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• Leukemic evolution of donor-derived cells harboring IDH2 and DNMT3A mutations after allogeneic stem cell transplantation

  An individual with acute myeloid leukemia (AML) received peripheral blood stem cell (PBSC) transplantation, but later experienced relapse. Whole-exome sequencing of bone marrow cells obtained from different stages of this patient as well as PBSC of the donor revealed that relapsed AML was not the regrowth of the original leukemic clones, but donor cell leukemia (DCL). Interestingly, some of the oncogenic mutations found in DCL were already present at a low frequency in the donor PBSC. Target deep sequencing of these genes indeed confirmed this observation, and revealed that the emergence of additional oncogenic mutations triggered leukemic evolution.

  Study JGAS000017

• Tracing the molecular route to progression in miRNA biogenesis-defective thyroid lesions

  Alterations in the DICER1 and DGCR8 microprocessor genes confer risk to the development of benign and malignant thyroid lesions. The involvement of 2 miRNA biogenesis genes in benign and malignant thyroid tumors highlights the key role of miRNAs in the thyroid gland. We traced the progression from benignity to malignancy in DICER1- and DGCR8-mutated thyroid lesions by performing a multiomic characterization of these lesions aiming to uncover unique features characterizing either form for potential use as biomarkers. This multiomic characterization included whole exome sequencing (WES) (N=18), miRNA profiling (N=38), spatial transcriptomics (N=2) and/or methylome (N=281).

  Study EGAS50000001577

• The EGA joins EUCAIM, the European project powering AI and imaging in cancer research

  EUCAIM (EUropean Federation for CAncer IMages) is the cornerstone of the European Cancer Imaging Initiative, one of the flagships of the Europe’s Beating Cancer Plan (EBCP). The European Genome-Phenome Archive (EGA), as member of the EUCAIM consortium, attended the kick-off meeting organized this week in Brussels for the launch of the Initiative. The EGA will contribute to the project with the experience gained in the deployment of our federated network, the Federated EGA (FEGA), and the experience gained as partners of EuCanImage (AI4HI initiative) contributing to the definition of common data models, ontologies and data standards. The ultimate goal of the project is to unlock the power of imaging and Artificial Intelligence for the benefit of cancer patients, clinicians and researchers. The consortium will deploy a pan-European digital federated infrastructure hosting cancer-related images, and associated pathology, molecular and laboratory data from Real-World. This endeavour will provide a comprehensive dashboard for imaging data discovery, federated search, metadata harvesting, annotation and distributed data processing. EUCAIM joins 76 partners, gathering the experience and previous effort made by the different repositories of the AI4HI initiative, European Research Infrastructures and national/regional repositories. Find out more information about the EUCAIM launch here

  Blog the-ega-joins-eucaim

• scRNAseq analysis of CD8 T cells infiltrating the bladder and tumor of 4 non-muscle-invasive bladder cancer patients, before and after BCG treatment.

  We performed scRNAseq analysis of CD8 T cells infiltrating the bladder and tumor of 4 non-muscle-invasive bladder cancer patients, before and after BCG treatment. In order to identify tumor-specific T cells, we selected CD8 T cells that were enriched in the tumor of the patient. We also selected CD8 T cells appearing in the bladder after BCG treatment, with the hypothesis that BCG treatment stimulates tumor-specific CD8 T cells. Next, we cloned the TCR of these T cells in a Jurkat cell line and tested these TCR for recognition of tumor-specific antigens.

  Study EGAS50000001384

• Whole genome sequencing data of paediatric T cell acute lymphoblastic leukemia (T-ALL)

  T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic malignancy accounting for approximately 15–25% of pediatric and adult ALL cases. Despite significant therapeutic improvements over the last decade, the prognosis of T-ALL remains less favorable than that of B-ALL, with 5-year EFS and OS of around 76–82% and 80–88%, respectively, depending on the treatment protocol used. T-ALL patients often suffer from failure of induction therapy or early relapse, which is associated with a dismal prognosis. Approximately 10–15% of T-ALL patients experience relapse, and survival after relapse is poor.

  Study EGAS50000001387

• Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks

  The identification of functional non-coding mutations is a key challenge in the field of genomics. Here we introduce μ-cisTarget to filter, annotate and prioritize cis-regulatory mutations based on their putative effect on the underlying ‘personal’ gene regulatory network. We validated μ-cisTarget by re-analyzing the TAL1 and LMO1 enhancer mutations in T-ALL, and the TERT promoter mutation in melanoma. Next, we re-sequenced the full genome of ten cancer cell lines and used matched transcriptome data and motif discovery to identify master regulators with de novo binding sites that result in the up-regulation of nearby oncogenic drivers.

  Study EGAS00001002571

• Feasibility Study to Identify the Optimal Adjuvant Combination Scheme of Ipilimumab and Nivolumab (OpACIN) in resectable stage III melanoma patients

  OpACIN is a feasibility study including 20 patients with palpable stage III melanoma that were 1:1 randomized to receive ipilimumab 3mg/kg and nivolumab 1mg/kg, either 4 courses after surgery (adjuvant arm), or 2 courses prior to surgery and 2 courses post-surgery (neoadjuvant arm). WES and RNA-seq was performed on baseline biopsy material and correlated with outcome of the patients (relapse free survival). TCRseq from baseline tumor samples was used to analyse the top 100 tumor resident clones and analyse their change in PBMC comparing baseline versus week 6 of immunotherapy.

  Study EGAS00001003099

• MutWP5__CRUK_Mutographs_of_Cancer__Lung__PD43291_Novaseq__WG_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from lung tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will deeply sample from individuals with smoking-related lung diseases (COPD, pulmonary fibrosis, lung cancer) and those without smoking history. This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003502

• Multi-omics analysis of cocaine use disorder in postmortem brain tissue of the ventral striatum [Proteomics data to study EGAS50000000623]

  We performed a multi-omics analysis of cocaine use disorder in postmortem human brain tissue of the ventral striatum in N=41 individuals (N=20 CUD cases, N=21 non-affected individuals). From the postmortem brain tissue samples, we generated miRNA-seq, RNA-seq, proteomics, and snRNA-seq data. The miRNA-seq, RNA-seq and snRNA-seq datasets can be found in the EGA under study ID EGAS50000000623. Proteomics data is deposited under study ID EGAS00001007945 (this study). The proteomic dataset was obtained using TMT-labeling. Measurement was performed on an Orbitrap Fusion Lumos device.

  Study EGAS00001007945

• Targeted sequencing of follicular lymphoma tumour samples from the UK's Haematological Malignancy Research Network

  Follicular lymphoma displays morphological and clinical heterogeneity, underpinned by shared molecular pathogenesis. Mutations in epigenetic regulators alongside t(14;18) have been identified as disease initiating events. Additional mutational diversity suggests disease heterogeneity. Whether this resolves into mechanistically distinct subsets remains an open question. Targeted sequencing was applied to an unselected population-based FL cohort (n=548) diagnosed in a catchment population of ~4 million (14 centers), with full clinical follow-up (n=538) that included 96 DLBCL transformations. We investigated whether molecular subclusters of FL can be identified, and whether mutational data provide predictive information relating to transformation.

  Study EGAS00001005238