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• RNASeq data from one small cell prostate cancer patient (4 samples from 3 time points)

  RNASeq data from one small cell prostate cancer patient - 4 cancer samples (FFPE) from Patient 1 collected at 3 different time points. mRNA was selected using the Magnetic mRNA Isolation Module (NEB) and sequenced on the Illumina NextSeq 500 as 75bp paired end reads (total read length 150bp).

  Dataset EGAD00001011154

• Atezolizumab monotherapy following dCRT indicated a promising cCR rate in patients with unresectable locally advanced esophageal squamous cell carcinoma (EPOC1802)

  The objective is to analyze tumor and normal cell exome sequencing of esophageal cancer patients participating in the Tenergy trial before treatment and RNA sequencing specimens of tumor biopsy specimens at three points before treatment, after radiation chemotherapy, and after atezolizumab administration, in order to search for biomarkers to predict treatment response. Exome sequencing of pretreatment tumor tissue (27 specimens) and normal tissue (27 specimens) from esophageal cancer patients participating in the Tenergy trial, and RNA sequencing of tumor biopsy specimens at three time points before treatment (28 specimens), after radiation chemotherapy (25 specimens) and after atezolizumab administration (25 specimens).

  Study JGAS000708

• "Elucidation of Immune Status and Its Clinical Significance in Patients with Solid Tumors, Including Gastrointestinal Cancers": A Phase II Clinical Trial of Lenvatinib Plus Pembrolizumab in Patients with Advanced Gastric Cancer

  The objective is to analyze tumor and normal cell exome sequencing of gastric cancer patients participating in the EPOC1706 trial before treatment and RNA sequencing specimens of tumor biopsy specimens at two points before treatment and after the combination therapy of Lenvatinib plus pembrolizumab, in order to search for biomarkers to predict treatment response. Exome sequencing from 10 gastric cancer patients participating in the EPOC1706 trial, and RNA sequencing of tumor biopsy specimens at two time points before treatment (9 patients) and after the combination therapy (8 patients) were obtained.

  Study JGAS000894

• This data consists of iPSC derived model systems stimulated with different media.

  This data consists of iPSC derived model systems stimulated with different media (where possible from the top/bottom separately) to provide insight into which more accurately reflects the human gut environment.

  Dataset EGAD50000001918

• Fastq files from target enrichment

  Fastq files generated during target sequencing of 10MB genomic region surrounding top hits in GWAS in a subset of 86 individuals in case families. Paired end sequencing performed on Illumina NextSeq.

  Dataset EGAD00001007801

• Single-cell RNA sequencing reveals cell-type specific eQTLs in peripheral blood mononuclear cells

  This proof-of-concept study shows that single-cell RNA sequencing in ~25,000 peripheral blood mononuclear cells (PBMCs) of 45 donors allows for the identification of cell type-specific cis expression quantitative trait loci effects (cis-eQTLs). Moreover, the significant top-eQTL effects show consistent allelic direction (94%) with previously published whole blood deepSAGE data. These cell type-specific eQTLs may give us additional insight into the downstream consequences of genetic risk factors for immune-mediated diseases.

  Study EGAS00001002560

• Youth-GEMs, the project using data to define the mental health trajectories of young people

  Mental health trajectories are shaped by genetic, cognitive, social, and environmental factors that are particularly influential during human development. How exactly the interplay between these factors is impacting mental health, however, is yet unknown. The project “Gene Environment interactions in Mental health trajectories of Youth (Youth-GEMs)”, funded by the European Commission under the Horizon Europe programme, aims to help reducing mental suffering among European youth. How do Youth-GEMs contribute to bettering mental health in young people? Youth-GEMs aims to identify specific neurological, (epi)genetic and environmental drivers on mental health trajectories of young people. To do so, the project is working on a public knowledge base on functional genomics of the developing human brain, between birth and 24 years old. Reliable predictive models for trajectories of onset and course of mental illness in young people of the general population in Europe will be developed. Additionally, a secure and FAIR data infrastructure in mental health is being produced. Engaging and empowering young people Youth-GEMs is also working on the engagement of young people in the scientific field of Psychiatry. For that, the project is developing initiatives such as Science Café, intended to create a learning community where ideas and stories are shared. The 10th Science Café will take place today, with the participation of Lauren Fromont from the EGA. How do the EGA contribute to Youth-GEMs? The contributions require careful data management and harmonisation: we are dealing with an extraordinary amount of data types, sources, and time points (since the studies are longitudinal). To analyse them together and to determine which factors and interactions are truly key to account for mental health trajectories, the variables need to be transformed in a common “language”, i.e., harmonised under a common data model. Further, to guarantee FAIRness of data storage and sharing for future projects that will further advance our knowledge in the mental health field, we are ensuring that data are processed securely but can also be discovered easily. Find out more information about the project in the Youth-GEMs website.

  Blog youth-gems-mental-health

• Genome analysis of oesophageal cancer and Barrett's oesophagus

  The median survival of oesophageal cancer this year is only 13 to 19 months after diagnosis and more than 90% will die from their disease. Therefore better treatment options are needed. The likelihood of cure for early screen-detected cancers is much higher. Barrett's oesophagus is a pre-cancerous lesion associated with a 30-40 fold increased risk of developing cancer. In an attempt to detect cancer early many patients with Barrett's are enrolled into surveillance programs involving regular endoscopies. A major problem with this approach is that the prevalence of BO in the population is estimated to be around 2%, but most patients with BO will never develop cancer. We are undertaking genomic and/or transcriptomic analysis of oesophageal tumours, Barrett's oesophagus and matched normal samples. The aim is to identify oesophageal-related genomic and transcriptomic alterations, which may reveal mutational process occurring, suggest biomarkers of tumour progression and treatment and identify novel treatment strategies.

  Study EGAS00001002864

• SmMIP-tools:a computational toolset for processing and analysis of single-molecule molecular inversion probes derived data

  Single-molecule molecular inversion probes (smMIPs) provides a modular and cost-effective platform for high-multiplex targeted next-generation sequencing (NGS). Nevertheless, translating the raw smMIP-derived sequencing data into accurate and meaningful information currently requires proficient computational skills and a large amount of computational work, prohibiting wide-scale adoption of smMIP-based technologies. To enable easy, efficient, and accurate interrogation of smMIP-derived data, we developed SmMIP-tools, a computational toolset that combines the critical analytic steps for smMIP data interpretation into a single computational pipeline. Here, we describe in detail two major components of the software. The first is a read processing tool that performs quality control steps, generates read-smMIP linkages and retrieves molecular tags. The second is an error-aware variant caller capable of detecting single nucleotide variants (SNVs) and short insertions and deletions (indels). Using a cell-line DNA dilution series and a cohort of blood cancer patients, we benchmarked SmMIP-tools and evaluated its performance against clinical sequencing reports. We anticipate that SmMIP-tools will increase accessibility to smMIP-technology, enabling cost-effective genetic research to push personalized medicine forward.

  Study EGAS00001005359

• Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia

  Key Points• Multiple mechanisms of acquired CD19 mutations and splicing contribute to CD19 loss and relapse to blinatumomab.• Identification of CD19 ex2part levels represents a new biomarker predictive of resistance or likely failure of blinatumomab

  Study EGAS00001004027