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• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__head___neck

  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. Non-tumour DNA is also studied for some cancer types. 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 EGAS00001005450

• Characterization of CNS Metastases

  Metastatic disease to the central nervous system (CNS) is devastating, with a poor prognosis. There are limited treatment options for patients with CNS metastases, and in particular with leptomeningeal carcinomatosis (LMD). In this study, we evaluated the molecular and cellular features of parenchymal brain metastases and LMD. We used single-cell RNA and cell-free DNA profiling of CSF from patients with LMD receiving immunotherapy to demonstrate shifts in the liquid LMD tumor microenvironment. We also characterize the tumor microenvironment of parenchymal brain metastases using single cell sequencing, before and after treatment with immunotherapy.

  Study phs002416

• Korean WGS

  We sequenced the genomes of 141 Korean never-smoker lung adenocarcinoma patients, excluding EGFR and ALK alterations. We utilized the TruSeq DNA Library Prep Kit and performed by the Illumina NovaSeq 6000 instrument, yielding sequencing paired reads of approximately 150 bp in size. Afterward, we processed the FASTQ files using the GATK Best Practice pipeline.

  Dataset EGAD50000000346

• MINCR is a MYC-induced lncRNA able to modulate MYC’s transcriptional network in Burkitt lymphoma cells

  Despite the established role of the transcription factor MYC in cancer, little is known about the impact of a new class of transcriptional regulators, the long non-coding RNAs (lncRNAs), on the way MYC is able to influence cellular transcriptome. To this aim we have intersected RNA-sequencing data from two MYC-inducible cell lines and from a cohort of 91 mature B-cell lymphomas carrying, or not carrying, genetic variants resulting in MYC over-expression. By this approach, we identified 13 lncRNAs differentially expressed in IG-MYC-positive Burkitt lymphoma and regulated in the same direction by MYC in the model cell lines. Among them we focused on a lncRNA that we named MINCR, for MYC-Induced long Non-Coding RNA, showing a strong correlation with MYC expression in MYC-positive lymphomas and also in pancreatic ductal adenocarcinomas. To understand its cellular role we performed RNA interference (RNAi) experiments and found that MINCR knock-down is associated with a reduction in cellular viability, due to an impairment in cell cycle progression. Differential gene expression analysis following RNAi showed a strongly significant enrichment of cell cycle genes among the genes down-regulate following MINCR knock-down. Interestingly these genes are enriched in MYC binding sites in their promoters, suggesting that MINCR acts as a modulator of MYC transcriptional program. Accordingly, following MINCR knock-down, we observed a reduction in the binding of MYC to the promoters of selected cell cycle genes. Finally we provide evidences that down-regulation of AURKA, AURKB and CTD1 may explain the reduction in cellular proliferation observed upon MINCR knock-down. We therefore suggest that MINCR is a newly identified player in the MYC transcriptional network able to control the expression of cell cycle genes.

  Dataset EGAD00001001441

• 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

• NeoRhea Bulk RNA and Single nuclei RNA & ATAC

  The aim of this study is to compare baseline and surgery samples of ER+/HER2- early breast cancer patients. Patients have been treated with endocrine therapy in combination with palbociclib. Samples have been collected pre and post treatment.

  Study EGAS50000001403

• COVID-19 Postmortem Lung snRNA-seq

  A deeper understanding of the pathological mechanisms of SARS-CoV-2 infection is required to combat COVID-19. Through this dataset, we analyze postmortem lung cells from patients that are infected/uninfected with SARS-CoV-2 with snRNA-seq.

  Study EGAS00001004689

• CSER: Clinical Implementation of Carrier Testing Using Next Generation Sequencing (NextGen)

  We will investigate the clinical implementation of genome sequencing (GS) for carrier screening to aid reproductive decision-making in adults. The study is organized into three inter-related Projects. The study population will include women and their partners who receive pre-conception testing. In Project 1, we will conduct a Randomized Clinical Trial to test clinical implementation of WGS compared with usual care. We will integrate WGS results with the electronic medical record (EMR), and measure outcomes from patient and physician perspectives. In Project 2, we will perform whole genome sequencing, including validation and interpretation of the identified variants to identify "actionable variants", meaning variants deemed worthy of reporting. This will include a robust approach using a Return of Results Committee (RORC) for determination of reportable results. In Project 3, we will evaluate the ethical and psychosocial implications of expanded carrier screening using WGS for the return of carrier status and secondary findings, and measure the impact on downstream healthcare utilization and cost. Two groups of women are identified through the electronic medical record. The first group has a clinical carrier screening test, usually Cystic Fibrosis (CF), ordered and completed as part of a preconception planning visit. The second group has a carrier screening test, usually CF, performed during pregnancy, they have delivered their baby and are planning a future pregnancy. Eligible women are randomized to either usual care or genome sequencing (GS). Women randomized into the usual care arm have already received their clinical genetic test. These women will not receive genome sequencing. Women in the GS arm will receive their carrier status results for about 700 gene/condition pairs approximately three months after randomization. If there are results to return, women come in for a genetic counseling session. If there are no results, a letter is sent in the mail. Incidental findings (IF) are returned about one month later. As with the carrier status results, all IF are returned in person, and if there are no results a letter is sent in the mail. If a participant is found to be a carrier of an autosomal recessive condition, her male partner is then eligible and invited to participate in the study and receive GS.

  Study phs000927

• Introducing Federated EGA Affiliates: a newly defined tier in the Federated EGA Network

  We're happy to announce that we are now accepting Affiliates in the Federated EGA Network! Federated EGA is a global network of repositories enabling secure discovery and access to sensitive human data. Currently, Federated EGA consists of Central EGA (CEGA), which serves the global community, and nine national Nodes that serve respective jurisdictions. Did you know that the Federated EGA (FEGA) has always envisioned a third tier within the network? This brings us to FEGA Affiliates, recently defined in the newly approved "Federated EGA Structure and Organisation" document. This new tier broadens the range of institutions or organisations that can become part of FEGA. Thus begins a new era for the network. What is a FEGA Affiliate? A FEGA Affiliate archives and serves controlled-access data within its own governance scope, while still participating in federated discovery through the EGA catalogue. Affiliates can be individual organisations or institutions, healthcare genomics initiatives, consortia of institutions, as well as project-specific consortia (national or international). In practical terms, a FEGA Affiliate: Hosts and safeguards the data it archives. Submits non-personal metadata to CEGA so studies are discoverable and can receive EGA accessions. Manages permissions and data access workflows for its datasets. Provides data access and/or distribution, along with support, to authorised users. Key takeaways about FEGA Affiliates FEGA is now organised into three tiers: CEGA, FEGA Nodes, and FEGA Affiliates. Affiliates archive data from their own organisation and/or selected partner institutions (for example, an international consortium). Affiliates make studies discoverable through the EGA catalogue by submitting non-personal metadata for accessioning. Access decisions and conditions are managed locally by the Affiliate (e.g. distribution or access in a trusted research environment). Are you considering whether your institution or project might be a good fit as a FEGA Affiliate? Would you like to learn more about this tier? We have published a blog post that addresses potential common questions, providing answers on this topic. You can read it here.

  Blog fega-affiliates

• A Clone's Genomic Stability as a Biomarker of Its DNA-Damage Resilience

  A main problem in the treatment of advanced cancers, including gastric cancers and glioblastoma, is the incertitude at which we predict how individual patients will respond to DNA-damaging agents, especially on the long run. Knowing the mechanism behind a patient's response, or the lack thereof, will help us depart from the oversimplified “more-is-better” and “one-size-fits-all” principles according to which DNA-damaging agents are administered. This will improve clinical outcome by allowing us to pinpoint those who would respond better and longer to lower doses than to higher doses of DNA-damaging agents. Under the assumption that the success of DNA-damaging therapy increases with the proliferation rate of a relatively homogeneous tumor population, there was little reason to assume anything other than monotonic dose-response relations. With the recent paradigm shift that most cancers are in fact DNA mosaic products of ongoing evolution, comes the urgency to reconsider these fundamental principles behind DNA-damaging therapy administration. As the developers of one of the first DNA deconvolution methods and with access to technologies to profile the transcriptomes of up to 10,000 cells simultaneously, we are equipped to embark on first personalized dose-finding strategies for DNA-damaging therapies. We will test the potential of the very long-term legacy that DNA-damage entails on a cell “genomic instability” as new biomarker of DNA-damage response. Our preliminary studies showed that, for most cancer types, DNA-damaging agents change a clone's genomic instability and that clones succumb to a limit in the amount of genomic instability they can tolerate. In particular, our results showed that patients with intermediate genomic instability have a very poor outcome and that this relation is only evident among treatment-naive patients, but not among patients treated with DNA-damaging agents. Further they show that we can measure genomic instability per clone and that clones with extreme genomic instability typically don't grow large. Our hypothesis that genomic instability, rather than proliferation rate, determines how sensitive a tumor is to DNA-damaging agents on the long-term, is founded on two unexpected findings. Patients with extremely high genomic instability per tumor clone have an exceptionally good outcome. Aim 1 will integrate exome- and single cell RNA-Seq (scRNA-Seq) data to characterize clones and to measure how much genomic instability they can tolerate. Low genomic instability is associated with reduced benefit from DNA-damaging agents. Aim 2 will use comet assays and treatment history to quantify DNA damage per clone, relating it to the clones' ability to tolerate DNA damage and to changes in the genomic instability of therapy-surviving clones.

  Study phs003762