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• Clinical and genetic factors associated with tumor response to neoadjuvant (chemo)radiotherapy, survival and recurrence risk in rectal cancer

  Rectal cancer poses challenges in preoperative treatment response, with up to 30% achieving a complete response (CR). Personalized treatment relies on accurate identification of responders at diagnosis. This study aimed to unravel CR determinants, overall survival (OS), and time to recurrence (TTR) using clinical and targeted sequencing data. Analyzing 402 patients undergoing preoperative treatment, tumor stage, size, and treatment emerged as robust response predictors. CR rates were higher in smaller, early-stage, and intensively treated tumors. Targeted sequencing analyzed 216 cases, while 120 patients provided hotspot mutation data. KRAS mutation dramatically reduced CR odds by over 50% (odds ratio [OR]=0.3 in the targeted sequencing and OR=0.4 hotspot cohorts, respectively). In contrast, SMAD4 and SYNE1 mutations were associated with higher CR rates (OR=6.0 and 6.8, respectively). Favorable OS was linked to younger age, CR, and low baseline carcinoembryonic antigen levels. Notably, CR and an APC mutation increased TTR, while a BRAF mutation negatively affected TTR. Beyond tumor burden, SMAD4 and SYNE1 mutations significantly influenced CR. KRAS mutations independently correlated with radiotherapy resistance, and BRAF mutations heightened recurrence risk. Intriguingly, nonresponding tumors with initially small sizes carried a higher risk of recurrence. These findings offer insights into rectal cancer treatment response, guiding personalized therapeutic strategies. By uncovering factors impacting CR, OS, and TTR, this study underscores the importance of tailored approaches for rectal cancer patients. These findings, based on extensive analysis and mutation data, pave the way for personalized interventions, optimizing outcomes in the challenges of rectal cancer preoperative treatment.

  Study EGAS00001007501

• The University of Hong Kong Intestinal Metaplasia Organoids Study

  Background: Gastric intestinal metaplasia (IM) is a pre-cancerous stage spanning a morphological spectrum that is poorly represented by human cell line models. Objective: We aim to establish and characterize human IM cell models to better understand IM progression along the cancer spectrum. Design: A large human gastric IM organoid (IMO) cohort (n=28), their clonal derivatives and normal gastric organoids (n=42) for comparison were established. Comprehensive multi-omics profiling and functional characterization were performed. Results: Single-cell transcriptomes revealed IMO cells spanning a spectrum from hybrid gastric/intestinal to advanced intestinal differentiation. Their lineage trajectories connected different cycling and quiescent stem and progenitors, highlighting differences in gastric to IM transition and the potential origin of IM from STMN1 cycling isthmus stem cells. Hybrid IMOs showed impaired differentiation potential, high lineage plasticity beyond gastric or intestinal fates, and reactivation of a fetal gene program. Cell populations in gastric IM and cancer tissues were highly similar to those derived from IMOs and exhibited a fetal signature. Genomically, IMOs showed elevated mutation burden, frequent chromosome 20 gain, and epigenetic de-regulation of many intestinal and gastric genes. Functionally, IMOs were FGF10 independent and showed downregulated FGFR2. Several IMOs exhibited a cell-matrix adhesion independent (CMi) subpopulation that displayed chromosome 20 gain but lacked key cancer driver mutations, potentially representing the earliest neoplastic precursor of IM-induced gastric cancer. Conclusions: Overall, our IM organoid biobank captured the heterogeneous nature of IM, revealing mechanistic insights on IM pathogenesis and progression, offering an ideal platform for studying early gastric neoplastic transformation and chemoprevention.

  Study EGAS00001007899

• KiCS WGS data for academic and for-profit use

  Data from samples that are marked for both academic and for-profit use.

  Dataset EGAD00001009699

• WTCCC case-control study for Coronary Artery Disease, Hypertension, T2D - combined cases

  WTCCC genome-wide case-control association study using the cardiovascular disease CAD, HT and T2D as combined case collection and the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000005

• Epigenome-wide association study of asthma remission in whole blood and nasal epithelium

  Clinical remission (ClinR) was defined as the absence of asthma symptoms and medication for at least 12 months, and complete remission (ComR) was defined as ClinR with normal lung function and absence of airway hyperresponsiveness. We analyzed differential DNA methylation of ClinR and ComR comparing to persistent asthma (PersA) in whole blood samples (n=72) and nasal brushing samples (n=97) in a longitudinal cohort of well characterized asthma patients.

  Dataset EGAD00010002026

• FFPE cohort with RNA-seq data of tumor samples

  This dataset contains RNA-seq raw data in fastq format from 14 tumor samples. The samples are from primary tumors or metastasis and represent various cancer entities. The samples are formalin-fixed paraffin-embedded (FFPE) treated. For target enrichment SureSelect XT Human All Exon V6 was used. The libraries were sequenced in paired-end mode (2 x 50 nt) on a NovaSeq6000 S2 flow cell.

  Dataset EGAD00001006781

• imputed_bacterial_meningitis

  This study includes 1146 samples of host genotyping data (imputed) from Illumina Omni arrays, using https://imputation.sanger.ac.uk/ with the Haplotype Reference Consortium v1.1. Samples were collected from adults (>16 yrs) patients with CSF confirmed bacterial meningitis in the Netherlands between 2006 and 2015. Metadata includes patient outcome, species of bacteria, and for 467 samples a link to an ENA run with the associated bacterial genome (S. pneumoniae only).

  Dataset EGAD00010002327

• Dataset for Fragle Software Development and Evaluation

  Fragle is a deep learning based two stage model that quantifies ctDNA from blood plasma derived cfDNA bam files. Fragle was developed using some previously published datasets and some newly generated data. Fragle was evaluated using some validation cohorts and some unseen cohorts. Some of these cohorts are newly created consisting of total 365 low pass (2-3X) whole genome sequencing bam files mapped to hg19/GRCh37. This dataset contains these newly generated bam files.

  Dataset EGAD50000000167

• CITE-seq AdaptNK

  CITEseq was performed as outlined in Biolegend ‘TotalSeqTM-A Antibodies and Cell Hashing with 10x Single Cell 3' Reagent Kit v3 3.1 Protocol’ with minor modifications, using Biolegend oligo-conjugated antibodies and streptavidin TotalSeq reagents. Briefly, ADAPT-NK cells were stained with CD56-biotin mAb (Miltenyi, clone REA196), followed by TotalSeq antibodies and streptavidin-PE and Live/Dead Aqua (Invitrogen). Cells were subsequently sorted for viable CD56+ cells by flow cytometry.

  Dataset EGAD50000000329

• Variant calling from CC220-MM-001 cohorts A,B,D

  These are genomic and transcriptomic high risk molecular segments for 167 samples collected at baseline from deidentified patients enrolled in cohorts A,B or D in the CC-220-MM-001 clinical study. Data are provided in a patient call table in csv format. Calls are generated from WGS data with mutations called by mutect2 best practices pipeline, CNV calls from Battenberg; and RNA-seq aligned with star aligner and quantified by Salmon.

  Dataset EGAD50000000388