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• Direct genetic transformation bypasses tumor-associated DNA methylation alterations

  Tumors represent dynamically evolving populations of mutant cells, and many advances have been made in understanding the biology of their progression. However, key unresolved questions remain about the conditions that support their initial transformation, which cannot be easily captured in patient populations but are instead modeled using transgenic cellular or animal systems. Here, we used extensive patient atlas data to define common features of the tumor DNA methylation landscape as they compare to healthy human cells and used this benchmark to screen 21 engineered human and mouse models for their ability to reproduce these patterns. Notably, we find that genetically induced cellular transformation can trigger global changes in DNA methylation levels that are consistent with extensive proliferation but rarely recapitulate the widespread de novo methylation of Polycomb targets as found in clinical samples. Our results raise pertinent questions about the relationship between genetic and epigenetic aspects of tumorigenesis and provide an important molecular reference for evaluating existing as well as newer tumor models.

  Study EGAS50000000902

• Processing of tissue and cfDNA samples of CRC patients using Active-seq

  In this study, we have developed a novel technology called Active-Seq (Azide Click Tagging for In Vitro Epigenomic sequencing), a base conversion-free technology used to profile the DNA methylation status of a sample, based on the isolation of DNA containing unmodified CpG sites using a mutated bacterial methyltransferase enzyme and a synthetically prepared cofactor analogue. We procured samples from colorectal cancer (CRC) patients including tumour tissue as well as normal adjacent tissues. The data enabled us to identify CRC-specific markers that could then be used to track and monitor the presence of tumour DNA in cell-free DNA plasma (cfDNA) samples procured in the same patients. The FASTQ files of all the colorectal cancer tissues, normal adjacent tissues as wells as the cfDNA samples are available in this submission. The data made available in this study have been used to outline an approach for tumour-informed disease profiling in colorectal cancer cfDNA samples using Active-Seq.

  Study EGAS50000001226

• Molecular Profiling and Sequential Somatic Mutation Shift in Hypermutator Tumors Harboring POLE Mutations

  Defective DNA polymerase ? (POLE) proofreading leads to extensive somatic mutations that exhibits biased mutational properties; however, the characteristics of POLE-mutated tumors remain unclear. In present study, we described a molecular profile using whole exome sequencing based on the transition of somatic mutations in 10 POLE-mutated solid tumors that obtained from 2,42 Japanese patients. The bias of accumulated variations in this mutant was quantified to follow a pattern of somatic mutations, thereby classifying the sequential mutation shift into three periods. During the period prior to occurrence of the aberrant POLE, no accumulation of mutations in cancer-related genes was observed, whereas PTEN was highly mutated in conjunction with or subsequent to the event, suggesting that POLE and PTEN mutations were responsible for the development of POLE-mutated tumors. Furthermore, homologous recombination was restored after occurring PTEN mutations. Our strategy for estimation of the footprint of somatic mutations may provide new insight toward the understanding of mutation-driven tumorigenesis.

  Study JGAS000130

• Immune trajectory of response and adverse effect in immunotherapy-treated hepatocellular carcinoma

  Whilst anti-PD1 immune checkpoint blockade (ICB) has revolutionised treatment for many cancers, its response rates in hepatocellular carcinoma (HCC) remain modest, coupled with common incidences of immune-related adverse events (irAEs). To identify biomarkers and decipher the mechanisms for response and irAEs, we performed multi-dimensional immunoprofiling on peripheral blood and tissue collected before and during anti-PD1 ICB treatment from HCC patients. Single-cell analyses enabled us to identify peripheral biomarkers, in particular, CD11c+ antigen-presenting cells with varying degrees of HLA-DR expression and CD8 effector memory (EM) T cells with CXCR3 tissue-homing capability that are associated with both response and irAEs. We also dissected the mechanisms behind how these immune subsets interface between response and toxicity, showing their intersecting yet diverging trajectories leading to these distinct clinical fates. This study offers new insights on the mechanisms and potentially novel strategies to enhance response and ameliorate irAEs in cancer immunotherapy.

  Study EGAS00001004843

• Psoriasis Patient PBMC scRNA-seq data

  This dataset contains raw and processed data of four scRNA-seq PBMC samples from four Psoriasis patients (Pso3 = male, Pso4 = female, Pso7 = female, Pso8 = male). Raw sample libraries were prepared with 10x 5'-kit v2 multiplexing the individual samples using TrueSeq barcoded antibodies to stain the cells. Resulting sequencing data consists of four FASTQs (2 x antibody multiplex to demultiplex the samples + 2 x transcriptome data containing the typical cell x UMI barcode data for count matrix generation). The raw sequencing data was processed with cellranger 6.0.1 with the GRCh38 3.0.0 reference and cell to sample assignment was subsequently done with couhto 1.1.0 (https://github.com/dmalzl/counhto) employing the same algorithm as cellranger multi (couldn't be used here though as multi does not handle 5'-chemistry data). Processed data contains all main outputs of cellranger count in raw text format or in h5 formats including the used feature reference for (i.e. antibody barcode to sample assignment) as well as the computed cell to sample assignment computed by counhto. For further details including all used code in the analysis of the data please consult https://doi.org/10.5281/zenodo.13846873

  Dataset EGAD50000001102

• TARGET Trial Study Cohort

  In a randomized controlled clinical trial, investigators will compare the effects on [18F]-fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET/CT) from two treatment regimens in rheumatoid arthritis (RA) patients deemed methotrexate inadequate responders (MTX-IRs). Two common RA treatments will be compared: triple therapy (sulfasalazine, methotrexate, and hydroxychloroquine) versus tumor necrosis factor (TNF) inhibitor (etanercept or adalimumab, plus background methotrexate for all subjects and hydroxychloroquine for subjects who were taking this at screening). Consenting subjects will be screened for eligibility and randomized to a treatment arm. Subjects will be randomized to a treatment arm with either synthetic disease-modifying antirheumatic drugs (DMARDs) [triple therapy: sulfasalazine, methotrexate, and hydroxychloroquine] or biologic DMARDs [etanercept or adalimumab, plus background methotrexate for all subjects and hydroxychloroquine for subjects who were taking this at screening]. Once randomized, a baseline visit will be conducted with each subject. Baseline data collection includes questionnaires, disease activity score, and the first FDG-PET/CT imaging. After the baseline at week 0, subjects will visit with their rheumatologist at weeks 6, 12, 18, and 24 for safety labs and further collection of disease activity scores and questionnaires. The second FDG-PET/CT will be performed at week 24. Blood specimens will be collected at weeks 0, 6, 18, and 24 for bioassays. Subject participation will end after the week 24 visit. Patients and care providers will be unblinded. The FDG-PET/CT image readers will be blinded to treatment arm as well as timepoint of image acquisition.

  Study phs003720

• Preeclampsia InterPregGen Consortium: Large-scale GWAS meta-analysis of maternal preclampsia cases and controls from Europe and Central Asia. Plus extension of earlier European fetal preeclampsia GWAS meta-analysis (see EGAS00001001048) by adding Central Asian fetal preeclampsia cases and controls. Datasets provided under this study are GWAS meta-analysis summary statistics and individual level GWAS genotype data. Related InterPregGen Consortium data are also provided under studies EGAS00001000416 and EGAS00001000417 (whole genome sequence data for 100 unrelated Uzbeks and 100 unrelated Kazakhs) and EGAS00001001048 (European fetal preeclampsia GWAS summary statistics and genotype data

  Preeclampsia (PE) is a syndrome affecting pregnant mothers and fetus/babies characterised by hypertension and proteinuria, and is a leading cause of maternal and fetal death and of premature births worldwide. The InterPregGen Consortium was funded by a European Framework 7 (FP7) grant and grew out of the WTCCC3 GWAS comparing ~2000 UK PE mothers with ~6000 common UK controls. The EGAS00001001266 study includes two components the FP7 InterPregGen project: (a) GWAS case-control meta-analysis of maternal PE cases from Europe (UK, Iceland, Norway, Denmark, Finland) and Central Asia (Kazakhstan, Uzbekistan); (b) GWAS case-control meta-analysis of PE fetal (baby) cases from Europe (UK, Iceland, Norway, Denmark) and Central Asia (Kazakhstan, Uzbekistan)

  Study EGAS00001001266

• DAC for access to array genotypes from the PREGO biobank.

  Dac EGAC00001003484

• DAC_TWINS

  DAC related to monozygotic twins discordant for ALS

  Dac EGAC50000000517

• Berlin Neuroblastoma Patient Genomic Data from Targeted Sequencing for Detection of TERT rearrangement breakpoints to monitor neuroblastoma

  Our objective was to establish a liquid biopsy-based monitoring strategy for pediatric high-risk neuroblastomas that are harboring genomic TERT rearrangements at diagnosis. TERT rearrangement breakpoints are detected by a hybrid capture-based neuroblastoma DNA panel sequencing (published in PMID: 34442335) in tumor material and are reflected in cell-free tumor DNA and can serve as robust biomarkers for disease activity. Within the dataset, 5 tumors of 4 pediatric patients with a neuroblastoma were DNA sequenced. Provided are FASTQ data files, bam and bambai files, as well as breakpoint spanning and encompassing read (enspan) bam and bambai files. Sequencing bam data files are aligned to GRCh37.p13 reference genome (processed).

  Dataset EGAD00001011088