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• PSCP_bisulphite analysis in hESCs

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. 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 EGAD00001002235

• Swarm Learning to identify COVID-19, tuberculosis and leukemia patients based on blood transcriptomes

  Identification of patients with life-threatening diseases including leukemias or infections such as tuberculosis or COVID-19 is an important goal of modern precision medicine. However, there is an increasing divide between what is technically possible and what is allowed because of privacy legislation. We have recently illustrated that classical machine learning can identify leukemia patients based on their blood transcriptomes. To facilitate integration of any omics data from any data owner world-wide without violating privacy laws, we here introduce Swarm Learning (SL), a decentralized machine learning approach uniting edge computing, artificial intelligence (AI), blockchain and privacy protection without the need for a central coordinator thereby going beyond federated learning. To illustrate its feasibility, using more than 12,000 transcriptomes from peripheral blood mononuclear cells and more than 2,000 peripheral blood transcriptomes we demonstrate that SL of omics data distributed across different individual sites leads to disease classifiers that outperform those developed at individual sites. Yet, SL completely protects local privacy regulations by design. We propose this approach to noticeably accelerate the introduction of precision medicine.

  Dataset EGAD00001006231

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__clear_cell_renal_cell_carcinoma

  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. 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.

  Study EGAS00001002608

• Clinical outcomes and immune correlates of response to nivolumab plus chemoradiotherapy in women with locally-advanced cervical cancer – NiCOL study

  Concurrent chemoradiotherapy (CRT) with blockade of the PD-1 pathway may enhance immune-mediated tumor control through increased phagocytosis, cell death, and antigen presentation. The NiCOL phase 1 trial was designed to determine safety, tolerance, and immune correlates of response to the PD-1 blocking antibody, nivolumab, with and following concurrent CRT in 16 women with locally advanced cervical cancer (LACC). Three patients experienced grade 3 dose-limiting toxicities. The overall response rate was 93.8% [95%CI: 69.8%-99.8%] with a 2-year PFS of 75% [95% CI: 56.5%-99.5%]. Compared to patients with progressive disease (PD), progression-free (PF) subjects showed a brisker stromal immune infiltrate, higher proximity of tumor-infiltrating CD3+ T cells to PD-L1+ tumor cells and of Foxp3+ T cells to proliferating CD11c+ myeloid cells. PF had higher baseline levels of PD-1 on EMRA CD4+ T cells and ICOS-L on tumor-associated macrophages (TAMs) vs PD, which instead displayed enhanced PD-L1 expression on TAMs and higher, circulating frequencies of proliferating Tregs at baseline. Concomitant nivolumab plus definitive CRT is safe and associated with encouraging PFS rates. Further validation in the subset of LACC displaying pre-existing, adaptive immune activation is warranted.

  Study EGAS00001007297

• Loss of astrocytic markers and impaired metabolic function in spinocerebellar ataxia type 7 patient-derived neural cultures

  Spinocerebellar ataxia type 7 (SCA7) is a rare neurodegenerative disorder caused by a CAG repeat expansion in the ATXN7 gene. This repeat expansion results in an abnormally long polyglutamine (PolyQ) tract in the Ataxin-7 protein. This ultimately leads to the degeneration of most notably Purkinje cells and retinal cells. Because no treatment exist that can halt or slow disease progression, there is a critical need for patient-specific disease models to uncover new pathogenic mechanisms and enable therapeutic testing. In this study, induced human pluripotent stem cells (hiPSCs) derived from healthy controls and individuals with SCA7 were differentiated into a mixed neural cell population consisting of neurons and astrocytes. Although control and SCA7 neurons appeared morphologically similar, SCA7-derived astrocytes exhibited a pronounced loss of the astrocyte-specific markers GFAP and S100B. Transcriptome analysis revealed substantial alterations in genes related to glial differentiation, cellular metabolism and oxygen handling, protein homeostasis, and neuronal differentiation and neuronal signaling. Mitochondrial stress assays further confirmed a mitochondrial phenotype in SCA7 neural cells. Together, these findings demonstrate that hiPSC-derived neural cells provide a robust platform that can be used for studying disease mechanisms and testing potential therapies for SCA7.

  Study EGAS50000001869

• Netherlands Cancer Institute (NKI-AVL) general DAC

  Data is available under reasonable request. All data requests will be reviewed by the NKI IRB and must be supported by the Principal Investigator of the study. The researcher will need to sign a data access agreement with the NKI after approval. Go to https://ega.nki.nl to fill out the form to request access.

  Dac EGAC50000000055

• Flexible and rapid validation of structural variants using adaptive sampling

  This is the DAC that oversees the application and approval process for access to the Oxford Nanopore fastq files associated with the study, "Flexible and rapid validation of structural variants using adaptive sampling". The DAC members include Dr. Stephen W. Scherer (swscherer@sickkids.ca) and Dr. Lars Feuk (lars.feuk@igp.uu.se).

  Dac EGAC50000000748

• The life-saving benefit of dexamethasone in severe COVID-19 is linked to a reversal of monocyte dysregulation

  Assessment of dexamethasone response in human lung through scRNA-seq analysis of bronchoalveolar lavage (BAL) samples from patients with severe COVID-19.

  Study EGAS50000000203

• Dataset of Recurrent resistance mutations to lirafugratinib delineate treatment sequences for FGFR2-driven tumors

  This dataset is made of 23 pairs of RNAseq and 36 pairs of Exome-seq, both sequenced from Illumina Novaseq. This includes 47 samples, composed of 25 tumors, 13 healthy and 9 xenograft

  Dataset EGAD50000001981

• Bulk RNASeq of metastatic colorectal cancer organoids with ATOH1 knockout

  Bulk RNA sequencing was performed on mCRC organoids subjected to cetuximab treatment, comparing ATOH1 knockout and control conditions. The dataset is intended to elucidate the contribution of ATOH1-regulated secretory cell population to cetuximab persistence mechanisms.

  Dataset EGAD50000002060