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FEGA FAQs: a summary of the Q+A session from the FEGA workshop at ELIXIR AHM 2024

The ELIXIR All Hands Meeting (AHM) was held in Uppsala, Sweden this June. We at EGA always look forward to this meeting as a chance to see many of our partners and colleagues face-to-face. The Federated EGA (FEGA) is one initiative that always benefits from the AHM, and this year FEGA was in the spotlight, with several questions related to the advances we've made recently. We held this year's FEGA workshop a little differently, with most time for discussions on various “hot topics”. Organised in different breakouts, over 2 rounds, participants could choose which session they wanted to attend. One breakout was a general Q+A about FEGA and the path to join. We had a diverse range of participants, including experts from Central EGA (CEGA) and FEGA inaugural nodes, people from up and coming nodes at various stages of readiness, as well as participants not directly a part of FEGA but curious to learn more. It made for a great discussion! In this blog post, we highlight some of the questions for those who didn’t have a chance to be there. What is the FEGA Collaboration Agreement? It is a legal agreement between the node and Central EGA (CEGA) where both parties agree to certain responsibilities, like what services will be provided, sharing of public metadata with CEGA, interoperable technologies and more. The agreement is for 4 years, with the expectation of long-term sustainability. If a node is made up of multiple institutes, one institute must be the signatory. This could require a legal agreement within the node. CEGA is composed of CRG and EMBL-EBI (EGA itself has its own legal agreement between these institutes) Check the FEGA Collaboration Agreement What about purely medical data? Is this accepted in FEGA? CEGA only accepts data approved for secondary research use. We do accept medical data collected in this context, as do some nodes. Nodes are able to accept any data they like, as long as it is sensitive, thus in need of controlled access. What about other data types other than genomics? Like proteomics or images? They can be accepted, although CEGA is currently not designed with those formats in mind, so they might not fit with precision in the data model. The FEGA nodes are welcome to accept any data they want. Proteomic studies generating sensitive data are increasing, and specific work will likely be developed in the near future to adress this need. Does CEGA require a certain amount or type of data to be shared by the node? No, we do not and it's up to each node to decide what specific data types they accept and in what format. Nonetheless, a FEGA node has the duty to be open to data submission from any institution of their country, and can't be limited by design to a single or limited data source. Does CEGA and FEGA require a certain amount or type of details and description on the data to be submitted to the node? Data description (technical and biological), usually called metadata in this field, is crucial for the findability of the submitted data. Thus, we highly recommend including as much information as available to maximise the discoverability of the data. Specifical minimal metadata is defined in the submission schema, and thresholds are specified by the nodes. We are currently working towards a unified FEGA metadata model. What are the geographical borders of FEGA? FEGA should make the E for Everyone, because any institute worldwide could join and we indeed do have countries and use-cases worldwide. Some of them are very close to officially joining the federation. What are the main differences between FEGA and GDI? The two networks have a lot in common and also some critical differences. You can read all about this in one of our latest blog post. If you have more questions, please consider having a look at the FEGA onboarding webpage and, of course, don't miss our workshop at the ELIXIR AHM next year!

Blog fega-faqs-elixir-ahm-2024

Comprehensive analyses of clinicopathological features and genomic mutations of combined hepatocellular-cholangiocarcinoma

Combined hepatocellular and cholangiocarcinoma (cHCC-CCA) is a rare primary liver cancer. We performed whole exome sequencing to clarify the relationship between genetic mutations and clinicopathological features in cHCC-CCA.

Study JGAS000599

Early-onset Colorectal Cancer Study TOGETHER Data Access Committee

The Early-onset Colorectal Cancer Study TOGETHER Data Access Committee (DAC) is responsible for reviewing requests to access sequencing and clinical data from the study. Access to the data is restricted to researchers with approved ethical clearance and scientifically valid research projects. Each request will be evaluated by the DAC to ensure compliance with participants’ informed consent and all applicable data protection regulations.

Dac EGAC50000000752

Data Access Committee for Genomics of bone marrow failure (BMF) and myelodysplastic syndromes (MDS)

The Data Access Committee for the genomics of bone marrow failure and myelodysplastic syndrome project is responsible for reviewing applications for access to controlled human genomic and phenotypic datasets generated as part of this project. The DAC ensures that data sharing with qualified researchers is conducted in accordance with participant consent, institutional ethical approvals, and all applicable data protection regulations.

Dac EGAC50000000754

PDAC Phenotype and Germline Genotype Data Access Committee

This Data Access Committee (DAC) is responsible for reviewing and approving requests for access to controlled phenotype metadata and derived germline FUT2/FUT3 genotype data from patients with pancreatic ductal adenocarcinoma (PDAC). Access is granted to bona fide researchers for non-commercial research purposes only, subject to approval by the DAC and in accordance with the original informed consent and applicable ethical regulations.

Dac EGAC50000000893

DAC for Cornell-NCI DLBCL NGS Genomic Project

Genome-wide sequencing experiments were conducted on 103 DLBCL biopsy samples, of which the datasets (called Cornell-NCI DLBCL cohort) are available for authorized scientists. The Center of Technology Licensing at Cornell University is in charge of this data access policy and approval. Particularly, Cornell University will email a DAA to each requestor to have their institution sign before access is granted

Dac EGAC50000000704

Rare_renal_tumours_RNA_

Rare renal tumours are by hard to classify and there is very little available information regarding prognosis and sensitivity to treatment. Here we endevour to understand their genomic properties in order to better understand their biology.

Study EGAS00001004323

Rare_renal_tumours_WGS_

Rare renal tumours are by hard to classify and there is very little available information regarding prognosis and sensitivity to treatment. Here we endevour to understand their genomic properties in order to better understand their biology.

Study EGAS00001004322

Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy"

Dataset of the study "Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy". This dataset contains the cellranger's gene-expression matrices for the 5 prime single-cell RNA sequencing experiments

Dataset EGAD50000000748

WES of probands in KLB project

These are the vcf files of exome sequencing of the two probands who were found to harbor mutations in KLB. Sample: EGAN00001564799 is the proband 1; Sample: EGAN00001564800 is the proband 11 in the KLB paper. Exome capture was performed using the SureSelect All Exon capture (Agilent Technologies, Santa Clara, CA USA) and sequenced on the HiSeq2500 (Illumina, San Diego CA USA).

Dataset EGAD00001003463

FFPE CRC sequence data and somatic variants

We included 3 BAM files of the genome sequencing data: 2 of 3 are from tumour samples, namely 1 repaired-FFPE and 1 unrepaired FFPE; the third BAM file is from normal tissue of FFPE block. There is also a VCF file containing all somatic mutations in the dataset.

Dataset EGAD00001007723

Global Microbiome Conservancy Sequence Data

The human body is a complex ecosystem, hosting tens of billions of bacteria, primarily in the gut. This community, known as the 'gut microbiome', is vital to human health, affecting functions ranging from metabolism, immunity, and development, to behavior. Conversely, reduced microbiome diversity and other imbalances of the gut community (dysbiosis) are associated with many diseases of the industrialized world, such as metabolic syndrome, asthma, and inflammatory bowel diseases among others. Microbiome-based interventions thus hold the potential to revolutionize our understanding of, and therapeutic approaches to, many aspects of human health and disease. Despite many advances, current understanding of the human microbiome is largely limited to majority ethnic groups in industrialized nations, and does not reflect the full diversity of human commensal microbiota. In addition to the scientific ramifications of minority underrepresentation, there are significant translational and ethical implications as well: first, failing to capture the full diversity of healthy human microbiota may limit our ability to understand and generate effective therapeutics for many microbiome-associated diseases. Second, underrepresented groups are less likely to benefit from microbiome-based medical advances tailored to well-studied populations, propagating healthcare inequities.  Human gut microbial diversity is diminishing around the globe, due to the spread of industrialized diets and lifestyles, which are associated with reduced microbiome biodiversity. The Global Microbiome Conservancy (GMbC) is a non-profit collaboration between scientists and communities around the world that aims to 1) preserve the full biodiversity of the human gut microbiome, 2) characterize its evolution across populations and host lifestyles and 3) investigate its interactions with the human host. We are collecting gut microbiome and human DNA samples from diverse populations around the world, from isolated groups to urbanized populations, to culture and study this essential biodiversity and to preserve it in a living "seed bank" of bacterial isolates as a long-term safeguard against future extinctions. Human genetic data for the samples sequenced in this study can be found in phs002205.

Study phs002235

Genetic Associations in Idiopathic Talipes Equinovarus (Clubfoot) - GAIT

Isolated clubfoot or idiopathic talipes equinovarus (ITEV) is one of the five most common birth defects, affecting approximately 4,000 newborns each year in the US. While the orthopedic care of these children has improved, long-term problems persist and the health care costs are significant. Studies suggest that clubfoot is a complex disorder with segregation analyses and family studies indicating that genetic factors play an important etiologic role in the development of clubfoot. Only one environmental factor, maternal smoking during pregnancy, has been implicated. We postulate that a small number of genes account for a substantial fraction of clubfoot and that these genes can be identified in a defined population. The challenge now is to identify the genetic loci and, later, the effect of environmental exposures. To accomplish this task, it is important to have a well-defined population and the methodology to detect linkage with and without association. Towards these goals, we have identified and characterized multiplex clubfoot families, including two large clubfoot families, a resource which is among the largest ITEV populations in existence. We will perform a high-density SNP genome scan (GWAS) on our clubfoot dataset to identify chromosomal regions that may harbor clubfoot genes with subsequent interrogation of these regions and candidate genes. We are in a position with our unique clubfoot population and with the methodology in place to undertake this study. The study phases are: 1) continued ascertainment of multiplex and simplex families and 2) GWAS and characterization of identified chromosomal regions and candidate genes. The results of this study will provide data essential to the identification of the gene(s) contributing to the clubfoot phenotype. Identification of high-risk genotypes can lead to the development of prevention programs in selected populations and may suggest gene-based prevention strategies.

Study phs000314

Identifying novel DNA damage response genes in radiosensitive individuals

Ionizing radiation is an effective therapeutic agent for cancer treatment as well as a potent carcinogen. Sensitivity to the cell-killing effects of radiation can vary across human population with a subset of individuals displaying extreme hypersensitivity. It is usually attributable to inherited defects in DNA damage response pathways. The present study was designed to elucidate the genetic basis of variation in hypersensitivity to radiation exposure through exome sequencing of radiosensitive individuals, with the ultimate goal of identifying genes with the most significant effects on cellular DNA damage responses. The study participants included subjects referred for clinical testing for Ataxia-telangiectasia (A-T), Nijmegen Breakage Syndrome (NBS) or Ligase IV Syndrome. These are rare, recessive genetic disorders and hypersensitivity to radiation exposure is a common phenotype among individuals affected by all the three disorders. The study participants exhibited phenotypic characteristics similar to individuals with A-T, NBS or Ligase IV Syndrome, but lacked the causative mutations in ATM (GeneID:472) or NBN (GeneID:4683) genes. For further validation of the radiation sensitivity phenotype among the enrolled subjects, B-lymphoblastoid cells lines were established for each subject from peripheral blood lymphocytes. Each cell line was evaluated for displaying impaired survival rates relative to normal controls after exposure to ionizing radiation. 53 subjects with validated phenotype were finally included in the study and DNA extracted from their B-lymphoblastoid cell lines was used for exome sequencing. This sequencing data for radiation sensitive subjects is being made available in the dbGaP. It is hoped that this resource will be beneficial for researchers who wish to further investigate components of human cellular DNA damage response pathways and/or genetic architecture underlying radiation hypersensitivity. This data may also aid in the rational design of new radiosensitizing or radioprotective agents.

Study phs001911

Polymorphisms in the mitochondrial genome are associated with bullous pemphigoid in Germans

Bullous pemphigoid (BP) is the most prevalent autoimmune skin blistering disease and is characterized by the generation of autoantibodies against the hemidesmosomal proteins BP180 (type XVII collagen) and BP230. Most intriguingly, BP is distinct from other autoimmune diseases because it predominantly affects elderly individuals above the age of 75 years, raising the question why autoantibodies and the clinical lesions of BP emerges mostly in this later stage of life, even in individuals harboring known putative BP-associated germline gene variants. The mitochondrial genome (mtDNA) is a potential candidate to provide additional insights into the BP etiology; however, the mtDNA has not been extensively explored to date. Therefore, we sequenced the whole mtDNA of German BP patients (n=180) and age- and sex-matched healthy controls (n=188) using next generation sequencing (NGS) technology, followed by the replication study using Sanger sequencing of an additional independent BP (n=89) and control cohort (n=104). While the BP and control groups showed comparable mitochondrial haplogroup distributions, the haplogroup T exhibited a tendency of higher frequency in BP patients suffering from neurodegenerative diseases (ND) compared to BP patients without ND (p= 0.1448, Fisher’s exact test). A total of four single nucleotide polymorphisms (SNPs) in the mtDNA, namely, m.16263T>C, m.11914G>A, m.16051A>G, and m.16162A>G, were found to be significantly associated with BP based on the meta-analysis of our NGS data and the Sanger sequencing data (p=0.0017, p=0.0132, p=0.0129, and p=0.0076, respectively, Peto’s test). In summary, our study is the first to interrogate the whole mtDNA in BP patients and controls and to implicate multiple novel mtDNA variants in disease susceptibility. Studies using larger cohorts and more diverse populations are warranted to explore the functional consequences of the mtDNA variants identified in this study on immune and skin cells to understand their contributions to BP pathology.

Study EGAS00001003932

Exploration of CNV’s and SNV’s in cancers with well-known genetic rearrangements: Identification of additional genetic changes in rearrangements-driven cancer

Specific cancers are well known to have specific gene rearrangements. Representative cancer is chronic myeloid leukemia (CML) which is famous for BCR/ABL gene rearrangements. By the way, also genetic rearrangements are not infrequently found in acute leukemia, and those include CBFB/MYH11 rearrangements, PML/RARA rearrangements, AML/ETO rearrangements, and BCR/ABL rearrangements. The situation is same is for lung adenocarcinoma of non-smokers and prostate cancers, and ALK and RET gene rearrangements are recently found. However, not all these rearrangements are sufficient to develop cancer, and it is suggested that some genetic aberrations are required for the development and progression of cancer in addition to these genetic rearrangements. In this study, we have a plan to explore the existence of additional genetic changes including single nucleotide variants (SNV’s) and copy number variations (CNV’s) in cancers with specific genetic rearrangements so as to define additional genetic changes that confer full oncogenic potential to cancer cells. So as to look at SNV’s and small indels, we are going to use whole exome sequencing (WES) data. And as for CNV’s, we are going to use array-CGH data. Also, to check the functionality of these genetic changes, we are going to use whole transcriptome data (WTS). In addition, in samples with whole genome sequencing (WGS ) data, we are going to explore genetic changes in intronic regions also. In fact, we sequenced 10 AML samples which are known to have specific genetic rearrangements. Analysis of these WGS, WES and WTS data are under the way. If we have a chance to access WES, array-CGH and WTS data of other cancer samples with specific genetic rearrangements, we would be able to compare additional genetic changes required for oncogenesis in cancer cells with various genetic rearrangements. We hope this result will enlighten our understanding of cancer genetics further.

Study EGAS00001000673

Best Practices for DACs

Best Practices Data access committees (DACs) are institutional safeguards responsible for ensuring a balance between data protection and accessibility. However, there are no procedural standards that apply across DACs, which can lead to inconsistencies in their reviews and compromise their quality and effectiveness. Standardising DAC processes can foster trust and mutual recognition, paving the way for greater coordination, collaboration, and delegation between DACs and other oversight bodies to improve the efficiency of data access without sacrificing protection. To provide guidance, the following are suggestions for actions a DAC might take upon receiving a data access request: Aim to respond to all initial requests in less than 2 weeks. Failure to do so may result in follow-up emails from the EGA, journals, and ultimately dataset withdrawal. First, check that the data/EGAD number is consistent with your data submission. In other words, ensure that the requester has contacted the correct DAC. Verify that the user will be using the data within the terms of consent by asking them to sign up to the terms within the DAA. Ensure that data users who are granted access to the data comply with the terms of a Data Access Agreement (DAA) and to use the data only in approved ways. Look for an institutional email address for the requester. Search for evidence that the requester is "appropriately qualified/bona fide" for using the data, for example on PubMed, Research Gate, LinkedIn, etc. Confirm that the affiliated organisation is real and that the requester still works there. Inquire with the requester about who should have accounts created at the EGA under the terms of the agreement. If a negative decision is made, promptly communicate it to the requester and support it with the terms of the Data Access Policy that the requester has not met or cannot meet. Keep the information in the DAC up to date. If you leave your institution and are unable to manage data access requests on their behalf, you should add your replacement as a new contact in the DAC. Assist with data access requests for any further questions related to your data. The EGA can only check information that has been deposited in the repository. If the user has a specific question that the EGA cannot answer, we will redirect the user to the DAC. All the EGA studies and datasets referenced in a publication under your DAC must be publicly searchable on the EGA website before the paper is released. If possible, describe the permitted purposes for subsequent research projects, including associated limits and conditions, for all resources hosted in a repository using a common ontology, such as the GA4GH Data Use Ontology (DUO). It is considered best practice to try and release data only to those with an institutional email address. This gives reassurance to the EGA, research participants, and the general public that an appropriate individual is accessing and using the data. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security.

Documentation access/data-access-committee/best-practices

IL7-receptor expression is frequent in T-cell acute lymphoblastic leukemia and predicts sensitivity to JAK-inhibition

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy with a dismal prognosis related to refractory/relapsing diseases, raising the need for new targeted-therapies. Activating mutations of the IL7-receptor pathway genes (IL7Rp) play a proven leukemia-supportive role in T-ALL. JAK-inhibitors such as ruxolitinib have recently demonstrated preclinical efficacy. However, prediction markers for sensitivity to JAK-inhibitors are still lacking. Herein, we show that IL7R (CD127) expression is more frequent (~70%) than IL7Rp-mutations in T-ALL (~30%). We compared the so-called non-expressers (no IL7R-expression/IL7Rp-mutation), expressers (IL7R-expression without IL7Rp-mutation) and mutants (IL7Rp-mutations). Integrative multi-omics analysis outlined IL7R-deregulation in virtually all T-ALL subtypes, at the epigenetic-level in non-expressers, genetic-level in mutants, and post-transcriptional level in expressers. Ex-vivo data using primary-derived xenografts support that IL7Rp is functional whenever the IL7R is expressed, regardless of the IL7Rp mutational status. Consequently, ruxolitinib impaired T-ALL survival in both expressers and mutants. Interestingly, we show that expressers displayed ectopic IL7R-expression and IL7Rp-addiction conferring a deeper sensitivity to ruxolitinib. Conversely, mutants were more sensitive to venetoclax than expressers. Overall, combination of ruxolitinib and venetoclax resulted in synergistic effects in both groups. We illustrate the clinical relevance of this association by reporting achievement of complete remission in two patients with refractory/relapsed-T-ALL. This provides proof of concept for translation of this strategy into clinics as bridge to transplant. Altogether, IL7R-expression can be used as a biomarker for sensitivity to JAK-inhibition, thereby expanding the fraction of T-ALL patients eligible to ruxolitinib up to nearly ~70% of T-ALL.

Study EGAS00001007144

Gabriella Miller Kids First Pediatric Research Program in Craniofacial Microsomia

The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Craniofacial microsomia (CFM), also termed hemifacial microsomia or oculo-auricular-vertebral spectrum, is the third most common congenital craniofacial condition. CFM comprises a variable phenotype and the most common features include malformations of the ear (i.e. microtia) and lower jaw (i.e. mandibular hypoplasia) on one or both sides. Microtia in the absence of other anomalies is believed to represent the mildest form of CFM. The cause of CFM is unknown for most affected individuals. We have established a cohort through previous studies and collected DNA to identify the genetic contributions to CFM, which could facilitate diagnosis, tailored treatments and guide prevention strategies. Successful completion of this proposal will advance knowledge in the genetic architecture of susceptibility to CFM and will provide insight about the biological mechanisms underlying craniofacial development. The results from this study have the potential to further research on the etiology of other craniofacial conditions, and the pathogenesis of typical and atypical craniofacial development.

Study phs002130

Phenotype Risk Scores Identify Patients with Unrecognized Mendelian Disease Patterns

This study was designed to assess the phenotypic effects of rare variants. Rare variants are difficult to study in a high-throughput manner because most cohorts are underpowered to detect associations. In order to gain power to test rare variants, we use Phenotype Risk Scores (PheRS) based on features of Mendelian diseases. PheRS is calculated using claims data from an EHR that is mapped to clinical features from OMIM's clinical descriptions of Mendelian disease. We calculated PheRS for 1,204 Mendelians diseases in a cohort of 21,701 individuals genotyped on the HumanExome BeadChip. We then tested for association between these diseases and rare variants in causal genes. A phenotype risk score is calculated as the weighted sum of features for a given disease. The features are defined as a set of phecodes (consolidated ICD codes) associated with a particular Mendelian disease as described in OMIM. The weights for each phecode are calculated as the log inverse prevalence of the phecode in our cohort. For an individual, their score equals the sum of the weights for each phecode that is present in their medical record. Our study was based on a cohort of individuals with genotype data linked to de-identified electronic health records (EHR) from Vanderbilt's BioVU resource. We hope that this method will help generate phenotype-genotype correlation data on rare variants which in turn may inform rare variant interpretations use for diagnostics.

Study phs001516

Transdisciplinary Studies of Genetic Variation in Colorectal Cancer(CORECT): Meta-analysis

This study is part 2 of 2 for Schumacher et al, Nat Communication. 2015 Jul 7;6:7138. Part 2 is the pooled meta-analysis of 29 different studies of 37,955 European (18,299 Cases/19,656 Controls) participants using eight different genotyping platforms/variations. table, th, td { border: 1px solid black; border-collapse: collapse; } Study Name Participants Platform CFR-1 2976 Illumina 1M, 1M Duo, Omni1 CFR-2 3053 Affymetrix Axiom MECC 1 982 Illumina Omni 2.5 MECC2 1940 Affymetrix Axiom Kentucky 2172 Affymetrix Axiom ACS/CAPII 1086 Affymetrix Axiom Melbourne 1008 Affymetrix Axiom Newfoundland 672 Affymetrix Axiom ASTERKSI 1895 Illumina 300K COLO23 212 Illumina 300K DACHS1 3417 Illumina 300K DACHS2 1173 Illumina OmniExpress DALS1 1416 Illumina 550k/610K DALS2 874 Illumina 300K HPFS1 457 Illumina OmniExpress HPFS2 348 Illumina OmniExpress HPFS AA 658 Illumina OmniExpress MEC 674 Illumina 300K NHS1 1168 Illumina OmniExpress NHS2 340 Illumina OmniExpress NHSAA 1091 Illumina OmniExpress OFCCR 1172 Affymetrix 100k/500K PHS 771 Illumina OmniExpress PMH 402 Illumina 300K PLCO1 2509 Illumina 550k/610K PLCO2 901 Illumina 300K VITAL 573 Illumina 300K WHI1 1999 Illumina 550k/610K WHI2 573 Illumina 300K Since this study is a meta-analysis no corresponding phenotype, pedigree, sample, subjects, or primary molecular data are available. Each contributing study/platform will have fulfilled its own DBGAP submission commitment. This DBGAP entry is for European participants in the the pooled meta-analysis exclusively.

Study phs001499

Targeted Linked-Read DNA-seq Analysis of Castration-Resistant Prostate Cancers

Androgen receptor (AR) inhibition is standard of care for advanced prostate cancer (PC). However, its efficacy is limited by progression to castration-resistant PC (CRPC), usually due to AR re-activation via mechanisms that include AR amplification and structural rearrangement. These two classes of AR alterations often co-occur in CRPC tumors, but it is unclear whether this reflects intercellular or intracellular heterogeneity of AR. It is important to resolve the mechanisms of AR genomic rearrangements to develop new therapies and predictive biomarkers for PC. We developed a targeted linked-read DNA sequencing assay to interrogate alterations in AR and a panel of genes known to be amplified or mutated in CRPC. Linked-read DNA-sequencing libraries were generated using the 10X Genomics Chromium platform and subjected to hybridization enrichment using a custom-designed Agilent SureSelect bait panel. Post-capture DNA-seq libraries were pooled and sequenced on an Illumina HiSeq 2500 using 2x150 bp settings. This targeted linked-read DNA-seq assay was used to interrogate a set of 6 benchmarking samples harboring known AR gene rearrangements and other alterations in AR, as well a panel of 6 patient-derived xenograft CRPC tumors and 23 clinical CRPC tumors. In this cohort, we identified a subset of samples that developed complex, multiply-rearranged AR gene structures in conjunction with very high AR copy number. The data that will be made available through dbGaP are raw FASTQ files.

Study phs003343

Single Cell Genotypic and Phenotypic Analysis of Measurable Residual Disease in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a group of blood cancers with high mortality. Even though complete remission is often achieved, majority of the AML patients still relapse. Measurable residual disease (MRD), defined as the population of cancer cells which persists following chemotherapy, is responsible for AML relapse. Understanding the biology enabling MRD clones to resist therapy is necessary to guide the development of curative treatments more effectively. Discriminating residual leukemic clones, preleukemic clones, and normal precursors remains a challenge with current MRD tools. We developed a single cell MRD (scMRD) assay by combining flow cytometric enrichment of the targeted precursor/blast population with integrated single cell DNA sequencing (scDNA-seq) and immunophenotyping (Tapestri, Missionbio). The platform utilizes a custom amplicon panel covering 109 amplicons across 31 genes frequently mutated in AML and a panel of 42 oligo-conjugated antibodies against surface makers. We applied our scMRD assay to sequence 30 MRD samples (multiplexed into 6) from 29 AML patients to study the clonal architecture and protein correlation. In addition, 2 MRD samples were sequenced with scDNA+protein sequencing technology without enrichment or multiplexing. Five patients with AML at diagnosis were also sequenced with scDNA+protein sequencing technology without enrichment or multiplexing. In order to establish the sensitivity of our scMRD assay, we spiked AML cells into normal bone marrow cells. We sequenced 12 such spiked samples after multiplexing.

Study phs003233

Longitudinal Multi-Omic Immune Resource Reveals Dynamic Responses in Healthy Human Aging

The generation and maintenance of protective immunity is a dynamic interplay between host and environment that is impacted by age. Understanding fundamental changes in the healthy immune system that occur over a lifespan is critical in developing interventions for age-related susceptibility to infections and diseases. Here, we use multi-omic profiling (scRNA-seq, proteomics, flow cytometry) to examine human peripheral immunity in over 300 healthy adults, with 96 young and older adults followed over two years with yearly vaccination. The resulting resource includes scRNA-seq datasets of >16 million PBMCs, interrogating 71 immune cell subsets from our new Immune Health Atlas. This study allows unique insights into the composition and transcriptional state of immune cells at homeostasis, with vaccine perturbation, under Cytomegalovirus (CMV) infection and across age. We find that T cells specifically accumulate age-related transcriptional changes more than other immune cells, independent from inflammation and chronic perturbation. Moreover, impaired memory B cell responses to vaccination are linked to a Th2-like state shift in older adults' memory CD4 T cells, revealing possible mechanisms of immune dysregulation during healthy human aging. This extensive resource is provided with a suite of exploration tools at https://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/ to enhance data accessibility and further the understanding of immune health across age. Please note that the Sound Life Cohort raw data are spread across three dbGap submissions: phs003841.v1 (this study), phs003944.v1, and phs003400.v1.

Study phs003841

Geriatric Oncology Database of genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients to establish truly effective treatment strategy

Owing to the advent of super-aged society, cancer mortality in Japan is forecasted to become an all-time high. The management of elderly patients with cancer is a serious health issue and the need for specific care guidelines for this population is critical in Japan. The significant individual differences in comorbidity, physical and mental functioning, and social problems among aging individuals are obstacles to the progress. The response to cancer treatment varies significantly among patients, even in the same stage of the same type of cancer. Older aged patients are still less likely to be offered participation in clinical trials, thus the number of clinical evidences is limited. The molecular mechanisms regulating the physiological process of ageing and senescence, and cancer are far from understood. To establish a truly effective treatment algorithm, we attempted to develop a geriatric oncology database for genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients in this retrospective study. The genomic analysis was performed in 62, 106, and 173 cases, respectively for gastric, colon and lung cancers. The clinical data and survey results on psychosocial and physical conditions were collected from 166, 313, and 344 patients respectively for gastric, colon and lung cancers, and also collected from 357, 49, and 300 benign cases respectively for cardiovascular disorder, respiratory dysfunction, diabetes and nephropathy as the analysis control.

Study JGAS000061

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