Search Results - EGA European Genome-Phenome Archive

cfDNA methylation profiling on longitudinally collected blood plasma of patients with esophageal adenocarcinoma

cell-free Reduced Representation Bisulfite Sequencing (cfRRBS) data from blood plasma and FFPE tissue samples from patients with esophageal adenocarcinoma, and blood plasma of healthy donors.

Dataset EGAD50000000734

Cell-free DNA TAPS provides multimodal information for early cancer detection

TAPS data from 21 patients with HCC, 23 patients with PDAC, 30 non-cancer controls, 4 patients with cirrhosis, and 7 patients with pancreatitis.

Dataset EGAD00001006871

Longitudinal monitoring of cell-free DNA methylation in ALK-positive non-small cell lung cancer patients

Here, we performed genome-wide 5-mC profiling in plasma of metastatic ALK-rearranged non-small cell lung cancer (NSCLC) patients receiving tyrosine kinase inhibitor therapy. We established a strategy to identify ALK-specific 5-mC changes from cfDNA and demonstrated the suitability of the identified markers for cancer detection, prognosis and therapy monitoring. Longitudinal plasma samples (n = 79) of 21 ALK-positive NSCLC patients and 13 healthy donors were collected alongside 15 ALK-positive tumor tissue and 10 healthy lung tissue specimens. All plasma and tissue samples were analyzed by cell-free DNA methylation immunoprecipitation sequencing to generate genome-wide 5-mC profiles. Information on genomic alterations (i.e., somatic mutations/fusions and copy number alterations) determined in matched plasma samples were available from previous studies.

Study EGAS00001006573

GCparagon: Evaluation and correction of GC biases in cell-free DNA at the fragment level

We present GCparagon, a two-stage algorithm for computing and correcting GC biases in cell-free DNA (cfDNA) samples. The length of the highly fragmented cfDNAs and the number of GC bases are essential parameters in the calculations. Regions of low mappability, known reference genome assembly errors and regions surrounding assembly gaps are excluded from the bias computation. GCparagon outputs a bias matrix and an optional tagged BAM file with GC bias balance weights as alignment tags. Parallelization allows calculation of a GC bias estimate in less than 2 minutes per sample with between 99.0% and 99.9% of fragments already corrected. We propose that GCparagon can help standardize cfDNA applications and evaluate the impact of GC bias on algorithms used in the analysis of liquid biopsy data.

Study EGAS00001006963

Bam files for a metastatic bladder cancer patient with BAP1 variants

This dataset consists of three bam files (two cell-free DNA and one germline DNA) from a metastatic bladder cancer patient with BAP1 variants. Bam files were generated from targeted Illumina sequencing data.

Dataset EGAD00001005520

Performance assessment of total RNA sequencing of human biofluids and extracellular vesicles

SMARTer Stranded Total RNA-Seq method of human platelet-rich plasma, platelet-free plasma, urine, conditioned medium, and extracellular vesicles (EVs) from these biofluids. Including a titration experiment with spikes.

Dataset EGAD00001006150

HiSeq Colorectal Cancer Dataset

Set of 19 patients afflicted with colorectal cancer with matching preoperative and postoperative blood plasma, PBMC, and tumor biopsy sequencing data. Originally referenced by Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring. Nat Med. 2020, Zviran et. al.

Dataset EGAD00001011186

Noncoding Mutational Analysis of DLBCL Genomes

146 DNA samples obtained from 73 DLBCL patients (matching tumor and normal) were sequenced with PCR free 1.0 genome shotgun sequencing. All files are in bam format.

Dataset EGAD00001004142

FEGA and European GDI: working together to improve human health

The Federated EGA is a global resource for discovery of and access to sensitive human omics and associated data consented for secondary use, through a network of human data repositories to accelerate biomedical research and improve human health. The Federated EGA network was launched in September 2022 with five inaugural nodes, and since 2023 seven operational nodes can share data across national borders in adherence to European and national laws. A few weeks after FEGA's official launch, in November 2022, the European Genomic Data Infrastructure (GDI) project was kicked-off . This European Commission co-funded project, coordinated by ELIXIR, is aimed to deliver federated, sustainable and secure data infrastructure to access genomic and related phenotypic and clinical data across Europe. This project supports the aim of the 1+MG initiative (25 EU countries, Norway and UK) to enable personalised medicine and health through a shared framework and infrastructure for securely accessing and integrating high quality genomic data and other health data across borders.1+MG will be an integral component of the European Health Data Space (EHDS) for secondary use (Healthdata@EU) as an authorised participant. How are Federated EGA and GDI similar? Given their shared visions, the Federated EGA and European GDI networks have a lot in common. To begin, they share the same overall goal of establishing networks of “nodes” that host sensitive human data within a jurisdiction and connecting these nodes in a global network to support data discovery and promote human genome data access for research and healthcare. FEGA and GDI are both initially focused on enabling access to human genomic data, while FEGA ambition is to expand the scope to clinical research data and other omics data in the future. FEGA and GDI are both built on open and interoperable software solutions, a subset of which are based on the LocalEGA components. FEGA and GDI implementation solutions are based on international community standards, for example those developed by the Global Alliance for Genomics and Health, which contributes to making them interoperable. Both FEGA and GDI allow for the nodes to make use of any solution that is fully compatible. As illustrated in Figure 1, a final key point is the significant overlap of institutions involved in envisioning and operating FEGA and GDI nodes, with the clear wish to keep them interoperable in the future. What distinguishes Federated EGA from GDI? Despite being largely similar, there are some differences between the FEGA and GDI networks, which we aim to clarify in this post. The first difference is the governance model that the nodes will operate to comply with national laws and GDPR. In the FEGA network, nodes have taken inspiration from the EGA data access model, where the infrastructure is a data processor of the hosted data and data controllership remains with the originating Data Access Committees (i.e. Data controllers) for each dataset. On the other hand, in the GDI network the controllership of datasets will be transferred to a 1+MG European Digital Infrastructure Consortium (EDIC) legal entity created by the Member States (MS), who will make data access decisions, with data holders having veto powers for their datasets. Importantly, FEGA nodes have the flexibility to choose another model to fit with their data protection framework, including becoming data controllers for their datasets. The second difference is the inclusion criteria for data. While FEGA nodes are designed to accept almost any type of omics data in need of control access (e.g. genomics, transcriptomics, genotyping, single cells sequencing, patient-tracked metagenomics), GDI nodes are initially, but not only, focused on accepting whole genome and exome sequencing data and affiliated data from sources such as (i) the Genome of Europe use case of the 1+MG initiative which specifically aims to fulfil the mission of building “a European network of national genomic reference cohorts of at least 500,000 citizens”) (ii) data collection of other types of genomic data identified by countries through the 1+MG dashboard and (iii) genomic data coming from data holders which would need to fulfil EHDS requirements. The third difference is the maturity of the software stacks. The FEGA network provides a set of software for data and metadata submission, storage, permissions management, and file distribution (the LocalEGA package). GDI is building a complete set of open source reference for the five functionalities covering the full data life cycle (a few more compared to the LocalEGA) including federated processing (analytics, AI/ML), which is still under active development. Notably, one of the GDI functionalities - storage and interfaces - can be satisfied by using the LocalEGA storage solution, highlighting the ability of FEGA and GDI to be interoperable. In both FEGA and GDI, nodes are allowed to use alternative solutions as long as they are fully interoperable with the networks. Figure 1 provides a simple overview of these described commonalities and differences. Figure1: schematic overview of the main commonalities and difference among a FEGA and a GDI node Can the same institute run a FEGA and a GDI node at the same time? The answer is Yes! We believe this is entirely possible and encouraged. As long as 1+MG requirements are continuously fulfilled in the implementation. The same trained personnel could operate the infrastructure and leverage the same national funding to run a FEGA and a GDI node. Several European nodes, especially GDI vanguard nodes like Norway, Sweden, Finland and Spain are following this model. The idea is that a lot of the work can be reused, given the overlapping scope and the interoperable technology. Thus, the hosted datasets can be discovered via the two catalogues, perhaps accessible under the same or different governance models. From a FEGA node perspective, the GDI datasets could simply be a subset of the datasets hosted in the FEGA node, which have their specific governance as any other. What's next? So, the amazing teams of people building the Federated EGA network and the European GDI network are working together to create infrastructures able to provide secure access to human genomic and associated data around Europe. Because we all know how much human genomics can improve healthcare and precision medicine. And we all want to collaborate to make it happen. This article has been reviewed collectively by members of the EGA and the GDI coordination team.

Blog fega-and-gdi

Genome-Wide Association Study of Celiac Disease

Celiac disease (gluten-sensitive enteropathy, celiac sprue) is a common disease with significant morbidity and mortality. It is caused by sensitivity to the dietary protein gluten, resulting in a chronic enteropathy in the small intestine. Celiac disease is now recognized to be a common disease, with reports that the disease frequency is 1:133 in the United States, similar to European estimates. There is recent evidence to suggest that the incidence of the disease is rising. Occult disease is frequently present with minimal classic symptoms or signs. The ratio of symptomatic to asymptomatic celiac disease is estimated to be 1:7. Some complications of celiac disease include lymphoma, osteoporosis, anemia, miscarriages, seizures, vitamin deficiencies, and co-occurrence of other autoimmune diseases. The only treatment is a gluten-free diet, so that recurrence of symptoms and complications may occur after minor dietary indiscretions. Identifying the underlying genetic causes of celiac disease may allow us to identify susceptible individuals, as well as advance new ways to prevent the disease and to treat it once it occurs. Several genome-wide linkage studies and one genome-wide association study of celiac disease have been conducted. Other than the common locus at HLA, few putative celiac disease loci have been replicated between studies, suggesting that the disease is heterogeneous and complex. A portion of the genetic predisposition can be attributed to HLA, but the etiology is likely due to a number of rare, high penetrant genes (as would be identified in linkage analysis) and to more common, low penetrant genes (as would be identified in association studies). The objective of this study is to identify new loci that increase risk to develop celiac disease. We will capitalize on existing North American resources, including three large collections of celiac cases and controls (Aim 1) and an independent set of celiac cases and their families (Aim 3). We propose a comprehensive multi-stage approach, with the following specific aims. In Aim 1, we will conduct a genome-wide association (GWA) study of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs). The GWA will include1900 disease cases and 3400 matched controls, genotyped using the Illumina Human 610-quad chip. Statistical analyses will be performed to test for associations with celiac disease. In Aim 2, we will conduct a combined analysis of our GWA dataset from Aim 1 and a previous GWA dataset to identify additional low-penetrance loci. In Aim 3, we will attempt to replicate significant findings from the GWA study in two independent sample sets. At the conclusion of this study, we expect to have validated a number of SNPs and CNPs from regions in the genome that alter the risk of developing celiac disease. These SNPs may prove useful at both the clinical and research level. The data from the study will be shared with the scientific community.

Study phs000274

The National Heart, Lung, and Blood Institute (NHLBI)-funded Next Generation Genetic Association Studies (NextGen) Consortium: Phenotyping Lipid traits in iPS derived hepatocytes Study (PhLiPS Study)

The goal of the PhLiPS study is to create a library of induced pluripotent stem cell (iPSC) lines and iPSC-derived hepatocytes of diverse genotypes for use in metabolic profiling and interrogating lipid phenotypes. These cell lines were created as a part of the Next Generation Genetic Association Studies (Next Gen) Program, which was a five-year, $80 million program to investigate functional genetic variation in humans by assessing cellular profiles that are surrogates for disease phenotypes. To achieve this, researchers from multiple institutions across the U.S. were awarded grants to derive iPSC lines from more than 1,500 individuals representing various conditions as well as healthy controls for use in functional genomic ("disease in a dish") research. This extensive panel includes a diverse set of age, gender, and ethnic backgrounds, and therefore will be an invaluable tool for evaluations across demographics. Further enhancing the utility of these cell lines are data sets such as phenotyping, GWAS, genome sequencing, gene expression and -omics analyses (e.g., lipidomic, proteomic, methylomic) that can be matched to the cell lines. The PhLiPS Study focuses on individuals free of cardiovascular disease or with lipoprotein metabolism disorders in the community served by the Hospital of the University of Pennsylvania.

Study phs001341

IMPRESS: Improved methylation profiling using restriction enzymes and smMIP sequencing, combined with a new biomarker panel, creating a multi-cancer detection assay

Background Despite the worldwide progress in cancer diagnostics, more sensitive diagnostic biomarkers are needed. The methylome has been extensively investigated in the last decades, but a low-cost, bisulfite-free detection method for multiplex analysis is still lacking. Methods We developed a methylation detection technique called IMPRESS, which combines methylation-sensitive restriction enzymes and single-molecule Molecular Inversion Probes. We used this technique for the development of a multi-cancer detection assay for eight of the most lethal cancer types worldwide. We selected 1791 CpG sites that can distinguish tumor from normal tissue based on DNA methylation. These sites were analysed with IMPRESS in 35 blood, 111 tumor and 114 normal samples. Finally, a classifier model was built. Results We present the successful development of IMPRESS and validated it with ddPCR. The final classifier model discriminating tumor from normal samples was built with 358 CpG target sites and reached a sensitivity of 0.95 and a specificity of 0.91. Moreover, we provide data that highlight IMPRESS’s potential for liquid biopsies. Conclusions We successfully created an innovative DNA methylation detection technique. By combining this method with a new multi-cancer biomarker panel, we developed a sensitive and specific multi-cancer assay, with potential use in liquid biopsies.

Study EGAS50000000624

The PEMDAC phase 2 study of pembrolizumab and entinostat in patients with metastatic uveal melanoma

Patients with metastatic uveal melanoma (UM) have an abysmal prognosis. Preclinical studies have suggested that epigenetic therapy could enhance immunogenicity of cancer cells. Here we test if epigenetic therapy would enhance PD-1 immunotherapy in patients with metastatic UM. We report the results of the PEMDAC phase 2 clinical trial (n=29; NCT02697630) where the HDAC inhibitor entinostat was combined with the PD-1 inhibitor pembrolizumab in patients with metastatic UM. The primary endpoint was objective response rate (ORR), and was met with an ORR of 14%. The clinical benefit rate at 18 weeks was 28%, median progression free survival was 2.1 months and the median overall survival was 13.4 months. Toxicities were manageable, and there were no treatment-related deaths. Extensive genomics studies were performed using DNA/RNA and single cell sequencing and flow cytometry. Objective responses and prolonged survival were seen in three patients with BAP1 wildtype tumors, and in one patient with an iris melanoma that exhibited a UV signature. Longer survival also correlated with low baseline ctDNA levels or LDH. In conclusion, HDAC inhibition and anti-PD1 immunotherapy results in durable responses in a subset of patients with metastatic UM. Further exploration of combined immunotherapy and epigenetic therapy in metastatic UM is warranted.

Study EGAS00001005478

An RCOR1 loss-associated gene expression signature identifies a prognostically significant DLBCL subgroup

Effective treatment of diffuse large B cell lymphoma (DLBCL) is plagued by heterogeneous responses to standard therapy, and molecular mechanisms underlying unfavorable outcomes in lymphoma patients remain elusive. Here, we profiled 148 genomes with 91 matching transcriptomes in an R-CHOP-treated DLBCL cohort to uncover molecular subgroups linked to treatment failure. Systematic integration of high-resolution genotyping arrays and RNA-seq data revealed novel deletions in RCOR1 to be associated with unfavorable progression free survival (P = 0.001). Integration of expression data from the clinical samples with data from RCOR1 knockdowns in the lymphoma cell lines KM-H2 and Raji yielded an RCOR1 loss-associated gene signature comprising of 233 genes. This signature identified a subgroup of patients with unfavorable overall survival (OS) (P = 0.023). The prognostic significance of the 233-gene signature for OS was reproduced in an independent cohort comprising of 195 R- CHOP treated patients (P = 0.039). Additionally, we discovered that within the IPI low risk group, the gene signature provides additional prognostic value that was independent of the cell-of-origin phenotype. Taken together, we present a novel and reproducible molecular subgroup of DLBCL, impacting risk-stratification of R- CHOP treated DLBCL patients and revealing a new avenue for therapeutic intervention strategies.

Study EGAS00001001000

NEOPREDICT-Lung: Neoadjuvant Immunotherapy for Resectable NSCLC

Links via: DOI: https://doi.org/10.1038/s41591-024-02965-0 PubMed: https://pubmed.ncbi.nlm.nih.gov/38689060/ Journal: https://www.nature.com/articles/s41591-024-02965-0 Abstract Antibodies targeting the immune checkpoint molecules PD-1, PD-L1 and CTLA-4 administered alone or in combination with chemotherapy are standard of care in most patients with metastatic non-small cell lung cancers. When given prior to curative surgery, tumor responses and improved event-free survival are achieved. New antibody combinations may be more efficacious and tolerable. In an ongoing, open-label phase II study, 60 biomarker-unselected, treatment-naïve patients with resectable non-small cell lung cancer were randomized to receive two preoperative doses of nivolumab (anti-PD-1) with or without relatlimab (anti-LAG-3) antibody therapy. The primary study endpoint was feasibility of surgery within 43 days, which was met by all patients. Curative resection was achieved in 95% of patients. Secondary endpoints included pathological and radiographic response rates, pathologically complete resection rates, disease-free and overall survival rates, and safety. Major pathological (≤10% viable tumor cells) and objective radiographic responses were achieved in 27% and 10% (nivolumab), and 30% and 27% (nivolumab and relatlimab) of patients, respectively. In 100% (nivolumab) and 90% (nivolumab and relatlimab) of patients tumors and lymph nodes were pathologically completely resected. With 12 months median duration of follow-up, disease-free survival and overall survival rates at 12 months were 89% and 93% (nivolumab), and 93% and 100% (nivolumab and relatlimab). Both treatments were safe with grade ≥ 3 treatment-emergent adverse events reported in 10% and 13% of patients per study arm. Exploratory analyses provided insights into biological processes triggered by preoperative immunotherapy. This study establishes the feasibility and safety of dual targeting of PD-1 and LAG-3 prior to lung cancer surgery.

Study EGAS00001007753

Genetic coupling of enhancer activity and connectivity in gene expression control

In this study, we investigated whether the genetic effects of eQTLs on enhancer activity and enhancer-promoter contacts (connectivity) are inherently coupled or distinct. To address this, we performed Capture Hi-C targeting ~1100 eQTL loci, along with ATAC-seq and RNA-seq, in monocytes from 34 healthy male donors. Using single-modality and multi-modality Bayesian statistical approaches, we demonstrated that eQTL effects are predominantly shared across enhancer activity, connectivity, and gene expression. However, we also identified a locus where an eQTL disrupts a CTCF binding site at a putative insulator, facilitating contacts between the PCK2 gene promoter and downstream enhancers. To validate these findings, we used 4C-seq to confirm the allelic effects of eQTLs on enhancer-promoter connectivity at the PCK2 locus and another eQTL region associated with THBS1 expression, both of which showed consistent eQTL effects across all three modalities. Additionally, we conducted Hi-C on monocytes from two donors to map reference TADs and performed ChIP-seq to confirm the allelic effects of the PCK2 eQTL on CTCF binding. Together, these data provide comprehensive insights into the genetic coupling of enhancer activity, connectivity, and gene expression.

Study EGAS50000000756

Treatment-mediated selection of lethal prostate cancer clones defined by copy number architectures

Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient relationships of metastases that evade treatment, we performed genome- wide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 142 metastatic regions from 10 organs harvested post-mortem from nine men who died from prostate cancer. We identified diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number change, we confirmed a common clone of origin across metastases and diagnostic biopsies; and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations. Autosome-defined clusters were characterized by cluster-specific AR gene architectures that in two index cases were topologically more congruent than by chance (p-values 0.03, 3.07x10-8). Integration with anatomical site suggested patterns of spread and points of genomic divergence. Copy number boundaries identified treatment-selected clones with putatively distinct lethal trajectories.

Study EGAS00001006598

A Genome-Wide Association Study in Patients Experiencing Musculoskeletal Adverse Events on NCIC CTG Trial MA.27 Evaluating Aromatase Inhibitors as Adjuvant Therapy in Early Breast Cancer. A Collaboration Between the NIH Pharmacogenetics Research Network and the RIKEN Yokohama Institute Center for Genomic Medicine.

Source of Patients The source of the patients for this genome-wide case control study was MA.27, which was conducted as a multi-cooperative group effort under the auspices of the NCI Breast Cancer Intergroup of North America. The NCIC Clinical Trials Group (CTG) serves as the coordinating group, with participation by the NCI-sponsored North Central Cancer Treatment Group, Eastern Cooperative Oncology Group (ECOG), Southwest Oncology Group, and Cancer and Leukemia Group B (CALGB). MA.27 involved postmenopausal women with histologically confirmed and completely resected invasive breast cancer with surgical margins clear of invasive carcinoma and DCIS in the following TMN categories (AJCC Version 6): pT1, pT2, pT3; pNx, pN0, pN1, pN2, pN3 (only when the sole basis is presence of 10 or more involved axillary nodes); MO. The primary tumor must have been ER and/or progesterone receptor positive. Patients were stratified by lymph node status at diagnosis, prior adjuvant chemotherapy, and trastuzumab use and were randomized to 5 years of adjuvant therapy with anastrozole or exemestane. The trial was activated on May 26, 2003, and reached its accrual objectives on July 31, 2008, after the randomization of 6827 North American patients, with the majority (79%) providing DNA and consent for genetic testing. Non-North American patients were also entered by the International Breast Cancer Study Group but they did not contribute DNA. From 2003 to December 21, 2004, patients also underwent a second randomization to celecoxib 400 mg twice daily or placebo but, after the entry of 1,622 patients, this treatment was discontinued because of reports of increased cardiovascular risk associated with celecoxib. Case Definition for Musculoskeletal Adverse Events Cases were defined to have had at least one of the following six MSAE): 1. pain - joint, 2. pain - muscle, 3. pain - bone, 4. arthritis, 5. joint - function, 6. musculoskeletal - other. Cases were required to have at least grade 3 toxicity, according to the NCI Common Terminology Criteria for Adverse Events v3.0, or go off treatment for any grade of the six MSAEs; and were required to have had an MSAE within the first two years (i.e., a MSAE occurring after 2 years was not be considered a case). Subjects were excluded from the case group who met the case definition while on celecoxib or in the three months after stopping celecoxib but subjects were allowed to be cases if they developed their first MSAE more than three months after stopping celecoxib. Study Design The design was a nested matched case-control study with two controls selected for each case. Random matching from the potential control group (i.e., risk-set sampling such that controls had at least the same length of followup as the timing of the case event) was done by matching the case on the following factors: 1. treatment arm (exemestane vs. anastrozole, blinded), 2. prior adjuvant chemotherapy (yes vs. no), 3. age at start of treatment (+/- 5 years), 4. Celecoxib allocation (yes vs. no). Attempts were made to exactly match each case with two controls according to the above criteria. If, however, controls could not be exactly matched, "close" matching was used to define a distance between each case and all potential controls in an optimal matching algorithm. Race is a potential confounding factor, and 94% of the MA.27 population is Caucasian, 3% are Black, 1% Asian, 1% American Indian, and 1% are of unknown race. Because there are so few non-Caucasian participants, was restricted to only Caucasians. Following identification of cases and controls, the list was sent to the CALGB Pathology Coordinating Office (PCO) at Ohio State University Medical Center for plating of the samples. Other patient factors that might influence the association of SNP genotypes with a MSAE, either as confounding factors or as effect modifiers, were included as investigational covariates. These include 1. body mass index (BMI), 2. bisphosphonate use, 3. fractures in past 10 years, 4. baseline ECOG performance status, 5. prior hormone replacement therapy, 6. prior adjuvant radiotherapy, and 7. prior taxane treatment. An Honest Broker Process was utilized to ensure patient confidentiality. Genotype Assays and Quality Control A GWAS was performed with the Illumina Human610-Quad at the RIKEN Center for Genomic Medicine. The DNA for all of the samples were adjusted to a concentration of 50 to 100 ng/µL in a final volume of 50 µL. The 96-well plates were designed to have a unique distribution pattern with x duplicates per plate to evaluate genotype concordance. Samples with <98% call rate were removed from analyses. SNPs with ambiguous call will be excluded using the following criteria: 1. low signal intensity of each allele, 2. low cluster separation score, 3. SNP call rate <0.98, 4. SNPs with Hardy Weinberg Equilibrium p-value <0.001 were excluded. X-chromosome SNPs were used to validate female sex and quality control measures were examined across the different submitting centers. For all pairs of subjects, the percentage of matching genotypes were computed to screen for unexpected duplicate samples. All SNPs found to be associated with MSAE were subjected to visual inspection of the cluster plots to verify that the genotype clustering was adequate.

Study phs000210

Diet, Genetic Factors, and the Gut Microbiome in Crohn's Disease

We investigate the hypothesis that consistent changes in the human gut microbiome are associated with Crohn's disease, a form of inflammatory bowel disease, and that altered microbiota contributes to pathogenesis. Analysis of this problem is greatly complicated by the fact that multiple factors influence the composition of the gut microbiota, including diet, host genotype, and disease state. For example, data from us and others document a drastic impact of diet on the composition of the gut microbiome. No amount of sequencing will yield a useful picture of the role of the microbiota in disease if samples are confounded with uncontrolled variables. We aim to characterize the composition of the gut microbiome while controlling for diet, host genotype, and disease state. Diet is controlled by analyzing children treated for Crohn's disease by placing them on a standardized elemental diet, and by testing effects of different diets on the gut microbiome composition in adult volunteers. Genotype is analyzed by large scale SNP genotyping, which is already underway and separately funded--team member Hakon Hakonarson is currently genotyping 50 children a week at ~half a million loci each and investigating connections with inflammatory bowel disease. Clinical status is ascertained in the very large IBD practice in the UPenn/CHOP hospital system. Effects of diet, host genotype, and disease state on the gut microbiome are summarized in a multivariate model, allowing connections between microbiome and disease to be assessed free of confounding factors. This project is divided into four sub-studies. In the Fecal Storage Methods (FSM) study, methods of stool storage and DNA extraction are compared to examine their impact on DNA sequence analysis results. The Controlled Feeding Experiment (CaFE) addresses the effects of controlled diets on the gut microbiome. In the Cross-sectional Study of Diet and Stool Microbiome Composition (COMBO), the effects of diet analyzed using surveys and deep sequencing of stool specimens. The fourth study, Pediatric Longitudinal Study of Elemental Diet and Stool Microbiome Composition (PLEASE), examines the effects of an elemental diet treatment on pediatric patients diagnosed with inflammatory bowel disease (IBD), particularly Crohn's disease. Fecal Storage Methods (FSM): Cross-sectional study Controlled Feeding Experiment (CaFE): Controlled trial Cross-sectional Study of Diet and Stool Microbiome Composition (COMBO): Cross-sectional study Pediatric Longitudinal Study of Elemental Diet and Stool Microbiome Composition (PLEASE): Longitudinal cohort study

Study phs000252

ctDNA quantification in Ewing sarcoma patients

Background. Treatment stratification and response assessment in pediatric sarcomas has relied on imaging studies and surgical/histopathological evidence of vital tumor cells. Such studies and evidence collection processes often involve radiation and/or general anesthesia in children. Cell-free circulating tumor DNA (ctDNA) detection in blood plasma is one available method of so-called liquid biopsies that has been shown to correlate qualitatively and quantitatively to some extent with the existence of vital tumor cells in the body. Our clinical observational study focused on the utility and feasibility of ctDNA detection in pediatric Ewing sarcoma (EWS) as a marker of minimal residual disease (MRD). Patients and Methods. We performed whole genome sequencing to identify the exact breakpoints in tumors known to carry the EWS-FLI1 fusion gene. Patient-specific fusion breakpoints were tracked in peripheral blood plasma using digital droplet PCR (ddPCR) before, during, and after therapy in six consecutive children and young adults with EWS. Presence and levels of fusion breakpoints were correlated with clinical disease courses. The genetic changes in the tumors were defined, and inter- and intra-individual changes in the tumor DNA copy loads were observed over time. Results. We show that the detection of ctDNA in the peripheral blood of EWS patients i) is feasible in the clinical routine and ii) allows for the longitudinal real-time monitoring of MRD activity in children and young adults. Although changing ctDNA levels correlated well with clinical outcome within patients, between patients, a high variability was observed (inter-individually) for the six patients described here. Conclusions. ctDNA detection by ddPCR is a highly sensitive, specific, feasible, and highly accurate method that can be applied in EWS for follow-up assessments as an additional surrogate parameter for clinical MRD monitoring and, potentially, also for treatment stratification in the near future.

Study EGAS00001006433

Genome-Wide Analysis of Aberrant Position and Sequence of Plasma DNA Fragment Ends in Patients With Cancer

This study investigated fragmentation characteristics in plasma cell-free DNA and evaluated the relevance of such analysis for cancer diagnostics. Specifically, we performed whole genome sequencing (WGS) of healthy individuals and cancer patients, and evaluated genome-wide coverage and sequences surrounding fragment ends. This was a retrospective study of archived plasma samples. The WGS data are available through this submission. Detailed study design and findings were published in Budhraja et al. Science Translational Medicine 2023.

Study phs003170

Diagnosis of pediatric central nervous system tumors using methylation profiling of cfDNA from cerebrospinal fluid

In this study, we explore the potential of classifying pediatric brain tumors based on methylation profiling of the cell-free DNA in cerebrospinal fluid (CSF). For this proof-of-concept study, we collected 20 cerebrospinal fluid samples of pediatric brain cancer patients via a ventricular drain placed for reasons of increased intracranial pressure. For 11 patients in this study we collected matched tumor DNA. This cohort contains fastQ files of cfRRBS data of these samples.

Study EGAS50000000377

Atezolizumab and Bevacizumab in Treating Patients With Rare Solid Tumors

This phase Ib/II single-arm study evaluated atezolizumab + bevacizumab for patients with treatment-refractory metastatic HPV+ anal cancer. The primary endpoint was best overall response, and secondary endpoints included progression-free survival, overall survival, and safety/tolerability. Paired tissue biopsies were collected in patients before treatment and at the time of first restaging and analyzed for whole-exome sequencing, RNAseq (Bulk), and multiplex immunofluorescence. The overall response rate among 20 patients was 10%. WES and RNAseq data are provided here.

Study phs003845

Targeted plasma cell-free DNA sequencing for tissue-of-origin determination and donor-derived cell-free DNA quantification in organ transplant recipients and healthy controls

The dataset comprises targeted deep methylation sequencing data used for both tissue-of-origin determination and donor-derived cfDNA quantification. It includes plasma cfDNA data from stable kidney transplant recipients (n = 31), stable liver transplant recipients (n = 20) and healthy controls (n = 23). In addition, plasma cfDNA samples collected early after transplantation were analyzed from kidney transplant recipients (n = 44) and liver transplant recipients (n = 40). The dataset also features genomic DNA data generated from whole blood (n = 10) and buffy coat (n = 3) from healthy controls, as well as from T cells (n = 1), B cells (n = 2), hepatocytes (n = 1) and kidney epithelium (n = 1). Lastly, genomic DNA data was generated from buffy coat of transplant recipients (n = 17). Here, “n” indicates the sample number.

Dataset EGAD50000001446

Integrated Methylation and Copy Number Analysis for Non-invasive Bladder Cancer Detection in Urine

The molecular analysis of urine cell-free DNA (cfDNA) offers a non-invasive tool to advance bladder cancer (BC) management. Assessment of somatic copy number aberrations (SCNA) and DNA methylation, as singular or complementary analysis, have emerged as promising approaches for BC detection. Here, we developed an integrated analysis to assess both SCNA and targeted methylation changes from the same template molecules, named the iSECURE (integrated SEquencing-based Copy number and methylation analysis in URinE) method.

Study EGAS50000001350

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