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• 1 Intratumoral genetic heterogeneity and clonal evolution following neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal tumors.

  Purpose: Neoadjuvant chemoradiotherapy (nCRT) is the standard treatment forpatients with locally advanced rectal cancer. However, little is known about the effect of nCRT in the mutational landscape and intratumoral genetic heterogeneity (ITGH) of rectal tumors. Moreover, response to nCRT vary substantially among patients and the genetic determinants of treatment response are not fully understood. Here, we sought to determine the impact of nCRT in the mutational landscape and ITGH of rectal tumors and to identify putative drivers of therapeutic resistance. Patients and Methods: We analyzed whole-exome sequencing (WES) and clinical data from 79 primary non-treated rectal cancers obtained from The Cancer Genome Atlas (TCGA). We also compared the mutational landscape of a matched set of peripheral blood cells, irradiated tumor-adjacent colonic mucosa and pre and post-treatment tumor samples to determine the iatrogenic effects of nCRT and its impact in tissue genetic heterogeneity. Finally, we performed WES of 7 matched pre and post-treatment tumor samples to examine how nCRT affects the clonal architecture of rectal tumors. Results: We show that rectal tumors exhibit remarkable ITGH, which increases with disease progression. We also show that nCRT, per se, does not introduce novel somatic mutations, nor alters the clonal architecture of the irradiated colonic mucosa. Instead, we show that it acts as a potent selective pressure, favoring the expansion of tumor cell subpopulations more prone to resist therapy and increasing ITGH in the residual tumor. Conclusion: Our results reveal the highly heterogeneous and dynamic clonal architecture of rectal tumors undergoing nCRT. Our results also uncover putative genetic determinants of response to nCRT and a possible role for ITGH in predicting treatment outcome.

  Study EGAS00001003250

• Biased allelic expression in human primary fibroblast single cells.

  The study of gene expression in mammalian single cells using genomic technologies now provides the possibility to investigate the patterns of allelic gene expression. We have used single-cell RNA sequencing to detect the allele-specific mRNA level in 203 single human primary fibroblast cells over 133,633 unique heterozygous single nucleotide variants (hetSNVs). We have observed that at the snapshot of analyses each cell contains mostly transcripts from one allele from the majority of genes; indeed 76.4% of the hetSNVs display stochastic monoallelic expression in single cells. Remarkably, adjacent hetSNVs exhibit haplotype consistent allelic ratio; in contrast distant sites located in two different genes are independent of the haplotype structure. Moreover, the allele-specific expression in single cells correlated with the abundance of the cellular transcript. We observed that genes expressing both alleles in majority of the single cells at a given time point are rare and enriched in highly expressed genes. The relative abundance of each allele in a cell is controlled by some regulatory mechanisms since we observed related single-cell allelic profiles according to genes. Overall, these results have direct implications in cellular phenotypic variability.

  Study EGAS00001001009

• MOSAIC Window Mesothelioma Data

  This dataset will include Spatial Transcriptomics from the 10x Genomics Visium SD technology, Single-Cell RNA-Seq from the 10x Genomics Chromium Flex protocol, Bulk RNA-Seq (sequenced on Illumina), WES (sequenced on Illumina), H&E, and Clinical data from 10 Mesothelioma patients. For Visium and Chromium data we are sharing the outputs of respectively Space Ranger and Cell Ranger. For Bulk RNA-Seq we are including processed files such as counts.tsv, FPKM.tsv, fusion_genes.tsv, TPM count matrix.tsv, DESeq2 count matrix.tsv, multiqc_report. For WES, we are sharing the presence or absence of single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variants (CNVs).* Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001706

• MOSAIC Window Ovarian Data

  This dataset will include Spatial Transcriptomics from the 10x Genomics Visium SD technology, Single-Cell RNA-Seq from the 10x Genomics Chromium Flex protocol, Bulk RNA-Seq (sequenced on Illumina), WES (sequenced on Illumina), H&E, and Clinical data from 15 Ovarian patients. For Visium and Chromium data we are sharing the outputs of respectively Space Ranger and Cell Ranger. For Bulk RNA-Seq we are including processed files such as counts.tsv, FPKM.tsv, fusion_genes.tsv, TPM count matrix.tsv, DESeq2 count matrix.tsv, multiqc_report. For WES, we are sharing the presence or absence of single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variants (CNVs).* Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001704

• MOSAIC Window DLBCL Data

  This dataset will include Spatial Transcriptomics from the 10x Genomics Visium SD technology, Single-Cell RNA-Seq from the 10x Genomics Chromium Flex protocol, Bulk RNA-Seq (sequenced on Illumina), WES (sequenced on Illumina), H&E, and Clinical data from 10 DLBCL patients. For Visium and Chromium data we are sharing the outputs of respectively Space Ranger and Cell Ranger. For Bulk RNA-Seq we are including processed files such as counts.tsv, FPKM.tsv, fusion_genes.tsv, TPM count matrix.tsv, DESeq2 count matrix.tsv, multiqc_report. For WES, we are sharing the presence or absence of single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variants (CNVs).* Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001702

• GoDARTS T2D-GENES Exome Sequencing Study is a subset of the ~52,000 Type 2 diabetes exome sequencing project.

  The GoDARTS T2D-GENES Exome sequencing study is a subset of a larger Type 2 Diabetes Exome Sequencing project. This effort is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date and includes samples from: T2D-GENES, GoT2D, ESP, SIGMA T2D, LuCAMP, and ProDIGY. This data generated from the Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for T2D through multiethnic sequencing studies. Sequencing for the GoDARTS study was performed at the Broad Institute using Illumina Rapid Capture on Illumina HiSeq machines.

  Study EGAS00001002937

• pancreatic ductal adenocarcinoma exomes in study: Pro-immunogenic Impact of MEK inhibition combined with an anti-CD40 immunostimulatory antibody

  Cancer types with lower mutational load and a non-permissive tumor microenvironment are intrinsically resistant to immune checkpoint blockade. While the combination of cytostatic drugs and immunostimulatory antibodies constitutes an attractive concept for overcoming this refractoriness, suppression of immune cell function by cytostatic drugs may limit therapeutic efficacy. Here we show that targeted inhibition of mitogen-activated protein kinase (MAPK) kinase (MEK) does not impair dendritic cell-mediated T-cell priming and activation. Accordingly, combining MEK inhibitors (MEKi) with agonist antibodies (Abs) targeting the immunostimulatory CD40 receptor resulted in potent synergistic anti-tumor efficacy. Detailed analysis of the mechanism of action of MEKi GDC-0623 by means of flow cytometric analysis of the tumor immune infiltrate and whole tumor transcriptomics showed that, in addition to its cytostatic impact on tumor cells, this drug exerts multiple pro-immunogenic effects, including the suppression of M2-type macrophages, myeloid derived suppressor cells and CD4+ T-regulatory cells. In addition, MEKi was found to induce tumor-cell intrinsic interferon signaling, which contributed to antigen presentation by tumor cells. Finally, the tumoridical impact of MEKi involves the activation of multiple pro-inflammatory pathways involved in immune cell effector function in the tumor microenvironment. Our data therefore indicate that the combination of MEK inhibition with agonist anti-CD40 Ab is a promising therapeutic concept, especially for the treatment of mutant Kras-driven tumors such as pancreatic ductal adenocarcinoma. The pancreatic ductal adenocarcinoma exomes were generated in the context of the Heidelberg Center for Personalized Oncology project HIPO-K28E.

  Study EGAS00001004196

• eccDNA in maternal plasma

  We developed a new bioinformatics method for detecting the eccDNA in plasma. We revealed that the biological properties between eccDNA and linear DNA are different. eccDNA could be potentially provided as a new class of circulating biomarker.

  Study EGAS00001003827

• Download Metadata

  Metadata Distribution Welcome to the realm of Metadata Distribution within the EGA ecosystem! Our Metadata REST API empowers you to effortlessly retrieve metadata from the expansive landscape of EGA. By utilising this API, you gain access to publicly available insights across various EGA domains, including studies, samples, experiments, runs, analyses, policies, DACs, and datasets. Furthermore, this API facilitates cross-referencing of objects, enabling you to gather, for example, all the datasets associated with a specific DAC, seamlessly. In addition, we have added the ability to query private data using the metadata API. If you possess the necessary permissions, you can access behind-the-login private data for a specified list of datasets. Metadata Distribution Index Identifiers Dataset Mappings Website Download Metadata API - Private Identifiers At the core of EGA's organisational structure are unique accessions that serve as essential tags for our diverse objects. Here's a quick overview of the accessions and their corresponding object types: EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID For further information check our metadata schema documentation. Dataset Mappings For authorised datasets, comprehensive mappings reveal meaningful connections: Sample_file: This file presents information about the linkage between samples and files available in the dataset. Study_experiment_run_sample: This file presents information about the linkage between studies, experiments, runs, and samples within the dataset. Study_analysis_sample: This file presents information about the linkage between studies, analyses, and samples contained within the dataset. Run_sample: This file presents information about the linkage between runs and samples within the dataset. Analysis_sample: This file presents information about the linkage between analyses and samples within the dataset. An empty file indicates the absence of corresponding information. Website Download Our website serves as your gateway to downloading metadata. Simply navigate to the dataset page, and you'll find a blue Metadata button. Once authenticated, you can click this button for authorised datasets. If you lack permissions for a particular dataset, request access by clicking the 'Request Access' button. For authorised datasets, choose your preferred metadata format: CSV, TSV, or JSON. Metadata API - Private Leverage the power of programmatic metadata downloads! Start by authenticating yourself with your credentials to obtain an access token. With this token, programmatically query private information. Queries mirror the structure of the Public Metadata API. However, behind the login, you can delve into specific mapping information (as mentioned above in dataset mappings) alongside object-level exploration. Authentication An active session is required to work with the API. Each time you log in with your credentials a new session is started, which is identified by an access_token. Below an example on how to obtain one using curl: curl https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token \ -d 'client_id=metadata-api' \ -d 'username=...' \ --data-urlencode 'password=...' \ -d 'grant_type=password' All responses from the API are in JSON format. A successful response should include a new token to be used for the session: {"access_token":"eyJhbGciOiJSUzI1NiIsInR5cCIgOiA...TNw", "expires_in":300, "refresh_expires_in":1800, "refresh_token":"eyJhbGciOiJIUzI1NiIsInR5cCIgOiA...pTX10", "token_type":"Bearer", ... } Save the access_token value and include it in the API call headers. Example query usage Below you can find some example of queries available behing authentication and authorisation. Querying study-experiment-run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_experiment_run_sample \ -H 'Authorization: Bearer access_token' Querying run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/run_sample \ -H 'Authorization: Bearer access_token' Querying study-analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_analysis_sample \ -H 'Authorization: Bearer access_token' Querying analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/analysis_sample \ -H 'Authorization: Bearer access_token' Querying sample-file mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/sample_file \ -H 'Authorization: Bearer access_token' You can get a different output format by adding one of these options to the curl command: -H 'Accept: text/tsv' -H 'Accept: application/json' -H 'Accept: text/csv' For more detailed information, refer to the Metadata API Specification.

  Documentation access/download/metadata

• Link to the Finnish FEGA Node's service provider

  We would like to direct you to the service provider for the Finnish FEGA Node, which is CSC – IT Center for Science (https://research.csc.fi/-/fega). It's important to note that this is not a genuine DAC and does not serve as the data controller. To obtain access to data stored in FI-FEGA, it is essential to utilize the local access management system SD Apply. Please be aware that applications submitted through the EGA DAC portal will not be processed. For a seamless experience, we kindly request you to refer to the policy of your selected dataset and submit your access application through SD Apply (https://sd-apply.csc.fi/). Your cooperation is highly appreciated.

  Dac EGAC50000000022

• Highlights from 2025: Our top 10 requested studies

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

  Blog top-10-studies-2025

• Generation of a Cellular Atlas of Human Adipose Tissue

  White adipose tissue (WAT), once regarded as morphologically and functionally bland, is now recognized to be dynamic, plastic, heterogenous, and involved in a wide array of biological processes including energy homeostasis, glucose and lipid handling, blood pressure control, and host defense.  High fat feeding and other metabolic stressors cause dramatic changes in adipose morphology, physiology, and cellular composition, and alterations in adiposity are associated with insulin resistance, dyslipidemia, and Type 2 diabetes (T2D). Here we provide detailed cellular atlases of human and murine subcutaneous and visceral white fat at single-cell resolution across a range of body weight. We identify subpopulations of adipocytes, adipose stem and progenitor cells (ASPCs), vascular, and immune cells and demonstrate commonalities and differences across species and dietary conditions. We link specific cell types to increased risk of metabolic disease, and we provide an initial blueprint for a comprehensive set of interactions between individual cell types in the adipose niche in leanness and obesity. We also utilize bulk RNA sequencing data of enzymatically digested human adipocytes to scale these findings to a larger cohort. These data comprise an extensive resource for the exploration of genes, traits, and cell types in the function of WAT across species, depots, and nutritional conditions. 

  Study phs002766

• TRACERx 100: metastatic samples

  Whole exome sequencing of 10 metastatic biopsies from four TRACERx100 patients (see EGA dataset EGAS00001002247), collected either after relapse or death. The data from these samples are initially published with Abbosh, C. et al. Phylogenetic ctDNA analysis depicts early stage lung cancer evolution. Nature http://dx.doi.org/10.1038/nature22364 (2017). Abstract: Earlier detection of relapse following primary surgery for non-small cell lung cancer and the characterization of emerging subclones seeding metastatic sites might offer new therapeutic approaches to limit tumor recurrence. The potential to non-invasively track tumor evolutionary dynamics in ctDNA of early-stage lung cancer is not established. Here we conduct a patient-specific approach to ctDNA profiling in the first 100 lung TRACERx (TRAcking Cancer Evolution through therapy (Rx)) study participants, including one patient co-recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release in early-stage non-small cell lung cancer and perform tumor volume limit of detection analyses. Through blinded profiling of post-operative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients destined to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastases, providing a new approach for ctDNA driven therapeutic studies.

  Study EGAS00001002415

• RNAseq of 76 samples from Uveal Melanoma tumors

  Hotspot mutations in the spliceosome gene SF3B1 are reported in 20% of uveal melanomas. SF3B1 is involved in 3'-splice site (3'ss) recognition during RNA splicing; however, the molecular mechanisms of its mutation have remained unclear. Here we show, using RNA-Seq analyses of uveal melanoma, that the SF3B1 R625/K666 mutation results in deregulated splicing at a subset of junctions, mostly by the use of alternative 3'ss.

  Dataset EGAD00001004398

• 54 metastatic colorectal cancer patients from Schleswig-Holstein in North Germany

  Personalized treatment vs standard of care is much debated, especially in clinical practice. Here we investigated whether overall survival differences in metastatic colorectal cancer patients are explained by their tumor mutation profiles or by their treatment differences in real clinical practice.

  Study EGAS00001004108

• RNA sequencing of multiple myeloma identifies genes dysregulated by structural variants.

  Multiple myeloma is a disease of structural changes brought about by copy number abnormalities and translocations. Many of these changes result in super-enhancers being placed next to key oncogenes. Here, we have investigated which genes are commonly dysregulated by these changes.

  Study EGAS00001003411

• WES on tumor DNA and germline DNA in pediatric cancer

  This dataset contains whole exome sequencing (WES) data from tumor DNA samples of various pediatric cancer entities. Files are provided in fastq format. Samples were sequenced on a Novaseq6000 or Hiseq2500 (Illumina). Data analysis is available at https://github.com/rmvpaeme/sWGS_pediatric_cancer.

  Study EGAS00001005429

• Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET)

  STARNET is a genetics of RNA expression study of multiple disease-relevant tissues obtained from living patients with cardiovascular disease. Tissue samples are obtained from blood, atherosclerotic-lesion-free internal mammary artery (MAM) and atherosclerotic aortic root (AOR), subcutaneous fat (SF), visceral abdominal fat (VAF), skeletal muscle (SKLM), and liver (LIV) during open thorax surgery of 600 coronary artery disease (CAD) patients. All patients gave written informed consent. The inclusion criterion was eligibility for coronary artery by-pass graft (CABG) surgery. Patients with other severe systemic diseases, such as active systemic inflammatory disease or cancer, were excluded. The primary clinical end points were the SYNTAX score based on the extent of coronary atherosclerosis assessed from preoperative angiograms. The STARNET patients are Caucasians (31% females); 32% had diabetes, 75% had hypertension, and 67% had hyperlipidemia; and 33% had an MI before age 60. By New York Heart Association criteria, 45% were class I, 42% class II, 9% class III, and 1% class IV. TYPES AND RNA SEQUENCING: 566 DNA genotype and 3577 RNA-seq profiles from seven tissues from 600 STARNET CABG patients passed quality control (on average 511 RNA-seq profiles/tissue). DNA was genotyped with the OmniExpress Exome array (Illumina, ~900k SNPs) and imputed to a total of 14,098,063 DNA variant calls (6,245,505 with minor allele frequency >5%). The STARNET subjects mainly overlap with Caucasian of Northern European (Finnish) descent. RNA sequencing was performed using the HighSeq2000 platform, poly-A (LIV, SKLM, VAF, SF and blood) and ribo-zero (AOR, MAM) protocols with 50-100 bp read lengths, single end to 15-30 million read depth.

  Study phs001203

• Molecular Genetic Studies of Developmental Brain Disorders

  Study 1 2R01-NS050375 (PI: DOBYNS, William B.) The genetic basis of mid-hindbrain malformations Our general goal for this project is to advance our understanding of human developmental disorders that involve the brainstem and cerebellum - brain structures derived from the embryonic midbrain and hindbrain - that affect a minimum of 2.4 per 1000 resident births based on data from the CDC. Importantly, this large class of disorders co-occurs with more common developmental disorders such as autism, mental retardation and some forms of infantile epilepsy, and shares some of the same causes. With this renewal, we propose to expand the scope of our work beyond single phenotypes and genes to focus on delineating the critical phenotype spectra to which the most common MHM belong, and defining the underlying biological networks that are disrupted. To pursue these goals, we will use our large and growing cohort of human subjects to map additional MHM loci using SNP microarrays that provide both high-resolution autozygosity and linkage data in informative families as well as detect critical copy number variants in sporadic subjects. The causative genes will be identified using traditional Sanger or new high-throughput sequencing methods as appropriate abased on size of the critical region. We will use these and other known MHM causative genes to construct and revise model biological networks of genes and proteins, and test these genes and networks in additional patients as a candidate gene or more accurately a candidate network approach. These approaches need to be supported by ongoing active subject recruitment, as studies of comparable disorders such as mental retardation and autism have benefited from even larger numbers of subjects that we have so far collected. We need to use new high-throughput sequencing methods to more efficiently test larger critical regions, and to test entire gene networks rather than individual genes in matched cohorts of subjects. At every step; phenotype analysis, CNV analysis, model network construction and high-throughput sequencing, we will need expanded bioinformatics capabilities. Finally, we need to test the biological function of new genes and networks to support our gene identification studies. We expect that these studies will contribute immediately to more accurate diagnosis and counseling, and over time will lead to development of specific treatments for a subset of these disorders. We further expect that studies of mid-hindbrain development will have broad significance for human developmental disorders generally, providing compelling evidence for a connection between cerebellar development and other classes of developmental disorders such as autism, mental retardation and epilepsy. Study 2 R01-NS058721 (PI: DOBYNS, William B.) De novo copy number variation and gene discovery in human brain malformations Project Summary/Abstract The number of recognized brain malformations and syndromes has grown rapidly during the past several decades, yet relatively few causative genes have been identified, especially for three common malformations that have been associated with numerous cytogenetically visible chromosome deletions and duplications, and that often occur together: agenesis of the corpus callosum (ACC), cerebellar vermis hypoplasia (CVH) including Dandy-Walker malformation (DWM), and polymicrogyria (PMG). We propose to perform high-resolution array comparative genome hybridization (aCGH), emerging technology able to detect small copy number variants (CNV), in 700 probands with one or more of these three malformations. Our central hypothesis states that more than 10% of patients with ACC, CVH or PMG will have de novo CNV below the resolution of routine cytogenetic analysis, but detectable by current array platforms. We therefore expect to identify 70-100 patients with small CNV. We will distinguish CNV found in normal individuals from potentially disease-associated changes, and will confirm CNV using fluorescence in situ hybridization (FISH) and microsatellite (STRP) analysis. We will give highest priority to CNV that are de novo and involve 2 or more BACs, and secondary priority to familial and smaller CNV excluding known polymorphisms. After that, we will evaluate and rank candidate genes in the critical regions using information from public databases and our own expression studies, and perform mutation analysis of the best candidate genes from well-defined critical regions by sequencing in a large panel of subjects with phenotypes that match the phenotypes of the patients whose CNV define the critical regions. Here, we will use more refined criteria to supplement our clinical classification, such as the developmental level and presence of epilepsy or other birth defects. Any abnormalities found will be analyzed using existing data regarding polymorphisms (i.e. dbSNP), cross-species comparisons, and functional assays appropriate for the specific sequence change. Study 2A In 1995, we described a novel multiple congenital anomaly syndrome associated with facial dysmorphism (congenital ptosis, high arched eyebrows, shallow orbits, trigonocephaly), colobomas of the eyes, neuronal migration malformation (frontal predominant lissencephaly) and variable hearing loss. We hypothesized from de novo mutations and used trio-based exome sequencing to identify de novo mutations in the ACTB and ACTG1 genes. Study 2B In 1997 and 2004, we and others defined two novel developmental syndromes associated with markedly enlarged brain size, or megalencephaly, and other highly recognizable features. The megalencephaly-capillary malformation syndrome (MCAP) consists of megalencephaly and associated growth dysregulation with variable asymmetry, developmental vascular anomalies, distal limb malformations, variable cortical malformation, and a mild connective tissue dysplasia. The megalencephaly-polymicrogyria-polydactyly-hydrocephalus syndrome (MPPH) resembles MCAP but lacks vascular malformations and syndactyly. We hypothesized that MCAP and MPPH result from mutations - including postzygotic events - in the same pathway, and studied them together. Using a combination of exome sequencing, Sanger sequencing, restriction-enzyme assays, and targeted ultra-deep sequencing in 50 families with MCAP or MPPH, we identified de novo germline or postzygotic mutations in three core components of the phosphatidylinositol-3-kinase/AKT pathway. These include two mutations in AKT3, a recurrent mutation in PIK3R2, and multiple mostly postzygotic mutations in PIK3CA (Rivière JB, Mirzaa GM, O'Roak BJ, Beddaoui M, Alcantara D, Conway RL, St-Onge J, Schwartzentruber JA, Gripp KW, Nikkel SM, Worthylake T, Sullivan CT, Ward TR, Butler HE, Kramer NA, Albrecht B, Armour CM, Armstrong L, Caluseriu O, Cytrynbaum C, Drolet BA, Innes AM, Lauzon JL, Lin AE, Mancini GMS, Meschino WS, Reggin JD, Saggar AK, Lerman-Sagie T, Uyanik G, Weksberg R, Zirn B, Beaulieu CL, FORGE Canada Consortium, Majewski J, Bulman DE, O'Driscoll M, Shendure J, Graham Jr. JM, Boycott KM, Dobyns WB. De novo germline and postzygotic mutations in AKT3, PIK3R2 and PIK3CA cause a spectrum of related megalencephaly syndromes. Nat. Genet. In press). Study 3 2R01-NS046616 (PI: GOLDEN, Jeffrey A) The role of ARX in normal and abnormal brain development This subcontract from the Children's Hospital of Philadelphia to the University of Chicago (UC) is intended to support research studies of the ARX and functionally related genes in human subjects with any one of several specific developmental disorders. The Co-investigator at UC (W.B. Dobyns) will identify a series of patients with mental retardation and severe infantile epilepsy, some of whom will have specific brain malformations and others who will have normal brain structure by brain imaging studies, and collect research samples from these subjects with informed consent. The studies to be performed will include mutation analysis of ARX, mutation analysis of specific downstream target genes, X inactivation studies in humans and X inactivation studies in mutant mice. The results will be analyzed to determine the significance of any changes found in the gene.

  Study phs000455

• Integration of Clinical and Molecular Biomarkers for Melanoma Survival (Berwick)

  The long-term goal of the InterMEL Program Project: Integration of Clinical and Molecular Biomarkers for Melanoma Survival is to identify molecular and clinical factors that predict survival of melanoma patients. Our overarching hypothesis is that we can identify factors in the primary melanoma tumor that will lead to more aggressive disease. Melanoma patients diagnosed at American Joint Committee on Cancer (AJCC) tumor, lymph nodes, and metastases (TNM) stages IIA/IIB/IIC/IIIA/IIIB/IIIC/IIID display highly variable clinical outcomes and responses to therapy. We wish to identify robust and reproducible biomarkers or sets of classifiers that distinguish patients likely to have poor prognosis. These biomarkers will help establish targets for adjuvant therapies for this set of patients before the tumors metastasize. Aim 1. Classify actionable somatic mutations, and copy number variations (CNVs) in relationship to melanoma survival. In Project 1, Targeted Sequencing and Clinicopathology to Evaluate Primary Melanoma Molecular Subtypes and Outcomes, we will profile 468 genes using the MSKIMPACT ™ assay and identify somatic mutations and CNVs associated with melanoma-specific survival, as well as their co-occurrence with other mutations, in 1,000 tumors from patients at AJCC TNM stages IIA-IIID: approximately 500 from patients who died with melanoma within five years and approximately 500 from individuals who have lived at least five years. We will also evaluate the joint effects of somatic mutations, CNVs and pathologic characteristics associated with good and poor outcomes. Aim 2. Identify primary melanoma DNA methylation profiles to evaluate subtypes and survival. Although it has been established that melanomas frequently have aberrant DNA methylation, it is unknown if DNA methylation in primary melanomas predicts outcome. In Project 2, Primary Melanoma DNA Methylation Profiling for Evaluating Subtypes and Survival, we will profile the same primary melanomas as in Project 1 with Illumina Infinium 850K methylation arrays. We expect to: identify and characterize DNA methylation-based melanoma subclasses; train, test and validate a CpG signature prognostic for survival from melanoma; determine whether this profile adds information to outcome prediction beyond AJCC TNM staging. This project is based on the hypothesis that DNA methylation in primary melanoma will define subgroups (including a poor-prognosis CIMP – ‘CpG island methylator phenotype' subtype) and that a CpG signature will be prognostic for melanoma survival. Aim 3. Define microRNA expression changes in relation to melanoma survival. MicroRNAs have been associated with poor prognosis in melanoma, as well as in other cancers. In Project 3, Prognostic and Functional Role of a Gene Expression Signature in Melanoma Patients, we hypothesize that altered miRNA expression, captured at the time of diagnosis, may contribute to the aggressive behavior of a subset of early stage primary melanomas. We will profile the same primary melanomas as in Projects 1 and 2 with a Nanostring assay. This project will define and validate a tissue-based microRNA signature in conducted to determine whether the prognostic miRNA signature, as well as other candidate genes emerging from other projects, contribute to melanoma survival. Aim 4. Integrate data from multiple platforms to identify melanoma subtypes and survival. Despite substantial literature on gene tumor mutation-, methylation- and gene expression-based prognostic and predictive signatures for melanoma, few such signatures are used in clinical practice. Project 4, Multiplatform Analysis of Melanoma Molecular Subtypes and Patient Survival Outcome, will use novel integrative clustering methods to identify molecular subtypes of melanoma jointly defined across these platforms.

  Study phs003099

• NHLBI TOPMed - NHGRI CCDG: Pakistan Risk of Myocardial Infarction Study (PROMIS)

  The Pakistan Risk of Myocardial Infarction (PROMIS) study is a retrospective multicenter case-control cohort study of individuals with and without coronary heart disease from Pakistan. Multiple biological samples have been collected from the participants including DNA, plasma, serum, and whole blood. The goal of the study is to recruit 20,000 cases and 20,000 controls of Pakistani descent. Eligible cases were individuals aged 30-80 who presented to the emergency department of a participating recruitment center in Pakistan with clinical symptoms consistent with a myocardial infarction (MI), ECG changes consistent with MI, elevated troponin levels consistent with MI, and no prior history of cardiovascular disease. Controls were individuals of Pakistani descent who did not have a self-reported history of cardiovascular disease. This site hosts data generated via NHLBI's TOPMed program and NHGRI's Common Disease Genomics (CCDG) program. Both whole exome and whole genome data are presented here, namely 4,211 whole genomes from TOPMed, 3,859 whole genomes from NHLBI supplemental funds, 1,136 whole genomes and 16,855 whole exomes from CCDG. Please note that there is additional legacy whole exome data (7,298 subjects) also generated via NHGRI funds as part of the MIGen Exome Sequencing project that can be found in dbGaP at phs000917.

  Study phs001569

• Natural History and Structural Functional Relationships in Fabry Renal Disease

  Fabry disease is a rare genetic disease with deficient activity of an enzyme, which leads to accumulation of inclusions in different organs including kidney, heart and vessels. The purpose of the study is to conduct a cross-sectional investigation of the natural history of Fabry renal disease and measure renal function and renal structure in male and female Fabry's patients. The study will utilize the resultant cross-sectional information to determine the renal structural parameters or composite of parameters that most closely relates to the onset and progression of clinical renal disease in Fabry patients. This is an observational, cross-sectional study of 60 individuals with Fabry disease. Those participating in the study will be evaluated during a one day visit and on a PRN basis. The primary study objectives are as follows: To study the natural history of Fabry renal disease and measure renal function and renal structure in male and female Fabry's patients. These patients would encompass the broad age range from childhood to adulthood and from normal renal function to moderate renal insufficiency [serum creatinine (SCr) ≤ 2.5mg/dl (chronic kidney disease or CKD3)]. To utilize the resultant cross-sectional information to determine the renal structural parameters or composite of parameters that most closely relates to the onset and progression of clinical renal disease in Fabry patients.

  Study phs001333

• Clinical Sequencing Exploratory Research Consortium: Incorporation of Genomic Sequencing into Pediatric Cancer Care

  This project includes data derived from subjects enrolled in the BASIC3 (Baylor College of Medicine Advancing Sequencing in Childhood Cancer Care) study. BASIC3 is a National Genome Human Research Institute (NHGRI) and National Cancer Institute-funded Clinical Sequencing Exploratory Research (CSER) consortium project that focused on prospective implementation of clinical whole exome sequencing in the pediatric oncology clinic. The primary study objective were to integrate information from CLIA-certified germline and tumor exome sequencing into the care of newly diagnosed solid tumor patients at Texas Children's Cancer Center, and to perform parallel evaluation of the impact of tumor and germline exomes on families and physicians. Blood and frozen tumor (if available) samples were collected from children undergoing surgery or biopsy of newly diagnosed solid tumors and subjected to exome sequencing in a CLIA-certified laboratory. Germline and tumor (if applicable) exome sequencing reports were generated and submitted into the electronic health record and returned to each patient/family by their primary oncologist. In addition to the clinical exome sequencing, specific (optional) consent was requested for research sequencing studies. If this consent was obtained then research studies of some of the children and parents participating in the BASIC3 study (including tumor transcriptome and whole genome sequencing of blood and/or tumor) are performed. The Clinical Sequencing Exploratory Research Consortium Cohort is utilized in the following dbGaP sub-study. To view molecular data, and derived variables collected in this sub-study, please click on the following sub-studies below or in the "Sub-study" section of this top-level study page phs001383 Clinical Sequencing Exploratory Research Consortium Cohort. phs001026 BASIC3 phs001878 GMKF BASIC3

  Study phs001683

• Transcriptomic classes of BCR-ABL1 lymphoblastic leukemia

  In BCR-ABL1 lymphoblastic leukemia, treatment heterogeneity to tyrosine kinase inhibitors (TKIs), especially in the absence of kinase domain mutations in BCR-ABL1, is poorly understood. Through deep molecular profiling, we uncovered three transcriptomic subtypes of BCR-ABL1 lymphoblastic leukemia, each representing a maturation arrest at a stage of B-cell progenitor differentiation. An earlier arrest was associated with lineage promiscuity, treatment refractoriness, and poor patient outcomes. A later arrest was associated with lineage fidelity, deep and durable leukemia remissions, and improved patient outcomes. Each maturation arrest was marked by specific genomic events that control different transition points in B-cell development. Interestingly, these events were absent in BCR-ABL1+ pre-leukemic stem cells isolated from patients regardless of subtype, which supports that transcriptomic phenotypes are determined downstream of the leukemia-initialing event. Overall, our data indicate that treatment response and TKI-efficacy is an unexpected outcome of the differentiation stage at which this leukemia transforms.

  Study EGAS00001007167

• Optimizing Primary Stroke Prevention in Children with Sickle Cell Anemia (STOP II)

  The STOP II trial evaluated whether prophylactic transfusion in patients with sickle cell disease and high risk of stroke can be safely halted after 30 months of treatment during which patients became low risk for stroke.Stroke causes substantial morbidity in children with sickle cell disease. To prevent first strokes, the Stroke Prevention Trial in Sickle Cell Anemia (STOP) used prophylactic transfusions in children who were identified by transcranial Doppler (TCD) ultrasonography as being at high risk for stroke. This strategy reduced the incidence of stroke among such children from 10% per year to less than 1% per year, leading to recommendations for TCD screening and prophylactic transfusion for children with abnormal velocities on ultrasonography. Despite the reduced risk of stroke, long-term use of transfusions can cause adverse side effects, such as iron overload or alloimmunization. However, cessation of transfusions is associated with recurrence of stroke, and at the time of the STOP II trial, there were no clinical or laboratory indicators to guide the duration of prophylaxis. Therefore the STOP II trial was initiated to determine whether transfusions could be limited by monitoring patients with TCD examinations after transfusions were halted and resuming transfusions if the examination indicated a high risk of stroke.The trial was halted for safety concerns after 79 of a planned 100 children were randomized. Discontinuation of transfusion for the prevention of stroke in children with sickle cell disease resulted in a high rate of reversion to abnormal blood-flow velocities on Doppler studies and stroke incidence.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.

  Study phs002386