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• Amplicon based re-sequencing of multi-region PDAC samples

  Multi-region tumor samples were cut from frozen sections or FFPEs and reviewed from microdissection and H&E staining in order to select ones with high cellularity. DNA extraction was done using DNeasy Blood & Tissue Kits for frozen samples following the manufacturer’s guideline. Extracted DNAs were processed on an Illumina HiSeq 2500 in a paired end mode (100x100) using a custom targeted panel based on the list of all unique somatic mutations from the original WES data by the Integrated Genomics Operation (IGO) at Memorial Sloan Kettering Cancer Center (New York, NY).

  Dataset EGAD50000000354

• Accurate sample assignment in a multiplexed, ultra-sensitive, high-throughput sequencing assay for minimal residual disease

  High throughput sequencing (HTS) (next generation sequencing) of the rearranged immunoglobulin and T-cell receptor genes promises to be cheaper and more sensitive than current methods for monitoring minimal residual disease (MRD) in patients with acute lymphoblastic leukemia. However, adoption of new approaches by clinical laboratories requires careful evaluation of all potential sources of error and the development of strategies to ensure the highest accuracy. Timely and efficient clinical use of HTS platforms will depend on combining multiple samples (multiplexing) in each sequencing run. Here we examine immunoglobulin heavy chain gene HTS on the Illumina MiSeq platform for MRD (HTS-MRD). We identify errors associated with multiplexing that could potentially impact on the accuracy of MRD analysis. We optimise a strategy combining high purity, sequence-optimised oligonucleotides, dual-indexing and an error-aware demultiplexing approach to minimise errors and maximise sensitivity. We present a probability-based demultiplexing pipeline, Error-Aware Demultiplexer (EAD) - that is suitable for all MiSeq sequencing strategies and accurately assigns samples to the correct identifier without excessive loss of data. Finally using controls quantified by digital PCR, we show that HTS-MRD can accurately detect as few as 1 in 106 copies of specific leukemic MRD.

  Study EGAS00001001303

• Sequencing_probands_and_families_with_severe_insulin_resistance_syndromes

  This is an ongoing project and continuation to all the sequencing we have been doing over the last few years. We have some additional families and probands with syndromes of insulin resistance not previously sequenced within uk10k or other core funded projects. We would like to complete the sequencing in all of the good quality families and probands we have, this would require another ~50 samples to be WES sequenced. This cohort has already proven to be a rich source of interesting findings with papers in Science and Nature genetics.

  Study EGAS00001000488

• Digital tEchnology For Lung Cancer Treatment

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

  Study EGAS00001007219

• Comprehensive molecular profiling for breast cancer patients and high-risk individuals.

  Although germ-line mutations in BRCA1 and BRCA2 gene are responsible for familial breast and ovarian cancer, the detailed mechanism of tumorigenesis is yet unknown. Here, we performed next-generation sequencing to determine the genomic profiles of familial breast cancer tumorigenesis. Target-capture sequencing of fresh-frozen or formalin-fixed-paraffin-embedded (FFPE) samples of breast cancer or normal breast tissue were performed.

  Study JGAS000368

• using-ega-account

  Using your EGA account The purpose of this page is to help you access and download the data you have been granted permission to view through your EGA account. To obtain an EGA account please register here. Once your account is created, you can find details on how to manage your EGA account here. EGA access policy (New account holders please read) Access to EGA services are only provided to EGA account holders. EGA accounts are created, updated and closed upon direct instruction from the relevant DAC contact, using the EGA account management tools or through EGA Helpdesk. As part of the EGA account creation process, the EGA account holder must reset their password when instructed. Password resets are checked and verified usually within 24 business hours, during which time the EGA account is inaccessible. EGA accounts are assigned on an individual basis for the exclusive use of the registered EGA account holder; log-in details must remain private and only be used by the EGA account holder. Controlled access data files are only provided, in accordance to the permissions set by the DAC, to EGA account holders. EGA controlled access data files are encrypted prior to download and must be decrypted on the EGA account holders side. EGA account holders are provided access to the EGA download streamer to download access approved datasets and files therein. The EGA download streamer represents the primary means for the EGA account holder to download access approved datasets and files therein. EGA account holders may be provided with an EGA download account for accessing approved datasets and files therein, using FTP or Aspera in response to clearly defined technical reasons, which may restrict the use of the EGA download streamer. It is the sole responsibility of the EGA account holder to ensure full compliance to all terms and conditions of the Data Access Agreement are met once data is downloaded from the EGA. Should you move institute you must contact all Data Access Committee's contacts to update your details and, if necessary, re-apply for data access. The Data Access Agreement (DAA) is a contract made between the DAC and the EGA account holder; the EGA is not responsible for enforcing the DAA. EGA reserves the right to place EGA accounts 'onhold', pending DAC approval to re-activate, should EGA account 'misuse' be suspected. Further information Introduction to the EGA Frequently Asked Questions Subscribe to the EGA mailing list

  Documentation using-ega-account

• Using your EGA account

  Using your EGA account The purpose of this page is to help you access and download the data you have been granted permission to view through your EGA account. To obtain an EGA account please register here. Once your account is created, you can find details on how to manage your EGA account here. EGA access policy (New account holders please read) Access to EGA services are only provided to EGA account holders. EGA accounts are created, updated and closed upon direct instruction from the relevant DAC contact, using the EGA account management tools or through EGA Helpdesk. As part of the EGA account creation process, the EGA account holder must reset their password when instructed. Password resets are checked and verified usually within 24 business hours, during which time the EGA account is inaccessible. EGA accounts are assigned on an individual basis for the exclusive use of the registered EGA account holder; log-in details must remain private and only be used by the EGA account holder. Controlled access data files are only provided, in accordance to the permissions set by the DAC, to EGA account holders. EGA controlled access data files are encrypted prior to download and must be decrypted on the EGA account holders side. EGA account holders are provided access to the EGA download streamer to download access approved datasets and files therein. The EGA download streamer represents the primary means for the EGA account holder to download access approved datasets and files therein. EGA account holders may be provided with an EGA download account for accessing approved datasets and files therein, using FTP or Aspera in response to clearly defined technical reasons, which may restrict the use of the EGA download streamer. It is the sole responsibility of the EGA account holder to ensure full compliance to all terms and conditions of the Data Access Agreement are met once data is downloaded from the EGA. Should you move institute you must contact all Data Access Committee's contacts to update your details and, if necessary, re-apply for data access. The Data Access Agreement (DAA) is a contract made between the DAC and the EGA account holder; the EGA is not responsible for enforcing the DAA. EGA reserves the right to place EGA accounts 'onhold', pending DAC approval to re-activate, should EGA account 'misuse' be suspected. Further information Introduction to the EGA Frequently Asked Questions Subscribe to the EGA mailing list

  Documentation download/using_ega_account

• Neurodevelopmental Genomics: Trajectories of Complex Phenotypes

  This study is a collaboration between the Center for Applied Genomics (CAG) at Children's Hospital of Philadelphia (CHOP) and the Brain Behavior Laboratory at the University of Pennsylvania (Penn). The cohort consists of youths aged 8-21 years who consulted the CHOP network and volunteered to participate in genomic studies of complex pediatric disorders. All participants underwent clinical assessment, including a neuropsychiatric structured interview and review of electronic medical records. They were also administered a neuroscience based computerized neurocognitive battery (CNB) and a subsample underwent neuroimaging. These are described separately below. Clinical Testing: GOASSESS, a computerized, structured screener developed from a modified version of the Kiddie-Schedule for Affective Disorders and Schizophrenia (K-SADS, Kaufman et al. 1997, PMID: 9204677). Components of the interview include a timeline of life events, demographics and medical history, Global Assessment of Functioning, and Interviewer Observations. A psychopathology symptom and criterion-related assessment of mood disorders (depression, mania/hypomania), anxiety disorders (overanxious/generalized-, separation-, social-anxiety, specific phobia, panic disorder, agoraphobia, obsessive compulsive disorder, post-traumatic stress disorder), behavioral disorders (attention deficit hyperactivity disorder, oppositional defiant disorder, conduct disorder), psychosis spectrum (psychosis and prodromal symptoms), eating disorders, suicidal thinking and behavior, and treatment history. This is also based on K-SADS. An abbreviated Family Interview for Genetics Studies (FIGS) to assess major domains of psychopathology in the proband's first-degree relatives. Computerized Neurocognitive Battery: The CNB, developed for large-scale studies, yields measures of accuracy and speed for domains of executive-control functions (abstraction, attention, working memory), episodic memory (verbal, facial, spatial), complex cognitive processing (language reasoning, nonverbal reasoning, spatial processing), social cognition (emotion identification, emotion intensity differentiation, age differentiation) and sensorimotor and motor speed. The following neurobehavioral domains were assessed: Penn Conditional Exclusion Test is a measure of abstraction and concept formation. Participants decide which of 4 objects does not belong with the other 3, based on one of three sorting principles, which change. Feedback is used. Attention: The Penn Continuous Performance Test. Participants respond to a set of 7-segment displays whenever they form a digit or letter. Working Memory: The Letter N-back Test displays sequences of uppercase letters with a stimulus duration of 500 ms (ISI 2,500 ms.) In the 0-back condition, participants respond to a single target (i.e., X). In the 1-back condition they respond if the letter is identical to that preceding it. In the 2-back condition, they respond if the letter is identical to that presented two trials back. Verbal Memory: The Penn Word Memory Test presents 20 target words that are then mixed with 20 distracters equated for frequency, length, concreteness and low imageability. A 20 min delayed recall procedure is also administered. Face Memory: The Penn Face Memory Test presents 20 digitized faces that are then mixed with 20 distracters equated for age, gender and ethnicity. The procedure is repeated at 20 min delay. Spatial Memory: The Visual Object Learning Test uses Euclidean shapes as stimuli with the same paradigm as the word and face. Language and Analogical Reasoning: The Penn Verbal Reasoning consists of verbal analogy problems. Spatial Processing: Penn Line Orientation Test presents two lines at an angle, and participants click on a button that makes one line rotate until it has the same angle as the other. Emotion Processing: Facial displays of 4 emotions (Happy, Sad, Anger, Fear) and Neutral faces, 8 each, are presented and the subject identifies the emotion in a multiple-choice format. The facial stimuli are balanced for gender, age, and ethnicity. Sensory-motor Processing Speed: The task requires moving the mouse and clicking on a green square that disappears after the click. The square gets increasingly small and appears in unpredictable locations. Neuroimaging Protocol: Studies were performed at Penn using a Siemens Trio (Erlangen, Germany) 3T scanner equipped with 40mT/m gradients and 200 mT/m/s slew-rates. RF transmission utilized a quadrature body-coil, and reception a 12-channel head coil optimized for parallel imaging. Total image acquisition time was about 45 min. Structural Imaging: The T1-weighted protocol utilized a 3D, inversion-recovery, and magnetization-prepared rapid acquisition gradient echo. Relevant imaging procedures include: Structural magnetic imaging Diffusion tensor imaging ASL perfusion BOLD fMRI Neuroimaging tasks: Fractal N-Back Task of Spatial Working Memory Face Emotion Identification Task Neuroimages: The current data release includes over 9700 MRI images that may be downloaded through Authorized Access.

  Study phs000607

• BIRC5 Upregulation Enhances DNMT3A-Mutant T-ALL Cell Survival and Pathogenesis

  The goal of this study was to determine how patients with T-ALL who have DNA methyltransferase 3 alpha (DNMT3A) mutations develop resistance to therapy. Since DNMT3A is a methyltransferase, we examined the effect of those mutations on epigenetic regulation using whole genome bisulfite sequencing (WGBS). We also assessed any changes in gene expression using RNA-sequencing. We found that T-ALL patients with DNMT3A mutations are resistant to apoptosis and some chemotherapies. WGBS showed that DNMT3A mutated patients clustered together by their epigenetic profile, which was associated with hypomethylation at TERT and HOX genes. RNA sequencing identified differences in JAK/STAT signaling.

  Study phs003623

• Genetic and Environmental Risk Factors for Hemorrhagic Stroke (GERFHS)

  GERFHS is a population-based, case-control study of hemorrhagic stroke in the Greater Cincinnati/Northern Kentucky region. Cases are recruited from within 50 miles of the University of Cincinnati and population-based controls are matched to cases by age (+/- 5 years), race and gender from the same population as cases. All study participants are of self-reported non-Hispanic Caucasian ethnicity and the data show consistency with the principal component projections. The current submission includes genome wide genotyping on a subset of these cases and controls.

  Study phs000874

• The mutational landscape of normal human endometrial epithelium

  All normal somatic cells are thought to acquire mutations. However, characterisation of the patterns and consequences of somatic mutation in normal tissues is limited. Uterine endometrium is a dynamic tissue undergoing cyclical shedding and reconstitution lined by a gland-forming epithelium. Whole genome sequencing of normal endometrial glands showed that most are clonal cell populations derived from a recent common ancestor, with mutation burdens differing from other normal cell types and many fold lower than endometrial cancers. Mutational signatures found ubiquitously account for most mutations. Many, in some women all, endometrial glands are colonised by cell clones carrying driver mutations in cancer genes, often with multiple drivers. Total and driver mutation burdens increase with age, but are also influenced by other factors, including body mass index and parity, and clones with drivers often originate during early decades of life. The somatic mutational landscapes of normal cells differ between cell types and are revealing the procession of neoplastic change leading to cancer.

  Dataset EGAD00001004547

• Integrative analysis of small cell lung cancer

  Small-cell lung cancer (SCLC) is an aggressive lung tumor subtype. We conducted integrated analysis of genome sequencing, transcriptome, and copy number analysis and found an extremely high mutation rate of 7.4±1 protein-changing mutations per million basepairs. Evidence for inactivation of TP53 and RB1 was found in all sequenced cases. Furthermore, we identified recurrent mutations in CREBBP, EP300, and MLL, observed mutations in PTEN, in SLIT2, and EPHA7, as well as focal amplifications of the FGFR1 locus. As a major feature of SCLC we found mutation in histone modifying genes, observed genome alterations that are therapeutically tractable, and provide a framework for identifying biologically relevant genes in the context of a high mutation rate. Peifer et al., 2012, Nature Genetics.

  Study EGAS00001000299

• EGAD00010000624

  A new beta-globin mutation responsible of a beta-thalassemia (HbVar database ID 2928) was observed in 8 unrelated French families. The mutation carriers originated from Nord-Pas-de-Calais, a Northern French region where the chief town is Lille. 5 unrelated mutation carriers were genotyped for a set of 12 microsatellites from chromosome 11, around the beta-globin gene. Among the 5 mutation carriers, 4 were genotyped for 97 European Ancestry Informative SNPs (EAIMs).

  Dataset EGAD00010000624

• EGAD00010000626

  A new beta-globin mutation responsible of a beta-thalassemia (HbVar database ID 2928) was observed in 8 unrelated French families. The mutation carriers originated from Nord-Pas-de-Calais, a Northern French region where the chief town is Lille. 5 unrelated mutation carriers were genotyped for a set of 12 microsatellites from chromosome 11, around the beta-globin gene. Among the 5 mutation carriers, 4 were genotyped for 97 European Ancestry Informative SNPs (EAIMs).

  Dataset EGAD00010000626

• Gene expression by RNAseq in bronchial biopsies of asthmatics, asthma in remission and healthy subjects

  The study focus was differential expression in bronchial biopsies between persistent asthma, asthma in remission and healthy controls using RNAseq. There were 184 samples that passed QC. RNA samples were processed using the TruSeq Stranded Total RNA Sample Preparation Kit (Illumina, San Diego, CA), using an automated procedure in a Caliper Sciclone NGS Workstation (PerkinElmer, Waltham, MA). In this procedure, all cytoplasmic and mitochondria rRNA was removed (RiboZero Gold kit). The obtained cDNA fragment libraries were loaded in pools of multiple samples unto an Illumina HiSeq2500 sequencer using default parameters for paired-end sequencing (2 × 100 bp). Data are available as 221 pairs of FASTQ-files. Note that several samples are associated with multiple sequence runs.

  Dataset EGAD00001005112

• Transgenerational Transmission of Post-Zygotic Mutations Suggests Symmetric Contribution of First Two Blastomeres to Human Germline

  Skin and blood samples were collected from four phenotypically normal individuals (mother, father, and children) from a randomly selected family. Whole genomes of the samples from these individuals were sequenced to a depth of 30X-200X. Sequencing data for the mother was previously analyzed and is available at NDA collection #2961. Sequenced reads from the children and father were aligned to the human reference genome (hg19) generating BAM files for each individual. We used post-zygotic mutations in the mother to trace cell lineages across human generations. Analysis of this family demonstrated that different cell lineages were transmitted to offspring. Coupled with analysis of publicly available data, this result revealed a fundamental difference between soma and germline in lineage allocation and suggested a 50:50 contribution of the first two blastomeres to the germline.

  Study phs003781

• Cambridge Neoadjuvant Cancer of the Prostate (CANCAP03): A Window Study into the Effects of Olaparib ± Degarelix in Primary Prostate Cancer.

  Study: Cambridge Neoadjuvant Cancer of the Prostate (CANCAP03): A Window Study into the Effects of Olaparib ± Degarelix in Primary Prostate Cancer. EudraCT Number: 2014-004417-86 Clinicaltrials.gov Number: NCT02324998 Purpose: Investigate combined PARP and androgen inhibition in primary prostate cancer. Aim: To understand the biological mechanism(s) underlying clinical efficacy, especially in the absence of mutations in homologous recombination (HR) repair pathways. Dataset: Single-nuclear RNA sequencing data from post-treatment radical prostatectomy tissue cores for six patients, 3 from each of olaparib and olaparib and degarelix cohorts. Samples were processed for nuclear isolation and extraction, prior to single-nuclear RNA sequencing. 10x libraries were constructed using the 10x supplied protocol, briefly: individual nuclei were trapped into droplets with a single bead, and poly A transcripts were barcoded during reverse transcription. Complementary DNA was amplified, and libraries were prepared for sequencing on NovaSeq 6000 using S4 flow cell (100k reads per cell). FASTQ files were processed using CellRanger pipeline (10X Genomics). Outputs from the CellRanger pipeline were analysed using the Seurat package (v4.9.9.9049) in R (v4.2.0). Processed data is provided as a Seurat object.

  Study EGAS50000000880

• Metadata Public API

  Metadata Rest Endpoints Common Aspects Functionality Identifiers Requests and Responses Request Response Querying Querying by Object Cross-Querying by Object Common Aspects Functionality The Metadata REST API allows EGA users to request metadata from the EGA. Using this api you will be able to obtain the publicly available information from EGA study, sample, experiment, run, analysis, policy, dac and dataset. The API also allows for objects to be cross-referenced in order to obtain for example all the datasets linked to a dac. Identifiers EGA objects can be identified by their unique accession. These are ID's displayed everywhere, shared among all EGA locations and specific for each data type (More information on the list below) EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID Server Request and Response Request All the endpoints implement these two HTTP methods, GET and HEAD. Moreover, there is an authentication layer that allows to disclose the private information about each object if the user runs the endpoint with their token and has permissions to the related dataset. HTTP Method Description GET Returns the objects and their public information (including private information if the user has permissions) HEAD Returns the count of objects to be returned Response API responses are diverse but they always return a status call. Below you have a summary on what these codes mean and some tips that can help you troubleshooting them: HTTP Status Code Description Resolution 200 OK No error handling necessary 206 Partial Content Expected status code when paginating the results. No error handling necessary 400 BAD REQUEST Request incorrectly formulated 401 UNAUTHORISED/FORBIDDEN You do not have permissions over the object you are trying to access. / The authorised user is not permitted to make the given request. 404 NOT FOUND The object/resource you are trying to access does not exist. 500 INTERNAL SERVER ERROR This is a server-side error, try later. If the issue persists, contact the Heldpesk. Querying Querying by Object In the below documentation, worked examples can be found on how to use the API, to query about each unique EGA object. https://metadata.ega-archive.org/analyses/{id} https://metadata.ega-archive.org/dacs/{id} https://metadata.ega-archive.org/datasets/{id} https://metadata.ega-archive.org/runs/{id} https://metadata.ega-archive.org/samples/{id} https://metadata.ega-archive.org/studies/{id} Worked example for the EGA data access committee(DAC) EGAC00001000514 https://metadata.ega-archive.org/dacs/EGAC00001000514 Points to notice Please, be advised that all EGA objects can be queried by using the same endpoint. For example: https://metadata.ega-archive.org/datasets Returns all the datasets registered at the EGA. https://metadata.ega-archive.org/datasets?limit=5&offset=15 Returns 5 results skipping the initial 15 results. Cross-Querying by Object The EGA REST API Metadata also allows for the crossquerying of public metadata. For example, should I want to query the datasets included in the ICGC DAC: https://metadata.ega-archive.org/dacs/EGAC00001000010/datasets Below, you can find worked examples on how to perform the call to the API. https://metadata.ega-archive.org/datasets/EGAD00001000645/analyses https://metadata.ega-archive.org/datasetsEGAD00001000645/files https://metadata.ega-archive.org/datasets/EGAD00001000620/runs https://metadata.ega-archive.org/datasets/EGAD00001000620/samples https://metadata.ega-archive.org/samples/EGAN00001092114/datasets https://metadata.ega-archive.org/files/EGAF00000056146/dacs https://metadata.ega-archive.org/files/EGAF00000056146/datasets https://metadata.ega-archive.org/files/EGAF00000056146/studies There are more endpoints included in this category. Please, find all the possibilities (green tick) in the table below. Table The table displays in a ordered fashion the objects that can be crossreferenced using the metadata API. BY Analysis Dac Dataset Experiment Policy Run Sample Study File Analysis ✔ ✔ Dac ✔ ✔ Dataset ✔ ✔ ✔ ✔ Experiment ✔ ✔ ✔ ✔ Policy ✔ Run ✔ ✔ ✔ Sample ✔ ✔* ✔ Study ✔ ✔ ✔ ✔ ✔ ✔* File ✔ *: These cross queries do not include data from Array-File submissions. Check out the SPEC

  Documentation discovery/metadata/public-metadata-api

• Center for Common Disease Genomics [CCDG] - Cardiovascular ATVB: Atherosclerosis Thrombosis and Vascular Biology

  Italian Atherosclerosis Thrombosis and Vascular Biology study is a prospective, nationwide, case-control study involving 125 coronary care units in Italy. The cases were patients who were hospitalised for a first MI before the age of 45 years and underwent coronary angiography. Acute MI was defined as resting chest pain lasting more than 30 minutes, accompanied by persistent electrocardiographic changes, and confirmed by an increase in total creatine kinase or in the MB fraction to more than twice the upper normal limits. The controls were healthy subjects without a history of thromboembolic disease who were unrelated to the patients, but individually matched with them by age, gender and geographical origin. They were enrolled from among the blood donors or staff of the same participating hospitals. Recruitment of cases and controls took place between 1994 and 2007. This site hosts data from ~60 whole exomes.

  Study phs001592

• 463 newly diagnosed patients with Multiple Myeloma underwent whole exome sequencing of tumour and peripheral blood DNA.

  463 newly diagnosed patients from the UK Myeloma XI clinical trial (NCT01554852) underwent whole exome sequencing plus targeted capture of the IGH/K/L and MYC loci. 200 ng of DNA were processed using NEBNext DNA library prepartion kit and hybridised to the SureSelect Human All Exon V5 Plus. Four samples were pooled and run on one lane of a HiSeq 2000 using 76-bp paired end reads. DNA from CD138+ selected bone marrow cells (myeloma tumour) as well as peripheral white blood cells were analysed and somatic mutations detected.

  Study EGAS00001001147

• WES of tumor samples from patients with renal medullary carcinoma (RMC)

  The dataset, in .bam file format, consists of whole exome sequencing (WES) data of tumors from patients (n=24) with Renal Medullary Carcinoma (RMC), generated using Illumina NovaSeq 6000 sequencing technology. DNA was extracted from FFPE solid tumor samples using the AllPrep DNA FFPE Kit (Qiagen, CA). Libraries from FFPE tissue were prepared with the SureSelect XT HS2 DNA Kit (Agilent, CA) for exome capture. The All Exon V7 exome probe set (Agilent, CA) was used for hybridization and capture of DNA.

  Dataset EGAD50000001822

• 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

• RNA sequencing of BCP-LBL and EM B-ALL patients samples

  In order to perform comprehensive transcriptomics and gene fusion analyses of a cohort of BCP-LBL and extramedullary (EM) manifestations of B-ALL patients, we performed RNA sequencing of 16 tissue samples from BCP-LBL and EM B-ALL patients. Because the material was available as FFPE, and had a relative low quality, we used a capture-based approach, where NGS libraries obtained from total RNA were captured in 4-plex, using a whole exome capture panel.

  Dataset EGAD50000002047

• 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

• Molecular subtypes of pancreatic neuroendocrine tumors mutated in MEN1/DAXX/ ATRX explain biological variability

  Pancreatic Neuroendocrine Tumors (PanNETs) most probably arise from the islets of Langerhans, although direct evidence is still lacking. About 40% of non-functioning (NF) PanNETs harbour mutations in MEN1, often in conjunction with alterations in DAXX/ATRX. Despite the homogeneous genetic background, the ADM (mutation in DAXX/ATRX and MEN1) group is heterogeneous regarding molecular features and response to treatment. To explore the molecular and clinical heterogeneity within this group, we integrated transcriptomic and DNA methylation data from 36 and 93 samples, respectively. Using a multi-omic approach we described a two-level hierarchy separating PanNET subtypes mutated in MEN1, DAXX and ATRX. First, DNA methylation discriminates ADM-PanNET from PanNET mutated in MEN1 only (α-like). Compared to α-like, all ADM tumors exhibit DNA methylation changes at enhancer and lowly methylated regions as well as at peri-centromeric and telomeric regions, associated with alternative lengthening of telomeres, increased chromosomal instability, and enhanced proliferative capacity. At a second level, transcriptomic analysis revealed three distinct ADM subtypes: ADM hypoxic, ADM NST (No Special Type), and ADM immunosuppressive. The ADM hypoxic subtype is characterized by strong hypoxia signature, likely regulated epigenetically. The ADM NST subtype appears to be primarily driven by epigenetic changes that promote proliferation. The ADM immunosuppressive is highly enriched in immune component and strong metastasis-like signature. While all the three subtypes are highly associated with liver metastasis formation and invasion, the ADM immunosuppressive are significantly smaller (<2.5 cm p.value=0.023) despite displaying aggressive molecular features. By defining these three novel ADM subtypes, our study provides a refined framework for understanding PanNET heterogeneity. This classification underscores potential diagnostic markers and highlights distinct biological vulnerabilities that may inform the development of subtype-tailored therapeutic strategies.

  Study EGAS00001008272