immune variables are also provided. RESULTS: From week 12 to week 48, all groups of patients showed a significant reduction in mean leukocyte counts. Statistically significant reductions in antibody titers were frequent, but only individuals immunized with CIGB-230 as early add-on treatment sustained the core-IgG response, and the neutralizing antibody response was enhanced only in patients receiving CIGB-230. Cell-mediated immune responses also tended to decline, but significant reductions in IFN-γ secretion and total absence of core-specific lymphoproliferation were exclusive of the control group. Only CIGB-230-immunized individuals showed de novo induced lymphoproliferative responses against the structural antigens. Importantly, it was demonstrated that the quality of the CIGB-230-induced immune response depended on the number of doses and timing of administration in relation to the antiviral therapy. Specifically, the administration of 6 doses of CIGB-230 as late add-on to therapy increased the neutralizing antibody activity and the de novo core-specific IFN-γ secretion, both of which were associated with the sustained virological response. CONCLUSION: CIGB-230, combined with IFN-α-based therapy, modifies the immune response in chronic patients. The study provides evidence for the design of more effective therapeutic vaccine interventions against HCV.