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• HELIUS cohort gut microbiome batch2

  The gut microbiota composition is unique to every individual but is shaped by common factors including diet, lifestyle, medication use, early-life determinants, living environment or genetics. Most of these factors may be influenced by ethnicity. This study explored variations in fecal microbiota composition in 6048 individuals with different ethnic backgrounds living in the same geographical area (Amsterdam, the Netherlands). The HELIUS data are owned by the Amsterdam University Medical Centers, location AMC in Amsterdam, The Netherlands. To allow sharing of microbiome data collected in HELIUS with (inter)national researchers, 16s rRNA sequence analysis has been stored at the European genome-phenome archive (EGA; accession code EGAD00001004106). This requires that access needs to be granted, also because the HELIUS data are stored with relevant phenotypical variables. Access is granted to all researchers affiliated with an internationally recognized research institution who request to use the HELIUS data within the EGA context, after having signed the data transfer agreement. Any researcher can request the data by submitting a proposal to the HELIUS Executive Board as outlined at http://www.heliusstudy.nl/en/researchers/collaboration, by email: heliuscoordinator at amsterdamumc dot nl. The HELIUS Executive Board will check proposals if they do not conflict with ethical approvals and informed consent forms of the HELIUS study.

  Dataset EGAD00001009732

• CRUK-ICGC Prostate DNA Methylation Sequencing Dataset (Prostatectomy Batches 1-6)

  This dataset includes Illumina EPIC Capture Sequencing Data of 376 samples from 188 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy, with matched pathologically assessed non-cancer control material. This DNA methylation data includes donors and samples included in previously published WGS datasets (from CRUK-ICGC batches 1 to 3 [EGAD00001001116] and batches 4 to 6 [EGAD00001003225]; including the majority of donors used in Wedge et al, Nature Genetics 2018 [PMID: 29662167]). The targeted DNA methylation sequencing data in this EGA dataset were generated using the Illumina TruSeq methyl capture method (EPICseq), covering over 3.3 million CpGs in the human genome, representing a total targeted hybridisation capture panel of 107Mbp. According to the EPICseq protocol, DNA samples extracted from prostatectomy tissue samples were enriched for target regions using hybridisation capture, prior to bisulfite conversion, amplification and sequencing in pools of 12 samples (150 single end reads over two Illumina HiSeq4000 lanes). This approach generated DNA methylation profiles from prostate cancer and control samples at base-pair resolution across millions of CpGs in the human genome.

  Dataset EGAD00001010184

• Whole-genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from long-term survivors.

  Whole-genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from long-term survivors performed as part of the Multidisciplinary Ovarian Cancer Outcomes Group (MOCOG) study. The dataset includes fastq files from 58 HGSC tumours (53 primary tumours and 5 recurrent tumours) and 53 matched normals from 53 long-term survivor patients. Sequence libraries were generated from tumour and matched normal genomic DNA using the KAPA HyperPrep PCR-free library preparation kit (Roche) according to manufacturer’s instructions. Sequencing was carried out by the Kinghorn Centre for Clinical Genomics Sequencing Laboratory (Sydney, Australia) on the HiSeq X Ten System (Illumina) to a minimum base coverage of 30-fold for normal DNA and 60-fold for tumour DNA samples.

  Dataset EGAD00001009398

• Whole transcriptome RNA sequencing on bone marrow and peripheral blood samples from patients with acute myeloid leukemia at diagnosis or relapse.

  One hundred cryopreserved bone marrow and peripheral blood samples from patients with acute myeloid leukemia (AML) with 10-90% blasts were selected from the biobank of the Department of Hematology of Leiden University Medical Center (LUMC). The AML cases cover all subtypes, and specifically include known subtype-defining balanced chromosomal translocations according to the WHO classification. The samples were obtained from 96 patients and include three pairs of de novo and relapsed AML and one pair of de novo and presumed therapy-related AML (tAML). Total RNA was isolated from mononuclear cells without prior enrichment for leukemic blasts. The quality and integrity of total RNA was checked and RNA libraries were prepared using the TruSeq RNA library preparation kit v2 (Illumina, San Diego, CA) in an ISO/IEC 17025-accredited protocol. This workflow started with enrichment of messenger RNA by oligo dT magnetic beads. After fragmentation, cDNA synthesis was performed, followed by adaptor ligation and PCR amplification. Paired-end sequencing with a read length of 126 bp was performed on an Illumina HiSeq 2500 v4 sequencer to at least 12.5 Gbp per sample. Image analysis, base calling, and quality check was performed with Illumina data analysis pipeline RTA v1.18.64 and Bcl2fastq v1.8.4. RNAseq reads are provided in compressed Sanger FASTQ format.

  Dataset EGAD00001004187

• HELIUS cohort gut microbiome

  The gut microbiota composition is unique to every individual but is shaped by common factors including diet, lifestyle, medication use, early-life determinants, living environment or genetics. Most of these factors may be influenced by ethnicity. This study explored variations in fecal microbiota composition in 6048 individuals with different ethnic backgrounds living in the same geographical area (Amsterdam, the Netherlands). The HELIUS data are owned by the Amsterdam University Medical Centers, location AMC in Amsterdam, The Netherlands. To allow sharing of microbiome data collected in HELIUS with (inter)national researchers, 16s rRNA sequence analysis has been stored at the European genome-phenome archive (EGA; accession code EGAD00001004106). This requires that access needs to be granted, also because the HELIUS data are stored with relevant phenotypical variables. Access is granted to all researchers affiliated with an internationally recognized research institution who request to use the HELIUS data within the EGA context, after having signed the data transfer agreement. Any researcher can request the data by submitting a proposal to the HELIUS Executive Board as outlined at http://www.heliusstudy.nl/en/researchers/collaboration, by email: heliuscoordinator at amsterdamumc dot nl. The HELIUS Executive Board will check proposals if they do not conflict with ethical approvals and informed consent forms of the HELIUS study.

  Dataset EGAD00001004106

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas (2019-04-03)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004893

• Small-molecule inhibitors in melanoma - Kenski / Kong - WES (2019-04-11)

  Small-molecule inhibitors targeting the most commonly activated pathway in melanoma, MAPK pathway (either alone or in combination) are already given to melanoma patients for few years, and initially reduce tumour burden dramatically, eventually melanomas become resistant and tumours progress while on treatment. Resistance to this treatment occurs by acquisition of additional mutations or other alterations that affect the mitogen-activated protein kinase (MAPK) pathway by either direct or indirect signalling. Many resistance mechanisms somehow lead to reactivation of extracellular signal-regulated kinase (ERK), thereby restoring signalling of the oncogenic BRAF/MEK/ERK pathway. In addition, PI3K pathway activation contributes to resistance to BRAF inhibition. Less frequent but equally important to the phenomenon of targeted drug resistance is the observation that B15-20% of BRAF mutant melanoma patients fail to respond to BRAF inhibition already early on treatment, owing to intrinsic resistance. These patients have little therapeutic options, unless immunotherapy can be given. To better understand the resistance mechanisms in MAPK inhibitor-treated melanoma patients and melanoma biology, our lab generated a big panel of MAPK inhibitor resistant melanoma cell lines by continuous drug exposure. The understanding of the genetic landscape and gene expression as well as cross resistance to other treatment regimens, and other aspects of melanoma biology such as phenotype switch, will allow us to better exploit new therapeutic strategies for melanoma patients. . This dataset contains all the data available for this study on 2019-04-11.

  Dataset EGAD00001004952

• WGS and WTS data of patient diagnosed with HSTCL

  WGS and WTS data of a single patient diagnosed with HSTCL. Whole-genome sequencing (WGS) was performed for the tumor-normal sample. Genomic DNA from tumor tissue was extracted with QIAamp DNA Mini Kit. The DNA for the matching normal was obtained from blood or buccal swabs and purified by Blood and Cell Culture DNA Mini kit or E.Z.N.A. Tissue DNA Kit (Omega Bio-tek) according to manufacturer’s instructions. The quantity and quality were assessed by Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen) and agarose gel electrophoresis. All sequencing libraries were prepared using TruSeq Nano DNA Library Prep Kit (Illumina). Paired-end sequencing was performed on Illumina HiSeq 4000 2x151 bp read length. Whole-transcriptome sequencing (WTS): Total RNA from snap frozen EITL tumor samples was extracted using TRIzol (Invitrogen) and purified with RNeasy Mini Kit (Qiagen) according to manufacturer’s instructions. The integrity of RNA was determined by electrophoresis using 2100 Bioanalyzer (Agilent Technologies). 500 ng of total RNA was reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). Quantification was performed using SsoFast EvaGreen Supermix and CFX96 Real-Time PCR System (both Bio-Rad). Sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero (Illumina) and WTS was performed on Illumina HiSeq 2500 with 2x101 bp read length.

  Dataset EGAD00001005229

• A human induced pluripotent stem cell toolbox for studying sex chromosome effects-Whole exome seq

  To generate autosomaly isogenic hiPSCs with various chromosome complement, we use Klinefelter syndrome patient skin fibroblasts. These cells harbour XXY sex chromosomes, which can be lost during the reprogramming event and generate cells which are autosomaly identical to each other but differ in sex chromosome complement. We use state of the art reprogramming methods to generate panels of isogenic XXY, XX and XY iPSCs from XXY patient fibroblasts. We have performed Whole exome sequencing on Klinefelter syndrome patient's skin fibroblasts in order to check if two X chromosomes are identical and to see if we can distinguish which X chromosome is more likely to be lost during the reprogramming event in XY cell lines.

  Study EGAS50000000930

• Short-term fasting before living kidney donation has an immune-modulatory effect

  Background: Short-Term Fasting (STF) is an intervention reducing the intake of calories, without causing undernutrition or micronutrient-related malnutrition. It aims to systemically improve resilience against acute stress. Several (pre-)clinical studies have suggested protective effects of STF, marking the systemic effects STF can induce in respect to surgery and ischemia-reperfusion injury. In addition, STF also affects the number of circulating immune cells. We aim to determine the effect of STF on the abundance and phenotype of different immune cell populations. Methods: Thirty participants were randomly selected from the FAST clinical trial, including living kidneys donors, randomised to a STF-diet or control arm. In an observational cohort sub-study we prospectively included 30 patients who donated blood samples repeatedly during study runtime. Using flow cytometry analyses, immune cell phenotyping was performed on peripheral blood mononuclear cells. Three panels were designed to investigate the presence and activation status of peripheral T cells, B cells, dendritic cells (DCs) and myeloid cells. Results: Eight participants were excluded due to sample constraints. Baseline characteristics showed no significant differences, except for fasting duration. Weight changes were minimal and non-significant across different time intervals, with slight trends towards long-term weight loss pre-surgery. Glucose, insulin, and β-hydroxybutyrate levels differed significantly between groups, reflecting adherence to the fasting diet. Flow cytometry analysis revealed no baseline differences between groups, with high variability within each group. We observed significant changes in immune cell populations due to fasting, particularly in B cells, T cells, and DCs. Discussion: In this study, we found that STF changes the levels and phenotype of immune cells, reducing abundance and activation of T cells and regulatory T cells, increased presence of (naïve) B cells, and elevation of type 1 conventional DCs. Further research should focus on the clinical implications of the changes in immune cell populations and significance of these observed immunological changes. Background: Short-Term Fasting (STF) is an intervention reducing the intake of calories, without causing undernutrition or micronutrient-related malnutrition. It aims to systemically improve resilience against acute stress. Several (pre-)clinical studies have suggested protective effects of STF, marking the systemic effects STF can induce in respect to surgery and ischemia-reperfusion injury. In addition, STF also affects the number of circulating immune cells. We aim to determine the effect of STF on the abundance and phenotype of different immune cell populations. Methods: Thirty participants were randomly selected from the FAST clinical trial, including living kidneys donors, randomised to a STF-diet or control arm. In an observational cohort sub-study we prospectively included 30 patients who donated blood samples repeatedly during study runtime. Using flow cytometry analyses, immune cell phenotyping was performed on peripheral blood mononuclear cells. Three panels were designed to investigate the presence and activation status of peripheral T cells, B cells, dendritic cells (DCs) and myeloid cells. Results: Eight participants were excluded due to sample constraints. Baseline characteristics showed no significant differences, except for fasting duration. Weight changes were minimal and non-significant across different time intervals, with slight trends towards long-term weight loss pre-surgery. Glucose, insulin, and β-hydroxybutyrate levels differed significantly between groups, reflecting adherence to the fasting diet. Flow cytometry analysis revealed no baseline differences between groups, with high variability within each group. We observed significant changes in immune cell populations due to fasting, particularly in B cells, T cells, and DCs. Discussion: In this study, we found that STF changes the levels and phenotype of immune cells, reducing abundance and activation of T cells and regulatory T cells, increased presence of (naïve) B cells, and elevation of type 1 conventional DCs. Further research should focus on the clinical implications of the changes in immune cell populations and significance of these observed immunological changes.

  Study EGAS00001008034