Search Results - EGA European Genome-Phenome Archive

Ouro-seq: Improved Recovery of Full-Length circRNAs from Samples with Limited RNA Content Using Short-Amplicon Suppression

Circular RNAs (circRNAs) represent an emerging class of RNAs with potential roles in disease pathogenesis and promising biomarker applications. However, their detection in samples with limited RNA content, such as liquid biopsies, remains challenging due to extremely low abundance. Here, we introduce Ouro-seq, a novel long-read sequencing protocol optimized for full-length circRNA recovery. We applied Ouro-seq to urine and self-sampled cervical swab (CVS) samples from cervical cancer patients and plasma from lung cancer patients and healthy controls. Our approach significantly outperformed conventional methods, recovering 2-5 times more and substantially longer circRNA molecules. Unexpectedly, while plasma samples predominantly contained exonic circRNAs, urine and CVS were dominated by previously under characterized intergenic circRNA. We identified extensive alternative circularization and splicing events. Functional annotation revealed distinct specialization patterns among circRNA subtypes, with exonic circRNAs exhibiting enhanced miRNA sponging potential and circRNAs from unplaced genomic scaffolds showing greater peptide-coding capacity. This study significantly advances our understanding of circRNA biology in liquid biopsies and establishes Ouro-seq as a valuable tool for comprehensive circRNA characterization with potential applications in biomarker discovery and disease monitoring.

Study EGAS50000001356

UNICORN Data Access Committee

The UNICORN Data Access Committee reviews and manages requests for controlled access to genomic, transcriptomic and associated clinical data generated within the UNICORN colorectal cancer study.

Dac EGAC50000001116

High-grade serous ovarian cancer is associated with increased TP53 mutation burden in uterine lavage

High grade serous ovarian cancer (HGSC) has low survival partly due to the lack of methods for detection, diagnosis, and risk prediction. TP53 mutations, which drive HGSC, are found in gynecological tissues as the result of somatic evolution, but it is unknown whether an excess of mutations is linked to ovarian cancer. Here we investigate if TP53 mutation burden measured in uterine lavage, a minimally invasive gynecological liquid biopsy, can discriminate between patients with and without HGSC. We used ultradeep TP53 duplex sequencing (>15,000x duplex depth) to detect TP53 mutations in uterine lavage collected pre-operatively in 278 patients undergoing gynecological surgery for pelvic masses (average risk) or cancer risk-reduction (high risk). All lavages contained multiple TP53 mutant clones, which were used to quantify TP53 mutation burden frequency (MBF). Average risk patients with HGSC had significantly higher TP53 MBF independently of age and other risk factors (77% sensitivity, 89% specificity, AUC =0.88). Excluding tumor TP53 clonal mutations from the lavage MBF calculation maintains this association, suggesting that it is the overall TP53 somatic mutation burden (rather than the discovery of the specific tumor driver mutation) that identifies HGSC. These results demonstrate that TP53 somatic mutations are common in uterine lavage but more abundant in patients with HGSC, highlighting a connection between TP53 somatic evolution and ovarian cancer. Uterine lavage offers a minimally invasive approach that could be valuable to identify patients with HGSC.

Study EGAS50000001910

Arcagen - Gynecologic cancer domain

Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files from patients with rare ovarian cancer and primary peritoneal cancer and/or fallopian-tube cancer, including low grade serous carcinoma, mucinous adenocarcinoma, clear cell adenocarcinoma; and other rare cancers such as sex cord tumors, germ cell tumor, yolk sac tumor, and malignant/immature teratoma (n=94).

Study EGAS50000000900

Circulating cell-free DNA methylation profiling for detection, distinction, and estrogen receptor status classification of advanced breast cancer

We developed cell-free DNA (cfDNA) methylation signatures for minimally invasive breast cancer detection, distinction, and estrogen receptor (ER) status classification with cell-free Methylated DNA Immunoprecipitation and Sequencing (cfMeDIP-seq). We profiled peripheral blood plasma from 87 patients with mBC spanning ER-positive/HER2-negative (ER+/HER2-), HER2-positive, and triple-negative breast cancer (TNBC).

Study EGAS50000001675

Whole Exome Sequencing and RNA Sequencing data

Whole Exome Sequencing and RNA Sequencing data for SCLC samples used in the study "A targetable dependency on nonsense-mediated decay for cellular homeostasis and immune control in small cell lung cancer"

Dataset EGAD50000002962

Serafini et al., Nuclear localization of the glutaminyl-tRNA synthetase QARS reveals its role in DNA damage response in ovarian cancer

Uncovering novel mechanisms controlling DNA damage response (DDR) is essential to better understand the molecular features of high-grade serous ovarian cancers (HGSOC), which remain a clinical challenge. Here, we demonstrate that the glutaminyl-tRNA-synthetase QARS is a new key player in DDR. We show that QARS is regulated at translational level by the MAPK pathway in HGSOC and controls homologous recombination (HR) through a translation-independent mechanism. Analyses combining RNA sequencing, immunohistochemistry, proteomic data and functional assays from HGSOC patient cohorts and relevant cellular models reveal that QARS promotes DNA repair via the HR pathway. Interestingly, we uncover that QARS is located in the nucleus and is enriched at chromatin upon DNA damage. Nuclear QARS controls HR by interacting with the nuclear autoantigen SP100, a major component of PML-nuclear bodies (PML-NB), that are regulatory hubs for DNA repair proteins. Our data highlight novel nuclear functions and mechanisms for QARS involving SP100, PML-NB and MRE11 that enhance HR in HGSOC.

Study EGAS50000001968

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

A targetable dependency on nonsense-mediated decay for cellular homeostasis and immune control in small cell lung cancer

Small cell lung cancer (SCLC) is one of the most aggressive malignancies, characterized by rapid metastatic dissemination and poor overall survival. Despite harboring one of the highest tumor mutational burden (TMB), expectedly resulting in immunogenic neoantigens, patients with SCLC remain largely refractory to immunotherapy. We found abundant frameshift mutations in SCLC, regarded as highly immunogenic, counterbalanced by a hyperactive nonsense-mediated decay (NMD) pathway, responsible for frameshift-mRNA degradation. NMD activity correlated with tumor mutational burden (TMB) across cancers, suggesting that SCLC and other TMB-high cancers may depend on NMD to limit the accumulation of mutation-derived byproducts in order to maintain cellular homeostasis and evade immune recognition. In TMB-high SCLC models, inhibition of NMD impaired cell proliferation and induced ER stress-dependent apoptosis due to the accumulation of misfolded proteins. Genetic and pharmacological NMD inhibition in vivo effectively controlled TMB-high tumor growth without overt toxicity. By integrating genome and transcriptome sequencing with MHC-I immunopeptidomics and functional in vitro and in vivo assays, we identified that NMD inhibition boosted neoantigen expression and presentation by tumor cells and increased T cell recognition, thus enhancing overall tumor immunogenicity and further improving immunotherapy efficacy in vivo. Our work shows that SCLC – as a TMB-high cancer – relies on NMD for survival and immune escape, uncovering a novel TMB-dependent tractable vulnerability for this devastating disease.

Study EGAS50000002061

PTEN homozygous deletion is a negative prognostic factor in Tumor Treating Fields-treated glioblastoma, IDH wildtype patients

This study investigates genomic determinants of outcome in glioblastoma, IDH-wildtype patients treated with Tumor Treating Fields (TTFields) in addition to standard radiochemotherapy. Tumor tissue from primary glioblastoma at initial diagnosis was profiled using the Illumina TruSight Oncology 500 (TSO500) targeted sequencing panel to characterise somatic alterations. The overarching goal is to provide exploration of genomic determinants of survival and treatment response in TTFields-treated glioblastoma, IDH-wildtype.

Study EGAS50000001469

Whole-exome sequencing and RNA-seq data of paired normal-tumour samples from MMR-proficient early-onset colorectal cancer patients

This study aims to identify novel hereditary colorectal cancer predisposition genes by performing whole-exome sequencing and RNA-seq of paired normal colonic mucosa and colorectal cancer samples from 19 patients diagnosed with MMR-proficient colorectal cancer at an age of 50 years or younger. Both whole-exome and RNA sequencing were performed on the Illumina platform.

Study EGAS50000001296

E-cadherin inactivation shapes tumor microenvironment specificities in invasive lobular carcinoma

Invasive lobular breast carcinoma (ILC) shows specific stromal features, T lymphocyte infiltration (TIL) being associated with poor prognosis. Here, we reveal the involved mechanism by performing single cell RNA sequencing, combined immunohistochemistry, deconvolution of bulk RNA sequencing from large retrospective ILC series, and functional assays using primary cells. We show that ILC accumulates FAP+ inflammatory cancer-associated fibroblasts (iCAF) through a previously undescribed mechanism mediated by E-cadherin/CDH1 on CAF plasticity. Indeed, CDH1 inactivation in ILC cancer cells prevents differentiation of iCAF into myofibroblastic CAF (myCAF), leading to iCAF accumulation. In turn, iCAF attract TILs into the tumor center and shape their spatial organization in ILC. Subsequently, CDH1-inactivated ILC cancer cells promote immune escape by lack of retention and activation of ITGAE-expressing resident memory CD8+ T lymphocytes (TRM). Hence, our study uncovers reciprocal interactions between CDH1-inactivated cancer cells, iCAF and CD8+ TRM, gaining insight into the underlying mechanism associated with the distinctive stromal reaction observed in ILC and revealing why and how TILs have a poor prognosis in ILC patients, a mechanism that can be generalized to other CDH1-inactivated cancer types.

Study EGAS50000001760

SCANDARE TNBC

Prospective biobanking study in breast patients aiming at better understand the link between the molecular alterations of the tumor itself, its microenvironment and immune response.

Study EGAS50000000970

Clonotypic characterization defines B‐cell drivers of clonal expansion and intratumor heterogeneity in IgM monoclonal gammopathies

Dataset accompanying the study entitled “Clonotypic characterization defines B‐cell drivers of clonal expansion and intratumor heterogeneity in IgM monoclonal gammopathies” (Moreno, Nadeu, et al. HemaSphere 2026), which includes genomic, epigenomic, and transcriptomic analyses of smoldering and symptomatic Waldenström macroglobulinemia (SWM and WM, respectively) as well as IgM monoclonal gammopathy of undetermined significance (MGUS).

Study EGAS50000002033

The UVA-induced single-base mutational signature of CX5461 in human cells

Drug-related UVA-induced photoreactions have been reported for several therapeutic compounds, including fluoroquinolones. CX5461 is a clinically relevant quinolone-derived anti-cancer small molecule with documented UVA-sensitising activity. Here we compared, by bulk and clonal whole genome sequencing (WGS) under light-protected conditions, the mutational signatures in human retinal pigment epithelial cells (RPE1) exposed to UVA, CX5461, or co-exposed to UVA and CX5461. Treatment with CX5461 or UVA alone resulted in a low SNV burden and background-like mutational profiles. In contrast, bulk sequencing of human cells co-exposed to UVA and CX5461 had a markedly higher SNV burden characterized by T>A and T>C substitutions. Furthermore, single-cell clonal expansion and sequencing of CX5461 alone, UVA alone or CX5461+UVA treatments confirmed that the pattern was only observed when cells were exposed to both UVA and CX5461. The CX5461+UVA-associated SNV signature we report arises only when CX5461-treated cells are exposed to UVA, and is not observed when CX5461-treated cells are shielded from light. We do not observe strong single base mutagenic activity of CX5461 alone, under light protected conditions. Our data emphasise the need for appropriate controls and light-exposure precautions when studying base mutagenesis activity of known photosensitiser molecules.

Study EGAS50000001145

Single-nucleus profiling of postmortem diffuse midline gliomas identifies mitochondrial biogenesis as a resistance mechanism to imipridone therapy

Diffuse midline glioma, H3 K27-altered (DMG), remains a lethal pediatric brain tumor with limited therapeutic options, and imipridone therapy produces only temporary responses before recurrence. To investigate resistance mechanisms, we performed single-nucleus RNA and chromatin accessibility profiling on 22 postmortem DMG specimens treated with imipridones and/or standard care, alongside functional assays of imipridone sensitivity and mitochondrial activity in DMG cell lines. Imipridone-treated tumors showed reduced mesenchymal transition, decreased myeloid-derived suppressor cells, and downregulation of aberrant enhancer activity associated with H3 K27 alterations. Mechanistically, treatment selected for increased mitochondrial density, turnover, and membrane potential. Together, these findings identify mitochondrial biogenesis as a key marker and driver of imipridone resistance, providing a rationale for combination strategies to improve therapeutic efficacy.

Study EGAS50000001447

Arcagen – thoracic malignancies

Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files from rare thoracic malignancies (n=102)

Study EGAS50000000123

Panel sequencing of endocrine-resistant breast cancer

Patients with endocrine-resistant breast cancer in Stockholm Sweden. DNA obtained from patients primary and relapse tumors, and tumor-free lymph nodes used as germline control. DNA was extracted from formalin-fixed paraffin-embedded tissue and sequenced by 370-gene panel-based sequencing with Kapa HyperPlus library preparation and Twist Bioscience hybrid capture. Custom bait sets (panels) from Twist Bioscience. Paired end 2x150 bp using NovaSeq X. The data is presented as fastq-files.

Study EGAS50000000236

Transcriptomic profiling of prostate cancer metastasis xenograft models reveals conservation of bone microenvironment signatures

Study EGAS00001004770

Arcagen - Skin cancer domain

Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files patients diagnosed with adnexal carcinoma of the skin, Merkel cells cancer, and malignant melanoma of the uvea (n=49).

Study EGAS50000000491

Arcagen – Adrenal and Thyroid cancers domain

Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here were are submitting the dataset that contains NGS files from patients with adrenocortical carcinoma, pheochromocytoma, anaplastic thyroid cancer, medullary thyroid cancer and radioiodine refractory thyroid cancer (n=103).

Study EGAS50000000626

Arcagen – Cancer of unknown Primary domain

Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files patients diagnosed with a locally advanced or metastatic Cancer of Unknown Primary (n=96).

Study EGAS50000000177

Arcagen - Head and Neck domain

Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here were are submitting the dataset that contains NGS files from patients with salivary gland tumors of major salivary gland; salivary gland type tumors of head and neck with a strong focus on acinic cell carcinoma, NUT carcinoma and sinus carcinoma (n=102).

Study EGAS50000000625

Arcagen - Sarcoma domain

Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files from patients with undifferentiated sarcoma of the bone; aggressive angiomyxoma; alveolar soft part sarcoma; small round cell sarcoma without EWSR1 and CIC translocations; undifferentiated pleomorphic sarcoma; undifferentiated sarcoma; myxofibrosarcoma; or sarcoma with an incidence of less than 1 per 10 million (n=62).

Study EGAS50000000639

Arcagen - Relapsing germ cell tumors domain

Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files from patients with Relapsing germ cell tumors, of any origin and of any histological type (n=23).

Study EGAS50000000645

Arcagen - Extra-pulmonary neuroendocrine tumour or cancer grade 3 (NET / NEC G3) domain

Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here were are submitting the dataset that contains NGS files from patients with extra-pulmonary neuroendocrine tumour or cancer grade 3 (NET / NEC G3) (n=85).

Study EGAS50000000644

Djerroudi et al., E-cadherin inactivation shapes tumor microenvironment specificities in invasive lobular carcinoma

Invasive lobular breast carcinoma (ILC) shows specific stromal features, T lymphocyte infiltration (TIL) being associated with poor prognosis. Here, we reveal the involved mechanism by performing single cell RNA sequencing, combined immunohistochemistry, deconvolution of bulk RNA sequencing from large retrospective ILC series, and functional assays using primary cells. We show that ILC accumulate FAP+ inflammatory cancer-associated fibroblasts (iCAF) through a previously undescribed mechanism mediated by E-cadherin/CDH1 on CAF plasticity. Indeed, CDH1 inactivation in ILC cancer cells prevents differentiation of iCAF into myofibroblastic CAF (myCAF), leading to iCAF accumulation. In turn, iCAF increase TIL infiltration and shape their spatial organization in ILC. Subsequently, CDH1-inactivated ILC cancer cells promote immune escape by lack of retention and activation of ITGAE-expressing resident memory CD8+ T lymphocytes (TRM). Hence, our study uncovers reciprocal interactions between CDH1-inactivated cancer cells, iCAF and CD8+ TRM, revealing why and how TILs have a poor prognosis in ILC patients, a mechanism extrapolated to other CDH1-mutated cancer types.

Study EGAS50000000761

Arcagen - CNS domain

Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset from patients with rare tumor from the central nervous system (n=61).

Study EGAS50000001002

Tumor Profiler Ovarian Study

The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. Technologies used are digital pathology, targeted NGS, single-cell RNA, single-cell DNA, bulk RNA, bulk proteotyping, single-cell CyTOF, imaging mass cytometry, pharmacoscopy, 4i Drug Response Profiling, and cell-free DNA. These technologies were applied to 240 tumor samples collected over 3 years across three cancer indications: metastatic melanoma, metastatic epithelial ovarian cancer, and acute myeloid leukemia (AML). Here, we publish the scRNA and scDNA data of the ovarian cancer cohort.

Study EGAS50000000885

Precision tumor-on-chip for personalized assessment of drug efficacy and immune cell delivery

Tumor heterogeneity and drug resistance limit the efficacy of cancer therapies and highlight the need for patient-specific preclinical models. We developed a microfluidic tumor-on-chip (TOC) platform that integrates patient-derived organoids with a functional endothelial barrier to recreate drug and immune cell transport from the vasculature into tumor tissue. This system enables evaluation of therapeutic efficacy, toxicity, and immune cell migration under physiologically relevant conditions. In a clinical pancreatic cancer case, the TOC model predicted treatment resistance and uncovered gene expression shifts and pathway rewiring at single-cell resolution. By simulating vascular drug transport, the platform provides a scalable and clinically relevant tool for studying treatment response mechanisms and tailoring cancer treatments.

Study EGAS50000001605

Lung Cancer Research Program Genomics Data Access Committee, University of California, Los Angeles

The committee is responsible for reviewing and approving requests for access to genomic data generated by the Lung Cancer Research Program at the David Geffen School of Medicine at UCLA and ensuring compliance with applicable data-sharing policies, institutional requirements, and relevant regulations.

Dac EGAC50000001154

Combination of a CCL21-gene modified dendritic cell vaccine and pembrolizumab induces immune responses in non-small cell lung cancer.

In a phase I study of advanced NSCLC, intratumoral CCL21-DC vaccination combined with pembrolizumab was safe and resulted in stable disease in 36.8% of patients. Analysis of paired pre- and post-treatment tumor biopsy WES data, together with immune profiling of tumor biopsies and peripheral blood, revealed that disease stability was associated with increased T cell receptor diversity, enhanced CD4+ T cell infiltration, and expansion of novel CD4+ memory T cell clones. These findings suggest that CCL21-DC vaccination can stimulate antitumor immunity; however, its efficacy may be limited by insufficient tumor-specific T cell responses and persistent immunosuppressive signaling within the tumor microenvironment.

Study EGAS50000002127

Phenomic and multiomic characterisation of microsatellite-stable colorectal cancer reveals novel biology and targets of vulnerability (COLOSSUS project): snRNASeq cohort

This dataset contains single-nuclei RNA-sequencing (n = 18) samples. Primary tumour samples were obtained from a) colorectal cancer patients with stage 2 / 3 disease and b) colorectal cancer patients who developed metastatic colorectal cancer (stage 4), for whom tissue from the primary tumour was available.

Study EGAS50000002087

Phenomic and multiomic characterisation of microsatellite-stable colorectal cancer reveals novel biology and targets of vulnerability (COLOSSUS project): Stage (St) 2/3 CRC cohort

This dataset contains bulk RNA sequencing (n = 184), low-coverage whole-genome sequencing (n = 182) and whole-exome sequencing (n = 88) data. Primary tumour samples were obtained from colorectal cancer patients with stage 2 / 3 disease.

Study EGAS50000002088

Phenomic and multiomic characterisation of microsatellite-stable colorectal cancer reveals novel biology and targets of vulnerability (COLOSSUS project): metastatic (m)CRC cohort

This dataset contains bulk RNA sequencing samples (n = 111) and low-coverage whole-genome sequencing (n = 113). Primary tumour samples were retrospectively obtained from colorectal cancer patients who developed metastatic colorectal cancer (stage 4), for whom tissue from the primary tumour was available.

Study EGAS50000002086

After the completion of CINECA, EUCANCan, and euCanSHare. What's next?

CINECA, EUCANCan, and euCanSHare were part of the EUCAN Cluster, made up of six projects that received funding under the same Horizon 2020 call. All EUCAN projects (CINECA, EUCANCan, EUCAN-Connect, euCanSHare, Receptor Plus, and ReCoDID) were aimed at facilitating data reuse and knowledge discovery by enhancing data exchange and long-term collaboration in the health field. Here are some highlights about EGA’s contribution to these projects. CINECA: advances in Federated discovery and infrastructure for cohorts CINECA (Common Infrastructure for National Cohorts in Europe, Canada, and Africa) developed a federated cloud-based infrastructure for making genomic and biomolecular data accessible. The project has assembled a virtual cohort of 1.4 million individuals from sources such as the EGA, CanDIG and H3Africa. The EGA–CRG co-leaded a work package Work Package 1 on Federated Data Discovery and Querying. Beacon v2, championed by Jordi Rambla and Lauren Fromont, has been one of the central elements for the discovery of human genetic and phenotypic data. The EGA-CRG contributed to the development of a model for cohort discovery inside the Beacon v2 model. The team also delivered a Discovery Portal was implemented to explore cohorts and individuals of synthetic data. It is a UI that gathers a network of Beacons, a service for query expansion, and a visualisation tool. Have a look at the Discovery Portal UI, gathering a network of Beacons. You will find entities such as the Barcelona Supercomputing Center (BSC), BioData.pt and the European Genomic Data Infrastructure (GDI), among others. euCanSHare: facilitation of data access management This joint EU-Canada project aimed to build a European and Canadian FAIR platform for cardiovascular data sharing and analysis. The EGA’s tasks contributed to the development of the data management plan and data flows, main web-portal and interoperability protocols. An important part of the EuCanShare platform is the data access manager, a tool for the data owners to control the access to their sensitive datasets. We built a user-friendly interface for data access committees (data owners) to easily manage their data requests and access credentials. The data access portal facilitates the creation and internal organization of the data access committees as well as the linkage of data usage conditions to specific datasets. The interface includes filters for browsing requests and page to visualize the request history helping with the handling of data access requests. EUCANCan: toward a federation of clinical institutions in oncology The EUropean-CAnadian CANcer Network worked towards building a federated network to advance personalized medicine in oncology, by promoting the standard analysis, management and sharing of harmonized genomic and phenotypic data. The EGA led tasks on defining data flows and preparing an adapted infrastructure for long-term data storage and sharing. One of the key contributions was the conception of the EGA communities, offering standard and interoperable solutions for data discovery, processing, and sharing to projects and institutions that would like to manage and share data in the context of the EGA ecosystem. What's Next? The participation in projects such as CINECA, EUCANCan, and euCanSHare provide us with experience for future projects. We are happy to enhance data sharing and reuse, vital for advancing clinical and genomic research. The Discovery Portal is a wonderful proof of concept for the Beacon network. Next, we will finalise both the network and the user interface, and make sure it can be applied to more clinically-centred settings like hospitals. Most data hosted at the EGA are about cancer research. Currently, we contribute to building tools and infrastructure to empower oncology research in several European projects such as EUCAIM, EUCANIMAGE and EOSC4Cancer. We also do not lose sight of initiatives in the field such as the International Cancer Genome Consortium (ICGC) with the project ARGO, whose data model was adopted in EUCanCan.

Blog cineca-eucancan-and-eucanshare-were-concluded-in-june

Beacon v2 and Federated EGA, part of the GDI project Starter Kit to enable access to genomic and phenotypic data across borders

The European Genomic Data Infrastructure project has released a ‘Starter Kit’ based on the rare disease and cancer proof-of-concepts from the Beyond 1 Million Genomes (B1MG) project. The Starter Kit, freely available to any interested parties, contains a set of software applications and components co-developed by the 20 GDI nodes and based on open community standards from the Global Alliance for Genomics and Health (GA4GH). Products in the Starter Kit give all countries the technical capability to access synthetic genomic and phenotypic data across borders. The image above shows the full workflow of the GDI Starter Kit user journey. The dotted circles are not included in the Starter Kit yet The EGA’s work is represented in the Starter Kit with Beacon v2 and Federated EGA among the software applications and components. About Beacon v2 Beacon is a protocol for data discovery. This API allows the search of genomic variants and associated information without breaching the datasets privacy. The European Genome-phenome Archive (EGA) is a key contributor to the Beacon v2 Protocol, the Beacon v2 Reference Implementation (B2RI) and the EGA Beacon(s). About Federated EGA The Federated EGA network offers a tool for data storage and sharing. Officially launched in 2022, this network of connected resources enables transnational discovery of and access to human omics data for research, while also respecting jurisdictional data protection regulations. The Federated EGA Onboarding Website contains all the information related to the establishment of a Federated Node.

Blog beacon-v2-and-federated-ega-part-of-the-gdi-project-starter-kit

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

Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

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Providing safe access to sensitive human data across borders: Federated EGA becomes a reality

Enabling discovery and access to sensitive data across national boundaries is vital for improving human health. It enables more powerful and efficient research by increasing the volume and diversity of data available for analysis. It allows us to better understand the causes of diseases – cancer, rare diseases, infectious diseases like COVID-19 – and develop new medicines and treatments. Sensitive human omics data are typically generated by research initiatives and shared using specialist repositories which provide services for data submission, discovery, and access. The EGA is one such repository. Established in 2008 at EMBL’s European Bioinformatics Institute (EMBL-EBI) in the UK, since 2012 the EGA (“Central EGA”) has been jointly managed by EMBL-EBI and the Centre for Genomic Regulation (CRG) in Spain. Many countries have emerging personalised medicine programmes which generate data from national initiatives. These programmes are driving a transition in human genomics from being research-driven to receiving funding through healthcare. Data generated in a clinical context are subject to stricter governance than research data and must follow national data protection legislation. To solve these challenges, the Federated EGA provides a network of connected resources to enable transnational discovery of and access to human omics data for research, while also respecting jurisdictional data protection regulations. In this way, the Federated EGA infrastructure supports the goals of European initiatives such as the 1+ Million Genomes initiative (1+MG), the European Health Data Space, and a number of EU-funded 1+MG implementation projects including Beyond 1 Million Genomes. The Federated EGA is made up of “Nodes” – typically nationally funded and operated – which store and manage data locally while allowing global discovery within the Federated EGA network. Since 2016, multiple parallel efforts, supported by ELIXIR and other transnational and national initiatives, have created technical and legal frameworks for establishing the Federated EGA. In 2022, the first five Nodes – Finland, Germany, Norway, Spain, and Sweden – officially joined the Federated EGA by signing Federated EGA Collaboration Agreements with Central EGA. The Finnish FEGA Node is operated by CSC - IT Center for Science and provides data management services according to national laws and the requirements of the EU General Data Protection Regulation (GDPR). These services provide tools and support for the whole life-cycle of sensitive research data from collating to analysis, publication, and authorised re-use. The development of the services has been a joint effort with the other Nordic nodes within NeIC's Tryggve and Heilsa projects, and funded by Finnish Ministry of Education and Culture and projects coordinated by ELIXIR Finland. Read more about Finnish FEGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. In Norway, a key component of the infrastructure is the services of The Sensitive Data Service (TSD) offered by USIT at University of Oslo. The Federated EGA Norway Node is developed by ELIXIR Norway and operated by the University of Oslo as the responsible legal entity. Core software modules are developed jointly with the other Nordic nodes in the NeIC Tryggve and Heilsa projects. Read more about FEGA Norway signing. The Spanish FEGA (es-FEGA) is a national service for storing sensitive biomedical data in Spain. Supported by the Spanish Institute of Bioinformatics (INB) in collaboration with Central EGA, sensitive research datasets are primarily hosted at the Barcelona Supercomputing Centre facilities. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. By providing a solution for secure and efficient management of human omics data, the Federated EGA aims to foster data reuse, enable reproducibility, accelerate biomedical research, and improve human health. Find out more Interested in setting up your own Federated EGA Node? Check out the FEGA Onboarding Knowledge Base for more information. The ELIXIR Federated Human Data Community is a great entry point for anyone interested in learning more about the Federated EGA. You can: Join the ELIXIR Federated Human Data Community mailing list (select “Human Data”) Attend the ELIXIR Federated Human Data Community calls

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How upcycled prostate cancer sequences enabled key findings on telomeres length

The length of telomeres, the chromosomes’ end tails, as depicted in the figure below, physiologically shorten with aging. This means that younger cells have longer telomeres compared to their aged counterparts; one could say that the length of cells’ telomeres is a measure of their replicative power. Cancer cells are known to be able to turn this into their favour, and expand their replicative immortality through telomere lengthening and maintenance. Despite being a well-studied pan-cancer hallmark, the relation of the telomeres length to specific cancer genomic features is poorly understood. Julia Livingstone and her colleagues from P.C. Boutros' team in Los Angeles focused their work on prostate cancer. To investigate the relations between telomere length and the clinico-genomics of prostate tumours, they used whole genome sequencing (WGS) of 392 published tumour–reference pairs previously deposited at the EGA under accession numbers EGAS00001000400 and EGAS00001000900. Their work was published on Nature Communications in November 2021. They determined the telomere length of the sequencing sample, from both tumour and non-tumour adjacent tissues, and subsequently ran statistical analysis to investigate possible correlation between the telomeres length with several cancer features. The team discovered that telomeres length does not correlate with any specific driver gene mutation, but it does with the overall frequency of single nucleotides variants in a sample. This finding suggests that tumours with shorter telomeres accumulate more mutations without strong selective pressures for specific ones. While proliferation rate did not correlate directly with telomere length, methylation of almost half of all genes strongly did. The team’s results are massive and reveal a complicated and fascinating relation of different clinical and genomic features of prostate cancer with telomere length. In the paper discussion, they smartly consider different possibilities. As noted above, all these amazing results have been obtained analysing previously sequenced samples. Remarkably, the researchers who generated the samples did not focus at all on telomeres length. They indeed studied specific genes mutations and the features of early and late-onset prostate cancer. This proves, once again, the power of sequencing data re-use. This data is tremendously rich in information, and can hardly be exhausted with any number of analyses. Generating sequencing data, especially Whole Genome Sequencing, even better if tumor-reference paired, is like shopping every last article at the grocery store. You can then cook several recipes, or prepare a seven-course dinner, and still have ingredients left for someone else to borrow and cook something you have not thought about, a recipe that is just not in your cookbook. Noteworthy, the data retrieved from the EGA for this paper is associated with rich and complete metadata, meaning pheno-clinical information regarding the sample donors. As Julia Livingstone and her team wrote, using rich clinical annotations enabled them to assess the relationship between telomere length and patients outcome. This highlights once again the importance of reporting and annotating metadata correctly; It might feel like extra work for the researchers depositing their data, but it really has a huge value. Our team at the EGA is currently working to improve the metadata annotation process, with the aim to maximize the benefits for the scientific community.

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EuCANCan: EUropean-CANadian Cancer network

The EUropean-CANadian Cancer network (EuCANCan) is a project aiming to develop a federated network of aligned and interoperable infrastructures for the homogeneous analysis, management and sharing of genomic oncology data for Personalized Medicine. This initiative, funded by the European Commission and the Canadian Institutes of Health and coordinated by the Barcelona Supercomputing Center (BSC), is expected to process and provide the scientific community with around 30-35 thousand patient samples from different types of cancer, coming from different nodes involved in this project, during the four years of the project. Data generated as part of primary studies, often in small hospitals or research centers, is hardly reused by other projects or groups. EuCANCan is proposed to foster the homogenisation and discoverability of cancer samples from very different sources for the whole community. These efforts will help paving the way to future standardised and global genomics projects, specially for those participant countries that eventually integrate the methodology and infrastructure generated during the project. “The more data we have access to the more and better discoveries. We attempt to overcome the legal and technical limitations in order to generate, gather and exploit bigger datasets as well as answer more ambitious questions”. These were some of the words Dr. David Torrents, main coordinator of the project, shared with a regional radio during the kick-off meeting of the project, on February 11th, 2019. The EUCANCan network will be composed of reference nodes in Amsterdam, Barcelona, Berlin, Heidelberg, Paris and Toronto which have established strong research and clinical programs in the field of genomic oncology. The Centre for Genomic Regulation (CRG), specifically the European Genome-phenome Archive (EGA), is among the leading institutions. Its exhaustive experience in biomedical data archival and secure distribution is considered key for crucial developments within the project. It is also notable the recent inclusion of EUCANCan in the list of GA4GH driver projects. Further information and details can be found in the following links: InsideHPC BSC official description Techweek (Spanish)

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The last addition to the list of clonal evolution studies in the EGA

Tumours of different types may arise from a single cell with at least one malignant mutation. Accumulation of subsequent hits generates lineages of cells with different cancer transformation power; thus, every clone follows an autonomous evolution, and several clones may co-exist into the same solid or liquid tumour. Clonal evolution studies are not new: the conceptual power of this approach has been recognized since the early ’80, especially in leukaemia patients. Nonetheless, these studies greatly benefit from recent technological improvements -machineries and protocols-, which enable ever-increasing sequencing depth, allowing the detection of low frequency variants and consequently more tumour clones. Note: the figure belongs to the original paper and is owned by the authors. Researchers at the University of Kyoto in Japan, have indeed used state of the art knowledge to investigate the clonal evolution of chronic myeloid leukemia (CML) in a large panel of patients. CML progresses from a majoritarian benign chronic phase into an often fatal blast crisis phase. It is nowadays known that blast crisis are triggered by genetic instability and disrupted DNA repair, which lead to accumulation of DNA mutations. The use of thyrosine kinase inhibitors targeting the Philadelphia chromosome have enormously improved the treatment of blast crisis, nonetheless resistant patients are still a medical challenge. Yotaro Ochi and collegues used Whole Exome Sequencing of paired chronic phase and blast crisis samples to depict the genetic landscape of progression from the first to the second stage of the disease (as illustrated in their figure). Their results were published in Nature Communication on this May 2021. They used a dataset previously deposited at the EGA (EGAS00001003071) and their new generated data have been made available under accession number EGAS00001005075. Their analysis of the occurring mutations contribute to understanding the mechanisms of CML evolution and therefore develop a protocol for early management of patients with a TKI resistance signature. Up to date, the EGA hosts 99 clonal evolution studies, developed in several cancer types, including myeloma, renal carcinomas and ovarian cancer, in addition to various leukaemia subtypes, where this approach has been more widely applied and produced important results and seminal papers. From a pan-cancer point of view, the definition of tumour architecture through clonal evolution studies is instrumental to unravel the mechanisms of disease progression and treatment-resistance insource. At the EGA, we are honoured to contribute to exciting and important science advances with our service!

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Data Use Ontology (DUO) at EGA

For those of you that follow the updates of GA4GH you will have seen the unanimous approval of the steering committee for DUO to be included in its suite of technical standards for the sharing of genomic and health related data. DUO has three main features: Each term has been generated by the community and includes a human readable definition that can be expanded where necessary. It is a machine-readable file that encodes how that data can be used and how a researcher intends to use the data. Can be implemented alongside an advanced search algorithm which would allow authenticated users to query and gain access to datasets pertaining to their research. e.g., an industry researcher working on cancer could potentially be matched to any dataset that is allowed for commercial use and for cancer research and offered the opportunity to fetch them automatically. So, what does this mean for EGA? EGA as a driver project has adopted this standard and will be utilizing it for two main purposes in the first instance. i) It will allow EGA users to instantly identify what terms they will need to agree to as part of any Data Access Agreements. This will save valuable time for both applicants and Data Access Committees alike - as you will be able to see if you are likely to be able to access the data based on your research intentions and working background. ii) In the future it will allow users to be able to search for data based on Data Use Ontology terms e.g., you could search for all data that can be used for General Research Use (GRU). As EGA moves forwards submitters will be asked to align their data access policies with DUO so that their dataset(s) can be tagged appropriately on our web pages. If you would like to add DUO to any of your existing datasets, or to any future datasets, do please just let us know.

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Advancing fast in the analysis of circulating tumour DNA

In cancer patients, solid tumours also release DNA fragments into the blood, and they are called Circulating Tumours DNA (ctDNA). Nowadays, the standard procedure for cancer monitoring is analysis of surgically obtained biopsies. They generate a big amount of material, but the operation is highly invasive and provide medical doctors with a single-time snapshot of the tumours, which are often highly changeable. Analysis of ctDNA, on the other hand, can provide continuous information regarding the tumour itself without the need of invasive procedures. This is why interest in this method is growing, and with it, the need for its technological optimization. Guanhua Zhu and colleagues, at the Genome Institute of Singapore, developed a methodology to quantify ctDNA burden, which means to estimate the amount of tumours derived circulating DNA among all cell-free DNA in the blood of individuals. Their work, published in Nature Communications in april 2021 and summarized in a sketch below, uses state-of-the art methods to analyse cfDNA degradation patterns at promoters and exon regions, to discern it from the DNA coming from the tumours. The bright point of their approach is that simultaneously enable for profiling of actionable cancer mutations and quantitative estimation of ctDNA burden. Their sequencing data of ctDNA has been deposited in the EGA under the accession number EGAS00001004657. This study sums up to a total of 37 of cfDNA and 36 about ctDNA present up to date in the EGA archive. The existence of cfDNA was firstly described back in 2002, while the use of ctDNA analysis in the oncological field exploded only after 2016. The approach is rapidly evolving, moving in parallel with the ever-improving sequencing technologies. Especially, the possibility to obtain high quality sequences from minimal amount of material is a crucial factor. Being able to alleviate cancer patients of disturbing and often slow-recovery procedures, while at the same time improving the quality of diagnosis and disease monitoring seems like a lot to ask. Thankfully, we are blessed with brilliant and dedicated scientists from all around the world who collaborate to make this a reality, sharing their results, knowledge and data.

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Finding the way towards the eradication of therapy-related myeloid neoplasms

Therapy-related neoplasms are directly caused by the drugs used to eradicate a previous cancer. It is well known that a subset of drugs designed to kill cancer cells through DNA-damage-induced apoptosis can intrinsically, as secondary effect, cause DNA-damage in other cells, thus inducing a neoplasm. Those neoplasms have especially bad prognosis. Why are these drugs still in use? Because for many diseases we do not have anything better, at the moment. Approximately 0.5-1% of the kids treated for various types of cancers develop a therapy-related myeloid neoplasm (tMN) as a result of the treatment. Despite having the same origin, their prognostic and molecular features are different from the adult ones, and a complete understanding of the pathogenesis of tMN in children is still missing. A total of 84 paediatrics neoplasms have been profiled by either Whole Genome or Whole Exome sequencing by Jason R. Schwartz and his colleagues, in a collaborative effort guided at the St. Jude Children's hospital, in Memphis. They identified a mean of 28 somatic mutations per patient, a number which is significantly bigger than the number of mutations found in paediatrics primary neoplasms, as depicted in the original paper's figure 1b, shown here. Their sequencing data identified that Ras/MAPK pathway mutations, alterations in RUNX1 or TP53, and KMT2A rearrangements as the most frequent drivers of the disease. Clonal evolution analysis (the comparative study of the behaviour of cells harbouring different mutations) highlighted that, unlike in adults’ tMN, there were not pre-existing leukemic clones, and virtually all mutated cells were found arising as a direct consequence of cytotoxic therapy. This represents yet another important difference between adult and paediatric tMN. This important study have been published in Nature communications in February 2021. The sequencing data have been deposited at EGA under the study number EGAS00001004850. Thanks to this, other researchers around the world could re-use it to uncover more information, integrate and validate their studies. Revealing the molecular features underlying the development of cancers is the only way towards the development of new generation targeted therapies, which will allow us to finally drop the cytotoxic drugs eliciting such unwanted and catastrophic secondary effects as tMN. It is not an overstatement to say that, while improving the treatment of primary tumours, we could entirely eradicate therapy-related neoplasms right from their origin. Looking forward.

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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.

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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.

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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.

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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.

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