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• Hyperdiploidy impairs fetal hematopoietic progenitor cell fitness and differentiation enabling persistence of rare preleukemic aneuploid clones

  Cells previously cryopreserved in FBS-10%DMSO were thawed and resuspended in 1mL of cold lysis buffer (10 mM Tris-HCl pH 7.4, 154 mM NaCl, 0.2% BSA, 0.1% NP-40, 1 mM CaCl₂, 0.5 mM MgCl₂ in ultra-pure water) to lyse the cell membrane and release intact nuclei. The nuclei were stained with propidium iodide (10 µg/mL) and Hoechst 33258 (10µg/mL) to facilitate sorting based on cell cycle state and viability. Single nuclei from 48 cells per sample were isolated into 96-well plates containing 5µL of freeze buffer (1X PBS, 7.5% DMSO, and 40% ProFreeze freezing medium (Lonza)) using a MoFlo Astrios cell sorter (Beckman Coulter) at the Flow Cytometry Unit of the University Medical Center Groningen (UMCG), Netherlands. The plates were centrifuged at 500 g and stored at -80°C until library preparation. Single-nuclei libraries were prepared using a Bravo Automated Liquid Handling Platform (Agilent Technologies). Nuclei were lysed, and DNA was labelled with unique 10 bp dual barcodes and amplified as previously described. Sequencing was performed on an Illumina NextSeq 2000 platform with 77bp single end reads. The generated data were subsequently demultiplexed using sample-specific barcodes and converted to FASTQ files with bcl2fastq. Sequencing reads were aligned to the GRCh38/hg38 human reference genome using Bowtie2 (v2.2.4), and duplicate reads were marked with BamUtil (v1.0.3). Single-cell karyotypes were determined by performing copy number analysis using AneuFinder (v4.3.3) (https://github.com/ataudt/aneufinder). The analysis included GC-content correction and blacklisting of artifact regions identified from euploid controls. Copy number calling was conducted with the dnacopy and edivisive algorithms, employing a bin size of 1 Mb and a step size of 500 Kb. Libraries with an average of fewer than 10 reads per chromosome copy per bin or less than 95% concordance between the two algorithms were excluded from analysis. Whole-chromosome aneuploidies were identified when over 95% of bins exhibited deviation from the disomic state. Aneuploidy scores were calculated as weighted averages of absolute copy number deviations from the euploid state. 

  Dataset EGAD50000002314

• Data upcycling, powered by EGA

  In 2012 a collaborative effort headed by the teams of Carlos Caldas in Cambridge, UK and Samuel Aparicio, Canada, produced a pivotal study aimed at defining the mutational landscape of breast cancer. They gathered a collection of over 2000 breast cancer samples (METABRIC) associated with long-term clinical follow-up. They delineated an array of inherited and somatically acquired genetic variants and associated them to gene expression. This led to the identification of putative cancer-driving events and improved stratification of breast cancer patients. The study elicited huge attention and was tackled as herculean effort by fellow researchers. Cristina Curtis and her colleagues deposited the data in the EGA archive (EGAS00000000083). What they probably could not foresee is that their data would be reused more than 100 times, becoming one of the most downloaded datasets at EGA. In 2015, Frederik S. Varn and colleagues accessed the above-mentioned data from the New Hampshire, USA, to correlate it to transcriptional programs of hematopoietic cells infiltrated in breast tumours and found that those can influence patients' prognosis. Their findings, published in Nature Communications, improved the understanding of the interplay between immune system and cancer. Again, in 2017 the dataset was downloaded by an Italian/Polish collaboration and used to corroborate their mechanistic study that demonstrate how a long non-coding RNA (lncRNA) is aberrantly localized into the chromatin, where it modulates oncogenic isoforms expression, thus contributing to breast cancer. To date, the METABRIC dataset has been reused to contribute to 147 publications. Its impact on breast cancer research is incalculable, and it even spread beyond that, with recent contributions to the understanding of pan-cancer mechanisms and features. Some of the publications are translating into improvements in diagnosis and treatment of different types of breast cancer. This is just an example of how data upcycling can amplify the potential of any dataset, well past the scope of its creation, the imagination of its owners and any geographical border. At EGA, we are proud to empower such fruitful worldwide cycles of knowledge, providing a platform that enables safe sharing of sensitive genetic data.

  Blog data-upcycling-powered-by-ega

• Fragmentomics Uncover Non-Mutational HRD Features

  Homologous recombination deficiency (HRD) is a key biomarker in prostate cancer (PCa), predicting response to PARP inhibitors and platinum-based therapies. However, current diagnostics often rely solely on BRCA1/2 mutations or genomic scars, missing cases driven by other mechanisms. Tissue-based testing is further limited by tumor heterogeneity and biopsy challenges in metastatic bone disease. Here, we applied a comprehensive multimodal approach to assess HRD in 106 advanced PCa patients using circulating tumor DNA (ctDNA). This included targeted sequencing of homologous recombination repair (HRR) genes, low-pass WGS for genomic instability (sHRD), WES for mutational signatures, and cfDNA fragmentomics and chromatin accessibility profiling. BRCA2 was the most frequently altered gene, often co-occurring with PTEN loss. High sHRD scores correlated with BRCA2/RB1 loss, somatic copy number alterations, and poor survival. HRD tumors showed enrichment of SBS3/ID6 signatures, altered fragment lengths, and reduced accessibility at zinc finger transcription factor sites. These results support ctDNA-based multimodal profiling as a non-invasive strategy for HRD detection and stratification.

  Study EGAS00001008190

• Liverpool Preterm Birth Biomarker Study

  Preterm birth is a multifactorial condition defined as birth less than 37 weeks of gestation. This study aimed to identify early pregnancy biomarkers from maternal genome-wide and transcriptome-wide data of women experiencing two types of spontaneous PTB (sPTB): spontaneous preterm birth (SPTB) and preterm premature rupture of membranes (PPROM). Whole blood samples were obtained from women with singleton pregnancies (N=567) recruited at the Liverpool Women’s Hospital at 16 and 20 weeks of gestation. Women with a previous history of sPTB pregnancies <34 weeks were categorised on their index pregnancy outcome as spontaneous preterm birth (SPTB) and preterm premature rupture of membranes (PPROM) or high-risk term control (HTERM, ≥37 weeks). Women with no history of SPTB/PPROM and delivered at term were LTERM (≥39 weeks of gestation). DNA was genotyped on the UK Biobank Axiom™ array (Applied Biosystems™, Thermo Fisher Scientific) and RNA who processed using the Clariom™ D Human assay (Thermo Fisher Scientific). Genome-wide association analysis, differential expression analysis and expression quantitative trait loci (eQTL) were completed.

  Study EGAS00001005076

• DNA methylation atlas of normal human cell types

  DNA methylation is a fundamental epigenetic mark that governs chromatin organization, cell identity, and gene expression. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell-type are >99.5% identical, demonstrating robustness of cell identity programs to genetic variation and environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny, and identifies methylation patterns retained since gastrulation. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hyper-methylated loci are rare and are enriched for CpG islands, polycomb targets, and CTCF binding sites, suggesting a novel role in shaping cell type-specific chromatin looping. The atlas provides an essential resource for interpretation of disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies.

  Study EGAS00001006791

• Genomes of Relapsing Neuroblastoma

  Neuroblastoma is a malignancy of the developing sympathetic nervous system that is often lethal when relapse occurs, but the molecular mechanisms behind this process are poorly defined. We here used whole-exome sequencing, mRNA expression, array CGH and DNA methylation analysis to holistically characterize 16 paired samples from neuroblastoma patients at diagnosis and relapse. The mutational burden significantly increased in relapsing tumors accompanied by altered mutational signatures and reduced subclonal heterogeneity. Global allele frequencies at relapse indicated clonal mutation selection during disease progression. Promoter methylation patterns were consistent over disease course and patient-specific. Recurrent alterations at relapse included mutations in the putative CHD5 neuroblastoma tumor suppressor, chromosome 9p losses, DOCK8 mutations, inactivating mutations in PTPN14 and a relapse-specific activity pattern for the PTPN14 target gene, YAP. Recurrent new mutations in HRAS, KRAS, DOCK8 and genes mediating cell-cell interaction in 13/16 relapse tumors also indicate disturbances in signaling pathways mediating mesenchymal transition. Our data shed first light on genetic alteration frequency, identity and evolution in neuroblastoma.

  Study EGAS00001001387

• MED12L Gene Alterations Define Aggressive BRCA2-Mutant Prostate Cancers

  Germline mutation of BRCA2 increases the lifetime risk of developing prostate cancer (PCa) by over 700%. BRCA2-mutant PCa have poorer prognosis than sporadic PCa, with rapid development of metastatic, castrate-resistant prostate cancer (mCRPC) and 5-year cancer-specific survival rates of ~50-60%1-4. Despite this, unique genomic driver events that explain the aggressiveness of localized BRCA2-mutant PCa are lacking. We used whole-genome sequencing to fully characterize 14 BRCA2-mutant PCa and demonstrate that BRCA2-mutant PCa is associated with increased genetic instability and a mutually exclusive mutational burden when compared to sporadic PCa. Importantly, BRCA2-mutated cancers are defined by unique copy number gains and hypomethylation events, including alterations in the MED12L/MED12 axis, which are found solely in mCRPC and are enriched in PCa tumours harbouring aggressive intraductal carcinoma (IDC-P) pathologic sub-types. Our findings begin to explain the clinical entity of BRCA2-mutated PCa as these tumours have a unique and aggressive genotype de novo, associated with IDC-P and mCRPC, even in the hormone-naive setting.

  Study EGAS00001001615

• Mutant KIT as imatinib-sensitive target in metastatic sinonasal carcinoma (H021)

  Sinonasal carcinomas (SNCs) comprise various rare tumor types that are characterized by marked histologic diversity and largely unknown molecular profiles, yet share an overall poor prognosis owing to an aggressive clinical course and frequent late-stage diagnosis. The lack of effective systemic therapies for locally advanced or metastatic SNC poses a major challenge to therapeutic decision making for individual patients. Here, we used whole-exome and transcriptome sequencing to identify a KIT exon 11 mutation (c.1733_1735del, p.578_579del) as actionable target in a patient with metastatic SNC whose tumor, despite all diagnostic efforts, could not be assigned to any known SNC category and was refractory to multimodal therapy. Molecularly guided treatment with imatinib resulted in a dramatic and durable response with remission of nearly all tumor manifestations, indicating a dominant driver function of mutant KIT in this tumor. This observation highlights the potential of unbiased genomic profiling for uncovering the vulnerabilities of individual malignancies, particularly in rare and unclassifiable tumors, and underscores that KIT exon 11 mutations represent tractable therapeutic targets across different histologies.H021

  Study EGAS00001001845

• Scalable whole-genome single-cell library preparation without pre-amplification

  Single-cell genomics is critical for understanding cellular heterogeneity in cancer, but existing library preparation methods are expensive, require sample preamplification and introduce coverage bias. Here we describe direct library preparation (DLP), a robust, scalable, and high-fidelity method that uses nanoliter-volume transposition reactions for single-cell whole-genome library preparation without preamplification. We examined 782 cells from cell lines and triple-negative breast xenograft tumors. Low-depth sequencing, compared with existing methods, revealed greater coverage uniformity and more reliable detection of copy-number alterations. Using phylogenetic analysis, we found minor xenograft subpopulations that were undetectable by bulk sequencing, as well as dynamic clonal expansion and diversification between passages. Merging single-cell genomes in silico, we generated "bulk-equivalent" genomes with high depth and uniform coverage. Thus, low-depth sequencing of DLP libraries may provide an attractive replacement for conventional bulk sequencing methods, permitting analysis of copy number at the cell level and of other genomic variants at the population level.

  Study EGAS00001002170

• Sequencing_Acute_Myeloid_Leukaemia_

  This project will aim at sequencing and analysing three samples from a patient with acute myeloid leukaemia (AML) with t(15;17) translocation (acute promyelocytic leukaemia). The patient was treated with standard chemotherapy and samples (blood and bone marrow) taken for minimal residual disease measured during and after chemotherapy. 2-3years later the patient presented a second AML containing inv (16).In this project we will sequence both AML and normal genomes to find associated mutations This will allow unprecedented insights into the dynamics of appearance of secondary AML, since we will be able to use the MRD samples to track the emergence of the inv(16) leukaemia. We will also be able to distinguish whether the 2 leukaemias are clonally related or not. This project will entail sequencing and analysis of three samples (whole genome 30x coverage) using Hi-Seq. The funds from this grant will cover the cost of sequencing 9 lanes from the AML t(15;17) sample, 9 lanes from AML inv(16) sample and 8 lanes from the normal genome.

  Study EGAS00001000035