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• 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

• Gut microbiome dynamics unravelled with metagenomics sequencing

  It has been already several years since we discovered that microbial therapeutics like Faecal Microbiota Transplantation can be used to treat Clostridium difficile infection (CDI) and Inflammatory bowel disease (IBD) with great success. The concept has challenged us to test the limits of our knowledge with the perspective to improve health in the most diverse conditions like Parkinson disease, depression, autism and obesity, just to mention a few. Note: the figure belongs to the original paper and is owned by the authors. Allyson L.Bird and colleagues from Genentech Inc. (San Francisco) recently published an interesting study building up on the key concept that “As microbial therapeutics are increasingly being tested in diverse patient populations, it is essential to understand the host and environmental factors influencing the microbiome.” The authors of this work analysed 1359 gut microbiome samples using shotgun metagenomics sequencing.  The results of the comparison done between microbiota composition across the different groups showed that biological sex is the strongest driver of diversity, while aging (age range studied: 20–69) appears to be the second factor. As smartly outlined in the authors’ own graphical abstract (figure to the left), Bacteroidota species consistently increased with donors' age while Actinobacteriota species, including Bifidobacterium, decreased. This study also integrated data from oncological patients to draw cancer-related evidences. After correcting the biases for technical and geographic differences, they found that cancer patients show significantly altered gut bacterial communities compared with their healthy counterparts. Eg. E.coli was found to be increased in cancer patients together with Bacteroidota/Firmicutes ratios. By comparing sequential samples taken from the same donors (413) within short-distance time points, the authors found that in the short term, intra-individual differences were less than the inter-individual ones, indicating a certain community stability being the norm. One of the pivotal points from this interesting study is that the data proceeds from extremely well-defined and selected donors. Specifically, the data for 949 selected healthy donors came from the Milieu Intérieur (MI) Consortium and extensive metadata, including demographic variables, serological measures, dietary information, and systemic immune profiles, are available. This precise stratification allowed for the robust detection of smaller changes, compared to former works. All sequencing data has been deposited in the EGA archive under the accession number EGAS00001004437. Enjoy this amazing open access paper published in the Experimental Journal of Medicine on January 2021.

  Blog gut-microbiome-dynamics-unravelled

• Discover Cancer Image Europe, the first release of the EUCAIM platform to fuel cancer research and data sharing

  The EUCAIM consortium and the European Commission have announced the release of Cancer Image Europe, a platform to fuel collaborative innovation and data sharing across Europe. This constitutes a major milestone in EUCAIM's development and an exciting step towards achieving the project's vision and goals. The platform aims to accelerate the pace of AI development and other data-intensive cancer research activities, constituting the basis for a fully-fledged infrastructure for sharing, reusing, and exploiting cancer imaging data, especially using AI techniques. A platform paving the way for the future of cancer diagnosis and treatment Cancer Image Europe brings benefits to researchers, clinicians, and AI innovators across Europe as it addresses the fragmentation of existing cancer image repositories. The platform gathers a public catalogue of cancer imaging datasets from the repositories of the EU-funded AI for Health Imaging projects. A distributed Atlas of Cancer Imaging with over 60 million anonymised cancer image data from over 100,000 patients will be established as part of future updates. The first version of Cancer Image Europe also includes a public catalogue of cancer imaging datasets, a federated searching tool to understand the information available in the federated providers, and full integration with Life Science Login. Moreover, it reuses and adds value to key components of EU-funded research projects and infrastructure in the field of cancer. The Public Catalogue When we talk about data re-use, data discovery is key. The EUCAIM public catalogue is the result of a systematic and collaborative process to which the EGA-CRG has actively contributed. This browsing interface gathers the metadata of the available cancer imaging datasets. This descriptive information will help researchers in their data retrieval. Our contribution to the Public Catalogue comes from our experience gained in the deployment of our federated network, the Federated EGA (FEGA), and as partners in projects such as EuCanImage (AI4HI initiative), in which we worked on the definition of common data models, ontologies and data standards. The EUCAIM Project EUCAIM is a cornerstone of the European Commission-initiated European Cancer Imaging Initiative, a flagship of the Europe's Beating Cancer Plan, which aims to foster innovation and deployment of digital technologies in cancer treatment and care, to achieve more precise and faster clinical decision-making, diagnostics, treatments, and predictive medicine for cancer patients. For more information about the first release of the Cancer Image Europe platform and the EUCAIM project, please visit cancerimage.eu.

  Blog discover-cancer-image-europe

• First datasets available in the Federated EGA Network

  In February 2024, a great milestone was reached for the human omics data community: the first datasets are now available in the Federated European Genome-phenome Archive (FEGA). These datasets - hosted by national nodes in Poland, Norway, and Sweden - are discoverable in the EGA portal and accessible according to national laws. These datasets include: From FEGA Poland - The Genomic Map Of Poland From FEGA Norway - CRCbiome: Gut metagenome of Norwegian screening participants using FIT sampling Also from FEGA Norway - Single cell transcriptomics in expanded Tregs of APS-1 patients From FEGA Sweden - A Combined Omics and Tissue Biobank for Paediatric Cancers The establishment of these datasets represents a significant step towards achieving the broader objectives of the FEGA; to facilitate the sharing of high-quality human genomic and phenotypic data across borders. “The value for users is twofold: it becomes easier to make data available securely compared to storing data locally, and data becomes easier to find for other researchers. The possibility of reuse improves the chances of both verifying scientific discoveries and reaching groundbreaking conclusions, of benefit to the research community and later also patients,” said Anna Hagwall, project manager and head of human data at FEGA Sweden, NBIS. About Federated EGA FEGA was launched in 2022 as a network to store and lawfully share sensitive human omics data safely. It relies on the technology originally developed by the EGA and support from ongoing collaborations with ELIXIR - a European life sciences infrastructure. FEGA has contributed to and benefitted from the implementation of community standards for sensitive data management including those developed by the Global Alliance for Genomics and Health (GA4GH). “The FEGA concept and the development of the Nordic FEGA nodes have been made possible thanks to several projects coordinated by NeIC,” said Kjell Petersen, FEGA Norway technical lead. Managing human omics data is challenging due to its sheer size and privacy concerns, often resulting in restrictions on how and where sensitive data can be shared. The FEGA network follows a federated data access model whereby sensitive data is stored securely within a local or national jurisdiction, while discovery across the network for data of interest is enabled via a central portal. As of February 2024, the FEGA network comprises seven European national nodes with tens of additional national partners working towards establishing a FEGA node. As the FEGA network continues to onboard nodes from around the world, populated with more and more data, we move closer to a vision of a truly global resource for discovery of and access to sensitive human omics data to accelerate disease research and improve human health. "The Federated EGA network is entering a key phase where the first research datasets are now available across the network. In coming years, we look forward to expanding these datasets to cover key areas such as cancer and rare diseases for the benefit of patients" said Thomas Keane, Group Leader at EMBL-EBI.

  Blog first-datasets-available-in-Federated-EGA

• How mitochondrial DNA research can benefit from data reuse through EGA?

  Mitochondria are the only cellular organelles harbouring their own DNA, which encodes for proteins essentials in its respiration process. Despite its discovery in 1960, Mitochondrial DNA is often overlooked compared to nuclear DNA. Indeed, not all sequencing technologies capture a good representation of mtDNA (mitochondrial DNA). Recently, Ed Reznik's team (The Ed Reznik Lab | Memorial Sloan Kettering Cancer Center) carried out a massive analysis and reanalysis of single cells WGS (whole genome sequencing) produced with an amplification-free protocol (Direct library prep, DLP). As they demonstrated in the paper Single-cell mtDNA dynamics in tumors is driven by coregulation of nuclear and mitochondrial genomes - PMC, DLP is more effective in catching mtDNA compared to classical single-cell sequencing. These data allowed the team to unravel mtDNA dynamics in tumoral and normal samples, highlighting how mtDNA and nuclear DNA are co-regulated and their ratio is critical for phenotype. Data reuse to achieve the greatest results For this project, Reznik's team re-used data from 3 studies stored at the European Genome-phenome Archive (EGAS00001006343, EGAS00001004448 and EGAS00001003190) that comprised a total of 602 datasets. All of them were initially produced by the teams of Sam Aparicio and Sohrab P. Shah at the Memorial Sloan Kettering Cancer Centre, where Ed Reznik is a promising group leader. This demonstrates, once again, that networking, collaboration and data sharing can achieve the greatest results when coupled with innovative and smart ideas. At the EGA we are proud to provide the scientific community with an infrastructure to enable all those very smart ideas out there to find the right data to be tested.

  Blog mitochondrial-dna-research

• 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

• Highlights from 2025: Our top 10 requested studies

  In 2025, as in previous years, EGA has facilitated the reuse of numerous datasets spanning a broad range of research and healthcare topics. To reflect on this activity, we would like to highlight the top 10 studies behind the most requested datasets of last year. Notably, the vast majority of these highly requested datasets are cancer-focused, particularly involving the study of immune checkpoint inhibitor therapies. Immune checkpoint inhibitors (ICIs) have become one of the most transformative advances in modern cancer therapy. These monoclonal antibodies enhance antitumor immune responses by targeting inhibitory immune checkpoint molecules. While ICIs have led to remarkably favorable and durable responses in some patients, treatment outcomes vary widely. This variability has fueled intense research efforts aimed at understanding resistance mechanisms, exploring combination therapies, and discovering predictive biomarkers to better stratify patients and guide treatment decisions. Study Title Disease 1 EGAS00001005503 Integrated genomic analyses reveal molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma Liver Cancer 2 EGAS00001005013 Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer Lung Cancer 3 EGAS00001004809 BIOKEY: A single-cell catalogue of the dynamic changes underlying Checkpoint Immunotherapy response in Early Breast Cancer Breast Cancer 4 EGAS50000000138 BIOKEY: Immune heterogeneity in small cell lung cancer and vulnerability to immune checkpoint blockade Lung Cancer 5 EGAS50000000497 Bladder cancer subtyping study across 4 atezo clinical trials Bladder Cancer 6 EGAS50000000689 MOSAIC - Multi-Omics Spatial Atlas In Cancer Cancer Atlas 7 EGAS00000000083 METABRIC (Breast cancer - genome and transcriptome) Breast Cancer 8 EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Synthetic data 9 EGAS00001002556 TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells Bladder Cancer 10 EGAS00001004353 Molecular subsets in renal cancer determine outcome to checkpoint and angiogenesis blockade Renal Cancer The most requested dataset of the year was EGAD00001008128. It belongs to a study that analyzed 358 liver cancer patients enrolled in clinical trials and treated with the combination of atezolizumab (anti–PD-L1) and bevacizumab (anti-VEGF), atezolizumab alone, or sorafenib. The study highlights how bevacizumab enhances anti-PD-L1 effect and identifies candidate biomarkers to predict treatment response. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the third leading cause of cancer-related death worldwide [1]. Because symptoms often appear late, many patients are diagnosed at advanced stages, when curative options are no longer viable. For many years, sorafenib—a multikinase inhibitor approved in 2007—was the only systemic treatment available. Although numerous clinical trials followed, it was not until a decade later that additional therapies showed meaningful clinical benefit. Among these advances, immunotherapy emerged as a promising first-line option [2]. In particular, the combination of atezolizumab and bevacizumab demonstrated improved survival in patients with advanced HCC, reshaping the treatment landscape. However, treatment efficacy remains limited by the complex and diverse hepatic microenvironments that influence immune responses, as well as by high intratumoral heterogeneity. Identifying robust predictors of treatment response is critical to enable effective patient stratification and maximize the benefits of these therapies [2]. The continued demand for these datasets highlights the interest and critical role of data reuse in deepening our understanding of cancer, accelerating the development of more effective therapies, and improving patient outcomes. By providing secure access to high-quality genomic and clinical data, EGA acts as a catalyst for biomedical progress. References Sung, Hyuna, et al. "Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries."CA: a cancer journal for clinicians 71.3 (2021): 209-249. Ladd, Alexandra D, et al.“Mechanisms of drug resistance in HCC.” Hepatology 79(4) (2024): 926-940

  Blog top-10-studies-2025

• cBioportal lands at EGA: What this means for researchers

  cBioPortal is a widely used platform designed to simplify the exploration of complex cancer genomic data. It brings together large-scale datasets—covering mutations, copy number alterations, gene expression, and clinical annotations—and presents them through an intuitive, interactive interface. Since its launch, it has become a cornerstone of cancer research, helping translate raw genomic data into meaningful biological insights. cBioPortal Is Now Available at EGA At the European Genome-phenome Archive (EGA), we host controlled-access genomic and phenoclinical datasets. By integrating cBioPortal within EGA, researchers could explore cancer datasets (once access has been granted by data owners) through the powerful and user-friendly cBioportal interface. We believe this marks an important step forward for the cancer research community, with several key benefits: Faster Insights Researchers can quickly visualize and explore datasets through the cBioPortal interface before downloading and analyzing complex raw data. This provides an immediate overview, saving time and enabling more informed decisions about which datasets to pursue. Broader Accessibility Working with complex genomic data often requires advanced computational and bioinformatic expertise. This integration lowers the technical barrier, allowing a wider range of scientists to engage with high-value datasets and, for example, accelerate hypothesis generation. Enhanced Data Integration cBioPortal enables the seamless combination of genomic and clinical data, as well as the comparison and exploration of multiple datasets within a single platform. This promotes more comprehensive analyses and supports deeper biological insights. The arrival of cBioPortal at EGA brings together powerful visualization and controlled data access, making it easier than ever for researchers to transform complex cancer genomics data into actionable knowledge. Data submitters: Would you like to make your cBioPortal data available? See our documentation page.

  Blog cbioportal

• Epigenetic Heterogeneity in Breast Tumors with Implications for Disease Diagnosis and Monitoring

  This study investigates epigenetic heterogeneity in human breast cancer using complementary single-cell and bulk epigenomic approaches. Human breast tumor samples were profiled using whole-genome bisulfite sequencing, enzyme-mediated methylation sequencing of sorted tumor-cell populations, single-nucleus CUT&Tag, and single-cell RNA and chromatin-accessibility multiome profiling. These data were used to characterize recurrent epigenetic cell states and intra-tumor heterogeneity in breast cancer.

  Study EGAS50000002070

• NGS in FACSorted populations from AML patients

  FACS-enriched bone marrow cell populations from 22 AML patients were analyzed using a custom panel targeting 56 genes recurrently mutated in myeloid neoplasms. DNA was released from a median of 60,000 sorted cells by incubation with 2.5 μL proteinase K and 2 μL RNase A (Thermo Fisher Scientific) for 30 minutes at 37°C, purified using 2× AMPure XP beads (Beckman Coulter, Brea, CA), and stored in pH 8 elution buffer at −20°C. DNA quantity was measured using the Qubit dsDNA BR Assay on a Qubit 3.0 fluorometer (Thermo Fisher Scientific), and quality was assessed using the Genomic DNA ScreenTape assay on a 4200 TapeStation system (Agilent Technologies, Santa Clara, CA). Libraries were prepared from at least 20 ng of DNA according to the SOPHiA GENETICS protocol and sequenced on an Illumina MiSeq using 2 × 251-cycle paired-end reads. At least 95% of target bases achieved ≥1,000× coverage. FASTQ files were analyzed in SOPHiA DDM using the GRCh37/hg19 reference genome for alignment, variant calling, and annotation. Variants were retained when the variant allele frequency was ≥2%, coverage was ≥100 reads, and the alternate allele was supported on both strands. Synonymous, intronic, intergenic, 5′ untranslated-region, and recurrent panel-artifact calls were excluded. The remaining variants were classified according to Association for Molecular Pathology and American College of Medical Genetics and Genomics guidance using VarSome, ClinVar, COSMIC, and dbSNP. Only pathogenic or likely pathogenic variants were analyzed. All retained calls were visually confirmed in Integrative Genomics Viewer v2.11.3, and only variants previously reported as somatic in hematopoietic or myeloid neoplasms were retained.

  Study EGAS50000002132

• Single-Cell Multiomic and Whole-Genome Profiling of Primary and Metastatic Colorectal Cancer

  This study contains controlled-access single-cell multiomic sequencing (scRNA-seq and scATAC-seq) data generated from patients with colorectal cancer, including 33 primary tumours, 11 metastatic lesions, and 7 adjacent normal tissue samples. Whole-genome sequencing (WGS) data are available for the tumour samples. These data were generated to investigate the genomic and epigenomic landscape of colorectal cancer and to identify recurrent regulatory alterations associated with tumour progression and metastasis.

  Study EGAS50000002048

• Weizmann Breast Cancer Epigenetics Data Access Committee

  Data Access Committee responsible for reviewing requests for controlled access to human sequencing data generated in the study "Epigenetic Heterogeneity in Breast Tumors with Implications for Disease Diagnosis and Monitoring".

  Dac EGAC50000001136

• Committee of human data related to Livanova et al. paper submission

  This DAC controls access to single-cell multiomic (scRNA-seq and scATAC-seq) and matched whole-genome sequencing (WGS) data generated from colorectal cancer patient samples, including 33 primary tumours, 11 metastatic lesions, 7 adjacent normal tissues. The data were generated to investigate recurrent somatic chromatin accessibility alterations (SCAAs) associated with tumour progression and metastasis

  Dac EGAC50000001117

• UNICORN Visium HD spatial transcriptomics of colorectal cancer

  This controlled-access dataset contains raw paired-end sequencing data generated from 56 human colorectal cancer tissue samples using the 10x Genomics Visium HD spatial gene expression workflow. The dataset comprises 324 paired-end sequencing runs represented by 648 FASTQ files. Libraries were sequenced on an Illumina platform and are intended for spatial transcriptomic analysis of the colorectal cancer tissue microenvironment.

  Dataset EGAD50000002908

• Transcriptome Sequencing Data of High Grade Serous Ovarian Cancer

  Study EGAS00001004714

• Long-read whole genome sequencing of gastric cancer

  Gastric cancer (GC) remains a significant health challenge globally, with a particularly high incidence in Asia, including Singapore. Understanding the genomic landscape of normal gastric and the different GC subtypes along with its precursor lesions such as intestinal metaplasia (IM) as well as GC metastatic sites is crucial for advancing diagnostics, prognostics, and therapeutics. Long-read sequencing technologies offer an opportunity to delve deeper into the genomic and epigenetic alterations underlying these conditions and to complement existing short-read omics data. By integrating these data with previously generated in-house multi-omics data (such as RNA sequencing and whole exome sequencing), we hope to better elucidate the molecular mechanism underlying GC initiation and progression.

  Study EGAS50000001607

• scRNA-seq profile of three ATC and three lethal PTC samples

  To elucidate molecular and immunological characteristics distinguishing anaplastic thyroid cancer (ATC) from aggressive papillary thyroid cancer (PTC), we performed single-cell RNA sequencing on three ATC and three lethal PTC samples.

  Study JGAS000942

• NoSarC -- Norwegian Sarcoma Consortium. Towards individualized therapy for orphan cancer.

  This study is initiated and conducted by the Norwegian Sarcoma Consortium - a collaboration between 5 Norwegian hospitals and universities, coordinated by Oslo University Hospital. The NoSarC project was initiated in 2014 and aimed to perform molecular characterization of samples from a national, population-based cohort of sarcoma patients, to identify tumors which are sensitive to therapies already developed and approved for more common cancers. The NoSarC cohort in this study consists of Tumor-Normal pairs from 287 subjects that has been Whole Exome Sequenced.

  Study EGAS50000002163

• Recommended Text: Plasma cfChIP-seq profiling of cell-free nucleosomes in Small-Cell Lung Cancer and neuroendocrine carcinomas

  This dataset contains raw, encrypted Crypt4GH paired-end Fastq files from cell-free chromatin immunoprecipitation sequencing (cfChIP-seq) targeting histone modification H3K4me3 in plasma samples. The cohort includes small-cell lung cancer (SCLC) cases, neuroendocrine carcinomas (NEC) and non-small-cell lung cancer (NSCLC) samples. Access is restricted exclusively to non-commercial, duplicate-prevention SCLC research protocols approved by the Data Access Committee.

  Dataset EGAD50000002783

• Integrating transcriptional regulatory networks with chromatin accessibility as markers of survival outcome and drug response in triple-negative breast cancer

  Patients with triple-negative breast cancer (TNBC), a highly aggressive and heterogeneous breast cancer subtype, have limited effective targeted therapy options and frequently develop resistance to chemotherapy. Transcription regulators (TRs) guided precision medicine, namely anti-estrogen receptor therapy, has proven successful in hormone-dependent breast cancer, but remains a challenge in TNBC. Here, we identified key TRs underlying TNBC identity by combining a transcriptional interaction network with chromatin accessibility and defined TR activity score metrics. We show that the activity scores of these TRs independently discriminate patient outcome across different clinical endpoints. Matching TR activity scores to drug sensitivity identified drug-TR pairs across independent datasets, including NFE2L3 and CBFB activity associated with sensitivity to mTOR inhibition, which we validated using a cohort of TNBC patient-derived xenografts. Collectively, we present methodology to promote TR-guided precision medicine that captures inter-tumor heterogeneity in TNBC and nominates drug sensitivities according to TR activity scores inferred from expression and chromatin accessibility data.

  Study EGAS50000001691

• METABRIC miRNA landscape

  MicroRNAs (miRNAs) are key players in cancer pathogenesis1. They display differential expression across breast cancer subtypes, and play oncogenic and tumor-suppressive roles2-6. A systematic study of the global miRNA landscape in breast cancer and the factors shaping it has not been undertaken. Here we report the results of profiling miRNA expression in 1,302 breast tumors with detailed clinical annotation and long-term follow-up, and for which matching genomic and mRNA expression data were available7. This provides a comprehensive view of the quantity, distribution and variation of the miRNA population and dissects how much genomic, transcriptional and post-transcriptional events contribute to miRNA expression architecture. The key clinical parameters and cellular pathways related to the miRNA landscape are identified, exemplified by context-dependent interaction with cell adhesion and Wnt signaling. Strikingly, in breast cancer miRNAs appear to act as modulators of mRNA-mRNA interactions rather than molecular switches. We demonstrate an important modulatory role for miRNAs in the biology of breast tumors devoid of somatic copy number aberrations, a common subtype where immune response is prominent. Remarkably, prognostic miRNA signatures derived in this subtype are consistently prognostic across several other subtypes and validate in external cohorts. These findings represent a new framework to study the biology of miRNA in human cancer.

  Study EGAS00000000122

• SCANDARE HNSCC

  Prospective biobanking study in SCANDARE HNSCC (Head and Neck Squamous Cell Carcinoma) patients aiming at better understand the link between the molecular alterations of the tumor itself, its microenvironment and immune response.

  Study EGAS50000001158

• Whole genome and transcriptome sequences of hepatocellular carcinoma in patients with Fontan-associated liver disease

  Most liver cancers develop as a result of long-term liver disease caused by viruses, drugs or metabolic disorders. Fontan-associated liver disease (FALD) is a rare condition whose prevalence is increasing. We therefore conducted a multi-omics analysis targeting liver cancer arising from liver damage caused by rare diseases, with a particular focus on FALD.

  Study JGAS000904

• DAC for RNAseq data associated with transcriptomic profiling of ER alpha positive breast cancer patients before and after endocrine therapy

  This Data Access Committee (DAC) oversees access to RNAseq data collected as part of a study focussed on exploring transcriptomic profiles of ER alpha positive breast cancer patients who were treated with aromatase inhibitors for up to three months before surgical removal of the primary tumor. Sampling was performed at diagnosis and at surgery, and RNA-seq was performed. The DAC ensures that data access requests comply with the study's ethical and legal frameworks and that data is shared for non-commercial, academic research purposes under controlled access to protect participant privacy.

  Dac EGAC50000000499

• Transcriptomics profiling of paired pre- and post- neo-adjuvant endocrine therapy of ERa positive breast cancers

  Patients were treated with aromatase inhibitors for up to three months before surgical removal of the primary tumor. Sampling was performed at diagnosis and at surgery, and RNA-seq was performed.

  Study EGAS50000000832

• Colossus Project Single-nuclei RNA sequencing

  Single-nuclei RNA sequencing of human colorectal cancer samples. Nuclei were isolated on ice, followed by single-nuclei RNA-sequencing library preparation using the Chromium Single Cell 3’ reagent kit v3.1 (10x Genomics, Pleasanton, CA) Fastq files, N=18

  Dataset EGAD50000003002

• Colossus Project Whole exome sequencing

  Whole exome sequencing of colorectal cancer samples from stage 2/3 human patients. Whole-genome DNA libraries were prepared with the KAPA HyperPlus kit (Roche, Cape Town, South Africa), and exome fragments were captured using the SureSelect Human All Exon V7 kit (Agilent, Hangzhou, China) Fastq files, N=88

  Dataset EGAD50000003003

• Colossus Project Bulk Tumor RNA sequencing

  Bulk RNA sequencing of colorectal cancer samples from stage 2/3 human patients. RNA extraction using Qiagen RNeasy FFPE Extraction kit (Qiagen, UK), followed by RNA sequencing library generation with the QuantSeq 3' mRNA-Seq Library Prep Kit (FWD) (Illumina, USA). Fastq files, N=295

  Dataset EGAD50000003004

• Colossus Project Whole Genome Sequencing

  Low-coverage whole genome sequencing of colorectal cancer samples from stage 2/3 human patients. Tumor DNA from biopsies was extracted using the QIAamp circulating nucleic acid kit (Qiagen, UK), followed by generation of shot-gun whole genome libraries using the KAPA library preparation kit (KAPA Biosystems). Fastq files, N=295

  Dataset EGAD50000003005

• Expansion and cytotoxicity of mucosal T cells in enterocolitis associated with BCMA CAR-T cell therapy

  This study investigates immune effector cell enterocolitis (IEC-EC) associated with ciltacabtagene autoleucel (cilta-cel), a B-cell maturation antigen (BCMA)-targeting chimeric antigen receptor (CAR) T-cell therapy for relapsed or refractory multiple myeloma. IEC-EC was characterized by infiltration and expansion of clonal CAR-positive cytotoxic T-cell populations within the gastrointestinal tract. Molecular analyses were performed to characterize CAR T-cell clonality, persistence, vector integration, and genomic alterations associated with this complication. This dataset contains whole-genome sequencing (WGS) and whole-exome sequencing (WES) FASTQ files generated as part of the study and associated with the corresponding manuscript.

  Study EGAS50000002146

• Circulating tumour DNA in oligoprogressing metastatic castration-resistant prostate cancer treated with stereotactic body radiotherapy in the TRAP trial

  The TRAP trial (NCT03644303) reported that stereotactic body radiotherapy (SBRT) of up to two imaging-visible metastases in prostate cancer patients showing disease progression whilst continuing an androgen receptor pathway inhibitor (ARPI) improved outcomes. It is possible that the benefit from treatment is heterogeneous and patients with progressing sub-clinical metastases, not detected by imaging, derived no benefit from this intervention. The goal of this study was to determine if ctDNA levels detected before SBRT associates with worse outcome.

  Study EGAS50000002152

• Breast Cancer Atlas Research Consortium (BCARC)

  The Breast Cancer Atlas Research Consortium (BCARC) is an international translational research programme building a multi-modal atlas of breast cancer across subtypes, disease progression states, and treatment phases. Founding investigators span the Swarbrick Laboratory (Garvan Institute of Medical Research, Sydney), the Perou Laboratory (University of North Carolina at Chapel Hill), the Grimmond Laboratory (University of Melbourne Centre for Cancer Research), the Al'Khafaji Laboratory (Broad Institute of MIT and Harvard), and the Lundeberg Laboratory (KTH Royal Institute of Technology, Stockholm). Samples are drawn from primary and metastatic breast tumours together with matched adjacent tissues and where available, blood samples. All samples derive from participants consented under Garvan-approved research protocols. Access is controlled and governed by the BCARC data access agreement; requests are reviewed by the Data Access Committee named in the associated policy record

  Study EGAS00001008520

• Germline whole-genome sequencing (WGS) of colorectal cancer patients

  Whole-genome sequencing (WGS) data generated from matched germline blood DNA samples obtained from patients with primary or metastatic colorectal adenocarcinoma (n=37). These data were generated as part of a multiomic study integrating whole-genome sequencing with single-cell multiome profiling to investigate recurrent epigenetic alterations in colorectal cancer evolution and the tumour microenvironment.

  Dataset EGAD50000002942

• Whole Genome Sequencing (WGS) of Tumour Samples of Primary and Metastatic Colorectal Cancer

  WGS samples of primary (n=33) and metastatic (n=11) colorectal cancer tissues related to Livanova et al. manuscript 'Epigenetic evolution of colorectal cancer and its microenvironment reveals new vulnerabilities'

  Dataset EGAD50000002943

• Single-cell 10x Genomics Multiome ATAC-seq data from primary and metastatic colorectal cancers and normal colon tissues

  This dataset contains single-cell 10x Genomics Multiome ATAC-seq data from 33 primary colorectal cancer, 11 metastatic colorectal cancer, and 7 matched normal colon tissue samples generated as part of the study "Epigenetic evolution of colorectal cancer and its microenvironment reveals novel vulnerabilities."

  Dataset EGAD50000002944

• Single-cell 10x Genomics Multiome RNA-seq data from primary and metastatic colorectal cancers and normal colon tissues

  This dataset contains single-cell 10x Genomics Multiome RNA-seq data from 33 primary colorectal cancer, 11 metastatic colorectal cancer, and 7 matched normal colon tissue samples generated as part of the study "Epigenetic evolution of colorectal cancer and its microenvironment reveals novel vulnerabilities."

  Dataset EGAD50000002945

• Human breast cancer epigenetic sequencing data

  Controlled-access sequencing data generated from human breast tumor samples in the study "Epigenetic Heterogeneity in Breast Tumors with Implications for Disease Diagnosis and Monitoring". The dataset includes whole-genome DNA methylation sequencing, enzyme-mediated methylation sequencing of sorted tumor-cell populations, single-nucleus CUT&Tag, and single-cell RNA and chromatin-accessibility multiome sequencing. Raw sequencing data are provided as FASTQ files.

  Dataset EGAD50000002972

• ICGC PanCancer Analysis of Whole Genomes

  The Pancancer Analysis of Whole Genomes (PCAWG) study is an international collaboration to identify common patterns of mutation in more than 2,800 cancer whole genomes from the International Cancer Genome Consortium. Building upon previous work which examined cancer coding regions (Cancer Genome Atlas Research Network, The Cancer Genome Atlas Pan-Cancer analysis project, Nat. Genet. 2013 45:1113), this project is exploring the nature and consequences of somatic and germline variations in both coding and non-coding regions, with specific emphasis on cis-regulatory sites, non-coding RNAs, and large-scale structural alterations.

  Study EGAS00001001692

• CRCbiome: Gut metagenome of Norwegian screening participants using FIT sampling

  The study aims to characterize the gut metagenome of Norwegian screening participants and assess the ability of the gut metagenome to identify those at need for colonoscopy. Background: Colorectal cancer (CRC) screening reduces CRC incidence and mortality. However, current screening methods are either hampered by invasiveness or suboptimal performance, limiting their effectiveness as primary screening methods. To aid in the development of a non-invasive screening test with improved sensitivity and specificity, we have initiated a prospective biomarker study (CRCbiome), nested within a large randomized CRC screening trial in Norway. We aim to develop a microbiome-based classification algorithm to identify advanced colorectal lesions in screening participants testing positive for an immunochemical fecal occult blood test (FIT). We will also examine interactions with host factors, diet, lifestyle and prescription drugs. The prospective nature of the study also enables the analysis of changes in the gut microbiome following the removal of precancerous lesions. Methods: The CRCbiome study recruits participants enrolled in the Bowel Cancer Screening in Norway (BCSN) study, a randomized trial initiated in 2012 comparing once-only sigmoidoscopy to repeated biennial FIT, where women and men aged 50–74 years at study entry are invited to participate. Since 2017, participants randomized to FIT screening with a positive test result have been invited to join the CRCbiome study. Self-reported diet, lifestyle and demographic data are collected prior to colonoscopy after the positive FIT-test (baseline). Screening data, including colonoscopy findings are obtained from the BCSN database. Fecal samples for gut microbiome analyses are collected both before and 2 and 12 months after colonoscopy. Samples are analyzed using metagenome sequencing, with taxonomy profiles, and gene and pathway content as primary measures. CRCbiome data will also be linked to national registries to obtain information on prescription histories and cancer relevant outcomes occurring during the 10 year follow-up period. Discussion: The CRCbiome study will increase our understanding of how the gut microbiome, in combination with lifestyle and environmental factors, influences the early stages of colorectal carcinogenesis. This knowledge will be crucial to develop microbiome-based screening tools for CRC. By evaluating biomarker performance in a screening setting, using samples from the target population, the generalizability of the findings to future screening cohorts is likely to be high.

  Study EGAS50000000170

• METABRIC

  The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (CNVs, SNPs) and acquired somatic copy number aberrations (CNAs) were associated with expression in 40% of genes, although the landscape was dominated by cis and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP, and MAP2K4. Unsupervised analysis of paired DNA/RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, ER-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration 0152hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the 0152CNA-devoid sub-group and a Basal-specific chromosome 5 deletion-driven mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic copy number aberrations on the transcriptome.

  Study EGAS00000000083

• Non-small cell lung cancer sequencing

  Study EGAS00001005499

• The evolutionary dynamics of human colorectal cancer using single-gland spatial multi-omic profiling of DNA, RNA and chromatin.

  Study EGAS00001005827

• WES of breast cancer patients and controls

  This study assessed the variant profiles of 408 samples from 126 breast cancer patients with various survival outcomes, including paired uninvolved mammary gland samples collected at proximal distances from primary lesions. As a reference, control samples from 15 mammoplasty individuals without cancer history were studied. Whole exome sequencing was performed to identify post-zygotic and germline variants present in the studied samples. Variant annotation in known databases, interpretation, and statistical analyses followed to discern the clinical relevance of called variants.

  Study EGAS50000000539

• Zanidatamab in Patients with Early Stage HER2-positive Breast Cancer: The NeoZanHER Phase 2 Single-Arm Open-Label Trial

  Strategies are needed to avoid chemotherapy in early stage HER2-positive (HER2+) breast cancer (BC). We conducted a neoadjuvant therapy trial with zanidatamab, a dual HER2-directed bispecific antibody, in patients with 1-3 cm, node-negative HER2+ BC. Primary endpoint was pathologic complete response (pCR). Secondary endpoints were radiographic response by ultrasound and magnetic resonance imaging. US and MRI, pathologic response by residual cancer burden (RCB), rate of adverse events, feasibility of accrual and biomarkers of response. Fifteen patients with HER2 IHC 3+, and 5 with HER2 IHC 2+/ISH+ BC were enrolled. Patients received zanidatamab 20 mg/kg every 2 weeks for 6 (n=11) or 10 doses (n=9). Fourteen patients also received endocrine therapy. At 6 weeks, there was a significant decrease in tumor size and volume. At surgery, six patients (30%) had pCR, meeting the prespecified pCR target, and four had limited RCB (RCB-1; 20%). Treatment was well tolerated. All patients with pCR had HER2 IHC 3+ tumors, ERBB2 amplification on WES, PAM50 HER2-high subtype, and a trend towards higher HER2 mRNA expression (p=0.06). In conclusion, de-escalation to HER2-targeted therapy alone may be feasible. Further research is needed to refine patient selection.

  Study EGAS50000001930

• Oslo University Hospital Data Access Committee for I-BCT study datasets submitted to FEGA Norway

  This is the Data Access Committee appointed by Oslo University Hospital for controlled access to datasets from the Improved Breast Cancer Treatment (I-BCT) study under the Ethical approval reference EU CT 2024-515087-31-00 (Originally approved by REK: 2014/167/REK sør-øst A) .

  Dac EGAC50000001170

• I-BCT-1 (Improved Breast Cancer Therapy) - WXS

  A prospective, randomized neoadjuvant study that evaluates DNA-based biomarkers to identify breast cancer patients most likely to benefit from carboplatin (Cb). While Cb improves outcomes in triple-negative breast cancer (TNBC), responses vary, and its role in aggressive hormone receptor–positive breast cancer (HR+BC) remains uncertain. Patients (N = 187) with early, high-risk, HER2-negative cT2-4 tumors received 12 weekly paclitaxel with or without Cb, followed by four cycles of epirubicin and cyclophosphamide. Whole Exome Sequencing data for normal-tumor pairs from the same subjects is available in the matching study titled I-BCT-1 (Improved Breast Cancer Therapy) - WES

  Study EGAS50000002154

• I-BCT-1 (Improved Breast Cancer Therapy) - WES

  A prospective, randomized neoadjuvant study that evaluates DNA-based biomarkers to identify breast cancer patients most likely to benefit from carboplatin (Cb). While Cb improves outcomes in triple-negative breast cancer (TNBC), responses vary, and its role in aggressive hormone receptor–positive breast cancer (HR+BC) remains uncertain. Patients (N = 187) with early, high-risk, HER2-negative cT2-4 tumors received 12 weekly paclitaxel with or without Cb, followed by four cycles of epirubicin and cyclophosphamide. Transcriptomic analysis data for the tumor samples in this study is available in the matching Study titled I-BCT-1 (Improved Breast Cancer Therapy) - WXS.

  Study EGAS50000002155

• Genomic correlates with survival after treatment of oesophageal adenocarcinoma by surgery alone

  A 451 cancer-associated gene panel, described in McCabe et al. 2019, was used to assess genomic alterations associated with survival in a Swedish cohort of 65 oesophageal adenocarcinoma (OAC) patients who underwent surgical resection without perioperative treatment. Primary tumour tissues and matched normal squamous oesophagus tissues were collected from each individual. Laboratory studies were performed at the Centre for Applied Medical Research (AMR) and sequencing was performed at the Kinghorn Cancer Centre. 64 of 65 cancer samples and 61 matched squamous oesophageal mucosa control tissues were successfully sequenced and passed minimal quality metrics.

  Study EGAS50000002190

• Genomic gain of EBV's LMP-1 in NKTCL

  The study found a high recurrence of genomic gain of LMP1 locus within EBV-associated NKTCL. The pilot data set and extended dataset of 77 WGS NKTCLs found 18/77 tumoral genomes to harbour genomic gain of LMP-1 locus within the EBV viral genomes within NKTCL tumoral sequencing data. The study also found 1/10 NKTCL cell lines to be positive for LMP-1 locus gain within EBV genomes too. This dataset includes solely the confirmatory WGS data of LMP-1 gain from NKYS cell lines using Oxford Nanopore long-read sequencing technology.

  Study EGAS50000000260

• Nanopore whole-genome sequencing of human sarcomas

  We performed single and multi-region nanopore whole-genome sequencing on human sarcoma samples from adult and paediatric patients.

  Study EGAS50000000651