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• Arcagen - NET / NEC G3

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here were are submitting the dataset that contains NGS files in .BAM format from 85 patients with extra-pulmonary neuroendocrine tumour or cancer grade 3 (NET / NEC G3).

  Dataset EGAD50000000913

• DAC for human-derived clonal organoid studies

  This is the DAC for human-derived clonal organoid culture studies. It includes the study to investigate the clonal evolution of metastatic CRC at the single-cell level, where we performed WGS in 58 clonal organoids and 18 fresh-frozen (FT) bulk-tissue samples from surgically resected primary and metastatic tumors before and after anticancer therapies in 6 patients. This approach enabled detailed phylogenetic reconstruction of individual clones. We discovered the timing and burden of treatment-related mutations as well as the heterogeneous evolution in driver mutations and genomic rearrangements in late-stage clonal evolution under anticancer therapies in metastatic CRC.

  Dac EGAC50000000628

• Investigating the genetics of immunity against Salmonella in humans (2019-09-05)

  This study entails whole genome sequencing of an interleukin (IL)-12 b-1 receptor-deficient individual who presented with a chronic systemic Salmonella Enteritidis infection that did not resolve with standard IFNg and antibiotic treatment. Whole genome sequencing of the patient's parents are also included. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-09-05.

  Dataset EGAD00001005311

• TARGET-seq+ single-cell transcriptome sequencing

  Single-cell whole transcriptome sequencing data for bone marrow samples from 9 cases with clonal hematopoiesis and 4 control samples. The TARGET-seq+ protocol was used to generate plate-based 3' transcriptome data. For details on cell sorting and the TARGET-seq+ protocol see the methods section of the manuscript. One FASTQ file is provided per cell. Cells are named with their plate and well IDs and the subject ID. Empty wells (no-cell controls) are named "blank". Corresponding genotyping files use the same naming without the "_transcriptome" suffix.

  Dataset EGAD00001011175

• The British Autozygosity Populations BioResource (2019-08-14)

  This data set contains whole exome sequences of individuals with self-stated parental relatedness from the East London Genes & Health cohort. Rare frequency functional variants in these healthy individuals will be studied with respect to the genetic health of the participants and loss-of-function analysis of human genes. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005253

• Exploring the heterogeneity of sarcoma using single cell sequencing

  Multi region samples are collected from patients, with consent, immediately after resection of the tumour. Samples are digested and sorted using FACS as single cells into lysis buffer. Cells are then stored until further processing for G&T-seq. After sequencing, we will explore intra-tumour heterogeneity using computational approaches to integrate RNA and DNA data onto the tumour phylogeny This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ .

  Dataset EGAD00001006786

• Metabolic context regulates the competitive fitness of oncogenic PIK3CA mutant clones in the normal esophagus

  Activating mutations in PIK3CA generate large clones in the aging human esophagus. Here we investigate the underlying cellular mechanisms regulating their expansion by lineage tracing. Expression of an activating heterozygous Pik3caH1047R mutation in single progenitor cells of the mouse esophagus tilts cell fate towards proliferation, generating mutant clones that outcompete their wild type neighbours. The mutation leads to increased aerobic glycolysis through the activation of Hif1α transcriptional targets. In vitro and in vivo interventions that level out differences in activation of the PI3K/HIF1α/aerobic glycolysis axis between wild type and Pik3caH1047R cells attenuate the competitive advantage of the mutants. In contrast, metabolic conditions that alter Insulin/PI3K signalling, such as type-1 diabetes or diet-induced insulin resistance, further increase Pik3caH1047R mutant competitiveness in mice. Consistently, the density of activating PIK3CA mutations in human esophagus is increased in overweight individuals. We conclude that the metabolic environment influences the mutational landscape of normal epithelia. Clinically feasible interventions that even out signalling imbalances between wild type and mutant cells may therefore limit the expansion of oncogenic mutants in normal tissues.

  Dataset EGAD00001008281

• Cell-type eQTLs for single-cell Mendelian Randomisation

  The following study mapped eQTLs in the post-mortem human brain from snRNA-seq generated on 391 individuals. Following eQTL discovery and identification of state-specific eQTLs (dynamic associations interacting with disease), colocalisation and MR was performed integrating GWAS from 42 traits, for the identification of putatively causal genes with cell-type specific context. This study contains raw sequencing data and genotype for two datasets used in this work; - The MRC 60 dataset, which contains snRNA-seq generated on post-mortem brain from 60 control individuals (104 samples total, split across prefrontal cortex and hippocampus). Samples were pooled into 27 distinct pools, each of which was split across 4 lanes. Following sequencing and mapping using cellranger, demultiplexing was done using Demuxlet using the pool-specific genotype data (which contain sample IDs). - The Roche PD dataset, which is 10X multiome data generated on on 70 PD and 22 control individuals.

  Study EGAS50000000687

• A clinically applicable connectivity signature for glioblastoma includes the tumor network driver CHI3L1

  Tumor microtubes (TMs) connect glioma cells to a network with considerable relevance for tumor progression and therapy resistance. The determination of TM-interconnectivity in individual tumors has been challenging and the impact on patient survival unresolved. Here, a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells has been established using a dye uptake methodology, confirmed with recording of cellular calcium epochs and validated with clinical correlations. Astrocyte-like and mesenchymal-like GB cells have the highest connectivity signature scores in scRNA-sequenced patient-derived xenografts and patient samples. In large GB cohorts, network connectivity correlated with the mesenchymal subtype and dismal patient survival. CHI3L1 has been identified and validated as a robust molecular marker of connectivity with functional relevance. The connectivity signature allows novel insights into brain tumor biology, provides a proof-of-principle that tumor cell TM-connectivity is relevant for patients’ prognosis, and serves as a robust prognostic biomarker.

  Study EGAS00001007611

• Metformin for Oral Cancer Prevention

  The M4OC-PREVENT clinical trial addressed whether metformin has utility in the prevention of oral cancer. It is a phase IIa clinical trial of metformin ER 2,000 mg per day given for 12-14 weeks to individuals with oral premalignant lesions, either oral leukoplakia or erythroplakia (which are precursors to oral cancer). The goal was to determine if metformin decreases the size of oral leukoplakia (clinical response). Additionally, effects on biomarkers of cancer risk and metformin effect were ascertained. The clinical trial was performed at the University of California San Diego Moores Cancer Center, the University of Minnesota, and the British Columbia Cancer Agency, with monitoring and oversight provided by the University of Arizona.

  Study phs002437