Search Results - EGA European Genome-Phenome Archive

A panel of reference haplotypes for imputing complement component 4 (C4) gene structural variation

Neuropsychiatric and autoimmune disorders have substantial epidemiological correlations (Benros et al., JAMA Psychiatry 2013, PMID: 23760347) and broad, genome-wide patterns of shared genetic risk (Pouget et al., Hum Mol Genet, PMID: 31211845; Tylee et al., Am J Med Genet B Neuropsychiatr Genet 2018, PMID: 30325587). Some cases of psychosis involve autoantibodies against the NMDA receptor, AMPA receptor, or other synaptic proteins (reviewed in Dalmau et al, Lancet Neurol 2011, PMID: 21163445). The related autoimmune conditions lupus and Sjogren's Syndrome also involve the development of autoantibodies. The possibility that neuropsychiatric disorders can have molecular mechanisms in common with autoimmune disorders - for example, that psychosis involves an inflammatory or autoimmune component in some patients, or that immune molecules are re-used in the brain to underlie other important biological activities (Stevens et al., Cell 2007, PMID: 18083105) - could open novel therapeutic possibilities for neuropsychiatric disorders. At a genetic level, the strongest genetic associations of schizophrenia, lupus, and Sjogren's Syndrome to common genetic variation involve associations to genetic markers in the Major Histocompatibility Complex (MHC) locus. Bipolar disorder in some studies also associates with variation in or near the MHC locus, though less strongly than schizophrenia does. Intriguingly, the same specific SNPs appear to associate strongly with schizophrenia, lupus, and Sjogren's; these strongly associating SNPs span a genomic segment that includes the HLA class II genes (which have an important role in antibody production) and the complement component 4 (C4) genes. The specific genes and alleles responsible for these associations need to be completely defined, and the extent to which they represent shared or distinct genetic influences in neuropsychiatric and autoimmune illnesses needs to be clarified. The complement component 4 (C4A and C4B) genes are present in the MHC locus, between the class I and class II HLA genes. C4A and C4B commonly vary in genomic copy number and encode complement proteins with distinct affinities for molecular targets. The complex genetic variation at C4 - arising from many alleles with different numbers of C4A and C4B genes - has been challenging to analyze in large cohorts. We recently developed an approach to this problem based on imputation: people share long haplotypes with the same combinations of SNP and C4 alleles, such that C4A and C4B gene copy numbers can be imputed from SNP data (Sekar et al., Nature 2016, PMID: 26814963). In the current work, to analyze C4 in large cohorts, we developed a way to identify C4 alleles from whole-genome sequence (WGS) data, then analyzed WGS data from 1,234 individuals to create a large multi-ancestry panel of 2,530 reference haplotypes of MHC SNPs and C4 alleles that can then be imputed into still-larger cohorts for which SNP data are available. With this dbGaP submission, we make this reference panel available for other studies. Protocols and software for imputing C4 alleles into genome-wide SNP data, and for performing molecular analyses on the C4 genes (such as direct measurement of copy number from genomic DNA), can be found on the McCarroll Lab web site (http://mccarrolllab.org/resources). We are also working to create additional reference panels for imputation of C4 alleles that will be based on still-larger and more diverse population samples; links to these will also be available on the McCarroll Lab web site as we create and validate them.

Study phs001992

Raw FASTQ files from TSO500 hybrid capture sequencing of prostate cancer tissue and plasma.

This dataset contains raw genomic sequencing data in FASTQ format for a total of 49 libraries. It includes 22 samples derived from formalin-fixed paraffin-embedded (FFPE) tissue and 27 samples from plasma cell-free DNA (cfDNA). All samples were processed using the Illumina TruSight Oncology 500 (TSO500) hybrid capture panel to identify relevant genomic alterations. These files represent the primary, non-aligned data used for the comparative performance analysis described in the associated study.

Dataset EGAD50000002463

WGS data of pediatric T-ALL acute lymphoblastic leukemia (set3)

The dataset includes FASTQ and CRAM files from diagnostic and matched remission (control) samples of two T-ALL patient (ALLK-126, ALLT-503). ALLT-503 sample has two diagnostic samples one extracted from the BM (ALLT-503D) and from the lymph node (ALLT-503lympD). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using Novogene NGS DNA Library Prep Set (Cat No. PT004). Both diagnostic/relapse (90x) and remission (30x) samples were sequenced using Illumina NovaseqX Plus.

Dataset EGAD50000002015

Fragmentomics analyses of urinary cfDNA for urologic cancers

This dataset contains sequencing data of human urinary cell-free DNA. Whole-genome sequencing (WGS) and whole-genome bisulfite sequencing (WGBS) was performed after DNA extraction from the urine samples. All samples were pair-end sequencing on Illumina system and were aligned to human genome GRCh37 (hg19). WGS and WGBS reads were aligned by SOAP2 and Methyl-Pipe, respectively. The dataset includes samples from healthy subjects, haematuria (non-cancer), and patients of bladder, kidney, or prostate cancer. Pair-end FASTQ files were provided for all the samples mentioned above.

Dataset EGAD50000002068

WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set3)

The dataset includes FASTQ and BAM/CRAM files from diagnostic and matched remission (control) samples of 10 B-other ALL patients (ALLT-369,ALLT-378, ALLK-109, ALLK-110, ALLK-115, ALLT-391, ALLK-101, ALLK-113, ALLK-123, ALLT-393). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using NEBNext® Ultra™ II DNA Library Prep Kit. Both diagnostic (90x) and remission (30x) samples were sequenced using Illumina NovaSeq 6000.

Dataset EGAD50000002158

WGS of clonal organoids, bulk-tumor tissues, and matched blood samples derived from metastatic colorectal cancer patients

This dataset consists of WGS fastq files from 58 clonal organoids and 18 fresh-frozen (FT) bulk-tissue samples from surgically resected primary and metastatic tumors before and after anticancer therapies in 6 patients with matched blood control samples from each patient. After DNA extraction from each sample using DNeasy Blood and Tissue Kit (Qiagen), library preparation was done using TruSeq DNA PCR-free kit. Then, paired-end fastq files were generated using Illumina NovaSeq 6000.

Dataset EGAD50000001493

Transrenal DNA Analysis

The current sequencing dataset consists of 91 whole genome sequencing data files (Fastq files) of human cell-free DNA (cfDNA) obtained from plasma and urine samples. Specifically, we extracted 20 ucfDNA and 17 plasma DNA samples from healthy pregnant women, 11 ucfDNA samples from pregnant women with preeclampsia, 19 ucfDNA samples from healthy controls, and 24 ucfDNA samples from patients with proteinuria. These extracted cfDNA samples were then constructed into DNA libraries using the TruSeq Nano DNA Library Prep Kit (Illumina) and subsequently sequenced on the Nextseq2000 platform (Illumina).

Dataset EGAD50000001127

cfRRBS methylation profiling of cfDNA from cerebrospinal fluid from pediatric CNS tumor patients

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.

Dataset EGAD50000000554

limbal stem cells from Aniridia patients

Limbal stem cells obtained during penetrating keratoplasty from aniridia patients with congenital aniridia (Lagali Stage 4), limbal tissue was digested in collagenase A solution (4 mg/ml) in keratinocyte serum-free medium (KSFM) (Thermo Fisher Scientific; Waltham, MA) for 20 h at 37 °C. Cell suspensions were filtered through a use of Flowmi® micro strainer (SP Bel-Art; Wayne, NJ). LSC clusters were dissociated with trypsin-EDTA (0.05%) solution and cultivated in KSFM. Medium was refreshed every other day. Subconfluent (80–90%) limbal epithelial cells were harvested at passage 2

Dataset EGAD00001011124

Whole genome sequence of monozygotic twins

We generated whole genome sequence data from a family of monozygotic twins. DNA was obtained from blood, buccal epithelial cells, placenta, and umbilical cords of monozygotic twins. DNA from the parents were also obtained. Libraries were generated using Truseq-PCR free, Truseq nano, and NEBnext Ultra II depending on the availability of DNA. Data was generated on Illumina NovaSeq platform. Raw sequence data was aligned to the human reference genome GRCh38 using bwa mem aligner.

Dataset EGAD00001008677

Whole-genome and transcriptome sequencing of NUT midline carcinoma

In this study, we sequenced three NUT midline carcinoma genomes and their transcriptomes (NMC1, NMC2 and Ty-82), and two paired normal blood samples (for NMC1 and NMC2). Whole-genome sequencing libraries were generated by PCR-free methods, and sequencing run was made in HiSeq X machines. Transcriptome (mRNA) sequencing was performed in HiSeq 2500 machines. PCR duplicates-marked, indel-realigned, and base-recalibrarted BAM files are provided in our dataset.

Dataset EGAD00001003117

Evolutionary Genome Analysis of Transformation into Small Cell Carcinomas from Lung Adenocarcinomas

This dataset includes the high-throughput sequencing data from a study entitled "Clonal History and Genetic Predictors of Transformation into Small Cell Carcinomas from Lung Adenocarcinomas". Whole-genome sequencing libraries were generated by PCR-free methods, and sequencing run was made in HiSeq X or HiSeq 2500 machines. PCR duplicates-marked, indel-realigned, and base-recalibrarted BAM files are provided in our dataset.

Dataset EGAD00001003315

Single Cell and Spatial Transcriptomic Profiling of Haemophilus ducreyi Infection

We investigated the immune response in end-point pustules formed by Haemophilus ducreyi in volunteers using an experimental infection model. Six volunteers were infected in the skin of the upper arm at three sites with 41-85 CFU of H. ducreyi loaded on an allergy testing device; a sham-inoculated (e.g., wound) site was also performed. Five volunteers (4 men and 1 woman; 2 Asians and 3 Whites; aged 27-46 years) formed pustules 6-8 days post infection; 1 volunteer spontaneously resolved all sites. If a volunteer formed pustules, biopsies were performed to collect their pustule and wound sites. Biopsy pairs for all 5 pustule formers were subjected to single cell (sc) RNA-seq. Sequencing libraries were prepared using the 10X Genomics Single-cell 3' RNA-seq kit. Spatial transcriptomics was performed on biopsy pairs from 4 of the 5 pustule formers. Ten micron sections were placed on 10X Genomics Visium slides for fresh-frozen tissue, and libraries were prepared with the 10X Genomics Visium spatial 3' gene expression kit. All samples were sequenced on an Illumina NovaSeq 6000. Count tables were produced with CellRanger and SpaceRanger, respectively, and Seurat was used to analyze the data. We identified 13 major cell types by scRNA-seq; the proportion of some immune cell subsets was increased in pustules compared to wound sites. We also localized the major cell types within the tissue by using the scRNA-seq data to deconvolve the spatial transcriptomic data. The FASTQ files and count tables from CellRanger and SpaceRanger are provided.

Study phs003754

Frequent post-treatment monitoring of colorectal cancer using individualized ctDNA validated by multi-regional molecular profiling

Purpose: Circulating tumor DNA (ctDNA) analysis has been proposed as an approach for prediction of post-treatment patient outcomes. However, whether a single platform will provide optimal information in all patients or alternatively a patient-specific monitoring approach based on assessment of mutations in the primary tumor from that patient remains an urgent question. Experimental Design: We conducted multiregional sequencing of 42 specimens of 14 colorectal tumors (Stage III and more) from 12 patients, including two double cancer cases, to identify the full spectrum of mutational heterogeneity and identify aberrations that could be used to develop personalized ctDNA assays. Results: ?Founder? mutations that occur in all regions of the sample were identified in 12/14 (85.7%) tumors. Subsequent phylogenetic analysis of each tumor showed that 12/14 tumors (85.7%) carried at least one ?truncal? mutation. Most founder and truncal mutations exhibited higher variant allele frequency (VAF) than ?non-founder? and ?branch? mutations. In addition, both founder and truncal mutations were more likely to be detected as ctDNA than non-founder and branch mutations. Synchronized ctDNA dynamics of multiple mutations suggested those mutations from the same clonal origin. For 10/12 patients (83.3%) with nearly 1,000 days of post-operative observation, the validity of frequent personalized ctDNA monitoring was confirmed in terms of early relapse prediction, treatment efficacy, and non-relapse corroboration. Conclusions: Personalized ctDNA monitoring based on aberrations with a high VAF in the primary tumor site should be explored in larger prospective clinical trials to determine the full clinical validity.

Study JGAS000243

The Oral Microbiome and Head and Neck Cancer

Oral microbiota may influence head and neck squamous cell carcinoma (HNSCC) development, potentially related to carcinogen metabolism. The human oral cavity hosts a diverse microbiota, including bacteria and fungi. We performed shotgun sequencing and ITS1 sequencing on 236 HNSCC case participants who developed HNSCC during a mean follow-up of 5.1 years and 458 matched controls who remained HNSCC-free. Oral samples were obtained from a prospective nested case-control study within three epidemiological cohorts: the American Cancer Society Cancer Prevention Study II Nutrition Cohort (ACS CPS-II), the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), and the Southern Community Cohort Study (SCCS). Control participants were selected using 2:1 frequency matching based on cohort, age, sex, race and ethnicity, and time since oral sample collection.

Study phs004018

Size-tagged preferred ends in maternal plasma DNAshed light on the production mechanism and showutility in noninvasive prenatal testing

Cell-free DNA molecules in the plasma of pregnant women exhibit nonrandom fragmentation with preferred end sites. We studied if such preferred end sites might bear any re- lationship with fragment lengths of plasma DNA. Short and long plasma DNA molecules were associated with different preferred DNA end sites. Analysis of size-tagged preferred ends could be used for measuring fetal DNA fraction and for facilitating fetal trisomy 21 detection. Fetal preferred end sites were generally located in the nucleosome cores, while the maternal ones were located in the linker regions. This con- ceptual framework provides an explanation of the relative shortness of fetal DNA in maternal plasma and brings us closer to understanding the biological mechanisms that influence plasma DNA fragmentation.

Study EGAS00001002831

Implementation of the GDPR

Data Protection 1 About the EGA The European Genome-phenome Archive (EGA) was formally launched in 2008 at the European Bioinformatics Institute (EMBL-EBI), an outstation of the European Molecular Biology Laboratory (EMBL), to address an identified need for archiving and sharing the results of genome-wide association studies from the Wellcome Trust Case Control Consortium. In late 2012, with the signing of a memorandum of understanding (and subsequent formal agreement in 2016) between EMBL-EBI and the Centre for Genomic Regulation (CRG), the EGA formally became a joint project of the two institutes. The two institutes work together to support the EGA services, including supporting submissions, web site, strategic leadership, and data infrastructure developments. 2 EMBL-EBI & GDPR The EGA is co-managed by EMBL-EBI and CRG. EMBL-EBI is an international organisation established by treaty and has certain privileges and immunities (e.g. exemptions from the application of national law) and also may self-regulate its activities (e.g. establish its own institutional legal framework) within the framework of its founding act of 1973. The General Data Protection Regulation (GDPR) is a European Union (EU) regulation that legislates how organisations can share and process personal data of EU citizens. EMBL places great value in maintaining collaboration with researchers who are subject to GDPR. For that reason, it is of utmost importance for EMBL to handle data received from those collaborators in a secure and responsible manner. Mindful of its public mandate and the sensitivity of the data it handles, EMBL has always ensured a high level of data protection in its activities. Since the introduction of GDPR in May 2018, EMBL has established its internal policy on General Data Protection (IP68), exercising its right to self-regulate its operations,., IP 68 establishes a robust personal data protection framework that provides for data protection principles, enforceable data subject rights and oversight and redress mechanisms offering a level of protection comparable with GDPR. 3 CRG & GDPR The Centre for Genomic Regulation (CRG) is an international biomedical research institute of excellence, created in July 2000 and mainly participated by the Catalan Government. It is a non-profit foundation and its mission is to discover and advance knowledge for the benefit of society, public health and economic prosperity. The CRG is a CERCA center. CERCA is the collective organisation for all research centres of excellence in Catalonia. CERCA ensures these centres develop successfully by promoting synergies and strategic cooperation improving their visibility and the impact of their research and promoting the dialogue amongst both public and private stakeholders. As a legal entity based in Spain and operating within the EU, the CRG ensures the compliance with the GDPR and the legal regulations on personal data protection applicable at the national level, as well as any other legislation that may replace, modify or supplement the above-mentioned in terms of personal data protection. 4 EGA & GDPR EGA GDPR Schema 4.1 Genetic and phenotypic data Within GDPR, there are two main actors: data controllers and data processors. Data controllers are persons or entities which determine the purposes and means that the personal data may be processed, e.g. companies, researchers, or universities. For EGA, the data controller is ultimately the data producer and the submitter(s) who submit the data to EGA. The data controller also creates a Data Access Committee (DAC) who will decide on data access permissions at EGA. Data processors are the persons or entities which process the data on behalf of a data controller. With regard to GDPR, EGA is a data processor as it processes data as instructed by the data controller. GDPR applies to any organisation which accesses personal data from an individual within the EU. Under GDPR, personal data is defined as any data that is identifiable, including names and email addresses as well as health-related and genetic data. EGA does not accept personally identifiable data except genetic and phenotypic data, so all other data submitted to EGA, such as names and addresses, must be pseudonymised. GDPR requires that data controllers implement data protection principles, such as data minimisation, to minimise the risk of data leakage, and protect the rights of the data subjects. As a data processor, EGA has a set of security policies that are followed to minimise the risk of unauthorised data access or data loss. In its role as a data processor, EGA requires all submitters to sign a Data Processing Agreement (DPA) when the submission account is first created. This agreement is only required to be signed once per submitter, and will remain valid for future submissions to EGA. 4.2 Other personal data The EGA also collects personal data as part of our interactions with submitters, data access committees, and researchers accessing data distributed by EGA. The below privacy notices explain what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Privacy Notices for EGA Title Version Last Updated EGA Data Access Committee Account Privacy Notice for EGA Data Access Committee Account 1.0 February 6, 2019 EGA User Account Privacy Notice for EGA User Account 1.0 February 6, 2019 EGA Helpdesk Service Privacy Notice for EGA Helpdesk Service 1.0 February 6, 2019 EGA Website Service Privacy Notice for EGA Website Service 1.0 February 6, 2019 Documentation Title Version Description EGA Security Overview Security Document 1.1 The EGA Security Document provides an overview of EGA’s practices in ensuring the security of data stored at EGA. EGA Data Processing Agreement Data Processing Agreement 1.5 The Data Processing Agreement must be completed and returned as part of the submission process. Please note that this document is non-negotiable. Authorised Submitters Authorised Submitters Formulary 1.0 The Authorised Submitters Form must be completed and returned as part of the submission process. Please list all those that should have access to the submission account in order to submit to the EGA should be detailed here. Dispute Resolution Any controversy or claim arising out of, or relating to, the DPA (including the enforceability or breach thereof, any question regarding its existence, validity or termination) or relating to the EGA Service shall be resolved using the internal dispute resolution mechanisms of EGA including those related to Data Protection. The EGA’s internal dispute resolution mechanism has the following procedure: EGA OPERATIONAL PHASE: Meetings between EGA staff and the Data Controller.LEGAL MANAGEMENT PHASE: Meetings between legal teams of EMBL, CRG and the Data Controller. DIRECTION MANAGEMENT PHASE: Negotiation between the legal representatives of EMBL, the CRG and the Data Controller. If the internal dispute resolution mechanism doesn’t resolve the controversy or claim the next phase is:ARBITRATION PHASE: Resolution by arbitration under the WIPO Expedited Arbitration Rules (“Rules”).

Documentation about/privacy-notice

Phase I Study and Cell-Free DNA Analysis of T-DM1 and Metronomic Temozolomide for Secondary Prevention of HER2-Positive Breast Cancer Brain Metastases

This study is a phase I trial combining ado-trastuzumab emtansine (T-DM1) with Temozolomide (TMZ) for the prevention of additional brain metastases after previous occurrence and local treatment in HER2+ breast cancer patients. Twelve patients were enrolled in this study. Data includes whole exome sequencing (WES) from patients' cerebrospinal fluid (CSF) and plasma samples. The CSF was collected from each patient at trial entry and after the initial two treatment cycles of TMZ and T-DM1 treatment. Blood was collected through a standard peripheral venipuncture at the following four time points: 1) upon trial entry, 2) after two treatment cycles, 3) the treatment cycle prior to the last follow-up, and 4) most recent follow-up. Whole exome libraries were captured by the SureSelect Human All Exon V8 Kit (Agilent, Santa Clara, CA, USA) and sequenced by NovaSeq 6000 S2 Sequencer in paired-end sequencing mode (Illumina, San Diego, CA, USA). Gene mutations in DNMT3A, ELP1, NOTCH4, KMT2B, CRLF2, and KCNJ18 were observed in patients' CSF.

Study phs003165

RNA-sequencing from duodenal bipsies of Celiac disease patients

Samples, in a form of PAXgene ﬁxed and paraffin-embedded biopsies, were collected from the multi-site, double-blind, randomized, placebo-controlled trial, aimed at dose-finding and assessing the efficacy and tolerability of a 6-week treatment with ZED1227 capsules vs. placebo in subjects with well-controlled celiac disease undergoing gluten challenge. Total RNA was extracted from the PaxFPE biopsy specimens (n = 116) using additional cuttings from the samples on which histomorphometry was previously assessed. For the extraction, an RNeasy Kit (Qiagen, Hilden, Germany) was used according to the manufacturer’s instructions. Library preparation and next-generation sequencing (NGS) were performed by the Qiagen NGS Service. A total of 10 ng of purified RNA was converted into cDNA NGS libraries. Library preparation was quality controlled using capillary electrophoresis. Based on the quality of the inserts and the concentration measurements, the libraries were pooled in equimolar ratios and then sequenced on a NextSeq (Illumina Inc., San Diego, USA) sequencing instrument according to the manufacturer’s instructions, with 100 bp read length for read 1 and 27bp for read 2. The raw data were de-multiplexed, and FASTQ files for each sample were generated using bcl2fastq2 software (Illumina Inc., San Diego, USA).

Dataset EGAD50000000491

Genomic profiling of paediatric high grade gliomas from the HERBY clinical trial

The HERBY trial was a phase-II open-label, randomised, multicentre trial evaluating bevacizumab in patients with newly-diagnosed non-brainstem high grade glioma (HGG) between the ages of 3-18yrs. 121 patients were randomised with 1yr event-free survival as the primary end-point. Confirmation of HGG diagnosis by reference pathology was mandatory before randomisation, followed by review with five independent expert neuropathologists. We collected specimens from 89 patients consenting to translational research, and performed Sanger sequencing for H3F3A, Illumina 450K BeadArray methylation profiling, and whole exome sequencing and RNA sequencing where possible. 7/89 patients (8%) harboured H3F3A G34R/V mutations, whilst 24/89 (27%) harboured H3F3A K27M, the latter reflecting a high proportion of the novel entity recognised in the 2016 WHO classification of diffuse midline glioma with H3K27M mutation. Both histone mutations conferred a significantly shorter progression-free (p=0.0104) and overall survival (p=0.00159). 450K methylation subtyping additionally identified a number of subgroups in histone wild-type cases. These included infrequent (4/86, 4.6%) cases with IDH1 mutation in older children, further categorised into astrocytic ATRX-mutant (n=3) or 1p19q co-deleted with TERT promoter mutation (n=1). 9/74, (12%) of cases were classified as biologically resembling pleomorphic xanthoastrocytoma (PXA) by methylation profiling, with 5/9 harbouring BRAF V600E mutations and epithelioid histology, and 3/9 NF1 mutation and giant cell features. Three cases had methylation profiles more closely resembling low grade gliomas, though were morphologically high grade, and harboured MAPK dysregulation in two cases, with the third part of an additional infant (<3yrs) cohort. Finally, four cases had a mutational burden several orders of magnitude higher than the rest, with (2197-5332) somatic coding variants/sample reflecting a hypermutator phenotype. These data provide an important insight into the wide biological diversity of ‘HGG’ found in the paediatric age group and allow for a profound refinement of clinical trial interpretation.

Study EGAS00001002328

The G2 gene expression signature and MYC overexpression are independent poor prognostic factors in childhood high-grade osteosarcoma

Purpose In high-grade osteosarcoma, prognostic factors at diagnosis are insufficient for stratifying patients into relevant subgroups. Recently, a transcriptomic study developed the G1/G2 gene expression signature, in which the G2 signature was associated with unfavorable survival. An orthogonal study identified MYC amplification as an unfavorable prognostic factor using targeted next-generation sequencing. The purpose of this study was to validate the independent prognostic value and to investigate the combined prognostic value of the G1/G2 signature with, MYC amplification and/or MYC expression for survival prediction. Material and methods This study included pediatric and adolescent patients with high-grade osteosarcoma. RNA sequencing was performed in 48 patients. Whole-exome sequencing was performed in 40 patients. Gene expression signature scores, MYC amplification (defined as > 7 copies) and MYC expression levels were calculated. Multivariable Cox proportional hazards analysis was performed for event-free survival (EFS) (primary endpoint) and overall survival (OS) (secondary endpoint). Results In the full cohort, the 3-year event-free survival rate was 37%. In multivariable Cox regression analysis with metastatic disease stage (n=21, 44%) as covariate, the G2 signature and MYC expression were independently associated with worse outcomes in terms of EFS (Hazard ratio (HR) 3.32, 95% confidence interval (CI) 1.34-8.21 and HR 3.38, 95%-CI 1.71-6.66, respectively) and OS (HR 4.07, 95%-CI 1.19-13.9 and HR 2.88, 95%-CI 1.22-6.76, respectively). MYC amplification was not associated with EFS or OS in univariable analysis (HR 1.88, 95% -CI 0.74-4.77 and HR 0.79, 95%-CI 0.21-3.05, respectively). Conclusion The G2 gene expression signature and MYC expression were independently associated with unfavorable outcomes in a pediatric cohort of patients with high-grade osteosarcoma. The combined prognostic value warrants further prospective validation and could potentially serve as a stratification marker for future osteosarcoma treatment protocols.

Study EGAS00001008073

cell-Free DNA Genomic Profiling and its Clinical Implementation in Advanced Prostate Cancer

Sixty-eight patients with advanced prostate cancer in castration-resistant or castration-sensitive settings undergoing treatment at the University Hospital Basel or the St. Claraspital Basel (Switzerland) were selected for targeted parallel sequencing analysis on liquid biopsy (plasma cfDNA) and matched formalin-fixed, paraffin-embedded (FFPE) tumor tissue samples.

Study EGAS50000000234

BAM file s of WGS data of Progressive supranuclear palsy patients

BAM files of healthy controls (3) and Progressive supranuclear palsy (PSP) patients (4). Genomic DNA from donors was fragmented, end-polished, A-tailed, and ligated with Illumina adapters, followed by size selection. Libraries were PCR-amplified (unless PCR-free), purified with AMPure XP, assessed on the Agilent Fragment Analyzer, and quantified using Qubit and qPCR. Qualified libraries were pooled and sequenced on Illumina platforms, and low-quality reads or adapter-contaminated reads were removed. Clean data were then mapped to the hg38 reference genome using BWA.

Dataset EGAD50000001758

cfMeDIP data for 72 VPC samples for validation

We analyzed the cell free DNA methylomes using 72 plasma samples from patients with mCRPC prostate cancer in the VPC project for validation. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology. Files from multiple lanes exists per sample.

Dataset EGAD00001008737

cfMeDIP data for 67 VPC samples

We analyzed the cell free DNA methylomes using 67 plasma samples from patients with mCRPC prostate cancer in the VPC project. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology.

Dataset EGAD00001008711

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