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• Nurminen et al ("GP2Men") Study Primary and Metastatic Prostate Cancer Whole Genome Sequence Data

  We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones.

  Study EGAS50000000005

• SUM-seq data for spontaneously differentiated iPSCs to EBs

  Clonal CRISPRi/a hiPS cell lines were plated to induce spontaneous differentiation in KSR medium (KSR medium: knockout DMEM/F12 (Gibco, 12660012), 2 mM GlutaMAX, 1× NEAAs, 20% knockout serum replacement (Gibco, 10828010) and 0.1 mM β-mercaptoethanol (Merck-Millipore)). non-TC plates and dishes were used. At the day of plating, KSR medium was supplemented with Y-27632 (10 µM). The next day, medium was replaced with fresh KSR medium. Medium changes were performed every other day. EBs were transferred to 15 ml conical tubes and allowed to sediment at room temperature for 5 min. The supernatant was replaced with fresh KSR medium and cells were transferred onto non-TC treated plates and maintained at 37 °C, 5% CO2. On day 12 of differentiation, the KSR medium was replaced with Essential 6 medium (Gibco, A1516401). EBs were collected and subjected to SUM-seq library preparation as described in Lobato-Moreno et al. 2025 Nature Methods.

  Dataset EGAD50000001589

• Single-cell RNA sequencing of control and Notch inhibitor treated HCC PDX model

  We generated single-cell RNA-seq data for anti-Notch2 (n=3), anti-JAG1 (n=1) and anti-gD (n=4) treated LIV78 tumors. NCR nude mice bearing similarly sized LIV78 tumors (volumes between 300-900mm3) were injected intravenously with 30mg/kg body weight of either anti-Notch2, anti-Jag1 or anti-gD control antibody 72hrs prior to tumor harvest and tumor cell isolation. Following the depletion of CD45+ and Ter119+ cells, the samples were processed for single-cell RNA-seq (scRNAseq) as described previously (Long et al., 2019) using the Chromium Single Cell 3’ Library and Gel bead kit v2, following the manufacturer’s manual. cDNAs and libraries were prepared following the manufacturer’s manual (10X Genomics). Libraries were profiled by Bioanalyzer High Sensitivity DNA kit (Agilent Technologies) and quantified using Kapa Library Quantification Kit (Kapa Biosystems, Wilmington, MA). Each library was sequenced in one lane of HiSeq 2500 (Illumina) following the manufacturer’s sequencing specification (10X Genomics) to produce the resulting FASTQ files.

  Dataset EGAD50000000738

• Targeted Myeloid DNA-Panelsequencing, DKFZ

  Targeted myeloid DNA-Panelsequencing from purified bone marrow blasts of 104 treatment naive AML patients from the discovery cohort. For more details, we refere to Jayavelu, Wolf, Buettner et al. Libraries were prepared from 40 ng DNA using the QIASeq Human Myeloid Neoplasms Panel (Qiagen) according to the manufacturer’s protocol. Samples were tagged with the QIAseq 96-Unique Dual Index Set A for Illumina platforms (Qiagen) to yield unique combinations of i5 and i7 barcodes for each sample. Sample fragment size distribution and concentration was estimated using the Agilent High Sensitivity DNA kit on a 2100 Bioanalyzer (Agilent). Samples were pooled in an equimolar fashion, denatured, and diluted to 1.5 pM according to Illumina’s recommendations. The diluted library was sequenced on a NextSeq 500 benchtop sequencer (Illumina) using NextSeq High Output cartridges. Demultiplexing was performed using the BaseSpace cloud platform (Illumina).

  Dataset EGAD00001008501

• The effect of freezing delay of cell-type specific transcriptome responses in human brain via snRNA-seq

  In other analysis in the current manuscript, we find a similar gene signature (to dissociation based artifacts in mouse and human tissue) is present in post-mortem microglia and astrocytes, across all snRNA-seq datasets analyzed, although it is highly variable between subjects. ​ Using acutely-resected neurosurgical tissue, we performed single-nucleus RNA-seq and reveal that a similar signature can be detected in microglia following prolonged exposure to room temperature. Tissue handling and methods details, as well as sequencing and analysis details) can be found in the methods section of related manuscript (Marsh et al., 2022). Together, these results suggest that the presence of this signature in post-mortem brain samples may be the result of a combination of acute pre-mortem (agonal state, cause of death, comorbidities, etc.) and post-mortem (post-mortem interval (PMI), storage time, RNA quality, etc.) variables and may not represent normally present cell state.

  Dataset EGAD00001008541

• Tagged-amplicon deep sequencing

  This dataset contains a collection of tumour samples from high grade serous ovarian carcinoma patients with recurrent disease collected near the point of diagnosis as well as tumour samples collected after patient relapse upon or some time after study entry. Whole blood samples were also collected from patients at study entry for the purpose of germline variant detection. The majority of diagnosis samples were preserved in neutral buffered formalin whereas the majority of post-relapse samples were preserved in universal molecular fixative (UMFIX, Sakura Finetek USA, Inc). DNA was extracted and the tagged-amplicon deep sequencing assay was applied (TAm-Seq, Forshew et al. 2002, Sci Transl Med) with the aid of fluidigm access array technology. Targeted loci were sequenced at very high depths (typically >100X) for the detection of both somatic and germline variants. Sequenced reads were aligned to the GRCh37 reference genome (release hs37d5).

  Dataset EGAD00001011058

• Mucociliary Clearance Consortium (MCC) Rare Genetic Disorders of the Airways: Cross-section Comparison of Clinical Features, and Development of Novel Screening and Genetic Test

  We have established a consortium of 7 geographically-dispersed clinical research sites that are designed to study rare diseases of the airways, which involve defects in clearance of mucus secretions from the airways (defective "mucociliary clearance"). These sites will collaborate in diagnostic, genetic, and other studies in patients with impairments of mucociliary clearance, including primary ciliary dyskinesia (PCD), variant cystic fibrosis (CF), and pseudohypoaldosteronism (PHA). These disorders reflect genetic defects in airway host-defense, and typically result in chronic infection of the airways. Patients with these disorders of the conducting airways and sinuses have delayed (or incorrect) diagnoses, because diagnostic tests are not readily available. These patients may also have sub-optimal management of their clinical disease, because the cause of these disorders is not well-defined, and treatment regimens are usually not driven by evidence-based medicine. This current protocol is designed to employ a systematic approach to the diagnostic evaluation of these patients with chronic airways disease, which will yield precise diagnoses in individual patients, and will be associated with development of better diagnostic techniques, including genetic testing. In addition, we will compare/contrast clinical features (phenotype) across these disorders. A rigorous cross-sectional comparison of the clinical features will provide better understanding of the clinical disease of these disorders; in turn, this will lead not only to a better standard of clinical care, but will also assist in the identification of novel therapeutic approaches. The patient population for these studies includes individuals carrying a tentative diagnosis of the three disorders (PCD, variant CF or PHA), plus individuals suspected to have one of these disorders, but with inadequate or inconclusive diagnostic tests. Individuals in this latter category must have a preliminary clinical evaluation to evaluate for other more common disorders that may have similar manifestations including classical CF, immunodeficiency, asthma, and severe gastroesophageal reflux. We have an informal agreement with a network of pulmonologists across the United States to perform clinically-indicated (not research) preliminary clinical testing, if not directly available to patients who inquire about these studies. Blood will be collected for DNA to test for genetic mutations. The blood samples will be processed to establish a cell line (lymphocyte transformation) for a source of DNA for future genetic studies, in participants with disease. For participants unable to provide a blood sample, a buccal sample will be obtained for DNA.

  Study phs000595

• Drug development for pediatric cancers: the importance of patient' s genomic data re-use

  Cancer in children is uncommon and the overall prognosis for most pediatric cancers is good. However, while the combined survival rates have improved over the last decades, certain childhood malignancies, such as high-grade gliomas or metastatic sarcomas, still remain incurable in most patients. New strategies for targeting those devastating diseases are imperative, and patient genomic data can become a key asset in the process [1]. The Pediatric Cancer Genome Project’s datasets At EGA, we store over 500 datasets with sequencing data from pediatric cancer patients. A remarkable case is the datasets belonging to the Pediatric Cancer Genome Project (PCGP) from St. Jude Children’s Research Hospital–Washington University (Table 1 - EGAS list). PCGP is an ambitious effort to identify the mutations that drive childhood cancer and find new cures. Those datasets include 600 patients with complete tumor and normal genomes from 15 different tumor types. PCGP datasets have been an important resource for various studies that pooled genomic data from different public and in-house datasets to perform extensive genomic characterizations and publish comprehensive pan-cancer pediatric studies [2],[3]. Other interesting pediatric cancer datasets are from the Pediatric Brain Tumor Consortium, Sickkids or ICGC PedBrain project. How data reuse impacts drug development for pediatric cancers Recently, in October 2024, Nature Communications published a work led by the University of Michigan where authors used data from EGA (PCGP) check the table below as part of their strategy to pursue the identification of new tumor vulnerabilities susceptible to becoming novel therapeutic targets in diffuse midline glioma. Diffuse midline gliomas (DMG) are treatment-resistant and uniformly fatal pediatric brain tumors. The prognosis of this brainstem tumor is dismal with a median overall survival of 9–12 months from diagnosis. In this study, the authors first developed a lab model of the disease and reanalyzed data from the EGA to identify genes potentially linked to tumor severity. This approach revealed involvement of specific metabolic pathways, suggesting new possibilities for therapeutic intervention. In mice, the study shows that the use of statins can improve survival. For a brief overview of the underlying science, diffuse midline gliomas present intratumor heterogeneity with subpopulations of less-differentiated oligodendrocyte precursors and more differentiated astrocytes. Authors established in vitro models to recapitulate both phenotypes and identify metabolic programs in both subpopulations. To determine the clinical relevance, the authors re-used gene expression data from 76 DMG patients identifying a gene signature predicting decreased overall survival. After extensive metabolic characterization of subpopulations, authors defined strategies to target specific metabolic vulnerabilities. Pre-clinical experiments in mice using OXPHOS inhibitors and statins showed a reduction in tumor burden and increased overall survival [4]. In this scenario, the re-use of high-quality patient’s sequencing data appeared as an advantageous strategy to support the clinical relevance of in-vitro and pre-clinical findings. On the other hand, in rare conditions such as childhood cancer, the availability of public datasets and the possibility of pooling data from different sources can be the only way to obtain impactful results that lead to improvements for patients. References Davidoff, A. M. Pediatric Oncology. Seminars in pediatric surgery 19, 225–233 (2010). Gröbner, S. N. et al. The landscape of genomic alterations across childhood cancers. Nature 555, 321–327 (2018). Venu Thatikonda et al. Comprehensive analysis of mutational signatures reveals distinct patterns and molecular processes across 27 pediatric cancers. Nature Cancer 4, 276–289 (2023). Mbah, N. E. et al. Therapeutic targeting of differentiation-state dependent metabolic vulnerabilities in diffuse midline glioma. Nature Communications 15, (2024). Datasets and Studies ID Title Access Policy Year EGAD00001000134 Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAS0000100192 Somatic Histone H3 Mutations in Diffuse Intrinsic Pontine Gliomas and Non-Brainstem Paediatric Glioblastomas St. Jude Children's Research Hospital - Washington University Pediatric Cancer Genome Project 2017 EGAS00001000575 Whole genome sequencing and whole exome sequencing of DIPG tumors and matched normal tissue The hospital for sick children ("SickKids") 2016 EGAD00001000792 Exome sequencing reads of paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAD00001002006 Whole genome sequencing of paediatric glioblastoma in the ICGC PedBrain project ICGC PedBrain project 2016

  Blog drug-development-for-pediatric-cancers

• San Francisco Bay Area Latina Breast Cancer Study

  The genome-wide association study (GWAS) includes participants enrolled into two different studies. The first study, the San Francisco Bay Area Cancer Study (SFBCS) is a population-based case-control study of breast cancer conducted in the San Francisco Bay Area and included women ages 35-79 years from three racial/ethnic groups: Non-Hispanic whites, African Americans, and Hispanics/Latinas. For the GWAS, only Hispanic/Latina women were included. Women diagnosed with invasive breast cancer between 1995 and 2002 were identified through the Greater Bay Area Cancer Registry. Controls were identified by random digit dialing and were frequency-matched to cases by age in 5 year increments and by race/ethnicity. Hispanic/Latina ethnicity was assessed by self-report. 175 Hispanic/Latina cases and 307 Hispanic/Latina controls from the SFBCS had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission. The second study is the Northern California site of the Breast Cancer Family Registry (NC-BCFR). This population-based family study recruited breast cancer cases ages 18-64 years diagnosed from 1995-2009 that were identified through the Greater Bay Area Cancer Registry. Cases included all women at increased genetic susceptibility for breast cancer who met one or more of the following criteria: (a) being diagnosed with breast cancer at age <35 years; b) having a personal history of ovarian cancer or childhood cancer; (c) being diagnosed with two different breast cancers (bilateral breast cancers), with the first one diagnosed at age <50 years; and d) having one or more first-degree relatives with breast cancer, ovarian cancer or childhood cancer. Cases not meeting these criteria were randomly sampled and racial/ethnic minorities were oversampled. Controls were recruited by random digit dialing and were matched by 5-year age increments and by race/ethnicity. For the current GWAS only Latina/Hispanic cases and controls were included. Latina/Hispanic ethnicity was assessed by self-report. 631 Hispanic/Latina cases and 61 Hispanic/Latina controls from the NC-BCFR had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission.

  Study phs000912

• DNA Methylation Analysis of Prostate Cancer Cell Lines and Tissues Using Next Generation Sequencing

  Aberrant DNA methylation changes are known to occur during prostate cancer progression beginning with precursor lesions. Utilizing fifty nanograms of genomic DNA in Methylplex-Next Generation Sequencing (M-NGS) we mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2). Peaks were located from mapped reads obtained in each sequencing run using a Hidden Markov Model (HMM)-based algorithm previously used for Chip-Seq data analysis(http://www.sph.umich.edu/csg/qin/HPeak). The total methylation events in intergenic/intronic regions between benign adjacent and cancer tissues were comparable. Promoter CGI methylation gradually increased from -12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues and approximately 20% of all CpG islands (CGIs) (68,508) were methylated in tissues. We observed distinct patterns in promoter methylation around transcription start sites, where methylation occurred directly on the CGIs, flanking regions and on CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific and several previously studied targets were among them. A novel cancer specific DMR in WFDC2 promoter showed 77% methylation in cancer (17/22), 100% methylation in transformed prostate cell lines (6/6), none in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested a role for DNA methylation in alternate transcription start site utilization. While methylated promoters containing CGIs had mutually exclusive H3K4me3 modification, the histone mark was absent in CGI sparse promoters. Finally, we observed difference in methylation of LINE-1 elements between transcription factor ERG positive and negative cancers. The comprehensive methylome map presented here will further our understanding of epigenetic regulation of the prostate cancer genome. Overall Design: We mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). For replicate analysis in cell lines, a total of 4 runs were completed for PrEC prostate normal cell line, and 5 runs were completed for LNCaP prostate cancer cell line. For tissue samples, 2 benign prostate samples were sequenced twice on Illumina next generation sequencing platform to access overall repeatability of M-NGS.

  Study phs000597