6048 results for "canc*"

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• Genetic landscape of pediatric ependymoma

  We performed whole-genome sequencing of 42 paired tumor/normal EPD genomes and analyzed somatically acquired single nucleotide variations (SNVs), insertion/deletions, structural variations and copy number variations in the cancer genomes

  Study EGAS00001000254

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Colorectal

  he Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003774

• 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

• Stratifying and Targeting Pediatric Medulloblastoma through Genomics

  In this project, genomic analyses of pediatric medulloblastoma samples, obtained through the international medulloblastoma consortium, will be performed. RNA and miRNA expression profiles of 1000 samples, representing all four subgroups (Wnt, Shh, Group C, and D), will be studied to identify novel subtypes within each subgroup. The resulting subtype-specific expression profiles will support the development of reliable and robust biomarkers to more accurately and reliably classify medulloblastomas for treatment in clinical trials. For that purpose, two assays will be developed: an antibody-based immunohistochemical assay and an orthogonal nucleic acid-based hybridization assay. Additional genomic DNA analysis of the 300 high risk subgroup cases will support the discovery of subgroup specific somatic mutations in order to inform current clinical trials of targeted therapies, and to identify genes and pathways already targeted in other diseases. Such therapies could be rapidly transitioned to Phase II trials in medulloblastoma. Furthermore, the discovery of somatic mutations could be used for developing as well as validating specific biomarkers. The project team will also try to identify risk factors that predispose children to this type of cancer.

  Study EGAS00001000273

• BIOKEY: A single-cell catalogue of the dynamic changes underlying Checkpoint Immunotherapy response in Early Breast Cancer

  Checkpoint immunotherapy combined with neoadjuvant chemotherapy improves complete pathologic response in a subset of breast cancer patients. Here, we applied single-cell profiling to tumor biopsies collected before and during anti-PD1 therapy. One-third of tumors exhibited proliferative T-cells expanding along CD8+ or CD4+ lineages, which were either characterized by increased cytotoxicity and exhaustion or improved T-helper function, respectively. Lineage tracing in non-expanding tumors revealed at which point in the lineage T-cells were impaired, while gene expression modeling along these lineages revealed novel genes and underlying transcription factors involved in T-cell expansion. Interestingly, different dendritic and myeloid cell phenotypes could either stimulate or inhibit expanding T-cells, while cell-to-cell communication revealed an integrated immune context highly predictive of T-cell expansion, consisting of immune-stimulatory/-inhibitory interactions between cancer and various immune cell types. Our data yield unprecedented insights into the dynamic changes underlying checkpoint immunotherapy response in breast cancer.

  Study EGAS00001004809

• Whole-exome sequencing and microRNA profiling predicted relapse risk of stage I lung adenocarcinomas

  Despite the advance in precision therapy, about 20% of stage I non-small cell lung cancer patients suffer a relapse after surgical resection. To develop molecular signatures for relapse prediction of stage I lung adenocarcinoma (LUAD), we conduct comprehensive analyses of multiplatform molecular profiling from 113 treatment-naïve stage I Taiwanese LUAD patients. We identify 16 nonsynonymous non-sporadic point mutations (NSPOPMs) harbored at EGFR, KRAS, TP53, CTNNB1 and 6 other genes, and find that the Non-EGFR NSPOPMs were associated with early relapse in a dose-dependent manner via variant allele fraction (VAF). We define a score, maxVAF, to aggregate the VAFs of these NSPOPMs by the maximum value. MicroRNA expression analysis shows a strong correlation between miR-31 and maxVAF. Combining maxVAF with miR-31 led to a powerful risk prediction for surgically resected stage I patients (hazard ratio = 8.65, P = 0.001). Our study opens up more options for precision management of stage I LUAD patients.

  Study EGAS00001004461

• UROMOL 2020 - RNA-seq data

  The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we performed a large integrative multi-omics analysis of patients diagnosed with NMIBC (n=834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters.

  Study EGAS00001004693

• UROMOL 2020 - SNP data

  The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we performed a large integrative multi-omics analysis of patients diagnosed with NMIBC (n=834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters.

  Study EGAS00001004862

• The clinical utility of genomics in childhood cancer extends beyond targetable mutations

  Survival of children with relapsed cancer remains unacceptably low. Cancer genomic profiling may identify new therapeutic options, enhance diagnostic accuracy, and improve understanding of tumors’ origins and continued evolution. We deeply sequenced 864 cancer-associated genes and the complete genomes and transcriptomes for 300 pediatric and adolescent/young adult (AYA) patients with poor prognosis or rare tumors. Using integrative somatic-germline analyses, we assessed the clinical utility of cancer genomics in this population. We analyzed tumor mutational signatures and burden to interrogate the relevance of germline variants in DNA repair genes and the impact of therapeutic exposures on tumor evolution. We also evaluated the frequency of changes to tumor drivers and therapeutic targets at relapse in those with serial samples. Integrative analysis yielded clinically actionable variants in a majority of patients. Improved diagnostic accuracy led to modified management in a subset. Therapeutically targetable variants were of unanticipated timing and type, with many of these derived from the germline. Enrichment in corroborating mutational signature 3 (‘BRCAness’) in patients with germline homologous recombination defects suggests they are drivers of pediatric cancers and potential targets for PARP inhibition. We show that mutation burden, which may in part be driven by prior therapeutic exposures, was significantly elevated in a minority of patients. Over one-third of patients with sequential samples analyzed showed a change in therapeutically-targetable drivers. Comprehensive somatic-germline cancer genomic profiling is useful at multiple points in the care trajectory for pediatric/AYA patients, supporting its integration into early clinical management. Re-biopsy at the time of relapse should be considered, and specific attention to mutational burden is indicated. Defective DNA repair genes in the germline may represent important targetable drivers.

  Study EGAS00001006034

• The clinical utility of genomics in childhood cancer extends beyond targetable mutations - WGS data

  We deeply sequenced 864 cancer-associated genes and the complete genomes and transcriptomes for 300 pediatric and adolescent/young adult (AYA) patients with poor prognosis or rare tumors. Using integrative somatic-germline analyses, we assessed the clinical utility of cancer genomics in this population. Clinically actionable variants were identified in 56% of patients. Improved diagnostic accuracy led to modified management in a subset. Therapeutically targetable variants, found in 54% of patients, were of unanticipated timing and type, with over 20% of these derived from the germline. Enrichment in corroborating mutational signature 3 (‘BRCAness’) in patients with germline homologous recombination defects suggests they are drivers of pediatric cancers and potential targets for PARP inhibition. Comprehensive somatic-germline cancer genomic profiling is useful at multiple points in the care trajectory for pediatric/AYA patients, supporting its integration into early clinical management. Re-biopsy at the time of relapse should be considered, and specific attention to mutational burden is indicated. Defective DNA repair genes in the germline may represent important targetable drivers.

  Study EGAS00001006610

• The impact of mutational clonality in predicting the response to anti-PD-L1/PD-L1 in advanced urothelial cancer

  The advent of immune checkpoint inhibitors (ICI) has radically changed the management and therapeutic treatment landscape for patients with cancer. It has been shown that the use of these inhibitors can result in long-term complete remissions even in cases with advanced stages of the disease. However, only a small fraction of patients respond to the treatment. A better understanding of which factors could drive this clinical benefit is fundamental to building more accurate predictive biomarkers and developing alternative therapeutic options for patients who are unlikely to benefit. In order to address this issue, we have generated and analyzed whole exome sequencing (WES) and RNA sequencing (RNASeq) data from a cohort of metastatic urothelial carcinoma patients (N = 27) treated with ICI such as anti-PD-(L)1 monoclonal antibodies.

  Study EGAS00001007086

• Digital tEchnology For Lung Cancer Treatment

  The aim of the DEFLeCT project (Digital tEchnology For Lung Cancer Treatment) is to generate a technological platform for precision medicine in order to set predictive personalised algorithms for patient diagnosis and therapy. All resectable patients having histologically confirmed stage IB-IIIA non-small cell lung cancer(NSCLC) will be enrolled in the PROMOLE study, a related and ongoing observational prospective clinical study, for tissue sampling. A large biobank of lung cancer samples and the corresponding healthy tissues and biological components (ie, blood, stools, etc.) with complete clinical, pathological and molecular information will be collected. The project will lay the basis of a knowledge hub and qualified technology aimed not only at answering the medical and scientific community's questions, but also meant to be useful to individual patients by predicting the response to adjuvant and second-line drugs in case of relapse of the disease.

  Study EGAS00001007219

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

  Study EGAS00001004770

• Transcriptome Sequencing Data of High Grade Serous Ovarian Cancer

  Study EGAS00001004714

• Therapeutic Targeting of Ependymoma as Informed by Oncogenic Enhancer Profiling

  Genomic sequencing has driven precision-based oncology therapy; however, genetic drivers remain unknown or non-targetable for many malignancies, demanding alternative approaches to identify therapeutic leads. Ependymomas are chemotherapy-resistant brain tumours, which, despite genomic sequencing, lack effective molecular targets. Here, we mapped active chromatin landscapes in 42 primary ependymomas in two non-overlapping primary ependymoma cohorts. Enhancer regions revealed novel oncogenes, molecular targets, and pathways, which when subjected to small molecule inhibitor or shRNA treatment, increased survival and slowed proliferation in mouse and neurosphere patient-derived models of ependymomas. This study represents one of the largest enhancer mapping study of any cancer type to date, and provides a framework for target and drug discovery for other cancers recalcitrant to therapeutic development because of their lack of known genetic drivers.

  Study EGAS00001002696

• Comprehensive genomic profiles of small cell lung cancer

  We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. We found bi-allelic inactivation of TP53 and RB1 in nearly all the tumors analyzed, sometimes by complex genomic rearrangements. Two tumors with wild-type RB1 had evidence of chromothripsis leading to overexpression of Cyclin D1, revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumor suppressors TP53 and RB1 is obligatory in SCLC. We further discovered somatic genomic rearrangements of TP73 that create an oncogenic version of this gene, TP73Δex2/3. In few cases, SCLC tumors exhibited kinase gene mutations, providing a possible therapeutic opportunity for individual patients. Finally, we observed inactivating mutations in NOTCH family genes in 25% of human SCLC. Accordingly, activation of Notch signaling in a pre-clinical SCLC mouse model dramatically reduced the number of tumors and extended the survival of the mutant mice. Furthermore, neuroendocrine gene expression was abrogated by Notch activity in SCLC cells. This first comprehensive study of somatic genome alterations in SCLC uncovers several key biological processes and identifies candidate therapeutic targets in this highly lethal form of cancer.

  Study EGAS00001000925

• Whole Genome Sequencing Data of High Grade Serous Ovarian Cancer

  Longitudinal whole genome sequencing data to study chemoresponse in ovarian cancer. These samples belong to an ongoing sample collection and the data already includes hundreds of samples from over 200 patients. Samples are from primary and metastatic tissues and ascites. All patients have been treated with platinum-taxane based chemotherapy and majority of them are diagnosed with high-grade serous ovarian cancer.

  Study EGAS00001006775

• Single-cell RNA-sequencing reveals that glioblastoma recapitulates a normal neurodevetlopmental hierarchy

  We discovered a conserved neural tri- lineage cancer hierarchy centered around glial progenitor-like cells. We also found that this progenitor population contains the majority of the cancer’s cycling cells, and, using RNA velocity, is often the originator of the other cell types. Finally, we show that this hierarchal map can be used to identify therapeutic targets specific to progenitor cancer stem cells. Our analyses show that normal brain development reconciles glioblastoma development, suggests a possible origin for glioblastoma hierarchy, and helps to identify cancer stem cell-specific targets.

  Study EGAS00001004422

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

  Study EGAS00001005827

• Non-small cell lung cancer sequencing

  Study EGAS00001005499

• DATA-1169 test

  DATA-1169 testing

  Study EGAS50000000555

• The subclonal architecture of metastatic breast cancer: Results from a prospective community-based rapid autopsy program 'CASCADE'

  Background: Understanding the cancer genome is seen as a key step in improving outcomes for cancer patients. Genomic assays are emerging as a possible avenue to personalised medicine in breast cancer. The majority of work in this area has targeted primary tumours however, and very few studies have performed comprehensive profiling of advanced disease. Evolution of the cancer genome during the natural history of breast cancer is largely unknown, as is the profile of disease at death. We sought to study in detail these aspects of advanced breast cancers that have resulted in lethal disease. Methods and Findings: Three patients with ER-positive, HER2-negative breast cancer and one patient with triple negative breast cancer underwent rapid autopsy as part of an institutional prospective community-based rapid autopsy program. Cases represented a range of management problems in breast cancer, including late relapse after early stage disease; de novo metastatic disease; discordant disease response and disease refractory to treatment. Between 5 and 12 metastatic sites were collected at autopsy together with available primary tumours and longitudinal metastatic biopsies taken during life. Samples underwent paired tumour-normal whole exome sequencing and single nucleotide polymorphism arrays. Subclonal architectures were inferred by jointly analysing all samples from each patient. Mutations were validated using high depth amplicon sequencing.Between cases, there were significant differences in mutational burden, driver mutations, mutational processes and copy number variation. Within each case, we found dramatic heterogeneity in subclonal structure from primary to metastatic disease and between metastatic sites, such that no single lesion captured the breadth of disease. Metastatic cross seeding was found in each case and treatment drove subclonal diversification. Subclones displayed parallel evolution of treatment resistance in some cases, and apparent augmentation of key oncogenic drivers as an alternative resistance mechanism. We also observed the key role of mutational processes in subclonal evolution.Limitations of this study include the potential for bias introduced by joint analysis of formalin fixed archival specimens with fresh specimens, and the difficulties in resolving subclones with whole exome sequencing. Other alterations that could define subclones such as structural variants or epigenetic modifications were not assessed. Conclusions: This study highlights the variety of mechanisms that shape the genome of metastatic breast cancer, and the value of studying advanced disease in detail. Treatment drives significant genomic heterogeneity in breast cancers which has implications for disease monitoring and treatment selection in the personalised medicine paradigm.

  Study EGAS00001002153

• Whole-exome sequencing of breast cancer metastasis and corresponding blood samples

  This study included samples from metastatic breast cancer patients who underwent a biopsy in the context of SAFIR01 (NCT01414933), SAFIR02 (NCT02299999), SHIVA (NCT01771458) and MOSCATO (NCT01566019) prospective trials. These French multicentre trials used high throughput genome analysis on fresh frozen tumor biopsies as a therapeutic decision tool for metastatic cancer patients, with solid cancers (SHIVA, MOSCATO) or specifically with breast cancer (SAFIR01, SAFIR02). All patients gave their informed consent for translational research and genetic analyses of their somatic DNA. Overall, whole-exome sequencing for a total of 216 pairs of metastatic tumor and unmutated DNA derived from corresponding blood samples was performed using Illumina technology. The results of the analysis of the mutational profile of metastatic breast cancer was reported in Lefebvre et al. (PMID:28027327).

  Study EGAS00001001695

• ICGC PanCancer Analysis of Whole Genomes

  Study EGAS00001001692

• A novel transcriptional signature identifies T-cell infiltration in high-risk paediatric cancer

  Background Molecular profiling of the tumour immune microenvironment (TIME) has enabled the rational choice of immunotherapies in some adult cancers. In contrast, the TIME of paediatric cancers is relatively unexplored. We speculated that a more refined appreciation of the TIME in childhood cancers, rather than a reliance on commonly used biomarkers such as tumour mutation burden (TMB), neoantigen load and PD-L1 expression, is an essential prerequisite for improved immunotherapies in childhood solid cancers. Methods We combined immunohistochemistry (IHC) with RNA-sequencing and whole genome sequencing across a diverse spectrum of high-risk paediatric cancers to develop an alternative, expression-based signature associated with CD8+ T-cell infiltration of the TIME. Further, we explored transcriptional features of immune archetypes, T-cell receptor sequencing diversity, assessed the relationship between CD8+ and CD4+ abundance by IHC and deconvolution predictions, and assessed common adult biomarkers such as neoantigen load and TMB. Results A novel 15-gene immune signature, Immune Paediatric Signature Score (IPASS), was identified. Using this signature, we estimate up to 31% of high-risk cancers harbour infiltrating T-cells. In addition, we showed that PD-L1 protein expression is poorly correlated with PD-L1 RNA expression and TMB and neoantigen load are not predictive of T-cell infiltration in paediatrics. Furthermore, deconvolution algorithms are only weakly correlated with IHC measurements of T-cells. Conclusions Our data provides new insights into the variable immune-suppressive mechanisms dampening responses in paediatric solid cancers. Effective immune-based interventions in high-risk paediatric cancer will require individualised analysis of the TIME.

  Study EGAS00001007029

• The Medical Genome Reference Bank: a whole genome data resource of 4,000 healthy elderly individuals.

  Allele frequency data from human reference populations is of increasing value for filtering and assignment of pathogenicity to genetic variants. Aged and healthy populations are more likely to be selectively depleted of pathogenic alleles, and therefore particularly suitable as a reference populations for the major diseases of clinical and public health importance. However, reference studies of the healthy elderly have remained under represented in human genetics. We have developed the Medical Genome Reference Bank (MGRB), a large scale comprehensive whole genome dataset of confirmed healthy elderly individuals, to provide a publicly accessible resource for health related research, and for clinical genetics. It also represents a useful resource for studying the genetics of healthy aging. The MGRB comprises 4,000 healthy, older individuals with no reported history of cancer, cardiovascular disease or dementia, recruited from two Australian community based cohorts. DNA derived from blood samples will be subject to whole genome sequencing. The MGRB will measure genome wide genetic variation in 4,000 individuals, mostly of European decent, aged 60 to 95 years (mean age 75 years). The MGRB has committed to a policy of data sharing, employing a hierarchical data management system to maintain participant privacy and confidentiality, whilst maximizing research and clinical usage of the database. The MGRB will represent a dataset of international significance, broadly accessible to the clinical and genetic research community.

  Study EGAS00001003511

• Whole genome, transcriptome and methylome profiling enhances actionable target discovery in high-risk paediatric cancer

  Zero Childhood Cancer is a precision medicine program to benefit children with poor-outcome, rare, relapsed or refractory cancer. Utilising tumour and germline whole genome sequencing (WGS) and RNA sequencing (RNAseq) across 252 tumours from high-risk paediatric cancer patients, we identified 968 reportable molecular aberrations (39.9% in WGS and RNAseq, 35.1% WGS-only, 25.0% RNAseq-only). 93.7% of patients had at least one germline or somatic aberration, 71.4% had therapeutic targets and 5.2% had a change in diagnosis. WGS identified pathogenic cancer-predisposing variants in 16.2% of patients. In 76 CNS tumours, methylome analysis confirmed diagnosis in 71.1% and contributed to a change of diagnosis in two cases (2.6%). To date 43 patients have received a recommended therapy, 38 of whom could be evaluated. A small but encouraging proportion of 31% showed some evidence of clinical benefit. Comprehensive molecular profiling resolved the molecular basis of virtually all high-risk cancers, which in some cases has significant clinical impact.

  Study EGAS00001004572

• Molecular subsets in renal cancer determine outcome to checkpoint and angiogenesis blockade

  We conducted integrated multi-omics evaluation of 823 tumors from advanced renal cell carcinoma (RCC) patients and identified molecular subsets associated with differential clinical outcomes to angiogenesis blockade alone or with a checkpoint inhibitor. Unsupervised transcriptomic analysis revealed six molecular subsets with distinct angiogenesis, immune, cell cycle, metabolism, and stromal programs. While sunitinib was effective in subsets with high angiogenesis, atezolizumab+bevacizumab improved clinical benefit in tumors with high T-effector and/or cell cycle transcription. Somatic mutations in PBRM1 and KDM5C associated with high angiogenesis and AMPK/Fatty acid oxidation gene expression, while CDKN2A/B and TP53 alterations were more prevalent in tumors with increased cell cycle and anabolic metabolism. Sarcomatoid tumors exhibited low prevalence of PBRM1 mutations and angiogenesis markers, frequent CDKN2A/B, BAP1 and TP53 alterations, and increased PD-L1 expression. These findings can be applied to molecularly stratify advanced RCC patients, explain improved outcomes of sarcomatoid tumors to checkpoint blockade, and develop personalized therapies.

  Study EGAS00001004353

• Comprehensive molecular profiling identifies novel genetic drivers and subtypes underlying medulloblastoma

  Current therapies for medulloblastoma (MB), a highly malignant childhood brain tumor, impose debilitating effects on the developing child, warranting the development of molecularly targeted treatments with reduced toxicities. Prior studies have failed to disclose the full spectrum of driver genes and molecular processes operative in MB or adequately explain heterogeneity among molecular subgroups. Herein, we detail the somatic landscape across 491 sequenced MBs and molecular heterogeneity amongst 1,256 epigenetically analyzed cases, identifying subgroup-specific mutational signatures, driver genes, and pathway alterations including previously unappreciated actionable therapeutic targets. Integrative approaches for assigning driver genes to subgroups explained >65-70% of Group 3 and Group 4, doubling previous knowledge. Novel subtypes underlying Group 3 and Group 4 were differentially enriched for specific driver events, including hotspot in-frame indels targeting KBTBD4 and ‘enhancer hijacking’ driving activation of PRDM6. Thus, application of integrative genomics to an unprecedented cohort of clinical samples derived from a single childhood cancer entity has disclosed a series of new cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for treating MB.

  Study EGAS00001001953

• The Proteogenomic Subtypes of Acute Myeloid Leukemia

  Acute myeloid leukemia (AML) is an aggressive blood cancer with poor prognosis. We report a comprehensive proteogenomic analysis of bone-marrow biopsies from 252 uniformly treated AML patients to elucidate the molecular pathophysiology of AML in order to inform future diagnostic and therapeutic approaches. In addition to in-depth quantitative proteomics, our analysis includes cytogenetic profiling and DNA/RNA sequencing. We identify five proteomic AML subtypes, each reflecting specific biological features spanning genomic boundaries. Two of these proteomic subtypes correlate with patient outcome, but none are exclusively associated with specific genomic aberrations. Remarkably, one subtype (Mito-AML), which is only captured in the proteome, is characterized by high expression of mitochondrial proteins and confers poor outcome, with reduced remission rate and shorter overall survival upon treatment with intensive induction chemotherapy. Functional analyses reveal that Mito-AML is metabolically wired towards stronger complex I dependent respiration and is more responsive to treatment with the BCL2 inhibitor venetoclax.

  Study EGAS00001005950

• Mutational_burden_in_oesophagus_following_chemotherapy_and_radiotherapy_treatment_WGS

  We wish to assess the changes in signature and mutational burden in patients who have undergone either chemotherapy or chemotherapy + radiotherapy. Using duplex sequencing will assess the mutational landscape in oesophageal epithelia in patients who have undergone these treatment regimes.

  Study EGAS00001007415

• The_effects_of_chemotherapy_and_radiation_in_human_oesophageal_epithelium__low_input

  Human oesophagus is a patchwork of competing mutant clones. We wish to see how this patchwork is altered under the extreme selection pressures of chemotherapy and radiotherapy both individually and combined. We will sequence 0.25mm diameter punch biopsies from patients who have undergone chemotherapy and radiotherapy to assess how the mutational landscape has changed.

  Study EGAS00001007416

• The_effects_of_chemotherapy_and_radiation_in_human_oesophageal_epithelium

  Human oesophagus is a patchwork of competing mutant clones. We wish to see how this patchwork is altered under the extreme selection pressures of chemotherapy and radiotherapy both individually and combined. We will sequence 2mm2 contiguous pieces of oesophageal epithelium from patients who have undergone chemotherapy and radiotherapy to assess how the mutational landscape has changed.

  Study EGAS00001007417

• Clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial

  ABACUS is a single arm phase 2 study that investigated 2 cycles of atezolizumab (1200mg Q3) prior to cystectomy in 95 patients with muscle invasive transitional cell cancer (T2-4N0M0). Pathological complete response (pCR) occurring in ≥20% of patients was the primary endpoint. Biomarker analysis on sequential tissue was a co-primary endpoint.

  Study EGAS00001004445

• 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

• Spatial Transcriptomics on prostate cancer heterogeneity

  Intratumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies.

  Study EGAS00001003001

• Deciphering somatic mosaic structural variation in human blood lineages using single-cell multiomics

  Somatic mosaicism (SM), referring to the presence of somatic mutations in sub-populations of cells within healthy individuals, is associated with an increased risk of a variety of diseases, including cancer. Blood is at particularly high risk of SM, given its rapid turnover and functionally- heterogeneous cell-type composition. While the roles of point mutations and large-scale rearrangements in blood SM have been scrutinised in recent years, the functional impact of mosaic structural variants (mSVs) remains poorly understood. Using haplotype-resolved single-cell multi-omics, we explored the mSV landscape of human hematopoietic stem and progenitor cells (HSPCs).

  Study EGAS00001006567

• Genome-wide discovery of somatic coding and regulatory variants in Diffuse Large B-cell Lymphoma

  Diffuse large B-cell lymphoma (DLBCL) is an aggressive cancer originating from mature B-cells. Prognosis is strongly associated with molecular subgroup, although the driver mutations that distinguish the two main subgroups remain poorly defined. Through an integrative analysis of whole genomes, exomes, and transcriptomes, we have uncovered genes and non-coding loci that are commonly mutated in DLBCL. Our analysis has identified novel cis-regulatory sites, and implicates recurrent mutations in the 3'UTR of NFKBIZ as a novel mechanism of oncogene deregulation and NFκB pathway activation in the activated B-cell (ABC) subgroup. Small amplifications associated with over-expression of FCGR2B (the Fcγ receptor protein IIB), primarily in the germinal centre B-cell (GCB) subgroup, correlate with poor patient outcomes suggestive of a novel oncogene. These results expand the list of subgroup driver mutations that may facilitate implementation of improved diagnostic assays and could offer new avenues for the development of targeted therapeutics.

  Study EGAS00001002936

• EGA synthetic data

  Synthetic Data One of the limitations in genomics research is that human genomics data is not openly available; access must be controlled according to participant consent agreements and data protection regulations such as GDPR. Obtaining authorization to access such data can sometimes take a long time, resulting in delays to important research work. In this context, synthetic genomic and phenotype data can be useful resources for researchers to avoid these delays. Synthetic data are artificially generated datasets, often created with algorithms, which can be used without the need for authorization to test new products and tools, build technical demonstrators, validate data models, and train AI models. The EGA provides access to synthetic cohort datasets augmented with rich synthetic metadata that overcomes these real data usage restrictions. Whilst synthetic datasets are not included in the general EGA mandate and services, we can consider such submissions and evaluate their acceptance on the basis of their unique use cases not already covered by existing synthetic datasets. All synthetic data studies are open and permission will be granted automatically, however it is still required to request access. Requests are handled by the responsible DAC at Central EGA or the relevant Federated EGA Node. Study ID Title Located in EGAS00001002472 CINECA synthetic cohort EUROPE UK1 referencing fake samples Central EGA EGAS00001005591 Synthetic data - Genome in a Bottle Central EGA EGAS00001005042 Test Study for EGA using data from 1000 Genomes Project - Phase 3 Central EGA EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Central EGA EGAS50000000190 EOSC4Cancer Synthetic Colorectal Cancer Genomic data Central EGA EGAS50000001932 Synthetic longitudinal breast cancer whole-genome sequencing dataset Central EGA EGAS50000000086 Synthetic - FEGA Sweden Heilsa synthetic dataset December 2023 Federated EGA Sweden EGAS50000000678 Synthetic - GDI synthetic data Federated EGA Spain

  Documentation synthetic-data

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an AND operator when a space is inserted between two words. Include OR (capitalised) between the keywords in your search in order to show pages containing either term or both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• What is the cBioPortal

  EGA cBioPortal What is the EGA cBioPortal? EGA hosts a dedicated cBioPortal instance that enables authorized researchers to explore and visualize selected cancer datasets archived at EGA. Data submitters can also contribute cancer datasets to be made available through the portal. The platform provides interactive tools to analyse genomic and clinical data once access has been granted by the relevant Data Access Committee (DAC). How to find and access an EGA cBioPortal Dataset 1. Register as an EGA user 2. Go to the dataset page of interest. You can use the Search function to find datasets available in cBioPortal. If the dataset is available on the EGA cBioPortal Instance, the cBioPortal icon will be displayed on the dataset page, as shown below: On the dataset page, you will find information about access requirements. For more details, please visit how to request access. 3. Once access has been granted Go to the EGA cBioPortal instance and log in with your EGA user accountThe approved dataset will be listed in cBioPortalSelect the dataset to start exploring the data What you can do in cBioPortal The EGA cBioPortal is designed for interactive exploration and visualization of controlled-access cancer datasets, including: Visualising genomic alterationsAnalysing mutation patternsFiltering by clinical attributesComparing molecular profilesGenerating plots and summaries Important Notes Datasets are only visible in cBioPortal after DAC approvalAccess requests must always be submitted through the EGA website If you encounter any issues gaining access to a dataset, please contact EGA Support.If your question is related to the cBioPortal features, please reach out to: cbioportal@googlegroups.com. The EGA Helpdesk does not support this platform. How to link a dataset to the EGA cBioPortal instance during a submission STEP 0 – Verify the cBioPortal metadataFollow the instructions at https://github.com/EGA-archive/ega-cbioportal to verify that your cBioPortal metadata can be successfully imported into the EGA.STEP 1 – cBioPortal File Upload to EGA Files must be uploaded to the SFTP INBOX. The supported cBioPortal file types are: Raw data (e.g., VCF files)cBioPortal-specific formats (e.g., MAF files) STEP 2 – Register the cBioPortal dataset in the Submitter Portal Register the cBioPortal files in an analysis objectRegister a dataset with the title “cBioPortal Metadata” and include the analysis and nothing else Please note that cBioPortal is not directly supported by the EGA Helpdesk. For questions about the platform, please visit the cBioPortal website or contact the cBioPortal support team at cbioportal@googlegroups.com. The EGA does not support this platform.

  Documentation submission/metadata/submission/cbioportal

• Submission FAQ

  Submission FAQ Before Submission Is the EGA the right archive for my data? The most suitable archive for your data is dependent on the type of data you are wishing to submit and whether the data require public or controlled access. Public access is defined as complete and open access to all submitted data. On the contrary, controlled access, exerted by the EGA, requires formal applications to be made to access the submitted data files and metadata. EGA only accepts human-derived data subject to controlled access. If your submission contains other types of data, please choose the appropriate repository for it (see image below): ENA, EVA, ArrayExpress, BioSD and GWAS catalog.  Should your submission be subjected to controlled access? Data access conditions are normally defined in the original informed consent agreements signed by the participants involved in your study. All data submitted to the EGA is subject to controlled access. These consents prevent the derived data files, potentially identifiable, from being dispersed by open and public access. Controlled access data often refers to human data derived from medical research and consortium projects. If in doubt, consult the informed consent agreements that apply to your study The EGA enables you to hold a submission before publication. What data types can be submitted to the EGA? Data types accepted by the EGA can be split into three categories: Sequences: both in generic and platform-specific formats. Array-based: from raw signal files to processed matrices. Phenotypes: all possible phenotype formats are accepted. All manufacturer-specific raw data formats derived from major next generation sequencing platforms are accepted. Also generic sequence formats: flat reads in a FASTQ file, aligned sequences (BAM or CRAM files) as well as sequence variation files in VCF format. All array-based technologies are accepted, including raw data, intensity and analysis files, without any restriction on data formats accepted. We also accept and distribute phenotype data (associated to the samples). How long does a submission take? Submissions to EGA come in a variety of formats and sizes, thus it is difficult for us to exactly predict how long a submission will take. We, therefore, advise all of our submitters to allow as much time as possible to make a submission. Based on previous records, we anticipate that the submission process may take at least one month. The submitter’s familiarity with the procedures, possible technical issues that may arise during submission and the amount of data that is being submitted are the main factors that will affect the length of the submission process. However, each step of a regular submission should be considered when estimating the time it would take: Encryption of the files Upload of the files Metadata submission Archival of the files Release of the study and datasets to EGA webpage For example, the upload of the files depends on the submission size, while metadata submission mainly relies on each submitter’s expertise. Further, some steps (e.g. answering to inquiries) depend on the EGA Helpdesk team, which may take some days to be processed during busy times Is data deposited in the EGA secure? The EGA set-up consists of a secure computing facility for data processing, a shared EBI set-up for data submissions and distribution of data via data requests made through the EGA website. Data is also copied in the Barcelona Supercomputing Center (BSC) infrastructure, where all stored and distributed data is encrypted Data is encrypted along the submission process and stored securely, granting its access to authorised users exclusively. During the download process, through our Python Client or Aspera, all requested data is downloaded over secure https connections. All data at the EGA is encrypted, and only accessible (for log-in and download) through secure protocols. For further information please, visit our security overview. What documentation do I need to provide? All submissions require policy’s documentation: 'Data Access Agreement (DAA)', 'Data Processing Agreement (DPA)' and 'Authorized Submitters Formulary'. The data processors (EGA) and the data owners will also sign the DPA. Will all metadata be public? Among the submitted metadata we need to make the distinction between identifiable and unidentifiable metadata: (1) the former may allow the identification of the human the sample derived from (e.g. detailed geographical providence, personal name, family ancestry…); (2) while the latter can be used to interpret the data without compromising the anonymity of the patients. The majority of the metadata submitted to the EGA corresponds to the unidentifiable category (e.g. sequencer's model). This type of metadata is publicly available on the EGA website and other EBI resources/partners’ websites. On the other hand, some parts samples’ metadata are subject to being identifiable, and thus only accessible by authorized data requesters, with the exception of: 5 submitter-defined attributes of the sample: alias, title, subject_id, gender and phenotype. It is the submitter’s responsibility not to submit sensitive metadata in these public fields. 3 anonymised fields that pinpoint the sample record in archivals: sample’s EGA stable ID (EGAN…), BioSample ID (SAMEA…) and submitter’s center name. During Submission Are there any sample specific requirements for EGA? All samples submitted to the EGA must include the attributes of biological sex, subject ID (anonymised individual identifier) and phenotype information. These are critical for data findability and its analysis, and we highly recommend using controlled ontology terms where applicable. For example: defining tumour and non-tumour samples and/or defining disease state. The EGA recommends using the Experimental Factor Ontology Database to find ontologized terms that describe your sample phenotypes. How do I get an accession number to use in my publication? You will receive your study accession number (EGAS…) upon complete your submission, either: Programmatically. As soon as the metadata is submitted and validated your study will be assigned an accession number that will be given in the submission’s response. Manually registering your study and relevant metadata using the online metadata submission tool: the EGA submitter Portal. How are files uploaded to the EGA? Data files are uploaded into private submission drop boxes (i.e. environments to which you are granted access and where you can transfer your files) using INBOX or FTP. These spaces are provided as part of the submission procedure. Before uploading any file, you must encrypt your files, . Only encrypted files shall be uploaded to the drop boxes. Why does data need to to encrypted for my submitted files? It is one of the security steps the EGA has implemented. In case of a security breach, people without the proper encryption key will not be able to read or use the information that could have been leaked. This measure is essential when working with sensitive data, such as controlled access human data. All submitters must use crypt4gh to create EGA compliant files prior to uploading them. This encryption is GPG-based, using EGA’s public key. Why are my files not available if I see them in the INBOX? There exists a time window between the data upload and the availability of such files via the Submitter Portal. For this reason, some metadata (run and analysis objects) cannot be registered until at least 24 hours after the files have been uploaded to your box. Why are MD5 sum values generated for my submitted files? We require pre- and post- encryption MD5 (message-digest) checksum values to be provided for all submitted files. These 128-bit values are computed using the content of each file, creating unique sequences that allow us to ensure that file integrity has been maintained during the transfer process. In other words, if the MD5 checksums we generate and those you generated match, we infer that the content of the transferred files is correct (i.e. files are not corrupted or truncated). MD5 checksums are computed automatically using the crypt4gh tool provided. Your submission will not be accepted and may be significantly delayed if you do not provide MD5 checksum values for all data files in the required format. How can I check if my files are correctly uploaded to the inbox? It is important to check the status pf your file so you know whether your files are in the inbox, being processed, or if there is any issue with one of them. In order to check this, you should: Look for the file locally. Drag and drop it to the file table. Then bars will appear on the table, which means that we are processing it. Green: The files checksum are correct and your file will move to “ingested files”. No further actions are needed from your end.. Red: The files checksum does not match and your file needs to be re-uploaded. Please re-upload relevant files to your inbox using the same path. How can I add my dataset to the cBioPortal instance? In order to link your data to the cBioPortal, you must register it as a normal dataset in the Submitter Portal. For more information, please refer to the cBioPortal documentation. After Submission How do I use my accession number in my publication? We suggest the use of the below template, using your study accession ID (EGAS…) : Data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX. Further information about EGA can be found at https://ega-archive.org and "The European Genome-phenome Archive of human data consented for biomedical research" Your study ID will be the one that groups your whole submission, and thus its usage is recommended as such. Nevertheless, all metadata submitted to EGA hold a unique and persistent identifier (starting with EGA…) that can be used to identify specific records. For example, you could reference a specific dataset (EGAD…) or sample (EGAN…) in your publications (see full list of identifiers). How do I make my data searchable? Once you have finalized your submission, you can schedule the data release. Please take into account that the release process needs time for the files to be archived in our system, and for the Helpdesk team to validate your submission. Can I withdraw (meta)data from the EGA? We have methods in place for the secure removal of deposited (meta)data. Contact EGA-helpdesk for further details. EGA complies with FAIRness of (meta)data, and thus, even when the data is removed we keep an entry for their identifiers in our system. In other words, we execute a soft delete on canceled objects (e.g. a study): metadata is still stored in our systems, but it loses all links, cannot be queried and data files cannot be retrieved anymore. The reason behind this behaviour is so that queries using withdrawn data properly respond back (see example of a canceled study). What happens to the data once it has been submitted to the EGA? When the data is submitted, the submitter can choose either keep their data private or schedule the release of their data.

  Documentation submission/metadata/submission/FAQ

• Projects

  Projects Jointly managed by the European Bioinformatics Institute (EMBL-EBI) in Cambridge (UK) and the Centre for Genomic Regulation (CRG) in Barcelona, the EGA provides an invaluable service to the worldwide biomedical research community. The teams leading the EGA are involved in several international partnerships and consortia in numerous scientific fields, where they contribute to ambitious projects. In addition to the project listed below, the EGA is in a long-standing partnership with the Global Alliance for Genomics and Health (GA4GH), as described on the dedicated page. On-going projects Project Duration Domain Funder Tags SCAILED | SCAILED (SCale-up Biotech AI Innovation by Leveraging Responsible Data Use under the European Health Data Space) aims to accelerate the development and deployment of Artificial Intelligence (AI) and digital solutions in the European biotech sector by harnessing high-quality health data within the secure, interoperable framework of the European Health Data Space (EHDS). 2026-2029 AI solutions; EHDS EU4Health Programme ACCESS DOCUMENTATION INFRASTRUCTURE CANDLE | CANDLE project aims to conceptualise and advance the development of National Cancer Data Nodes (NCDNs) in European countries. These NCDNs will boost the reuse of cancer data for research, innovation and policy making, in order to improve diagnostics and treatment for cancer patients, as well as prevention and early detection. 2025-2028 Cancer Horizon Europe DOCUMENTATION EASIGEN-DS | The EASIGEN-DS project aims to conduct a design study to establish a new European Research Infrastructure on Advanced Genomics Technologies, EASIGEN. To develop an excellent scientific, technological and operational design, we will conduct landscape studies, stakeholder consultations, and community surveying. 2025-2028 Genomic and health data Horizon Europe DATA MANAGEMENT DOCUMENTATION INFRASTRUCTURE Go-IMPaCT | Go-IMPaCT will contribute sequenced genomes and provide infrastructure as part of IMPaCT-Cohort, one of the three fundamental pillars of the Precision Medicine Infrastructure associated with Science and Technology (IMPaCT) program in Spain. Along with the Genome of Europe (GoE) project, around 18.000 people will have their genomes sequenced, also contributing to Spain's commitments in 1+MG. Go-IMPaCT will fund the development of an EGA node to manage and share this genomic and phenoclinic data, laying the foundations for regional and ethnic genomic variability in Spain to be available for research purposes. The IMPaCT cohort is created with the spirit of being an open research tool, compatible with the rest of the health research ecosystem, and other international initiatives. 2025-2027 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS FAIR-FEGA | This project seeks to accelerate data depositions into FEGA, significantly increasing the data flow in and from FEGA nodes. It will build capacity within the FEGA nodes and increase awareness in a wide range of stakeholders, thus altogether achieving the ultimate goal of enhancing data reuse. The project will be carried out by a strategic consortium comprising seven ELIXIR nodes and two ELIXIR communities. 2025-2026 Not applicable ELIXIR ACCESS DISCOVERY DOCUMENTATION INFRASTRUCTURE METADATA STANDARDS FEGA-Connect | A consortium of six ELIXIR nodes plus the Polish FEGA node (in-kind contribution) joining forces to build a solid base to develop solutions for effective multi-omic sensitive data integration between FEGA nodes and other infrastructures and specialised Data repositories. We aim to promote a more coherent data deposition, discoverability and retrieval of multi-omics datasets, providing FAIRer data and consequently accelerating research. 2025-2026 Multi-omics data ELIXIR ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE METADATA STANDARDS IMPaCT-Data 2 | IMPaCT-Data 2 will develop a digital platform for the integration and modelling of biomedical data associated with IMPaCT (Precision Medicine Infrastructure associated with Science and Technology) projects in Spain. It will deploy a sustainable infrastructure that facilitates the integration, standardisation, interoperability and analysis of clinical, genomic, molecular and medical imaging data. This platform will be aligned with European projects such as Genome of Europe (GoE), the first project to make use of the European Genomic Data Infrastructure (GDI), and EUCAIM. IMPaCT-Data 2 will benefit from advanced Artificial Intelligence and High Computing Capacity Systems capabilities, offering robust and accessible tools for researchers from the National Health System in Spain. 2025-2026 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS SenSec | This project aims to establish a mechanism for orchestrating secure access to sensitive data hosted by the EGA, whether in Central EGA or any Federated Node, from Galaxy, a popular open-source, community-driven VRE (Virtual Research Environment) for bioinformatics analysis. Building on a previous prototype that enabled Galaxy users within Trusted Research Environments (TREs) to decrypt sensitive data for workflow execution without sharing private encryption keys, SenSec will expand this prototype into a comprehensive solution for secure data analysis in Galaxy, facilitating encrypted data access and transfer from FEGA/EGA repositories to designated TREs. 2025-2026 Genomic and health data; trusted research environment ELIXIR ACCESS DATA ANALYSIS ERDERA | The European Rare Disease Research Alliance (ERDERA) takes over EJPRD to deliver concrete health benefits to rare disease patients in the next decade by advancing prevention, diagnosis and treatment research. To leave no one behind, over 170 organisations championed by the European Union and member states are working hand in hand to make Europe a world leader in rare diseases research and innovation. 2024-2034 Rare diseases Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution ACCESS DATA ANALYSIS DISCOVERY INFRASTRUCTURE SYNTHIA | The aim of SYNTHIA is to deliver validated, reliable tools and methods for synthetic data generation (SDG). The tools will cover multiple data types including lab results, clinical notes, genomics, imaging and m-health data. SYNTHIA also hopes to make possible the generation of longitudinal data. 2024-2029 Genomic and health data; multi-omics; AI solutions Innovative Health Initiative (IHI) DATA ANALYSIS DATA MANAGEMENT INFRASTRUCTURE GoE | The Genome of Europe initiative aims to build a European network of national genomic reference cohorts of at least 500.000 citizens. These reference cohorts will be selected to be representative of the European population. 2024-2028 Large-scale genomic and health data Horizon Europe ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS HEREDITARY | HEREDITARY aims to transform the way we approach disease detection, prepare treatment response, and explore medical knowledge by building a robust, interoperable, trustworthy, and secure framework that integrates multimodal health data (including genetic data) while ensuring compliance with cross-national privacy-preserving policies. 2024-2027 Neurodegenerative disorders, gut-brain interplay Horizon Europe DATA MANAGEMENT DATA ANALYSIS EOSC-ENTRUST | The mission of EOSC-ENTRUST is to create a European network of trusted research environments for sensitive data and to drive European interoperability by joint development of a common blueprint for federated data access and analysis. 2024-2026 Trusted Research Environment Horizon Europe INFRASTRUCTURE EBV-MS | "Targeting Epstein-Barr Virus Infection for Treatment and Prevention of Multiple Sclerosis". The ambitious goals of the project are to answer the questions why only a few EBV infected persons develop MS, and define the underlying mechanism of this process, as well as clarify if targeting the EBV infection can prevent MS or improve the disease course. 2023-2028 Viral-host genetics; immune response; disease modelling; disease prevention; AI/ML solutions Horizon Europe DATA MANAGEMENT DATA ANALYSIS WISDOM | WELL-BEING IMPROVEMENT THROUGH THE INTEGRATION OF HEALTHCARE AND RESEARCH DATA AND MODELS WITHOUT BORDER FOR CHRONIC IMMUNE-MEDIATED DISEASES aims to deploy novel approaches for data processing, harmonisation, management, and secure data sharing and federated access for diseases like multiple sclerosis. Using an end-user guided approach, it will facilitate responsible and critical assessment of the use of AI in healthcare. 2023-2028 Chronic immune-mediated diseases Horizon Europe DATA MANAGEMENT INFRASTRUCTURE EUCAIM | EUropean Federation for CAncer IMages is a project that will build a highly secure, federated and large-scale European cancer imaging platform, with capabilities that will greatly enhance the potential of Artificial Intelligence in oncology. 2023-2027 Cancer Digital Europe Programme (DIGITAL) DISCOVERY CONTAGIO | CONTAGIO (COhorts Network To be Activated Globally In Outbreaks) aims to create coordination mechanisms to rapidly react to infectious disease (re-)emergence in low- and middle-income countries (LMICs). 2023-2026 Infectious Diseases European Commission - Horizon Europe ACCESS DATA MANAGEMENT DISCOVERY Youth-GEMs | Youth-GEMS (Gene Environment Interactions in Mental Health TrajectorieS of Youth) will conduct research into the genetic and environmental factors of mental health in young European people. 2022-2027 Mental health European Commission - Horizon Europe DATA MANAGEMENT DISCOVERY GDI | The European Genomics Data Infrastructure project is enabling access to genomic and related phenotypic and clinical data across Europe. It is doing this by establishing a federated, sustainable and secure infrastructure to access the data. 2022-2026 Genomic and health data European Commission - Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution DISCOVERY DOCUMENTATION INFRASTRUCTURE IMPaCT-T2D | The IMPaCT-T2D project aims at studying the complete genomes of a large cohort of patients with Type 2 Diabetes mellitus (T2D), using modern sequencing technologies and artificial intelligence (AI) in order to improve the stratification and pharmacological treatment in the context of precision medicine. 2022-2025 Cardiovascular and Complex Diseases Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE Completed projects Project Duration Domain Funder Tags EOSC4Cancer | EOSC4Cancer builds on existing projects, research outcomes and established community solutions to create the federated FAIR data, analysis and services infrastructure needed for European Cancer research programmes. 2022-2025 Cancer European Commission - Horizon Europe DISCOVERY EuCanImage | A European Cancer Image Platform Linked to Biological and Health Data for Next-Generation Artificial Intelligence and Precision Medicine in Oncology. 2020-2025 AI Solutions in Oncology European Commission - H2020 Programme; "La Caixa" Foundation cofunds CRG's contribution DATA MANAGEMENT METADATA STANDARDS GenoMed4ALL | A consortium built to empower personalised medicine in the field of haematological diseases through the use of AI and the pooling of genomic and clinical data. 2020-2025 Hematological diseases European Commission - H2020 Programme DISCOVERY METADATA STANDARDS BY-COVID | The BeYond-COVID project aims to make COVID-19 data accessible to scientists in laboratories but also to anyone who can use it, such as medical staff in hospitals or government officials. Going beyond SARS-CoV-2 data, the project will provide a framework for making data from other infectious diseases open and accessible to everyone. 2021-2024 Infectious diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE IMPaCT-Data | IMPaCT-Data aims to create the infrastructure for secondary use of data from Spanish healthcare systems - electronic health records, medical imaging and genomic repositories - and contribute with the knowledge and methodology produced to the healthcare system. 2021-2024 Large-scale genomics and health dataSpanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE LaMarato | It is a project aimed at creating and developing a catalan interhospitalary network to interrogate genetic variants from thousands of genetic tests carried out in patients with rare diseases from the main catalan hospitals. 2021-2024 Genomic and health data Fundacio La Marato de TV3 (catalan foundation) DISCOVERY HealthyCloud | This consortium will contribute a Strategic Agenda towards the European Health Research and Innovation Cloud. The project will work in collaboration with a broad range of stakeholders to ensure that all voices are included and that the results are technically and ethically sound. 2021-2023 Not Applicable European Commission - H2020 Programme DOCUMENTATION B1MG | Beyond 1 Million Genomes aims to create a network of genetic and clinical data across Europe. The project provides coordination and support to the 1+ Million Genomes Initiative (1+MG). This initiative is a commitment of 24 EU countries, the UK and Norway to give cross-border access to one million sequenced genomes by 2022. 2020-2023 Not applicable European Commission - Horizon Europe DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS ELIXIR-CONVERGE | An alliance with the goal of Connecting and aligning ELIXIR Nodes to deliver sustainable FAIR life-science data management services. 2020-2023 Data Management and Infectious Diseases European Commission - H2020 Programme DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS IHCC | The International HundredK+ Cohorts Consortium aims to create a global platform for translational research ? informing the biological and genetic basis for disease and improving clinical care and population health. 2020-2022 Translational research NIH; The Wellcome Trust; CZI INFRASTRUCTURE METADATA STANDARDS PPCG | The Pan Prostate Cancer Group aims to harmonise and interrogate Whole Genome DNA Sequence data generated around the world from over 2000 men with prostate cancer, with associated transcriptome and methylome data to include men from different clinical categories, and ethnicities. This project is about providing breakthrough advances through analysis of a very large series of Whole Genome DNA data from prostate cancer contributed by many of the leading scientists and clinicians working in prostate cancer genomics. 2019-2024 Cancer Cancer Research UK DATA MANAGEMENT CINECA | Consortium providing a Federated solution enabling population-scale genomic and biomolecular data accessible across international borders accelerating research and improving the health of individuals resident across continents. 2019-2023 Large-scale Genomics and Health Data European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE EASI-Genomics | A project designed to provide easy access to cutting-edge DNA sequencing technologies to researchers from academia and industry, within a framework that ensures compliance with ethical and legal requirements, as well as FAIR and secure data management. 2019-2023 Next Generation Sequencing European Commission - H2020 Programme ACCESS EJP-RD | An European consortium built to create a comprehensive, sustainable ecosystem allowing a virtuous circle between research, care, and medical innovation. 2019-2023 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DOCUMENTATION METADATA STANDARDS EOSC-Life | EOSC-Life brings together the 13 Life Science research infrastructures (LS RIs) to create an open, digital and collaborative space for biological and medical research. The project will publish 'FAIR' data and a catalogue of services provided by participating RIs for the management, storage and reuse of data in the European Open Science Cloud (EOSC). 2019-2023 Not applicable European Commission - H2020 Programme DOCUMENTATION EUCANCan | A federated network aiming at implementing a cultural, technological and legal integrated framework across Europe and Canada, to enable and facilitate the efficient sharing of cancer genomic data. 2019-2023 Cancer European Commission - H2020 Programme DATA MANAGEMENT METADATA STANDARDS The Federated EGA framework: supporting sensitive data management across the ELIXIR Nodes | This project is a direct continuation of the FHD IS with the goal to position the FEGA framework as the core infrastructure driver to support human data sharing for research. 2019-2023 Human genomic data ELIXIR INFRASTRUCTURE UK Biobank | UK Biobank is a large-scale biomedical database and research resource, containing in-depth genetic and health information from half a million UK participants. This project is to archive whole genome sequencing and other genetic data for UK Biobank participants. 2019-2023 Large-scale Genomics and Health Data The Wellcome Trust; UKRI; Amgen; AstraZeneca; GSK; Johnson & Johnson DATA MANAGEMENT INFRASTRUCTURE VEIS | The core mission of VEIS is to create an open ecosystem of technologies that will address and adapt to the requirements of the systems used to analyse and interpret -omics and clinical data in research and application environments in biomedicine. The aim of the project is to leverage the value of the EGA for both industry and society. 2019-2022 Oncology and Rare diseases Generalitat de Catalunya and European Regional Development Fund (ERDF) ACCESS DISCOVERY ELIXIR BEACON IS | This study follows on from a number of earlier activities that have established the ELIXIR Beacon Project. The main aim is to extend the Beacon protocol, developed at EGA, to become the reference ELIXIR Data Discovery product 2019-2021 Not applicable ELIXIR DISCOVERY ELIXIR FHD IS | This project coordinates the delivery of FAIR compliant metadata standards, interfaces, and reference implementation to support the federated ELIXIR network of human data resources. 2019-2021 Human genomic data ELIXIR INFRASTRUCTURE ELIXIR Rare Disease | The Rare Disease Community extends and generalises the system of access authorisation and high volume secure data transfer developed within the EGA. The goal of the Community is to create a federated infrastructure that will enable researchers to discover, access and analyse different rare disease repositories across Europe. It is doing this in partnership with other European infrastructure projects, namely RD-CONNECT, BBMRI-ERIC and E-Rare.2019-2021 Rare diseases ELIXIR INFRASTRUCTURE Solve-RD | Solve-RD - solving the unsolved rare diseases - is a research project funded by the European Commission. It echoes the ambitious goals set out by the International Rare Diseases Research Consortium (IRDiRC) to deliver diagnostic tests for most rare diseases by 2020. The current diagnostic and subsequent therapeutic management of rare diseases is still highly unsatisfactory for a large proportion of rare disease patients - the unsolved RD cases. For these unsolved rare diseases, we are unable to explain the etiology responsible for the disease phenotype, predict the individual disease risk and/or rate of disease progression, and/or quantitate the risk of relatives to develop the same disorder. 2018-2024 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT METADATA STANDARDS EuCanShare | An EU-Canada joint infrastructure for next-generation multi-Study Heart research. 2018-2022 Cardiovascular Diseases European Commission - H2020 Programme ACCESS METADATA STANDARDS

  Documentation about/projects-and-funders/projects

• GA4GH

  Standards The EGA is a long-standing supporter of the Global Alliance for Genomics & Health (GA4GH) to enhance responsible sharing of human genetic data through the development of interoperable global standards for human data access. The EGA is one of the founding GA4GH Driver Projects and has contributed to the development and implementation of several GA4GH standards and APIs. Below is a list of the GA4GH standards and APIs that are currently available or planned for implementation at EGA. TechnicalStandards Purpose SpecificationVersion SupportedVersion Implementation Large Scale Genomics htsget A protocol for secure, efficient, and reliable access to sequencing read and variation data. V1.3.0 V1.0.0 Specification Documentation Endpoint Read File Formats (SAM/BAM/CRAM) Specifications for storing next-generation sequencing read data. V3.0.0 V3.0.0 Implementation Example of Usage Variation File Formats (VCF/BCF) The specifications for Variant Call Format Files (VCF) and its binary counterpart BCF. V4.0.0 V2.0.0 V4.0.0 V2.0.0 Implementation Example of Usage Crypt4GH v1.0 Enables direct byte-level compatible random access to encrypted genetic data stored in community standards (e.g. CRAM, VCF) V1.0 V1.0 Specification Documentation Endpoint refget API Enables access to reference sequences using an identifier derived from the sequence itself. V1.2.6 NA Specification RNAget API v1 Provides a means of retrieving data from several types of RNA experiments including (i) feature-level expression data from RNA-seq type measurements and (ii) coordinate-based signal/intensity data similar to a bigwig representation via a client/server model. V1.0.0 NA Documentation Discovery Beacon v2 Supports discovery of genomic variants, phenotypes, and individuals V1.0.1 V0.3 Web UI API Source Code Service Info API v1 The Service Info API is an endpoint for describing GA4GH service metadata, designed for extension and inclusion in other APIs. Service info is used to describe a single service, while Service Registry is used to describe multiple services. V1.0.0 NA Documentation Service Registry API v1 provides information about other GA4GH services, primarily for the purpose of organizing services into networks or groups and service discovery across organizational boundaries. V1.0.0 NA Documentation Data Use Researcher Identities Data Use Ontology (DUO) Allow users to semantically tag genomic datasets with usage restrictions, allowing them to become automatically discoverable based on a health, clinical, or biomedical researcher’s authorisation level or intended use. 2021-02-23 2021-02-23 Specification Documentation Endpoint Authentication & Authorization Infrastructure (AAI) The GA4GH AAI specification leverages OpenID Connect (OIDC) Servers for use in authenticating the identity of researchers desiring to access clinical and genomic resources from data holders adhering to GA4GH standards, and to enable data holders to obtain security-related attributes of those researchers. V1.2.0 V1.2.0 API URI: ega.ebi.ac.uk:8443 Documentation Repository Researcher IDs (passport, visa) Specify the collection of researchers that may access a dataset at any given time, and the credentials they must supply. V1.0.1 V1.0.1 Specification Documentation Endpoint Cloud Tool Registry Service API TRS is a standard API for exchanging tools and workflows to analyze, read, and manipulate genomic data. V2.0.1 NA Documentation Repostiory Data Repository Service API ​DRS API is a standard for building data repositories and adapting access tools to work with those repositories, works with other approved APIs from the GA4GH Cloud Work Stream to allow researchers to discover algorithms across different cloud environments and send them to datasets they wish to analyse. V1.0.3 NA Documentation Repostiory Workflow Execution Service API This API lets users run a single workflow (defined using CWL or WDL) on multiple different platforms, clouds, and environments, and be confident that it will work the same way. The API provides methods to request that a workflow be run, pass parameters to that workflow, get information about running workflows, and cancel a running workflow. V1.0.1 NA Documentation Repostiory Genomic Knowledge Standards Variation Representation v1 Provides a flexible framework of computational models, schemas, and algorithms to precisely and consistently exchange genetic variation data across communities. V1.3.0 EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Clin/ Pheno Data Capture Phenopackets Provides information models with different levels of complexity to enable high level clinical phenotype information as well as deep clinical phenotype information to be exchanged. V2.0.0 Included in Ongoing Submissions EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Driver Project The EGA, jointly coordinated by the EBI and the CRG, was announced, in 2017, to be one of the 15 Driver Projects for GA4GH. Driver Projects are international genomic data initiatives, focussed on real projects and challenges that will guide the development efforts in order to accelerate and enable completely responsible and standarised data sharing by 2022. All chosen Driver Projects make a cross-sectional effort by playing an important role across the different workstreams. Thomas Keane, Jordi Rambla, Mallory Freeberg, and Aina Jené have been named Driver Project Champions for the EGA. All Driver Project Champions will be leading this ambitious initiative for the following years.

  Documentation about/projects-and-funders/ga4gh

• Federated EGA

  Federated EGA Federated EGA Index Overview Map of FEGA status across the world Current status of the FEGA Network Documentation Overview Federated EGA is a global network of repositories enabling secure discovery and access to sensitive human data. Our vision is to accelerate scientific discovery and healthcare breakthroughs by creating the go-to worldwide sensitive human data resource. Our values are: Privacy & Trust: Ensuring privacy of data subjects, security of services and acting with integrity to build community trust.FAIRness: Driving reuse of data through standardisation of metadata and clear access policies.Diversity: Expanding our network and representing global diversity in the data we host to bring benefits worldwide. Federated EGA - European by name, global by nature Federated EGA collaborates with European and global initiatives (GA4GH, ELIXIR, 1+ Million Genomes Framework, GDI), demonstrating that a network for transnational discovery of and access to human data is possible. By providing a solution to emerging challenges around secure and efficient management of human omics and associated data, the FEGA Network fosters data reuse, enables reproducibility, and accelerates biomedical research. For general enquiries or to request more information about Federated EGA, please send an email to fega-info [at] lists [dot] ega-archive [dot] org. Read more about the Federated EGA in our commentary in Nature Genetics! Learn more about joining the Federated EGA Network in our onboarding documentation. Map of FEGA status across the world Current status of the FEGA Network Node Description Joined CEGA Central EGA is managed by the Centre for Genomic Regulation (CRG) and EMBL-EBI. The EGA has been a trusted repository for sensitive data since 2008. CEGA coordinates the FEGA network, hosts central services and the EGA catalogue. 2022 Finland FEGA Finland is hosted by CSC - IT Center for Science Ltd., which is the national ELIXIR Node in Finland. CSC is a state-owned company specialising in providing high-quality IT infrastructure and services for Finnish higher education and research. 2022 Germany The German Human Genome-Phenome archive (GHGA) is part of the German National Research Data Infrastructure (NFDI). It is coordinated by the German Cancer Research Center (DKFZ) and includes over 20 academic partners. 2022 Norway FEGA Norway is a service by ELIXIR Norway, the Norwegian node of the European organisation ELIXIR. University of Oslo as a partner institution in ELIXIR Norway is hosting the service relying on the TSD infrastructure for sensitive data. ELIXIR Norway is a consortium of 5 Norwegian universities and is coordinated by University of Bergen. 2022 Spain FEGA Spain is co-hosted by the Barcelona Supercomputer Center (BSC) and the Centre for Genomic Regulation (CRG), both part of ELIXIR Spain and the Spanish National Infrastructure for Personalised Medicine associated with Science and Technology (IMPaCT). 2022 Sweden FEGA Sweden is hosted by the National Bioinformatics Infrastructure Sweden (NBIS), which legally is part of Uppsala University. NBIS forms the bioinformatics platform at SciLifeLab and constitutes the Swedish node of the European organisation ELIXIR. 2022 Poland FEGA Poland is hosted by Biobank Lodz, which is part of University of Lodz. Biobank Lodz is an element of the infrastructure of the Regional Digital Medicine Centers established by the Medical Research Agency. 2022 Portugal FEGA Portugal is managed by BioData.pt, the distributed infrastructure for Life and Health data for Portugal. This entity is a non-profit association of 15 life sciences R&I organisations spread across the country, and the home of ELIXIR Node in Portugal. 2023 Canada Canadian Genome-phenome Archive is part of the Pan Canadian Genome Library, with the mandate to allow the secure and responsible sharing and analysis of Canadian genomic information. 2024 Switzerland Swiss FEGA is hosted by SIB Swiss Institute of Bioinformatics, which is the national ELIXIR Node in Switzerland, on behalf of the Swiss FEGA Partnership which includes 4 other key partners (ETH Zurich, Health 2030 Genome Center, Swiss Data Science Center and Switch). 2025 Documentation Title Version Description Mission, vision, values Federated EGA Mission, vision, values 1.0 The official Mission-Vision-Values statement for FEGA, produced and formally approved by the FEGA Strategic Committee in September 2025. Structure and Organisation Federated EGA Structure and Organisation 2.0 The structure of the FEGA network and service expectations, responsibilities and commitments. FEGA is organised into three tiers: Central EGA, FEGA Nodes and FEGA Affiliates. Strategic Committee Federated EGA Strategic Committee 1.1 Terms of reference for the FEGA Strategic Committee describe the purpose and objectives of the committee, which is to provide direction and strategic planning for the FEGA network. The committee receives input from, and provides feedback for the EGA Strategic Committee. Operations Committee Federated EGA Operations Committee 1.1 Terms of reference for the FEGA Operations Committee describe the purpose and objectives of the committee, which is to review operational performance and coordinate technical roadmaps of FEGA Nodes and Central EGA. The committee receives advice from, and provides operational reporting to the FEGA Strategic Committee. Guidelines Federated EGA Node Operations Guidelines 2.1 An overview of the operational areas which require resources in order to create a FEGA Node. The document is based on more than 15 years' experience of EMBL-EBI and CRG operating the EGA and initial expericences of the inaugural FEGA Nodes. The operational areas of responsability are in line with the FEGA Maturity Model, which guides establishment and operation of FEGA Nodes. Collaboration Federated EGA Node Collaboration Agreement 1.3 Nodes are welcome to make a copy of this current version of the CA to start its review with their legal teams and understand the responsibilities of joining FEGA. Nevertheless, this version (the one with a watermark) shall not be signed: the official version needs to be obtained from FEGA prior to signing through its official channels. Federated EGA Affiliate Collaboration Agreement 1.0 Affiliates are welcome to make a copy of this current version of the CA to start its review with their legal teams and understand the responsibilities of joining FEGA. Nevertheless, this version (the one with a watermark) shall not be signed: the official version needs to be obtained from FEGA prior to signing through its official channels.

  Documentation about/projects-and-funders/federated-ega

• Catalogue Statistics

  EGA Statistics Bibliography Growth Community Archive Distribution Catalogue What is in the EGA? The European Genome-phenome Archive (EGA) overview The EGA archives and distributes the results of several types of studies. Such studies include genome-wide association studies (GWAS), different purpose sequencing and molecular diagnosis assays among others. Moreover, these studies target many different kind of diseases from cancer to neurodegenerative alterations. We summarised all this data in the charts below. The statistics are computed daily based on an updated list of studies. Each pie chart depicts a different aspect of the studies: which disease type was studied, which type of sampling method was used and what was the scope of the genomic analysis. Number of studies per disease type Studies in the EGA by disease barHorizontalChart('disease-graph', 'https://stats.test.ega-archive.org/catalog/by_disease') Number of studies per technology type Studies in the EGA by technology barHorizontalChart('technology-graph', '/stats/studies/technology', 'Include dbGaP') Number of studies per sample type Studies in the EGA by samples barChart('samples-graph', '/stats/studies/sample-types', false, false, 'Include dbGaP')

  Documentation about/statistics/catalogue

• Mutant_clone_mapping_in_normal_oesophagus

  We will use targeted exome sequencing to examine normal appearing epithelium and whole exome and whole genome sequencing of microdissected clones identified by immunostaining Some of the samples will be of low DNA concentration and therefore may require extra rounds of amplification during library prep.

  Study EGAS00001001874

• German early-onset prostate cancer cohort of the Pan-Prostate Cancer Genome (PPCG) project

  Prostate cancer is the most frequent malignant tumor in males and the second most frequent cause of cancer-related death. Currently, in Germany, more than 60,000 prostate cancers are diagnosed every year. Although most of these patients are treated in a curative attempt, more than 10,000 German men die from prostate cancer annually. Owing to the demographic changes of our society, a further doubling of prostate cancer incidences during the next 20 years is expected. Prostate cancer is generally considered a tumor of elderly men. However, a fraction of prostate cancers are diagnosed at the age of 55 years or less. For several reasons, these “early onset prostate cancers” may represent a key entity for the understanding of prostate cancer biology. First, it is likely that early onset prostate cancers represent a distinct molecular subgroup of prostate cancer (PCa), potentially characterized by relatively small numbers of genetic changes, some of which may be particularly strong driver mutations for PCa development. Second, a fraction of prostate cancers in young individuals could represent classical prostate cancers that are detected at a very early stage and might therefore have accumulated molecular changes/mutations occurring that are most instrumental for prostate cancer early detection. Third, PCa with hereditary backgrounds are likely to accumulate in the age group below 55 years. A comparison with other sample sets (e.g. from other ICGC consortia), a systematic genomic analysis of young men with PCa could therefore lead to the detection of mechanisms for hereditary PCa. Fourth, a better understanding of these tumors is particularly relevant as finding optimal treatment regimens is most critical in young cancer patients. We are analyzing the entire genomic DNA sequences of at least 200 PCas (and matched non-tumorous DNA) of young men (≤ 55y), to at least 30 fold coverage, and integrate single-nucleotide variants and genomic structural variations with differential methylation, mRNA and miRNA expression data.Tissues were collected at the University Medical Center Hamburg-Eppendorf. Sequencing was performed at DKFZ and NCT (Heidelberg), EMBL (Heidelberg), and MPIMG (Berlin). Data management and bioinformatic data analyses is being conducted at DKFZ.

  Study EGAS00001003373

• Neoadjuvant immunotherapy leads to pathological responses in MMR proficient and MMR deficient early stage colon cancers

  PD-1 plus CTLA-4 blockade is highly effective in advanced-stage, mismatch repair (MMR)-deficient (dMMR) colorectal cancers, yet not in MMR-proficient (pMMR) tumors. We postulated a higher efficacy of neoadjuvant immunotherapy in early-stage colon cancers. In the exploratory NICHE study (ClinicalTrials.gov: NCT03026140), patients with dMMR or pMMR tumors received a single dose of ipilimumab and two doses of nivolumab before surgery, the pMMR group with or without celecoxib. The primary objective was safety and feasibility; 40 patients with 21 dMMR and 20 pMMR tumors were treated, and 3 patients received nivolumab monotherapy in the safety run-in. Treatment was well tolerated and all patients underwent radical resections without delays, meeting the primary endpoint. Of the patients who received ipilimumab + nivolumab (20 dMMR and 15 pMMR tumors), 35 were evaluable for efficacy and translational endpoints. Pathological response was observed in 20/20 (100%; 95% exact confidence interval (CI): 86–100%) dMMR tumors, with 19 major pathological responses (MPRs, ≤10% residual viable tumor) and 12 pathological complete responses. In pMMR tumors, 4/15 (27%; 95% exact CI: 8–55%) showed pathological responses, with 3 MPRs and 1 partial response. CD8+PD-1+ T cell infiltration was predictive of response in pMMR tumors. These data indicate that neoadjuvant immunotherapy may have the potential to become the standard of care for a defined group of colon cancer patients when validated in larger studies with at least 3 years of disease-free survival data.

  Study EGAS00001004160

• Immunogenomics of colorectal cancer response to immune checkpoint blockade

  Molecular and cellular determinants of response to immune checkpoint inhibitors are mostly unknown. Here we use whole exome, RNA and T cell receptor sequencing, imaging mass cytometry, immunohistochemistry and PD1-PDL1 interaction detection to profile 543 regions from 16 colorectal cancers (CRCs) subsequently treated with Pembrolizumab or Nivolumab. Independent of treatment response, CRCs express low levels of PD1 and PDL1 proteins and form less PD1-PDL1 complex than other cancers. Non hypermutated CRCs have no benefit from treatment, show WNT activation and low T cell infiltrates. Among hypermutated CRCs, those with durable benefit have clonal immunogenic alterations, clonally expanded T cells and potential for immune escape through dysfunctional antigen presentation. Responsive tumours are enriched in PD1-expressing cytotoxic and proliferating CD8 T cells and PDL1-expressing antigen presenting macrophages, which form high-density clusters of interacting cells. Our study shows that immune checkpoint inhibitors are most effective in highly infiltrated CRCs where they may release the interactions between macrophages and CD8 T cells thus promoting their priming and expansion in intra-tumour niches.

  Study EGAS00001004438

• Cell-free DNA TAPS for early cancer detection

  Multimodal, genome-wide characterization of epigenetic and genetic information in circulating cell-free DNA (cfDNA) could enable more sensitive early cancer detection. However, due to technological challenges associated with DNA methylation sequencing in low input cfDNA samples, most studies have been limited by DNA damage caused by bisulfite sequencing, or the qualitative nature of enrichment-based sequencing. Recently, we developed TET-assisted Pyridine Borane Sequencing (TAPS), which is a mild, bisulfite-free method for base-resolution direct DNA methylation sequencing. Here we optimized TAPS for cfDNA (cfTAPS) to provide high-quality and high-depth whole-genome cell-free methylomes. We applied cfTAPS to 85 cfDNA samples from patients with hepatocellular carcinoma (HCC) or pancreatic ductal adenocarcinoma (PDAC) and non-cancer controls. From just 10 ng cfDNA (1-3 mL of plasma), we generated the most comprehensive cfDNA methylome to date. We demonstrated that cfTAPS provides multimodal information about cfDNA characteristics, including DNA methylation, tissue of origin, and DNA fragmentation. Integrated analysis of these epigenetic and genetic features enables accurate identification of early HCC and PDAC.

  Study EGAS00001004962

• Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities

  Despite molecular and clinical heterogeneity, small cell lung cancer (SCLC) is treated as a single entity with predictably poor results. Using tumor expression data, we applied non-negative matrix factorization, which identified four SCLC subtypes defined largely by differential expression of transcription factors ASCL1, NEUROD1, and POU2F3 or low expression of all three transcription factor signatures accompanied by an Inflamed signature (SCLC-A, N, P and I, respectively). The presence of these subtypes were then validated in tumor gene expression data from the IMpower133 clinical trial.

  Study EGAS00001004888

• Detection and characterization of lung cancer using cell-free DNA fragmentomes

  Lung cancer remains the leading cause of cancer death world-wide, largely due to its late diagnosis. Non-invasive approaches for assessment of cell-free DNA (cfDNA) provide an opportunity for detection and intervention that may have broader accessibility than current imaging approaches. Using a machine learning model for detecting tumor-derived cfDNA through genome-wide analyses of cfDNA fragmentation, we examined a prospective study of 365 individuals at risk for lung cancer (Lung Cancer Diagnostic Study, LUCAS), including 129 individuals ultimately diagnosed with lung cancer and 236 individuals determined to not have lung cancer. We externally validated the cancer detection model using an independent cohort of 385 non-cancer individuals and 46 predominantly early stage lung cancer patients. Combining fragmentation features with clinical risk factors and CEA levels followed by CT imaging detected 94% of patients with cancer across stages and subtypes, including 91% of stage I/II and 96% of stage III/IV, at 80% specificity. Genome-wide fragmentation profiles across ~13,000 ASCL1 transcription factor binding sites could be used to distinguish individuals with small cell lung cancer (SCLC) from those with non-small cell lung cancer (NSCLC) with high accuracy (AUC=0.98). Among individuals with lung cancer, a higher cfDNA fragmentation score was associated with tumor size and invasion, and represented an independent prognostic indicator of survival. These studies provide a facile approach for non-invasive detection of lung cancer and clinical management of this disease.

  Study EGAS00001005340

• PanCuRx Translational Research Initiative

  The goal of the PanCuRx TRI is to seek solutions to the high fatality rate of pancreatic adenocarcinoma (PDAC), the most common type of pancreatic cancer, by generating new knowledge about the genetics and biology of the disease, mechanisms of how tumours grow and tailored treatment options. PDAC is the fourth leading cause of cancer death in Canada and is expected to become the second-leading cause of cancer death within the next decade. The current five-year survival rate of eight per cent is the lowest of all epithelial cancers. There are major clinical challenges to treating the disease, including the fact that PDAC spreads to other parts of the body early so surgical removal of the tumour benefits few patients, that PDAC has proven relatively resistant to systemic therapies such as chemotherapy and that there has been limited benefit from the use of newer molecular targeted agents. The PanCuRx team has created the world’s first resource of tumour-purified PDAC whole genomes; more than 500 PDAC samples, with combined clinical annotation, have been successfully sequenced and analyzed at the Ontario Institute for Cancer research in Toronto. The resulting clinical genomic resource created from this data has led to multiple new findings that have established a framework to better understand PDAC biology and lays the foundation for new genomic approaches to better understanding the disease. The team also launched a clinical trial called COMPASS (Comprehensive Molecular Characterization of Advanced Ductal Pancreas Adenocarcinoma for Better Treatment Selection: A Prospective Study), which is recruiting patients with advanced PDAC (both locally advanced and metastatic) at The Princess Margaret Cancer Centre (PM) in Toronto. The study uses the molecular results from individual patient tumours to guide selection of better second line treatment on a case-by-case basis. The primary objective of the initial study was to assess the feasibility of collecting tumour materials from patients with advanced PDAC and delivering results within 56 days of biopsy. Having achieved this objective, the trial has expanded to other cancer centres across Canada. Pancreatic cancer is one of the most deadly forms of cancer and outcomes have not improved in four decades. The PanCuRx initiative is providing a better understanding of the disease and actively applying new knowledge to cancer patients through clinical trials. This knowledge will help to improve quality of life and prolong survival for pancreatic cancer patients worldwide.

  Study EGAS00001002543

• TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells.

  We examined tumours from a large cohort of patients with metastatic urothelial bladder cancer (mUC) treated with an anti–PD-L1 agent (atezolizumab) and identified major determinants of clinical response and immune escape. Whole transcriptome profiles were generated for 368 patients using TruSeq RNA Access technology (Illumina). Somatic mutations were determined via whole exome sequencing for a subset of these patients. - Response was associated with CD8+ T effector cell phenotype and, to an even greater extent, high neoantigen or tumour mutation burden (TMB). On the other hand, lack of response was associated with a transforming growth factor β (TGF-β) signature, particularly in patients with CD8+ T cells preferentially residing in collagen-rich matrix surrounding tumours. Integration of these three independent biological features provided the best basis for understanding outcome in this setting. -

  Study EGAS00001002556

• Immune induction strategies to enhance the sensitivity to PD-1 blockade in metastatic triple negative breast cancer: the TONIC-trial

  The response rate in metastatic triple negative breast cancer (TNBC) to PD-1 blockade is low, highlighting an urgent clinical need for strategies that render the TNBC tumor microenvironment (TME) more sensitive to PD-1 blockade. Immunomodulatory mechanisms have been proposed for both chemotherapy and irradiation, but it has not been established whether these therapies may improve efficacy of PD-1 blockade by favorably changing the TME. In the first stage of this adaptive, non-comparative phase II trial (TONIC-trial; NCT02499367), 67 patients with metastatic TNBC were randomized to nivolumab without induction or to one of four induction treatments, consisting of irradiation of one metastatic lesion (3x8 Gy) or a two- week low-dose regimen of cyclophosphamide, cisplatin or doxorubicin, all followed by nivolumab. In the overall cohort of 66 evaluable patients, the objective response rate (ORR; iRECIST16) was 20% (95% CI: 11%-31%), with two complete responses and 11 partial responses. The majority of clinical responses were observed on nivolumab in the cisplatin (ORR 23%; 3/13) and doxorubicin (ORR 35%; 6/17) cohorts. After doxorubicin and cisplatin induction, we detected an upregulation of immune-related genes, involved in PD-1/PD-L1, and T-cell cytotoxicity pathways. This was further supported by enrichment among upregulated genes related to inflammation, JAK-STAT and TNFα-signaling after doxorubicin. In addition, we observed a trend towards increased T-cell infiltration, measured using T-cell receptor (TCR) sequencing, after doxorubicin. Together, the clinical and translational data of this study testing different immune induction strategies prior to nivolumab suggest that short-term doxorubicin and cisplatin may induce a more favorable TME and increase the likelihood of response to PD-1 blockade in TNBC. These data warrant further confirmation in TNBC and exploration of induction treatments prior to PD-1 blockade in other cancer types.

  Study EGAS00001003535

• Single-cell analysis for metastatic gastric adenocarcinoma

  Intra-tumoral heterogeneity (ITH) is the fundamental property of cancer, however, the origins of ITH remain poorly understood. Here we performed single-cell RNA sequencing of peritoneal carcinomatosis (PC) from patients with advanced gastric adenocarcinoma (GAC), constructed a transcriptome map of 45,048 PC cells, profiled the transcriptome states of diverse tumor cell lineages and types, incisively explored ITH of PC tumor cells, and identified significant correlates with patient survival.

  Study EGAS00001004443

• The aim of this project is to identify, on 15 French Caucasian and 10 African-Caribbean men, through an integrative approach of DNA sequencing and transciptomic analyses, relevant genomic events that characterize or allow targeting the various phenotypes of aggressiveness of early stages of prostate cancer.

  Every year about 70,000 new cases of prostate cancer are diagnosed in France and 8,700 men died from this disease. But the incidence and the rate of mortality per 100,000 men in the French West Indies are respectively 1.5x and 2x upper than the rates observed in the metropolitan France. The aim of this project is to identify, on 15 French Caucasian and 10 African-Caribbean men, through an integrative approach of DNA sequencing and transciptomic analyses, relevant genomic events that characterize or allow targeting the various phenotypes of aggressiveness of early stages of prostate cancer.

  Study EGAS00001002176

• Canadian prostate cancer samples (CPC-GENE) for PanProstate study

  CPC-GENE has sequenced the genomes of 350 intermediate risk prostate cancers to identify genetic signatures that differ in cancers that responded well to treatment compared with those that did not. CPC-GENE also has sequenced multiple regions of prostate cancer from the same gland to determine if and how the genetic make-up of prostate cancer varies within an individual man’s prostate

  Study EGAS00001003037

• Genomic analysis of high-risk prostate cancer.

  Whole genome sequencing analysis of high risk localised primary prostate cancer samples including metastatic samples was performed across 153 tumour samples with matching germline sequencing (whole blood). Samples were all fresh frozen frozen section confirmed tumour specimens and associated clinical and pathological metadata is available for these specimens.

  Study EGAS00001003088

• PanProstate Cancer Group UK data

  THE PAN PROSTATE CANCER PROJECT: Many groups around the world have generated Whole Genome DNA Sequence (WGS) data from prostate cancer patients. The pan prostate group have gathered with the idea that the accumulated data, should be collected and compared in a common format including common storage, re-analysis through a single pipeline, and investigation to achieve a variety of scientific goals. The combined collection would include the following categories: (i) cancers from different ethnic groups: eg Caucasian, Asian, Black Caribbean; (ii) cancer from different stages of progression from normal, to organ-confined disease, to metastases; (iii) early-onset prostate cancer; (iv) prostate cancer from aggressive and indolent disease; and (v) prostate cancer patients managed by different treatments with information linked to long-term clinical follow up data in many cases.This study contains the initial pilot samples (train 1) from the CRUK-ICGC prostate group.

  Study EGAS00001002876

• TRACERx 100: whole exome data of the first 100 TRACERx tumours

  BACKGROUNDTRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). METHODSMultiregion high-depth whole-exome sequencing (M-seq) was performed on 100 early stage NSCLC tumors resected prior to systemic therapy. A total of 327 tumor regions were sequenced and analyzed to define evolutionary histories, obtain a census of clonal and subclonal events, and assess the relationship between ITH and recurrence-free survival (RFS). RESULTSWidespread ITH was observed for both somatic copy number alterations (median 48% [0.03-88%]) and mutations (median 30% [0.5-93%]). Driver mutations in EGFR, MET, BRAF and TP53 were almost always clonal. However, heterogeneous driver alterations occurring later in evolution were found in over 75% of tumors and were common in PIK3CA, NF1 and genes involved in chromatin modification and DNA response and repair. Genome doubling and ongoing dynamic chromosomal instability (CIN), illustrated by mirrored subclonal allelic imbalance, were identified as causes of ITH resulting in parallel evolution of driver copy number events, including amplifications of CDK4, FOXA1, and BCL11A. Elevated copy number heterogeneity was associated with shorter RFS (HR=4.9, P=0.00044), which remained significant in a multivariate analysis.CONCLUSIONSITH mediated through CIN, rather than point mutational heterogeneity, was associated with increased risk of relapse, supporting its value as a prognostic predictor, and the need to target this high-risk phenotype.

  Study EGAS00001002247

• Psoriatic_arthritis

  This is a pilot single cell mRNA sequencing experiment to study immune cells in psoriatic arthritis.

  Study EGAS00001002104

• Tracing early predictors of glioma evolution under therapy

  Clonal evolution drives cancer progression and therapeutic resistance. Recent studies revealed divergent longitudinal trajectories in gliomas, but early molecular traits steering post-treatment cancer evolution remain unclear. We analyzed sequencing data of 544 initial-recurrent adult diffuse glioma pairs to identify genomic and transcriptomic early predictors of tumor evolution in each molecular subtype.

  Study EGAS00001006894

• Somatic Mutations and Their Etiological Determinants for Breast Cancer in African American Women (B-CAUSE Study)

  The breast cancer health disparity between women of African ancestry (AA) and European ancestry (EA) remains a major public health challenge in the United States. AA women are afflicted by higher rate of triple-negative breast cancer (TNBC) and bear the highest mortality rate of all populations from the disease. Even within TNBC, some data suggest that AA women have poorer outcomes than EA women. Mounting evidence points to population differences in cancer biology, a fundamental question that remains unsettled. The disparity also manifests in representativeness in tumor sequencing projects, due to the low inclusion of AAs in genomic studies. A recent analysis of The Cancer Genome Atlas (TCGA) data revealed that the number of AA cases sequenced was sufficient only for studying frequently mutated genes (≥10%), and the power was worse for TNBC as a separate disease entity. As a result, the breast tumor mutational landscape elucidated to date is derived mostly from EA cases, and may not necessarily represent AA cancer genomes. Moreover, as discovery potential for new driver genes has come close to a plateau, cancer in AAs derived from distinct genetic and environmental contexts may provide a powerful venue for discovering mutations that are rare in EA cases. This is showcased in recent studies in colon and prostate cancer. Thus, we carried out a collaborative project, B-CAUSE, to characterize the mutational landscape of AA breast cancer genomes by pooling resources from five established studies, including the Women's Circle of Health Study (WCHS), the Black Women's Health Study (BWHS), the Southern Community Cohort Study (SCCS), the Nashville Breast Health Study (NBHS), and the Southern Tri-State Breast Health Study (STSBHS). This effort has created the largest AA-specific breast tumor mutation dataset to date in an efficient manner. The data deposited here are from the whole-exome sequencing (WES) of matched tumor-normal pairs of 462 TNBC in AA women from the B-CAUSE Study.

  Study phs003962

• A Scalable, GMP-Compatible, Autologous Organotypic Cell Therapy for Dystrophic Epidermolysis Bullosa

  Gene editing in induced pluripotent stem (iPS) cells has been hailed for enabling new cell therapies for various monogenetic diseases including dystrophic epidermolysis bullosa (DEB). However, manufacturing, efficacy, and safety roadblocks have limited the development of genetically corrected, autologous iPS cell-based therapies. Dystrophic Epidermolysis Bullosa Cell Therapy (DEBCT), is a new generation, Good Manufacturing Practice-compatible (cGMP), reproducible, and scalable platform to produce autologous clinical-grade iPS cell-derived organotypic induced skin composite (iSC) grafts to treat incurable wounds of patients lacking type VII collagen (C7). DEBCT uses a single step, combined, high-efficiency reprogramming, and CRISPR-based genetic correction to generate genome scar-free, COL7A1 corrected clonal iPS cells from primary patient fibroblasts. Validated iPS cells are converted into epidermal, dermal, and melanocyte progenitors with a novel 2D organoid differentiation protocol, followed by CD49f enrichment and expansion to minimize maturation heterogeneity. iSC product characterization by single cell transcriptomics was followed by mouse xenografting for disease correcting activity at 1 month and toxicology analysis at 1-6 months. Culture-acquired mutations, potential CRISPR-off target effects, and cancer-driver variants were evaluated by targeted and whole genome sequencing. iPS cell-derived iSC grafts were reproducibly generated from four recessive DEB patients with different pathogenic mutations. Organotypic iSC grafts onto immune-compromised mice developed into stable stratified skin with functional C7 restoration. Single cell transcriptomic characterization of iSCs revealed prominent holoclone stem cell signatures in keratinocytes and the recently described Gibbin-dependent signature in dermal fibroblasts. The latter correlated with enhanced graftability. Multiple orthogonal sequencing and subsequent computational approaches identified random and non-oncogenic mutations introduced by the manufacturing process. Toxicology revealed no detectable tumors after 3-6 months in DEBCT-treated mice. In conclusion, DEBCT successfully overcomes previous roadblocks and establishes a robust, scalable, and safe cGMP manufacturing platform for the production of a CRISPR-corrected autologous organotypic skin graft to heal DEB patient wounds.

  Study phs003271

• NCTN: A Randomized, Phase III Study Comparing Carboplatin/Paclitaxel or Carboplatin/Paclitaxel/Bevacizumab with or without Concurrent Cetuximab in Patients with Advanced Non-Small Cell Lung Cancer (NSCLC) (S0819)

  Study ID: S0819NCT Number: NCT00946712 SWOG Cancer Research NetworkSubmitted in collaboration with the NCTN/NCORP Data ArchiveTrial Title: NCTN: A Randomized, Phase III Study Comparing Carboplatin/Paclitaxel or Carboplatin/Paclitaxel/Bevacizumab with or without Concurrent Cetuximab in Patients with Advanced Non-small Cell Lung Cancer (NSCLC) (S0819)Trial Description: This randomized phase III trial studies carboplatin and paclitaxel to compare how well they work with or without bevacizumab and/or cetuximab in treating patients with stage IV or non-small cell lung cancer that has returned after a period of improvement (recurrent). Drugs used in chemotherapy, such as carboplatin and paclitaxel, work in different ways to stop the growth of tumor cells, either by killing the cells, by stopping them from dividing, or by stopping them from spreading. Bevacizumab may prevent the growth of new blood vessels that tumor needs to grow. Cetuximab may also stop cancer cells from growing by binding and interfering with a protein on the surface of the tumor cell that is needed for tumor growth. It is not yet known whether giving carboplatin and paclitaxel are more effective with or without bevacizumab and/or cetuximab in treating patients with non-small cell lung cancer. Clinical data presented in the following publication(s):PMID 29169877Disease type(s): Lung, Mediastinal and Pleural Neoplasm - Non-Small Cell Lung CancerClinical Dataset(s) included:NCT00946712-D1 (PMID 29169877): There are three datasets associated with PMID 29169877: NCT00946712-D1, -D2, and -D3. This clinical dataset, NCT00946712-D1, contains patient-level data (one row per patient), including eligibility, evaluability, treatment, demographic, EGFR FISH results, protocol deviations, and baseline information. It also contains response and survival data.NCT00946712-D2 (PMID 29169877): There are three datasets associated with PMID 29169877: NCT00946712-D1, -D2, and -D3. This toxicity dataset, NCT00946712-D2, contains event-level information (one row per patient per adverse event experienced on trial).NCT00946712-D3 (PMID 29169877): There are three datasets associated with PMID 29169877: NCT00946712-D1, -D2, and -D3. This dataset, NCT00946712-D3, contains specific reasons for off treatment due to toxicity.You are encouraged to view the PDF data dictionaries found in the “Documents” tab of the dbGaP study page, which may contain additional information regarding the data or the associated publication(s).

  Study phs004231

• Atezolizumab Plus Personalized Neoantigen Vaccination in Patients with Urothelial Cancer: a Phase 1 Trial

  This is a phase 1 single center clinical trial evaluating a multi-peptide personalized neoantigen vaccine, PGV001, in combination with atezolizumab for patients with urothelial cancer. Patients were enrolled in either the adjuvant or metastatic setting. Those in the adjuvant setting included patients considered high risk of recurrence (pathological stage ypT2-T4 or ypN+ for those treated with prior neoadjuvant chemotherapy or pT3-T4 or pN+ for those not treated with prior neoadjuvant chemotherapy). Those in the metastatic setting included patients progressing after prior chemotherapy or those with at least stable disease after chemotherapy treated as “switch maintenance” therapy. The primary endpoint was feasibility (including the number of neoantigens identified per patient, vaccine production time, the proportion of patients consenting to the vaccine development phase for whom a vaccine product was prepared, and the proportion of patients eligible for the treatment phase who completed the priming cycle 1 of PGV001 plus atezolizumab) and safety. Secondary endpoints included the objective response rate, progression-free survival or disease-free survival, overall survival, and immunomodulatory effects of treatment. Urothelial tumor tissue and normal tissue or peripheral blood specimens were utilized for DNA sequencing. HLA typing was performed utilizing genomic DNA isolated from whole blood, and RNA sequencing was performed utilizing tumor tissue specimens. Neoantigen prediction and final selection for incorporation into the vaccine was determined by the OpenVax computational pipeline. 12 patients were initially enrolled into the vaccine development phase and 10 patients initiated the treatment phase. PGV001 was administered with poly-ICLC and tetanus peptide on subsequent days for up to 10 doses, including an initial priming cycle 1. Atezolizumab was administered every 3 weeks for up to 1 year in the adjuvant setting or 2 years in the metastatic setting. The vaccine was feasible and safe, the median vaccine production time was 20.3 weeks, and 100% of patients that initiated the treatment phase completed the priming cycle. The most common treatment-related adverse events were local grade 1 injection site reactions, fever, and fatigue. Three of the 4 patients in the adjuvant setting remained disease-free at median follow-up of 39.5 months. There was a 40% objective response rate among patients with measurable disease in the metastatic setting. The single patient treated as “switch maintenance” therapy remained with no evidence of disease at 39.4 month follow-up. All patients demonstrated on-treatment neoantigen-specific T cell reactivity, as measured by ELISPOT and flow cytometry assays. Overall, PGV001 plus atezolizumab was feasible, safe, and warrants further investigation. Whole exome sequencing from tumor tissue and normal tissue or whole blood specimens and RNA sequencing from tumor tissue specimens will be available through dbGaP.

  Study phs003922

• Somatic Mutations in Individual Skin Cells

  Ultraviolet (UV) radiation is the primary cause of melanoma through the acquisition of driver mutations in melanocytes. It also plays a significant role in oncogenesis in other skin cells, such as keratinocytes. However, the mutational profiles vary widely among different skin cancers, and the early mutational processes in different cell types from the same skin, is not well understood. Additionally, our preliminary studies also suggest that the mutation burden in different skin cells vary significantly based on risk factors such as the anatomical site and the use of tanning beds. To explore this, we employed innovative Next Generation Sequencing (NGS) tools to perform a site-matched comparison of the genomic landscapes of melanocytes, keratinocytes, and fibroblasts. From 20 biopsies of physiologically normal skin, collected from various anatomical sites across 16 donors, we have performed DNA-sequencing on 106 melanocytes, 78 keratinocytes and 13 fibroblasts. Of these samples, we have also simultaneously performed RNA-sequencing on 78 melanocytes, 46 keratinocytes and 9 fibroblasts. For normal bulk DNA, we also performed targeted (UCSF500; n=9) or exome sequencing (n=8) of skin or saliva samples from the donors.

  Study phs003683

• Transcriptome of Human Merkel Cell Carcinoma

  Merkel Cell Carcinoma (MCC) is a rare and aggressive skin cancer with poorly understood molecular characteristics. In this study, we conducted RNA sequencing (RNA-Seq) on tumor samples from 9 human MCC patients to unravel the intricate transcriptional landscape of MCC. Data available in dbGaP include bulk RNA sequencing of 9 tumor samples.

  Study phs003411

• Childhood Cancer Data Initiative (CCDI): CCDI Pediatric In Vivo Testing Program - Orthotopic CNS Tumors

  The goal of this project is to advance the development of effective therapies for pediatric brain cancers through preclinical in vivo testing of novel agents. We utilize a well-characterized panel of approximately 150 patient-derived orthotopic xenograft (PDOX) models that replicate the histopathologic and molecular features of the original patient tumors. These models represent multiple pediatric CNS tumor types, including high-grade glioma, medulloblastoma, ependymoma, diffuse intrinsic pontine glioma (DIPG), and atypical teratoid/rhabdoid tumor (ATRT), across diverse disease stages and molecular subtypes. As part of this effort, the PDOX models are being molecularly characterized to identify promising therapeutic candidates. Molecular profiling includes whole exome sequencing (WES), RNA-seq, MethylEPIC array, CytoSNP array, and DNA fingerprinting for quality control. Demographic and clinical data (e.g., diagnosis, disease site, disease status) are also shared.

  Study phs003162

• Kids First: Childhood Cancer Data Initiative (CCDI) - Discovering the Timing and Origins of Bone and Soft Tissue Cancers

  Sarcoma are cancers of bone and connective tissue that disproportionately affect children and are often difficult to diagnose. This study presents the genome and transcriptome sequences of carefully curated sarcoma tumors and matched non-neoplastic (normal) specimens including a cohort of benign bone and soft tissue tumors, totalling 1122 sequences from 310 participants, covering 69 various subtypes. High-quality pathology reviewed specimens (FF or FFPE) with detailed clinical data were selected to inform key temporal landmark in sarcoma development – from tumor initiation to the generation of critical oncogenic fusions and malignant potential, to possible relapse or metastasis.

  Study phs002827

• NCTN: Treatment for Very Low and Standard Risk Favorable Histology Wilms Tumor (AREN0532)

  Study ID: AREN0532NCT Numbers: NCT00352534Children's Oncology GroupSubmitted in collaboration with the NCTN/NCORP Data ArchiveTrial Title: NCTN: Treatment for Very Low and Standard Risk Favorable Histology Wilms Tumor (AREN0532)Trial Description: This phase III trial is studying vincristine, dactinomycin, and doxorubicin with or without radiation therapy or observation only to see how well they work in treating patients undergoing surgery for newly diagnosed stage I, stage II, or stage III Wilms' tumor. Drugs used in chemotherapy, such as vincristine, dactinomycin, and doxorubicin, work in different ways to stop the growth of tumor cells, either by killing the cells or by stopping them from dividing, or by stopping them from spreading. Radiation therapy uses high energy x-rays, particles, or radioactive seeds to kill cancer cells and shrink tumors. Giving these treatments after surgery may kill any tumor cells that remain after surgery. Sometimes, after surgery, the tumor may not need additional treatment until it progresses. In this case, observation may be sufficient.Clinical data presented in the following publication(s):PMID 27811504PMID 29211618Disease type(s): Kidney Neoplasm - Wilms TumorClinical Dataset(s) included:NCT00352534-D1 (PMID 27811504): There is one dataset (-D1) for the AREN0532 primary publication 27811504, reporting on the trial's very low-risk cohort. This dataset contains baseline characteristics, WT1 mutation status, loss of heterozygosity, relapse sites, presence of intralobar and perilobar rests, survival, secondary malignancy, and radiotherapy type data.NCT00352534-D2 (PMID 29211618): There are two datasets (-D2 and -D3) for the AREN0532 primary publication 29211618, reporting on patients with stage III favorable-histology Wilms tumor. There is one row for each patient enrolled. The dataset contains the data for the consort flow of patient enrollment, baseline characteristics, surgery details, 1p/16q loss of heterozygosity status, second malignant neoplasm, survival, relapse site, grade of adverse events, and tumor status data for the patients on AREN0532 as reported in the manuscript.NCT00352534-D3 (PMID 29211618): There are two datasets (-D2 and -D3) for the AREN0532 primary publication 29211618, reporting on patients with stage III favorable-histology Wilms tumor. This dataset contains EFS and OS data for patients enrolled on the Q9401 study described in the manuscript to compare outcomes for patients on AREN0532 to similar patients on Q9401 who received the same therapy.Select data from Q9401 (NCT00002611) used in AREN0532 publication PMID 29211618 are contained in NCT003525234-D3.You are encouraged to view the PDF data dictionaries found in the “Documents” tab of the dbGaP study page, which may contain additional information regarding the data or the associated publication(s).

  Study phs004139

• Genomic Characterization CS-MATCH-0007 Arm C1

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm C1 is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with MET amplification are treated with Crizotinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002177

• MP2PRT: PI3K Pathway Activation and Its Associated Genomic Profile as Predictive Biomarkers of HPV-Related Oropharyngeal Cancer: Evaluation of NRG HN002 and RTOG 1016

  The Molecular Profiling to Predict Response to Treatment (MP2PRT) program is part of the NCI Cancer Moonshot Initiative. The aim of this program is the retrospective characterization and analysis of biospecimens collected from completed NCI-sponsored trials of the National Clinical Trials Network. This study, titled “PI3K Pathway Activation and Its Associated Genomic Profile as Predictive Biomarkers of HPV-Related Oropharyngeal Cancer: Evaluation of NRG-HN002 and RTOG 1016”, is one of the selected studies under this program. For this study, molecular characterization (i.e., WES, Total RNAseq, and multiplex immunofluorescence staining) was performed on formalin-fixed paraffin embedded tumor tissue and matching germline previously collected from patients with HPV-related oropharyngeal cancer. This project will investigate genomic alterations within the PI3K pathway (PIK3CA and PTEN). It is hypothesized that an improved understanding of this pathway in a specific genetic context may lead to the development of novel therapies to guide future clinical trials and improve the clinical outcomes of patients with HPV-positive oropharyngeal cancer.

  Study phs003089

• Analysis of Epigenomes and Genome Topology in Colorectal Cancer

  When diagnosing cancer, pathologists use nuclear morphology as a hallmark of tumor cells, but the topological changes linked to alterations in the shape of the nucleus were poorly understood. To uncover the molecular changes that occur in the 3D structure of cancer genomes, we integrated topological maps for colon tumors and normal colon tissues with epigenetic, transcriptional, and imaging data. We characterized tumor-associated changes in chromatin loops, topologically associated domains (TADs), and large-scale compartments. We found that chromatin loop rewiring contributes to oncogenic gene expression programs. Whereas TAD structures are largely stable, the spatial partitioning of the open and closed genome compartments is compromised in tumors and is accompanied by hypomethylation and histone mark rearrangements. We also identified a compartment that is reorganized in tumors and is at the interface between the canonical A and B compartments. Similar changes were evident in non-malignant cells that had accumulated excessive cellular divisions. Our analyses suggest that these compartment changes repress stemness and invasion programs while inducing immunity genes, and they may therefore restrain malignant progression.

  Study phs002288

• NCTN: A Randomized Phase III Post-operative Trial of Platinum Based Chemotherapy vs. Capecitabine in Patients with Residual Triple-Negative Basal-Like Breast Cancer following Neoadjuvant Chemotherapy (EA1131)

  Study ID: EA1131 NCT Number: NCT02445391 ECOG-ACRIN Cancer Research Group Submitted in collaboration with the NCTN/NCORP Data Archive Trial Title: NCTN: A Randomized Phase III Post-operative Trial of Platinum Based Chemotherapy vs. Capecitabine in Patients with Residual Triple-Negative Basal-Like Breast Cancer following Neoadjuvant Chemotherapy (EA1131) Trial Description: This randomized phase III trial studies how well cisplatin or carboplatin (platinum based chemotherapy) works compared to capecitabine in treating patients with remaining (residual) basal-like triple-negative breast cancer following chemotherapy after surgery (neoadjuvant). Drugs used in chemotherapy, such as cisplatin, carboplatin and capecitabine, work in different ways to stop the growth of tumor cells, either by killing the cells, by stopping them from dividing, or by stopping them from spreading. It is not yet known whether cisplatin or carboplatin is more effective than capecitabine in treating patients with residual triple negative basal-like breast cancer. Clinical data presented in the following publication(s): PMID 34092112 Disease type(s): Breast Neoplasm - Breast Cancer - Invasive Clinical dataset(s) included: NCT02445391-D1 (PMID 34092112): There are three datasets for PMID 34092112. This dataset, NCT02445391-D1, contains baseline characteristics, stratification factors, treatment, second primary cancer, cause of death and efficacy data. The data reflect the study database as of April 7, 2021. All patients who were randomized to one of the three arms were included in the database (NCT02445391-D1). Accrual was open to arm A (observation) and arm B (platinum) prior to Amendment #3, and accrual to arm A was permanently closed and accrual to arm C (capecitabine) was opened in Amendment #3. NCT02445391-D2 (PMID 34092112): There are three datasets for PMID 34092112. This dataset, NCT02445391-D2 contains data on dose modification. The data reflect the study database as of April 7, 2021. NCT02445391-D3 (PMID 34092112): There are three datasets for PMID 34092112. This dataset, NCT02445391-D3, contains toxicity data. The data reflect the study database as of April 7, 2021. All treatment-related AEs were included in the database, and only the worst degree was reported in the paper. You are encouraged to view the PDF data dictionaries found in the “Documents” tab of the dbGaP study page, which may contain additional information regarding the data or the associated publication(s).

  Study phs004236

• Long-Read Sequencing of Ovarian Cancer Organoids

  Two patient-derived organoids were derived from separate ascites fluid collections from a patient diagnosed with high-grade mullerian carcinoma, that could not be confidently subclassified based on the limited specimen. Long-read sequencing whole genome sequencing (WGS) was performed on the organoids, OC104 and OC109, using the Oxford Nanopore Technologies PromethION24 with V14 ligation kit. Information from genomic findings and further pathology on organoids suggests refining the diagnosis to mucinous ovarian carcinoma.

  Study phs004795

• Childhood Cancer Data Initiative (CCDI): Pediatric In Vivo Testing Program – Sarcomas and other Solid Tumors

  The primary goal of this project involves the comprehensive molecular profiling of patient-derived xenograft (PDX) mouse tumor models. Molecular profiling of each PDX model will include whole exome sequencing (WES), RNAseq, MethylEPIC arrays, CytoSNP array, and DNA fingerprint for quality control. Limited clinical demographic data (e.g. diagnosis, disease site, disease status) will be obtained. This data can be utilized to validate PDX models with matched patient tumors and can be used to guide model selection for downstream preclinical drug testing.

  Study phs003161

• Childhood Cancer Data Initiative (CCDI): Integrating Longitudinal Clinical, Sociodemographic and Genomic Data into the NCCR

  The goal of this study is to contribute clinical and genomic data from a large institutional cohort of pediatric cancer patients who had tumor genomic profiling between 2013 and 2019 at Dana-Farber/Boston Children's Hospital Cancer and Blood Disorders Center. Clinical data include demographics, diagnosis (classified according to the International Classification of Diseases for Oncology (ICD-O-3.2), stage, and biospecimen associated data. Tumors were sequenced with OncoPanel, a targeted next-generation DNA sequencing panel of up to 447 cancer genes for detection of single-nucleotide variants (SNV), insertions, and deletions, and copy number alterations (CNA), as well as selected intronic regions for up to 60 genes for the detection of structural variants (SV). This dataset includes a patient and sample identifier (GENIE ID) that can be used to link the genomic data included in this dataset to additional longitudinal clinical cancer data on a subset of patients that was submitted to the National Childhood Cancer Registry (NCCR).

  Study phs002677

• Whole Exome and RNA Sequencing of 22 Patient-Derived Xenografts from Estrogen Receptor-Positive Breast Cancers

  We performed RNA and whole exome sequencing on 22 patient-derived xenografts (PDX) from estrogen receptor-positive (ER+) breast cancers, in the presence and absence of estradiol (E2) supplementation. Exome coverage across more than 3,500 clinically relevant genes that previously were covered below 20X (~2.72Mb) was achieved. On average, 11.2Gb of unique sequence data were generated with 95.3% of the bases in the exome design covered to 20x read depth or greater. RNA sequencing was generated from xenograft tumors. Between 50 and 85M total reads were performed. The average strand-specificity and rRNA rate was 98% and 1.5%, respectively. Transcripts for 17,000 to 27,087 genes were detected in these samples.

  Study phs003324

• NCTN: Randomized Phase III Study of Maintenance Therapy With Bevacizumab, Pemetrexed, or a Combination of Bevacizumab and Pemetrexed Following Carboplatin, Paclitaxel and Bevacizumab for Advanced Non-Squamous NSCLC (E5508)

  Study ID: E5508NCT Number: NCT01107626ECOG-ACRIN Cancer Research Group Submitted in collaboration with the NCTN/NCORP Data Archive Trial Title: NCTN: Randomized Phase III Study of Maintenance Therapy with Bevacizumab, Pemetrexed, or a Combination of Bevacizumab and Pemetrexed following Carboplatin, Paclitaxel and Bevacizumab for Advanced Non-Squamous NSCLC (E5508) Trial Description: RATIONALE: Drugs used in chemotherapy, such as paclitaxel and carboplatin, work in different ways to stop the growth of tumor cells, either by killing the cells or by stopping them from dividing. Monoclonal antibodies, such as bevacizumab, can block tumor growth in different ways. Some block the ability of tumor cells to grow and spread. Others find tumor cells and help kill them or carry tumor-killing substances to them. Bevacizumab may also stop the growth of non-small cell lung cancer by blocking blood flow to the tumor. Pemetrexed disodium may stop the growth of tumor cells by blocking some enzymes needed for cell growth. It is not yet known whether giving bevacizumab or pemetrexed disodium alone or in combination is more effective in treating non-squamous non-small cell lung cancer. PURPOSE: This randomized phase III trial is studying bevacizumab and pemetrexed disodium alone or in combination after induction therapy to see how well they work in treating patients with advanced non-squamous non-small cell lung cancer. Clinical data presented in the following publication(s): PMID 31361535 Disease type(s): Lung, Mediastinal and Pleural Neoplasm - Non-Small Cell Lung Cancer Clinical dataset(s) included: NCT01107626-D1 (PMID 31361535): There are two different datasets for PMID 31361535 from trial E5508. This dataset, NCT01107626-D1, contains baseline characteristics, treatment assignment, prior treatment, metastatic sites and efficacy data. Pemetrexed or bevacizumab is used for maintenance therapy of advanced no squamous non-small cell lung cancer (NSCLC). The combination of bevacizumab and pemetrexed has also demonstrated efficacy. This study contains two step registration, induction therapy step and maintenance therapy. All patients who were registered to at least one of the steps are included. Due to data cleaning efforts, data may contain slight discrepancies from that reported in Table 1 and Table 2 in the publication (PMID 31361535). The number of each metastatic site is incorrect in the publication: The data in this dataset is correct.NCT01107626-D2 (PMID 31361535): There are two different datasets for PMID 31361535 from trial E5508. This dataset, NCT01107626-D2, contains toxicity data. Pemetrexed or bevacizumab is used for maintenance therapy of advanced no squamous non‐small cell lung cancer (NSCLC). The combination of bevacizumab and pemetrexed has also demonstrated efficacy. This study contains two step registration, induction therapy step and maintenance therapy. All patients who were registered to at least one of the steps are included.You are encouraged to view the PDF data dictionaries found in the “Documents” tab of the dbGaP study page, which may contain additional information regarding the data or the associated publication(s).

  Study phs004240

• International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Oral Squamous Cell Carcinoma in Taiwan

  Oral cavity squamous cell carcinoma (OSCC) is the major subtype (~90%) of oral cancer, which is leading cancer with high mortality worldwide. The environmental risk factors associated with OSCC are quite different in Taiwan as compared to other populations. In most non-Taiwanese populations, OSCC is often associated with tobacco chewing, cigarette smoking, alcohol drinking, or human papillomavirus (HPV) infection. In Taiwan, in contrast, the OSCC occurs mainly in males aged 30 years or older who have habitual betel nut chewing, cigarette smoking, and alcohol drinking. To uncover molecular mechanisms and identify new therapeutic strategies of oral squamous cell carcinoma, this study recruited 112 treatment-naïve OSCC patients and generated multi-omics data, including WES, RNA-Seq, TMT-labeled proteomes, and phosphoproteomes from paired normal/tumor tissues. We have investigated our multi-omics data, covering molecular characterizations such as mutation signatures, impacts of mutations on RNA/protein/phosphoprotein, RNA-protein correlation, somatic copy number alteration, and the relationship with RNA & protein, proteome, and phosphoproteome analysis (T vs NAT), novel peptides (somatic variants, neoantigens, CT antigens, T cell receptors, etc.), as well as molecular subtyping (& pathway analysis). Notably, we have discovered a higher frequency of APOBEC3B deletion polymorphism in the Taiwanese population, and APOBEC3A is a potential prognostic biomarker. Our proteogenomic data enable us to further stratify patients into four groups based on APOBE3A expression level, which is found inversely correlated with EGFR expression. Therefore, the patients with high EGFR and low APOBEC3A expression may benefit from anti-EGFR therapy, while those with low EGFR and high APOBEC3A expression may benefit from immunotherapy. To clarify if there is an interaction between genetic polymorphisms and betel nut chewing habit in Taiwanese OSCC, we plan to concurrently evaluate the effect of habitual betel nut chewing on the gene mutation pattern, the dysregulated protein/phosphoproteins as novel biomarkers and/or therapeutic targets, and the molecular subtyping of patients for effective treatments. 

  Study phs002580

• Evolution of Structural Rearrangements in Prostate Cancer Intracranial Metastases

  Intracranial metastases in prostate cancer are uncommon but clinically aggressive. We sought to characterize prostate cancer intracranial metastases in order to improve our understanding of their pathogenesis and to promote the search for new treatment strategies. We evaluated the clinical and molecular characteristics of 36 patients with metastatic prostate cancer to either the dura or brain parenchyma. We performed whole genome sequencing (WGS) on samples from 21 patients. The WGS samples include 10 intracranial prostate cancer metastases, as well as WGS of primary prostate tumors from men who later developed metastatic disease (n=6) and non-brain prostate cancer metastases (n=26).

  Study phs003357

• Genetic Factors Associated with Anthracycline-Induced Cardiomyopathy (COG-ALTE03N1)

  We investigated the genetic mechanisms underlying anthracycline-induced cardiomyopathy, a serious long-term complication among childhood cancer survivors. We focused on the role of DNA damage response and repair (DDR) genes, which had not been previously studied in this context. A gene-based and pathway-based approach was applied to assess both the main effects and gene-by-anthracycline interaction effects of DDR genes on cardiomyopathy risk. The analysis was conducted using a matched case-control design within the COG-ALTE03N1 study, including 113 cases and 226 controls, all of whom were non-Hispanic White childhood cancer survivors exposed to anthracyclines. For each case, we randomly selected 1-3 childhood cancer survivors with no cardiomyopathy, matched on primary cancer diagnosis, year of diagnosis (±10y), and race/ethnicity. The selected controls had to have a longer duration of follow-up compared with time from cancer diagnosis to cardiomyopathy for the corresponding case. Participants provided blood or saliva for germline DNA isolation and genotyping. Genotyping was performed using Illumina HumanOmniExpress-12 v1.0 (709,358 SNPs) and IlluminaOmni5Exome-4 v1.3 arrays (4,293,368 SNPs), with merging of genotype data from the two arrays (683,781 overlapped SNPs) and quality control (QC) using PLINK. Of the 220 genes in the MD Anderson DDR gene website, 187 genes with 2,220 single nucleotide polymorphisms [SNPs] identified on our array data were included in the analyses. A total of 2,170 SNPs were retained in the final gene-based and pathway-based analysis in 339 anthracycline-exposed non-Hispanic White (NHW) patients (113 cases; 226 controls). Key findings included significant associations for FANCC and XRCC5 with cardiomyopathy risk (main effect), and a significant gene-environment interaction involving MGMT. The study also confirmed the involvement of DDR-related biological pathways through both genetic association and interaction analyses.Data Available Through dbGaP: • Genotype data (GWAS) for all study participants • Phenotype data: age at primary cancer diagnosis, sex, race/ethnicity, case-control status This dataset supports further research into genetic susceptibility to chemotherapy-induced adverse outcomes and enables cross-cohort comparisons in cardio-oncology.

  Study phs003792

• The Role of E2F4 in Controlling Resistance to Irinotecan (CPT-11) in Human Colon Cancer

  This study reports the results of RNA sequencing (RNA-seq) experiments performed on three isogenic clones of the human HT29 colon cancer cell line, genetically engineered to achieve the selective inactivation of the adenovirus early 2 (E2) gene transcription factor 4 (E2F4) protein, a key functional component of the multimeric transcriptional repression complex known as the dimerization partner (DP), retinoblastoma-like (RB-like), E2F and multi-vulva class B (MuvB) complex (DREAM). In previous studies, we identified E2F4 as a key regulator of colorectal cancer (CRC) resistance to irinotecan (CPT-11), a cytotoxic agent that stands at the backbone of multiple chemotherapy regimens for the treatment of metastatic CRCs. The molecular mechanisms linking E2F4 to irinotecan resistance, however, remain poorly understood. The present study was designed to identify which genes are under the transcriptional control of E2F4, either at baseline or following exposure to SN38 (i.e., the active metabolite of irinotecan, generated in vivo by biotransformation in the liver) in order to clarify the role played by E2F4 in shaping colon cancer resistance to chemotherapy. The cell line used for this study (HT29) is aneuploid and contains three copies of the E2F4 gene, because of a trisomy of chromosome 16, where the E2F4 gene is located (Kawai et al., Genes, Chromosomes & Cancer, 34:1-8, 2002; PMID: 11921276). HT29 cells were infected with lentivirus vectors encoding for CRISPR/Cas9 constructs designed to selectively inactivate the E2F4 gene, using three distinct guide-RNAs (gRNAs), each targeting a different sequence within the proximal exons of the E2F4 gene (exon 1, exon 2). Lentivirus-infected cells were sub-cloned by single-cell fluorescence-activated cell sorting (FACS), based on the differential expression of a fluorescent reporter (EGFP) expressed in tandem with the gRNAs. Isogenic clones (EGFP+) were then screened to identify those with a tri-allelic knock-out, as revealed by both genetic sequencing of the E2F4 gene (revealing the presence of three distinct frameshift mutations) and Western blot (revealing complete loss of E2F4 protein expression). The study includes twelve (n=12) RNA-seq experiments, representative of 3 experimental replicates (i.e., three distinct isogenic clones of the HT29 cell line, each displaying complete loss of E2F4 expression) and 3 negative controls (i.e., three independent preparations of the parent HT29 cell line, infected with a lentivirus vector encoding for a non-targeting gRNA) exposed to 2 distinct in vitro cell culture conditions: a) treatment with SN38 resuspended in dimethyl sulfoxide (DMSO); or b) treatment with DMSO alone (negative control). The in vitro treatment regimen used for SN38 (32 nM, 24 hours) was designed so that the exposure to SN38 experienced in vitro by HT29 cells would mirror the exposure to SN38 experienced in vivo by malignant tissues, as measured, for example, in metastatic CRC patients receiving a standard dose of irinotecan (180 mg/m2) administered by intravenous infusion over 90 minutes (Deyme et al., Cancer Chemotherapy and Pharmacology, 88:247-258, 2021; PMID: 33912999).

  Study phs003560

• Proteogenomic Characterization Unveils Biomarkers Associated With Chemoresistance in Muscle Invasive Bladder Cancer

  Cisplatin-based neoadjuvant chemotherapy (NAC) combined with radical cystectomy has been used as a standard of care for patients with clinically non-metastatic muscle invasive urothelial bladder cancer, but 40-50% patients will benefit from the treatment. Molecular subtypes of muscle invasive bladder cancer (MIBC) provide a possible biomarker roadmap that may help identify patients who may or may not respond to NAC. Recently, by integrating Mass Spectrometry-based proteomics, proteogenomic studies from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) have demonstrated the potential of this approach in prioritizing candidate driver genes and facilitating understanding of the chemotherapy resistance mechanisms. To demonstrate the proteogenomic workflow for investigating the mechanisms underlying chemotherapy resistance in MIBC, we conducted proteogenomic characterization of 46 pre- and 14 post- treatment tumors, including whole exome sequencing (WES), mRNA sequencing, Tandem Mass Tag (TMT)-proteomics, or TMT-phosphoproteomic. These samples were selected from an initial cohort of 143 MIBC tissues and filtered by tumor purity, clinical history, pathological response, and proteomic quality control metrics. The final cohort comprised samples from 53 patients, including 45 with both genomic and proteomic data and 8 with genomic data only.Our multi-omics-based clustering reveals subtypes associated with chemotherapy sensitivity. Protein abundance of a short isoform of ATAD1 and RAF family proteins were identified as biomarkers of chemosensitivity which highlights the importance of proteomics data. Integration of proteomic and phosphoproteomic data reveals Wnt signaling via GSK3B-S9 phosphorylation and the JAK/STAT pathway as potential targets to overcome chemoresistance. Correlations between PD-L1 and TROP-2/NECTIN-4 indicate an additive benefit of combination therapy targeting these proteins. Our data analysis clearly demonstrates that proteogenomic plays an important role in uncovering potential resistance mechanisms that operate only at protein and Post-Translational Modification (PTM) levels. Proteomics data can be accessed through PRIDE with ID PXD060290. RNA-seq and whole-exome sequencing (WES) FASTQ files are archived in the dbGaP database.

  Study phs004049

• Blood and Marrow Clinical Trials Network Trial of Non-Myeloablative Conditioning and Transplantation of Umbilical Cord Blood For Hematologic Malignancies (BMT CTN-0604-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To examine the safety and effectiveness of a non-myeloablative stem cell transplant using umbilical cord blood as a treatment option for patients with leukemia or lymphoma and no suitable related donor.Background: Chemotherapy is a common treatment option for patients with aggressive forms of the blood cancers leukemia and lymphoma, but other treatment methods may need to be considered if the cancer does not respond well to chemotherapy, or if the cancer returns. In such cases, it may be recommended that the patient receive a stem cell transplant, commonly using donated bone marrow. A first degree relative is likely to be the best candidate for donation if the human leukocyte antigen (HLA) markers are a sufficient match. For patients lacking a HLA-matched related donor, it is routine to initiate an unrelated donor search. However some patients, particularly ethnic minorities, experience disease progression while awaiting identification of a suitably HLA-matched donor. Recently, stem cell transplants using umbilical cord blood have become a viable alternative option to treat these types of cancers.Typically patients undergoing a stem cell transplant receive high doses of chemotherapy before the transplant to prepare their bodies to accept the donor stem cells. In this study, participants received a type of stem cell transplant called a non-myeloablative transplant, which is a reduced intensity conditioning (RIC) method of transplantation that does not require high doses of chemotherapy. RIC can be preferable in patients that are older and less clinically fit, and therefore less able to withstand the chemotherapeutic agents' toxicity levels.The BMT CTN 0604 study was one of two parallel multicenter phase 2 studies; the other of which was BMT CTN 0603, which used partially HLA-mismatched related bone marrow (Haplo-marrow) transplantation. The goal of these studies was to generate pilot multicenter data to support a future phase 3 randomized clinical trial.Participants: Patients less than 71 years of age with acute leukemia or lymphoma and lacking a suitable HLA-matched related donor were eligible to participate. Patients less than 22 years of age were eligible if they were ineligible for the BMT CTN 0501 trial. Acute leukemia was required to be in morphologic complete remission. Large-cell, mantle-cell, and Hodgkin lymphomas were required to have achieved at least a partial remission with treatment before allogeneic hematopoietic cell transplantation. Low-grade lymphoma patients were required to have failed two prior chemotherapy regimens. Patients who had undergone prior autologous transplantation were not excluded as long as three months had elapsed since the procedure. Participants were also required to have adequate organ function, including a left ventricular ejection fraction of at least 35% and specific liver, kidney, pulmonary, and physical functioning scores within acceptable ranges. A total of 54 individuals were enrolled in the study and 50 were included in the analysis.Design: Participants underwent a reduced intensity conditioning regimen prior to receiving the double umbilical cord blood (dUCB) transplant, which included two chemotherapeutic agents, cyclophosphamide and fludarabine, and a small dose of radiation. Cyclophosphamide was administered intravenously at 50 mg/kg six days before the transplant. Fludarabine was administered intravenously at 40 mg/m2 (adjusted for creatinine clearance) each day for five days before the transplant. A single dose of 200 cGy total body irradiation was performed one day prior to transplantation. Participants also received cyclosporine and mycophenolate mofetil (MMF) beginning three days before the transplant as prophylaxis for graft-versus-host-disease (GVHD). Participants could receive tacrolimus instead of cyclosporine.At transplantation, patients received two partially HLA-matched umbilical cord blood units from unrelated donors. The maximum allowable mismatch between the UCB unit and the recipient, or between the UCB units, was 2 of 6 HLA loci. Each unit contained a minimum of 1.5 × 107 nucleated cells, or 2.0 × 107 for units that were not red cell depleted, per kilogram of recipient weight. Units were thawed and infused per institutional practice after validation using methods approved by the study. After transplantation, filgrastim, a granulocyte-colony stimulating factor, was initiated at 5 μg/kg a day and continued until the absolute neutrophil count was at least 2000/μL for three consecutive days. Participants continued to receive MMF for 30 days after the transplant or 7 days after engraftment, whichever was later, and cyclosporine or tacrolimus until 180 to 200 days after the transplant. Supportive care, including blood product administration, prophylaxis, therapy for infection, and treatment of GVHD, was at the discretion of treating physicians and transplantation center practices.The primary outcome was participant survival from the time of transplant to 180 days. Secondary end points included progression-free survival and cumulative incidences of hematopoietic recovery, acute or chronic GVHD, relapse, and non-relapse mortality.Conclusions: Survival at 180 days after double umbilical cord blood transplant was 74%. Collectively, the results of BMT CTN 0603 and 0604 confirm the utility of dUCB and Haplo-marrow as alternative donor sources for reduced intensity conditioning hematopoietic cell transplantation, providing a rationale for an additional clinical trial to assess the relative efficacy of these two strategies.

  Study phs004890

• A Phase II Study: CRS207/GVAX Plus Anti-PD1 and Anti-CTLA4 Recruits Mesothelin- and KRAS-Specific T cells into PDAC

  This study examined immunologic correlatives from a phase II study evaluating CRS207/GVAX vaccines in combination with anti-PD1 and anti-CTLA4 in metastatic pancreatic cancer (NCT03190265). Arm A received CRS207/GVAX with anti-PD1 and anti-CTLA4 therapy; Arm B received CRS207 with anti-PD1 and anti-CTLA4 therapy. Patients undergoing treatment in this trial had peripheral blood mononuclear cells (PBMCs) and tumor tissue biopsied serially at pre-treatment and on-treatment timepoints. Single-cell RNA/TCR sequencing was employed on PBMCs. Bulk RNA/TCR sequencing was employed on tumor tissues. We identified treatment-enriched inflammatory pathways as well as T cell repertoires.

  Study phs003798

• Correlative Studies in Protocol GU16-287, which Studied Gemcitabine + (Carboplatin or Oxaliplatin) + Nivolumab in Metastatic Urothelial Cancer, which Included Collaboration with CIMAC-CIDC (Cohort 1 of 3)

  Purpose: Oxaliplatin has demonstrated the ability to sensitize tumors to immune checkpoint blockade through its immunomodulatory properties in model systems of cancer. This randomized trial aimed to evaluate gemcitabine/oxaliplatin and gemcitabine/carboplatin, each combined with nivolumab, in cisplatin-ineligible metastatic urothelial carcinoma (mUC) patients. Patients and Methods: Cisplatin-ineligible patients with mUC were randomized 1:1 to gemcitabine/carboplatin plus nivolumab or gemcitabine/oxaliplatin plus nivolumab for up to 6 cycles, followed by nivolumab monotherapy. A pick-the-winner design was employed with objective response rate (ORR) as the primary endpoint. Secondary endpoints included progression-free survival (PFS) and overall survival (OS). Exploratory analyses evaluated plasma protein analytes, circulating immune cell populations, and circulating tumor cells. Results: Forty-nine patients were enrolled (carboplatin arm, N = 25; oxaliplatin arm, N = 24). The ORR was 69.6% (95% confidence interval [CI] 0.48–0.87) for the carboplatin arm and 33.3% (95% CI 0.15–0.57) for the oxaliplatin arm. Median OS was 24.74 months and 16.43 months for the carboplatin group and oxaliplatin arms, respectively (hazard ratio 1.99, 95% CI 0.94–4.22; p = 0.07). Exploratory biomarker analyses revealed sustained adaptive immune activation in the carboplatin arm and features suggestive of tumor-promoting inflammation in the oxaliplatin arm. Conclusions:Oxaliplatin-based chemo-immunotherapy, versus carboplatin-based chemo-immunotherapy, did not yield a higher response rate, challenging assumptions based on preclinical data.

  Study phs004060

• Durvalumab and Cediranib with and without Olaparib in Recurrent Ovarian Cancer: A phase II Proof-of-Concept Study

  We report the efficacy and translational research findings of durvalumab, olaparib, and cediranib (D+O+C) and durvalumab and cediranib (D+C) therapies from the recurrent epithelial ovarian cancer (EOC) cohort within a single center, multi-arm, non-randomized, multi-cohort phase I/II trial (NCT02484404). Sixty-eight patients were enrolled (39 in D+O+C, 29 in D+C). The objective response rate (ORR) was 19.4% (95% CI, 9.5-43.5) for D+O+C and 29.6% (95% CI, 13.8-46.9) for D+C. Median progression-free survival (PFS) was 4.5 months in both arms, with each arm including four exceptional responders (PFS ≥ 12 months). Pre-treatment biopsies and paired normal peripheral blood mononuclear cells (PBMC) samples for whole exome sequencing (WES) were available for 31 patients in the D+O+C and 24 in the D+C, the remaining 13 patients were not biopsied due to safety concerns or being off treatment. WES was conducted to explore genomic profiles for potential correlations with clinical benefit (CB; partial response or stable disease [SD] with PFS ≥ 4 months) or no clinical benefit (NCB; progressive disease or SD with PFS TP53 mutations were found in most cases in both D+O+C and D+C arms. Overall, no consistent associations between baseline genomic alterations and CB were observed.

  Study phs004519

• NCTN: A Double Blind Randomization to Letrozole or Placebo for Women Previously Diagnosed with Primary Breast Cancer Completing Five Years of Adjuvant Aromatase Inhibitor either as Initial Therapy or after Tamoxifen (NCIC-MA.17R)

  Study ID: NCIC-MA.17RNCT Number: NCT00754845 Canadian Cancer Trials Group (CCTG)Submitted in collaboration with the NCTN/NCORP Data ArchiveTrial Title: NCTN: A Double Blind Randomization to Letrozole or Placebo for Women Previously Diagnosed with Primary Breast Cancer Completing Five Years of Adjuvant Aromatase Inhibitor either as Initial Therapy or after Tamoxifen (NCIC-MA.17R)Trial Description: RATIONALE: Estrogen can cause the growth of breast cancer cells. Hormone therapy using letrozole may fight breast cancer by lowering the amount of estrogen the body makes. It is not yet known whether letrozole is more effective than a placebo in treating in women with breast cancer who have already received 5 years of aromatase inhibitor therapy.PURPOSE: This randomized phase III trial is studying letrozole to see how well it works compared with a placebo in treating women with primary breast cancer who have received 5 years of aromatase inhibitor therapy. Clinical data presented in the following publication(s):PMID 27264120 Disease type(s): Breast Neoplasm - Breast Cancer - InvasiveClinical Dataset(s) included:NCT00754845-D1 (PMID 27264120): There is one dataset for NCIC-MA.17R's primary publication 27264120. This dataset contains number of major protocol violations, time from diagnosis to randomization, baseline characteristics, hormone receptor status, sites of recurrence, survival, toxicity, stratification factors, cause of death, and QOL data.You are encouraged to view the PDF data dictionaries found in the “Documents” tab of the dbGaP study page, which may contain additional information regarding the data or the associated publication(s).

  Study phs004248

• Somatic Evolution in Li-Fraumeni Syndrome

  In this study, we used ultradeep duplex sequencing (~15,000× depth) to measure somatic evolution in blood samples from a family of three individuals with Li-Fraumeni Syndrome (LFS) caused by an inherited TP53 pathogenic variant (p.R181H), and compared them to a cohort of unaffected controls using a set of genes related to Clonal Hematopoiesis of Indeterminate Potential (CHIP)/Acute Myeloid Leukemia (AML), as well as a mutagenesis panel designed to examine mutagenic processes. We found that individuals inheriting a single mutated copy of TP53 may experience less positive selection for subsequent TP53 mutations, as evidenced by a deficit of coding TP53 mutations, reduced dN/dS, and low predicted pathogenicity among the TP53 somatic mutations that do occur. However, the overall degree of mutagenesis in genomic regions without strong selection was higher in LFS patients. In addition, we investigated how LFS affects clonal evolution across multiple tissue contexts in one individual carrying p.R181H who succumbed to metastatic esophageal cancer.The data available through dbGaP includes BAM files, MAF files (mutation data), and genomic MUT files (showing per-position depth of sequencing), from ultradeep duplex sequencing of multiple tissues from a LFS patient as well blood samples from family members and controls.

  Study phs004484

• Prostate Cancer Upgrading Reference Set

  This study aimed to investigate clinical, demographic, and molecular features of men diagnosed with low-risk prostate cancer [ISUP Grade Group 1 (GG1)] at biopsy who underwent radical prostatectomy, and for whom an increased tumor grade (ISUP Grade Group 2 or above) was subsequently detected in the resected prostate. This phenomenon is termed upgrading. In collaboration with the Early Detection Research Network (EDRN), a blinded reference set was established to facilitate upgrading biomarker detection and validation. A prospective, multi-institutional, cohort of men with the GG1 prostate cancer and intention to undergo prostatectomy was recruited. Biospecimens (blood, urine) were collected and this biorepository comprises the official EDRN Upgrading Reference Set (URS). Recording of case-control status (case = upgrading at prostatectomy, control = no upgrading at prostatectomy) was coordinated by the Data Management and Coordinating Center (DMCC) of the EDRN, who ensured blinding of all participating researchers. A subset of the reference set (n = 192) was chosen to undergo whole genome sequencing (WGS) for the investigation of a germline genomic biomarker of upgrading. Variant calls from all sequenced URS whole genomes are available through dbGaP, with the exception of one sample for which sequencing was not successful. Among investigated clinical features, prostate-specific antigen (PSA) density and percent of cancer in pre-prostatectomy positive biopsy cores were significantly associated with upgrading. Two polygenic risk score-based biomarkers were computed in the genetic sub-cohort and tested against case-control status. Neither was predictive of upgrading.

  Study phs003670

• Improved Cardiovascular Risk Reduction to Enhance Rural Primary Care (ICARE-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To evaluate whether a centralized, remote clinical pharmacy service could improve guideline adherence and secondary measures of cardiovascular risk in primary care offices in rural and small communitiesBackground: More than 2200 Americans die of cardiovascular disease every day. Team-based care and medication therapy management have become useful strategies to reduce gaps in the delivery of guideline-concordant therapy for cardiovascular therapy. Physician offices, especially in rural and smaller communities, lack the resources to implement team-based care with pharmacists who can provide medication therapy management. The ICARE trial developed a physician-pharmacist collaborative model to provide virtual clinical pharmacy services from a central location to 12 family medicine offices in Iowa to evaluate whether a centralized, remote clinical pharmacy service could improve outcomes.Participants: Subject inclusion involved 3 separate processes. First, subjects were required to be an English-speaking male or female over the age of 50 who had been seen in the clinic/practice at least once in the past 24 months. Second, subjects were required to have at least one of the following conditions: uncontrolled diabetes (hemoglobin A1c > 7.5%); low-density lipoprotein cholesterol (LDL-C) > 110 mg/dl for patients with a history of peripheral artery disease, coronary artery disease, stroke, transient ischemic attack, or diabetes, elevated blood pressure with systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg in persons with diabetes or chronic kidney disease, or systolic BP ≥ 150 mmHg or diastolic BP ≥ 90 mm Hg in persons with uncomplicated hypertension. Third, subjects were required to additionally have three or more of the following cardiovascular conditions or risk factors: history of myocardial infarction, coronary artery disease, stroke, transient ischemic attack, atrial fibrillation, peripheral vascular disease/claudication, current smoker, or obesity with BMI > 30.Exclusion criteria included diagnosis of primary pulmonary hypertension, a cancer diagnosis with a life expectancy of less than 2 years, residence in a nursing home or diagnosis of dementia, no telephone access or a hearing impairment that prevented telephone use, or patient had plans to move from the area or transfer care to a different clinic in the next 12 months.In total, there were 302 subjects enrolled in the ICARE trial. Of these, 259 subjects completed the 12-month visit.Design: The study included 11 private physician offices and one Federally Qualified Health Center. Offices were identified from the Iowa Research Network and screened for their ability to conduct the trial, enroll subjects, and meet quality control measures. A Study Coordinator employed in each office identified, screened, and recruited subjects. All subjects and physicians in a given office received either the intervention or usual care.Blood pressure, hemoglobin A1c, and LDL cholesterol were collected at baseline and 12 months regardless of whether the subject had a diagnosis of hypertension, diabetes, or hyperlipidemia. Baseline data were collected on case report forms by Study Coordinators and entered centrally by the research team.Three clinical pharmacy specialists located within the research offices of the principal investigator provided the intervention. Pharmacists were required to have a Doctor of Pharmacy degree and a minimum of one year of clinical residency (or equivalent practice experience). The pharmacists travelled to each intervention office to be introduced to the providers and facilitate team-building before the intervention started. These sessions explored the providers' preferred methods and frequency of communication with the pharmacists based on other telemedicine studies. Pharmacists had access to the baseline data, including BP and laboratory values, which they used to reconcile medications and update the medical records. Pharmacists monitored blood glucose values, BP readings, laboratory values, and potential adverse events from the EMR or from the patient in order to recommend medication changes to the treating medical provider. Interventions for physicians were directed at improving guideline adherence for reducing CV risk and preventive care based on the Guideline Advantage (GA) criteria.Each subject was assigned to one of the three pharmacists to maintain continuity. Subjects were assigned to the pharmacists in the order they were enrolled into the study, independent of medical office. Subjects were primarily contacted by telephone and counseled by the pharmacists about beneficial health behavior changes related to tobacco use, diet, physical activity, and alcohol consumption. Medications and dosages were reconciled. The pharmacists identified problems related to poor disease control, subject misunderstandings, poor medication adherence or failure to receive preventive health services, adverse effects, drug interactions, and cost. Pharmacists provided patient education when problems were identified and developed a plan for follow-up contacts, generally every 1-2 weeks by telephone if there were continuing problems or medication issues. The primary outcome measure was adherence to the GA criteria.Conclusions: There was no improvement in the GA score from baseline to 12 months in the control group. There was a statistically significant improvement in the intervention group in the GA score plus several criteria were significantly better for intervention subjects including appropriate statin therapy, body mass index (BMI) screening and alcohol screening. Only 13.7% of subjects with diabetes had hemoglobin A1c at goal at baseline and this increased to 30.8% and 21.0% in the intervention and control groups, respectively, at 12 months.The improvements in outcomes were modest and not statistically significant, due to higher-than-anticipated baseline guideline adherence and greater inter-office variability than anticipated.

  Study phs004679

• Epigenomics of Neurocognitive Function in Breast Cancer

  This study harnessed the data and biospecimens from the Exercise Program in Cancer and Cognition (EPICC) study (parent study) that collected data on cognitive function, demographics, other symptoms and biospecimens at two time points (T1: enrollment, T2: six months later) within the context of a six-month randomized controlled trial of a moderate intensity aerobic exercise intervention. This study collected genome wide DNA methylation data from T1 and T2 and conducted epigenome-wide association-based analyses to find genes and biological pathways explaining variability in cognitive function and explaining how exercise mitigates cognitive decline. Our initial findings identified cg10331779 near CTNND2 (p-value=9.65×10-9) associated with processing speed and cg25906741 in MLIP (p-value=2.01×10-8) associated with subjectively measured cognitive function. Additionally, differentially methylated regions were identified near SLC6A11, PRKG1/CSTF2T, and FAM3B for processing speed and near PI4KB and SGCE/PEG10 for mental flexibility.

  Study phs003959

• Human GPR15 Deficiency Reveals CD8+ T Regulatory Cell-Macrophage Crosstalk in Intestinal Inflammation

  Inflammatory bowel disease (IBD) causes lifelong suffering from gastrointestinal inflammation and dysfunction with severe complications including colon cancer. The disease is increasing in global prevalence, and current therapies are insufficient, highlighting an urgent need to understand its pathogenic mechanism. We reported multiple patients with GPR15 deficiency which result in severe early-onset IBD. GPR15, a G protein-coupled receptor (GPCR), expressed in immune cells and previously described as an entry co-factor for human and simian immunodeficiency viruses, is a crucial marker and homing receptor for a unique subset of intramucosal GPR15-guided regulatory CD8+ T lymphocytes (CD8+ TIGR). These cells potently kill macrophages that become aggressively activated in response to intestinal damage or disease. Thus, our identification of CD8+ TIGR cells yields new insights into organ-specific immune regulation and potential treatment strategies for IBD.

  Study phs003950

• Combined PDCD1, BRAF and MAP2K7 Inhibition in BRAFV600E Colorectal Cancer: A Phase 2 Trial

  In this study, we evaluated the clinical efficacy of combined PDCD1, BRAF, and MAP2K7 inhibition in metastatic BRAFV600E Colorectal Cancer (CRC) patients (NCT03668431). We performed bulk whole exome sequencing (WXS) and bulk RNA sequencing (RNA-Seq) in 35 pre-treatment tumor biopsies and matching germline for tumor mutational burden (TMB), BM1/BM2 transcriptional subtypes, and consensus molecular subtypes (CMS) analysis, which were previously reported to affect prognosis and response to therapy (PMIDs: 32047001, 27354468, and 26457756). Analysis of bulk data showed that TMB, BM1/BM2 subtypes, and CMS did not correlate with clinical response in this study. Analysis of single cell RNA sequencing (scRNA-Seq) data of tumor epithelial cells from 23 paired day 0 and day 15 tumor biopsies revealed greater induction of tumor cell-intrinsic immune programs and more complete MAPK inhibition in patients with better clinical outcome.

  Study phs003178

• Childhood Cancer Data Initiative (CCDI): Single-Cell Atlas of NF1 Nerve Sheath Tumors

  The worst outcome of NF1 is the development of the aggressive and highly metastatic malignant peripheral nerve sheath tumors (MPNST), which transform from benign plexiform neurofibroma (PN) and lack effective treatment. In this study, we performed single-cell RNA sequencing of 63 clinically annotated NF1-associated peripheral nerve sheath tumors, including 24 PN, 34 premalignant atypical neurofibromas, and 5 MPNSTs. These results improve the ability of identifying high-risk neurofibromas and provide a unique opportunity for early detection of MPNST.

  Study phs003519

• Single Cell RNA-Sequencing of BCG Naive and Recurrent Non-Muscle Invasive Bladder Cancer Reveals a CD6/ALCAM-Mediated Immune-Suppressive Pathway

  Non-muscle invasive bladder cancer (NMIBC) represents 70–80% patients with newly diagnosed bladder cancer, and Bacillus Calmette-Guerin (BCG) remains a cornerstone treatment for intermediate- and high-risk NMIBC to prevent disease recurrence and progression. However, a significant number of patients experience recurrence after their first course of BCG, posing significant challenges in the management of the disease. We conducted single cell RNA sequencing (scRNA-Seq) on freshly collected NMIBC samples, distinguishing between those naive to BCG treatment and those that recurred post-BCG treatment. We observed a clear activation of inflammatory pathways across cell types during recurrence, but these were not associated with canonical immune checkpoint or T cell exhaustion phenotypes. Analysis of cell-to-cell communication revealed enhanced interactions between T cells and urothelial cells in BCG-recurrence, predominantly modulated by CD6 and activated leukocyte cell adhesion molecule (ALCAM). Furthermore, we found CD6hi T cells to be immunosuppressed and enriched in recurrent samples, suggesting a potential role for CD6 as an immune evasion signal in NMIBC.

  Study phs003742