Search Results - EGA European Genome-Phenome Archive

Resolving the immune landscape of human prostate at a single cell level in health and cancer

The prostate gland produces prostatic fluid, high in zinc and citrate and essential for the maintenance of spermatozoa. Prostate cancer is a common condition with limited treatment efficacy in castration-resistant metastatic disease, including with immune checkpoint inhibitors. We used single-cell RNA-sequencing to perform an unbiased assessment of the cellular landscape of human prostate and identified a previously unappreciated subset of tumour-enriched androgen receptor-negative luminal epithelial cells, with increased expression of cancer-associated genes. We also found a variety of innate and adaptive immune cells in normal prostate that were transcriptionally perturbed in prostate cancer. An exception was a unique, prostate-specific, zinc transporter-expressing macrophage population (MAC-MT), that contributed to tissue zinc accumulation in homeostasis, but showed enhanced inflammatory gene expression in tumours, including T cell-recruiting chemokines. Remarkably, enrichment of the MAC-MT signature in cancer biopsies was associated with improved disease-free survival, suggesting beneficial anti-tumour functions.

Study EGAS00001005787

GENOMIC MUTATION LANDSCAPE OF SKIN CANCERS FROM DNA REPAIR-DEFICIENT XERODERMA PIGMENTOSUM PATIENTS

Xeroderma pigmentosum (XP) is a genetic disorder caused by mutations in genes of the Nucleotide Excision Repair (NER) pathway (groups A-G) or in Translesion Synthesis (TLS) DNA polymerase η (group V). XP is associated with an increased skin cancer risk, reaching, for some groups, several thousand-fold compared to the general population. Here, we analyzed 38 skin cancer genomes from five XP groups. We found that the activity of NER determines heterogeneity of the mutation rates across skin cancer genomes and that transcription-coupled NER extends beyond the gene boundaries reducing the intergenic mutation rate. Mutational profile in XP-V tumors revealed the role of polymerase η in the error-free bypass of (i) rare TpG and TpA DNA lesions, (ii) 3’ nucleotides in pyrimidine dimers, and (iii) TpT photodimers. Our study unravels the genetic basis of skin cancer risk in XP and provides insights into the mechanisms reducing UV-induced mutagenesis in the general population.

Study EGAS00001006732

Rare SNPs in receptor tyrosine kinases are negative outcome predictors in multiple myeloma

Multiple myeloma (MM) is a plasma cell disorder that is characterized by a great genetic heterogeneity. Recent next generation sequencing studies revealed an accumulation of tumor-associated mutations in receptor tyrosine kinases (RTKs) which may also contribute to the activation of survival pathways in MM. To investigate the clinical role of RTK-mutations in MM, we deep-sequenced the coding DNA-sequence of EGFR, EPHA2, ERBB3, IGF1R, NTRK1 and NTRK2 which were previously found to be mutated in MM, in 75 uniformly treated MM patients of the "Deutsche Studiengruppe Multiples Myelom". Subsequently, we correlated the detected mutations with common cytogenetic alterations and clinical parameters. We identified 11 novel non-synonymous SNVs or rare patient-specific SNPs, not listed in the SNP databases 1000 genomes and dbSNP, in 10 primary MM cases. The mutations predominantly affected the tyrosine-kinase and ligand-binding domains and no correlation with cytogenetic parameters was found. Interestingly, however, patients with RTK-mutations, specifically those with rare patient-specific SNPs, showed a significant lower overall, event-free and progression-free survival. This indicates that RTK SNVs and rare patient-specific RTK SNPs are of prognostic relevance and suggests that MM patients with RTK-mutations could potentially profit from treatment with RTK-inhibitors.

Study EGAS00001001665

Androgen receptor blockade promotes response to BRAF/MEK-targeted therapy

We studied a group of melanoma patients treated with neoadjuvant BRAF/MEK-targeted therapy (NCT02231775, n=51), and observed significantly higher rates of major pathologic response (MPR= <10% viable tumor at resection) and improved recurrence-free survival (RFS) in females versus males (MPR-66% versus 14%, p=0.001; RFS-64% versus 32% at 2 years, p=0.021). Findings were validated in a several additional cohorts 2-4 patients with unresectable metastatic melanoma treated with BRAF and/or MEK-targeted therapy (n=664 patients in total), demonstrating improved progression-free survival (PFS) and overall survival (OS) in females versus males in several of these studies. Studies in pre-clinical models demonstrated significantly impaired anti-tumor activity in male versus female BRAF/MEK-treated mice (p=0.006), with significantly higher expression of androgen receptor (AR) in tumors of male and female BRAF/MEK-treated mice versus control (p=0.0006 and 0.0025). Pharmacologic inhibition of AR signaling improved responses to BRAF/MEK-targeted therapy in male and female mice (p=0.018 and p=0.003), whereas induction of AR signaling (via testosterone administration) was associated with significantly impaired response to BRAF/MEK-targeted therapy in males and females (p=0.021 and p<0.0001).

Study EGAS00001006196

FEGA Sweden Helpdesk

FEGA Sweden is an archive for storing and sharing all kinds of data resulting from biomedical research projects. As a national node of the Federated European Genome-phenome Archive (FEGA), we enable researchers to store their data in Sweden in a way that meets the requirements of the General Data Protection Regulation (GDPR). Any data submitted to the archive is subject to controlled access, meaning access to the data only will be granted after a formal application procedure. Using FEGA Sweden for storing and sharing data is free of charge for academic users affiliated with a Swedish university. However, the university must have a signed Data Processing Agreement (DPA) with Uppsala University. The current list of universities with a signed DPA can be found here: https://fega.nbis.se/submission/complying-with-gdpr.html. FEGA Sweden is hosted by the National Bioinformatics Infrastructure Sweden (NBIS), which legally is part of Uppsala University. NBIS forms the bioinformatics platform at SciLifeLab and constitutes the Swedish node of the European organisation ELIXIR. Contact the FEGA Sweden Helpdesk at fega-sweden@nbis.se for further questions.

Dac EGAC50000000077

FASTQ files of total RNA-Seq data from the POPS SGA (Small for Gestational Age) samples

All the samples were obtained from the Pregnancy Outcome Prediction–a prospective cohort study of nulliparous women attending the Rosie Hospital, Cambridge (UK) for their dating ultrasound scan between January 14, 2008, and July 31, 2012. Ethical approval for the study was given by the Cambridgeshire 2 Research Ethics Committee (reference number 07/H0308/163) and all participants provided written informed consent. Cases of preeclampsia (PET) were defined on the basis of the 2013 ACOG criteria and cases of small for gestational age (SGA)infants were confined to severe SGA, i.e. a customized birth weight <5th percentile. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

Dataset EGAD00001003507

Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) monitoring shows promise for risk stratification and decision-making in cancer patients. However, factors like background noise from non-tumor DNA, clonal haematopoiesis, and non-shedding tumors may complicate manual interpretation and limit its clinical application. In this proof-of-concept study in advanced non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), we developed an algorithm that automatically classifies serial cell-free DNA (cfDNA) samples, thereby enabling reliable and reproducible interpretation, and preventing time-consuming manual interpretation in approximately 75% of patients. Importantly, application of the algorithm allowed early risk stratification and decision-making, specifically identifying approximately 35% of patients with short-term clinical benefit and approximately 25% of patients who may potentially benefit from treatment escalation. Simultaneous serum tumor marker (STM) monitoring further improved risk stratification and decision-making in our study, enabling accurate identification of all patients with a clinical benefit of at least one year.

Study EGAS50000001554

Germline whole genome sequencing of patients with Li-Fraumeni syndrome

Five hundred ng to 1 ug of genomic DNA was submitted to The Centre for Applied Genomics (TCAG) at The Hospital for Sick Children for genomic library preparation and whole genome sequencing. DNA samples were quantified using the Qubit High Sensitivity Assay and purity was assessed using the Nanodrop OD 260/280 ratio. Approximately 500-700 ng of DNA was used as input material for library preparation using the Illumina TruSeq PCR-free DNA Library Prep Kit following the manufacturer’s recommended protocol. In brief, DNA was fragmented to 400 bp on average using sonication on a Covaris LE220 instrument. Fragmented DNA was end-repaired, A-tailed and indexed TruSeq Illumina adapters with overhang-T were added to the DNA. Libraries were then validated on a Bioanalyzer DNA High Sensitivity chip to check for size and absence of primer dimers and quantified by qPCR using Kapa Library Quantification Illumina/ABI Prism Kit protocol (KAPA Biosystems). Validated libraries were pooled in equimolar quantities and paired-end sequenced on an Illumina HiSeq X platform following Illumina’s recommended protocol to generate paired-end reads of 150-bases in length and an average depth of 40X. FASTQ files were aligned to the hg19 reference genome using BWA-mem v0.78. PCR duplicates were marked with Picard MarkDuplicates v1.1.08, and base recalibration and realignment was performed using GATK v2.8.1.

Study EGAS00001007061

CALGB/SWOG 80405 ct DNA Biomarker Evaluation

To investigate treatment-specific mutations that underlie resistance to treatment with chemotherapy +/- bevacizumab or cetuximab in first line metastatic Colorectal Cancer (mCRC) patients, we performed targeted sequencing of circulating free DNA (cfDNA) from longitudinal plasma samples. These samples were collected at baseline (PRE, n=354), during treatment (OTH, n=254), and/or at progression or end of the protocol treatment (EOT, n=345) from CALGB/SWOG 80405, a randomized phase III trial that evaluated the efficacy of chemotherapy plus bevacizumab or cetuximab treatment in first line colorectal cancer patients (NCT00265850).

Study phs002941

NIBIT-EPI-MESO study samples

Multi-omics analysis of pre-immuno checkpoint inhibitors (ICI) therapy lesions from 91 pleural mesothelioma (PM) patients enrolled in the multicenter NIBIT-EPI-MESO study. Neoplastic lesions were characterized using multiple molecular platforms, including RNA sequencing (n=82), Whole Exome Sequencing (WES) (n=87), Reduced Representation Bisulfite Sequencing (RRBS) (n=83) and cell-free methylated immunoprecipitation sequencing (cfMeDIP-seq) (n=18). Tumor samples were collected during the standard diagnostic pleuroscopy or thoracoscopy before ICI therapy. Matched Peripheral Blood Mononuclear Cells (PBMC) were collected from PM patients before ICI therapy.

Study EGAS50000001478

Whole exome sequencing of cell-free DNA reveals temporo-spatial heterogeneity and identifies treatment-resistant clones in neuroblastoma

Background: Neuroblastoma (NB) displays important clinical and genetic heterogeneity, with emergence of new mutations at tumor progression. Patients and Methods: To study clonal evolution during treatment and follow-up, an innovative method based on circulating cell-free DNA (cfDNA) analysis by whole exome sequencing (WES) paired with target sequencing was realized in sequential liquid biopsy samples of 19 NB patients. Results: WES of the primary tumor and cfDNA at diagnosis showed overlap of Single Nucleotide Variants (SNVs) and Copy Number Alterations (CNAs), with 41% and 93% of all detected alterations common to the primary NB and cfDNA. CfDNA WES at a second time point indicated a mean of 22 new SNVs for patients with progressive disease. Relapse-specific alterations included genes of the MAPK pathway and targeted the protein kinase A signaling pathway. Deep coverage target sequencing of intermediate timepoints during treatment and follow-up identified distinct subclones. For 17 seemingly relapse-specific SNVs detected by sequencing detected these alterations in minor subclones, with relapse-emerging SNVs targeting genes of neuritogenesis and cell cycle. Furthermore a persisting, resistant clone with concomitant disappearance of other clones was identified by a mutation in the ubiquitin protein ligase HERC2. Conclusion: Modelisation of mutated allele fractions in cfDNA indicated distinct patterns of clonal evolution, with either a minor, treatment-resistant clone expanding to a major clone at relapse, or minor clones collaborating towards tumor progression. Identification of treatment-resistant clones will enable development of more efficient treatment strategies.cfDNA WES at relapse but not tumor or cfDNA WES at diagnosis, deep coverage target.

Study EGAS00001002705

CDK4/6 inhibition in advanced chordoma: final results of the NCT PMO-1601

Background. Chordoma is a rare bone tumor with no approved systemic therapy. Inactivation of the tumor suppressor p16 (encoded by CDKN2A) leads to aberrant cyclin D-CDK4/6-RB pathway activity, which can be inhibited by palbociclib in chordoma cell lines. Patients and Methods. We conducted a phase II single-arm, open-labeled trial on palbociclib in adult patients with advanced chordomas with p16 loss (by immunohistochemistry) or CDKN2A loss (by genomic analysis) and CDK4/6 and RB1 presence (by immunohistochemistry or RNA-Sequencing). Patients received 125mg palbociclib once daily for 21 days in a 28-day cycle. The study used a Simon optimal 2-stage design. The primary endpoint was disease control rate after six cycles. Response was evaluated according to Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Secondary endpoints included progression-free survival, overall survival, and biomarker analysis. The study was considered positive if 25% of patients reached the primary endpoint. Results. Between December 2017 and April 2023, 28 patients (median age 60 years, range 31-84) were enrolled. After a median follow-up of 28 months, the disease control rate was 39%, with 11 out of 28 patients achieving stable disease. No objective responses were observed. The median progression-free survival was 5.6 months, and the median overall survival was 24.6 months. Treatment was well tolerated without new safety signals. CDKN2A deletions were the most common genomic alterations underlying p16 loss and were accompanied by MTAP co-deletion. There was no correlation between responder phenotypes by immunohistochemistry and outcome. RNA-based analysis showed heterogeneous pathways deregulation at study entry suggesting underlying primary resistance mechanisms Conclusion. This trial met its primary endpoint with a 39% disease control rate, though antitumor activity was modest. Molecularly tailored combination therapies should be considered to improve efficacy. (ClinicalTrials.gov number, NCT03110744).

Study EGAS00001007985

VESPA: Vanderbilt Electronic Systems for Pharmacogenomic Assessment

The Vanderbilt Electronic Systems for Pharmacogenomic Assessment (VESPA) Project is a large electronic medical record (EMR)- and biobank-based initiative for translational pharmacogenomics discoveries. Key research resources utilized in this effort include the BioVU DNA databank and associated Synthetic Derivative database of clinical information, and software tools developed to identify drugs and clinical events using EHR-derived structured and unstructured ("free text") data. Cohorts include subjects with primarily drug-response phenotypes, and most cases and controls identified include three data types: ICD-9 codes, medication regimens, and medical test results. Advanced informatics methods, such as natural language processing, were also used for some phenotypes. Algorithms used event-sequence analyses to establish temporal relationships between drugs and phenotypes. Both cases and control algorithms excluded records that contained specific comorbidities and were refined to achieve positive predictive value (PPV) > 90%. For automated algorithms failing to meet this threshold, manual review was coupled with algorithms to validate that the included cases were true positives. A total of 11,639 subjects met phenotyping criteria for a least one of the 28 phenotypes investigated. Across all phenotypes cases and controls, 90% were reused as either a case or control for a least one other phenotype. Data are deposited for individual phenotypes in the VESPA substudies. Substudies: VESPA: Genome Wide Association Study of Serum Creatinine during Vancomycin Therapy and Vancomycin Pharmacokinetics - phs000894 VESPA: Genome Wide Study of Clinically Diagnosed Ace Inhibitor Cough - phs000992

Study phs000991

Clinical and Genetic Evaluation of Individuals with Undiagnosed Disorders through the Undiagnosed Diseases Network (UDN)

The National Human Genome Research Institute and the NIH Clinical Center established the intramural Undiagnosed Diseases Program (UDP) in 2008 to make progress in uncovering, understanding, and treating rare disorders. Based on the success of the UDP, the NIH Common Fund established the Undiagnosed Diseases Network (UDN) in FY 2013 (Phase I, 9/16/2015-8/31/2018) to achieve this type of cross-disciplinary approach to disease diagnosis in academic medical centers around the United States. The NIH Common Fund expanded the network in 2018 (Phase II, 9/1/2018-6/20/2023) to increase the availability of diagnostic services, foster opportunities for collaboration between laboratory and clinical investigators, provide resulting data and protocols to the broader community, and assess development of a sustainable national resource after Common Fund support ends. The UDN transitioned from Common Fund in 2023. The National Institute of Neurological Disorders and Stroke (NINDS) will oversee the Network in Phase III, which launched in July 2023, with help from 17 different NIH Institutes and Centers along with the NIH Office of the Director. With help from patients, family members, patient advocacy groups, a Data Management and Coordinating Center (DMCC), several Clinical Sites, and other stakeholders, the NIH envisions the UDN evolving into a larger, diverse, and self-sustained network that fosters scientific discovery and provides expert diagnostic services for undiagnosed patients across the nation. The overarching goals of the UDN in Phase III include: Continuing the proven success of the UDN in improving the clinical evaluation of difficult-to-diagnose patients using a collaborative team approach and investigating and validating promising new diagnostic technologies. Facilitating research into the etiology of undiagnosed diseases by collecting and sharing standardized, high-quality clinical and laboratory data including genotyping, phenotyping, and documentation of environmental exposures. Promoting a broader integrated and collaborative community across multiple Clinical Sites and among laboratory and clinical investigators prepared to investigate the genetic, pathophysiologic, cell biologic, and molecular mechanisms underpinning these difficult-to-diagnose conditions.

Study phs001232

Single Cell Transcriptomics of peripheral immune cells pre- and post-Immune Checkpoint Blockade

This is raw sequencing data, analysis of which is presented in the paper "Sensitivity to Immune Checkpoint Blockade and Progression-Free Survival is associated with baseline CD8+ T cell clone size and cytotoxicity", DOI: https://doi.org/10.1101/2020.11.15.383786

Dataset EGAD00001007942

Copy number profiling of tissue and plasma samples from high grade serous epithelial ovarian cancer patients

This dataset includes 289 samples from 46 high grade serous epithelial ovarian cancer patients. Data are from both tissue samples (either primary tumor, or synchronous metastases) and circulating cell-free DNA (cfDNA) of plasma samples taken during therapy and follow-up.

Dataset EGAD00001006422

DPY30 ChIP-seq

H9 human embryonic stem cells (hESCs) were cultured in feeder-free chemically-defined conditions in medium containing 10ng/ml Activin A and 12ng/ml FGF2 (Vallier L. 2011, Methods in Molecular Biology, 690: 57-66). Chromatin immunoprecipitation was performed as described in Brown S. et al. 2011. Stem Cells 29: 1176-85 by using 5ug of anti-DPY30 antibody (Sigma, cat. number HPA043761). This protocol was performed in control hESCs (expressing a scrambled shRNA) and in hESCs stably expressing an shRNA against DPY30 (Sigma, clone n. TRCN0000131112).This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Dataset EGAD00001001268

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

Key objective Are the prognostic transcriptomic G1/G2 gene expression signature, MYC overexpression, and MYC amplification replicable stratifying biomarkers for future clinical trials in high-grade osteosarcoma? Knowledge gathered In an unselected cohort, the G2 gene expression signature and MYC overexpression, but not MYC amplification, were independently associated with poor event-free and overall survival. Relevance Transcriptomic biomarkers may serve as stratifying factors that guide the management of patients with high-grade osteosarcoma. Current data underlines the importance of prospective validation of the G1/G2 signature and MYC overexpression in an international, multicenter, study.

Dataset EGAD00001015503

PCGP Ph-like ALL

Background: BCR-ABL1-like, or Ph-like acute lymphoblastic leukemia is characterized by a gene expression profile similar to BCR-ABL1 positive ALL, genetic alterations of lymphoid transcription factor genes, and poor outcome. Sequencing of small numbers of Ph-like ALL cases has identified genetic alterations activating kinase signaling suggesting Ph-like ALL may be amenable to treatment with tyrosine kinase inhibitors. However, the spectrum of genetic alterations in childhood and adult Ph-like ALL is incompletely understood. Methods: We performed genomic profiling of 1736 B-ALL cases and next-generation sequencing for 160 Ph-like cases. We examined the functional effects of chimeric fusion proteins in mouse cell lines. Results: The frequency of Ph-like ALL rose from 11% in children to 26% in young adults, and was associated with very poor outcome. Kinase-activating alterations were identified in 90% of Ph-like cases, most commonly fusions involving 10 kinase or cytokine receptor genes (ABL1, ABL2, CRLF2, CSF1R, EPOR, JAK2, NTRK3, PDGFRB, PTK2B and TYK2), and mutations involving FLT3, IL7R and SH2B3. Expression of ABL1, ABL2, CSF1R and JAK2 fusions resulted in cytokine-independent proliferation of cell lines and activation of pSTAT5. Cells expressing ABL1, ABL2, CSF1R and PDGFRB fusions were sensitive to dasatinib, and JAK2 fusions to ruxolitinib. Conclusions: Ph-like ALL is characterized by a diverse range of genomic alterations that converge on a limited number of kinase signaling pathways amenable to inhibition with currently available tyrosine kinase inhibitors. Trials identifying Ph-like ALL and testing the efficacy of tyrosine kinase inhibitor therapy are warranted

Study EGAS00001000654

NextGen Consortium: Globin Gene Expression in Sickle Cell Genotype-Specific iPS Cells

Implement an efficient, highly reproducible and 'scalable' system for the production of large numbers of sickle cell anemia-specific iPS cells (iPSC). Derive and characterize a novel, in vitro system for the production of an unlimited supply of erythroid lineage cells from the directed differentiation of 'clinical grade' transgene-free iPS cells; use this system to recapitulate erythroid-lineage ontogeny in vitro with the sequential development of primitive and definitive erythropoiesis, accompanied by the appropriate expression of stage-specific globin genes. Identify developmental gene expression profile differences between erythroid precursors that produce primarily HbF and those that produce primarily HbA or HbS. Determine the effects of the three known HbF major quantitative trait loci (QTL) on globin gene expression in disease-specific iPS cells during in vitro erythropoiesis. Search for novel HbF genetic modifiers associated with markedly elevated HbF levels found in sickle cell anemia patients naturally, or in response to hydroxyurea treatment, by examining gene expression profiles and mRNA sequence of their iPSC-derived erythroid cells. Develop and use a CRISPR-based gene editing platform to study the effect of novel HbF genetic modifiers, explore globin switching, and correct the HbS mutation in sickle iPSC lines.

Study phs001212

Identifying New Genetic Subtypes in Follicular Lymphoma

Follicular lymphoma (FL) exhibits considerable variability in biological features and clinical trajectories across patients. To dissect the diversity of FL, we utilized a Bernoulli mixture model to identify genetic subtypes in 713 pre-treatment tumor tissue samples. Our analysis revealed the existence of five subtypes with unique genetic profiles that correlated with clinicopathological characteristics. The clusters were enriched in specific mutations as follows: CS (CREBBP and STAT6), TT (TNFAIP3 and TP53), GM (GNA13 and MEF2B), Q (quiescent, for low mutation burden), and AR (mutations of mTOR pathway-related genes). The subtype Q was enriched for patients with stage I disease and was associated with a lower proliferative history compared to the other subtypes. The AR subtype was unique in its enrichment for IgM-expressing FL cases and was associated with advanced-stage and more than 4 nodal sites. The existence of subtypes was validated in an independent cohort of 418 samples from the GALLIUM trial. Notably, patients assigned to the TT subtype consistently experienced inferior progression-free survival when treated with immunochemotherapy. Collectively, our findings offer insight into core pathways distinctly linked with each FL cluster and are expected to be informative in the era of targeted therapies.

Study EGAS50000000435

Microbiomic and immunogenic biomarkers of adjuvant chemotherapy efficacy in stage III colorectal cancer

The standard treatment for stage III colorectal cancer (CRC) is surgery, followed by adjuvant chemotherapy (AC). However, the efficacy of AC is limited, and approximately 30% of patients experience recurrence. Therefore, easily assessable molecular biomarkers that can predict response to AC are needed. Here, we aimed to identify predictive biomarkers of response to AC using tumor transcriptomic data. Tumor specimens from 253 patients who underwent surgery for stage III CRC between 1997 and 2019 were analyzed using RNA sequencing. Transcriptional subtyping and analyses of gut microbiome, immune cell fractions, and T-cell receptor (TCR) were performed to identify factors associated with recurrence-free survival (RFS) in patients treated with or without AC. Of 253 patients, 118 (46.6%) received AC. Twenty phyla and 799 species of the microbiomes were identified, among which Fusobacteria were identified in 247 patients (97.6%). Multivariable Cox proportional hazards regression analysis of patients who received AC showed that intratumoral Fusobacterium and M1 macrophage abundance and diversity of TCR alpha and delta (TRAD) were independently associated with RFS. Fusobacterium and M1 macrophage abundance, and TRAD diversity were associated with the response to AC, suggesting that these factors could serve as biomarkers for personalized treatment in stage III CRC.

Study JGAS000875

FASTQ files of total RNA-Seq data from the POPS PET (pre-eclamptic) samples

All the samples were obtained from the Pregnancy Outcome Prediction–a prospective cohort study of nulliparous women attending the Rosie Hospital, Cambridge (UK) for their dating ultrasound scan between January 14, 2008, and July 31, 2012. Ethical approval for the study was given by the Cambridgeshire 2 Research Ethics Committee (reference number 07/H0308/163) and all participants provided written informed consent. Cases of preeclampsia (PET) were defined on the basis of the 2013 ACOG criteria and cases of small for gestational age (SGA)infants were confined to severe SGA, i.e. a customized birth weight <5th percentile. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

Dataset EGAD00001003508

Circulating RNA profiles of healthy and preeclamptic pregnancies

This prospective study investigated whether circulating RNA (C-RNA; cell free RNA present in the bloodstream) measurements could non-invasively monitor pregnancy status, with emphasis on detecting molecular markers associated with preterm preeclampsia. Whole blood samples were collected from pregnant women at the time of diagnosis with early-onset preeclampsia with severe features. Blood samples were also obtained normotypical control pregnancies and from patients diagnosed with late-onset preeclampsia for comparison. For all samples, C-RNA was extracted from 4 mL blood and whole transcriptome enrichment performed on cDNA libraries prior to sequencing to a target depth of 50M reads on an Illumina HiSeq 2000 platform. Throughout the course of this work, whole transcriptome RNA sequencing data was obtained from 289 C-RNA samples collected from 178 subjects. The complete dataset consists of samples from the following cohorts: Illumina Preeclampsia Cohort (iPEC): 40 pregnancies at the time of early-onset preeclampsia diagnosis and 73 gestational age-matched controls PEARL preeclampsia cohort: 12 early-onset and 12 late-onset preeclampsia patients PEARL healthy control cohort: 152 longitundinal samples collected from 41 healthy pregnancies

Study phs002017

Prediction of homologous recombination deficiency identifies colorectal tumors sensitive to PARP inhibition

BRCAness is a well-established feature in breast, ovarian, prostate and pancreatic carcinomas, our recent findings indicate that up to 15% of colorectal cancers (CRC) also harbor defects in the HR pathway, presenting promising opportunities for innovative therapeutic strategies in CRC patients. We developed a new tool called HRDirect, which builds upon the HRDetect algorithm and is able to predict HRD from reference-free tumor samples. We validated HRDirect using matched breast cancer and CRC patient samples. Subsequently, we assessed its efficacy in predicting response to the PARP inhibitor olaparib by comparing it with two other commercial assays: AmoyDx HRD by Amoy Diagnostics and the TruSight Oncology (TSO) _500 HRD panel by Illumina NGS technology. While all three approaches successfully identified the most PARPi-sensitive CRC models, HRDirect demonstrated superior precision in distinguishing resistant models compared to AmoyDX and TSO500-HRD, which exhibited overlapping scores between sensitive and resistant cells. Furthermore, we propose integrating HRDirect scoring with ATM immunohistochemical analysis as part of our "composite biomarker approach" to enhance the identification of HRD tumors, with an immediate translational and clinical impact for CRC personalized treatment.

Study EGAS50000000426

Adaptive Therapy Exploits Fitness Deficits in Chemotherapy-Resistant Ovarian Cancer to Achieve Long-Term Tumor Control Open Access

Drug resistance results in poor outcomes for cancer patients. Adaptive therapy is a potential strategy to address drug resistance that exploits competitive interactions between sensitive and resistant subclones. Here, we showed that adapting carboplatin dose according to tumor response (adaptive therapy) significantly prolonged survival of murine ovarian cancer models compared to standard carboplatin dosing, without increasing mean daily drug dose or toxicity. Platinum resistant ovarian cancer cells exhibited diminished fitness when drug was absent in vitro and in vivo, which caused selective decline of resistant populations due to reduced proliferation and increased apoptosis. Conversely fitter, sensitive cells re-grew when drug was withdrawn. Using a bioinformatics pipeline that exploits copy number changes to quantify the emergence of treatment resistance, analysis of cell‐free DNA obtained longitudinally from ovarian cancer patients during treatment showed subclonal selection through therapy, and measurements of resistant population growth correlated strongly with disease burden. These preclinical findings pave the way for future clinical testing of personalized adaptive therapy regimens tailored to the evolution of carboplatin resistance in individual ovarian cancer patients.

Study EGAS50000001142

Comparative transcriptome of CD34+ hematopoietic progenitors from myeloproliferative patients and control donors

BCR-ABL-negative MPNs are related to mutations activating the JAK2/STAT pathway and occurring in hematopoietic stem cells (HSC). The most prevalent mutation is JAK2V617F. Calreticulin (CALR) and activating MPLW515 mutations are also observed in ET and PMF. Additional non-MPN mutations may be found, particularly in PMF, and can change disease phenotype or accelerate progression to myelofibrosis or leukemia. In this study, we wanted to compare the transcriptome of CD34+ progenitors from JAK2V617F postive MPN patients to the CD34+ progenitors from control donors. The patients were selected for their high JAK2V617F variant allele frequency (from 60 to 100% VAF). Peripheral blood from patients was collected in EDTA tubes. Hematopoietic progenitors (CD34+) were isolated from mononuclear cells (MNCs) by immunomagnetic enrichment (Miltenyi, Biotech) and were amplified for 5 days in serum-free medium in the presence of a cocktail of human recombinant cytokines containing EPO (1 U/mL) (Amgen Thousand Oaks, CA), TPO (20 ng/mL) (Kirin, Japan), SCF (25 ng/mL) (Biovitrum AB, Sweden), IL-3 (10 ng/mL), FLT3-L (10 ng/mL), G-CSF (20 ng/mL) and IL-6 (100 U/mL) (MiltenyiBiotec).

Study EGAS00001005106

Discover Cancer Image Europe, the first release of the EUCAIM platform to fuel cancer research and data sharing

The EUCAIM consortium and the European Commission have announced the release of Cancer Image Europe, a platform to fuel collaborative innovation and data sharing across Europe. This constitutes a major milestone in EUCAIM's development and an exciting step towards achieving the project's vision and goals. The platform aims to accelerate the pace of AI development and other data-intensive cancer research activities, constituting the basis for a fully-fledged infrastructure for sharing, reusing, and exploiting cancer imaging data, especially using AI techniques. A platform paving the way for the future of cancer diagnosis and treatment Cancer Image Europe brings benefits to researchers, clinicians, and AI innovators across Europe as it addresses the fragmentation of existing cancer image repositories. The platform gathers a public catalogue of cancer imaging datasets from the repositories of the EU-funded AI for Health Imaging projects. A distributed Atlas of Cancer Imaging with over 60 million anonymised cancer image data from over 100,000 patients will be established as part of future updates. The first version of Cancer Image Europe also includes a public catalogue of cancer imaging datasets, a federated searching tool to understand the information available in the federated providers, and full integration with Life Science Login. Moreover, it reuses and adds value to key components of EU-funded research projects and infrastructure in the field of cancer. The Public Catalogue When we talk about data re-use, data discovery is key. The EUCAIM public catalogue is the result of a systematic and collaborative process to which the EGA-CRG has actively contributed. This browsing interface gathers the metadata of the available cancer imaging datasets. This descriptive information will help researchers in their data retrieval. Our contribution to the Public Catalogue comes from our experience gained in the deployment of our federated network, the Federated EGA (FEGA), and as partners in projects such as EuCanImage (AI4HI initiative), in which we worked on the definition of common data models, ontologies and data standards. The EUCAIM Project EUCAIM is a cornerstone of the European Commission-initiated European Cancer Imaging Initiative, a flagship of the Europe's Beating Cancer Plan, which aims to foster innovation and deployment of digital technologies in cancer treatment and care, to achieve more precise and faster clinical decision-making, diagnostics, treatments, and predictive medicine for cancer patients. For more information about the first release of the Cancer Image Europe platform and the EUCAIM project, please visit cancerimage.eu.

Blog discover-cancer-image-europe

Bayesian-Based Noninvasive Prenatal Diagnosis of Single-Gene Disorders

In the last decade, non-invasive prenatal diagnosis (NIPD) has emerged as an effective procedure for early detection of inherited diseases during pregnancy. This technique is based on using cell-free DNA (cfDNA) and fetal cfDNA (cffDNA) in maternal blood, and hence, has minimal risk for the mother and fetus compared with invasive techniques. NIPD is used today for identifying chromosomal abnormalities (in some instances) and for single-gene disorders (SGDs) of paternal origin. However, for SGDs of maternal origin, sensitivity poses a challenge that limits the testing to one genetic disorder at a time. Here we present a Bayesian method for the NIPD of monogenic diseases that is independent of the mode of inheritance and parental origin. Furthermore, we show that accounting for differences in the fragment length distribution of fetal- and maternal-derived cfDNA results in increased accuracy. Our model is the first to predict inherited insertions-deletions (indels). The method described can serve as a general framework for the NIPD of SGDs; this will facilitate easy integration of further improvements. One such improvement that is presented in the current study is a machine learning model that corrects errors based on patterns found in previously processed data. Overall, we show that next generation sequencing (NGS) can be used for the NIPD of a wide range of monogenic diseases, simultaneously. We believe that our study will lead to the achievement of a comprehensive NIPD for monogenic diseases. (Reprinted from Bayesian-based noninvasive prenatal diagnosis of single-gene disorders, with permission from Genome Research)

Study phs001659

Detection of rare mutations, copy number variation, and DNA methylation in the same template DNA molecules

The analysis of cell-free DNA (cfDNA) from plasma offers great promise for the earlier detection of cancer. At present, changes in DNA sequence, methylation, or copy number are the most sensitive ways to detect the presence of cancer. To further increase the sensitivity of such assays with limited amounts of sample, it would be useful to be able to evaluate the same template molecules for all these changes. Here we report an approach, called MethylSaferSeqS, that achieves this goal, and can be applied to any standard library preparation method suitable for massively parallel sequencing. The innovative step was to copy both strands of each DNA-barcoded molecule with a primer that allows the subsequent separation of the original strands (retaining their 5-methylcytosine residues) from the copied strands (in which the 5-methylcytosine residues are replaced with unmodified cytosine residues). The epigenetic and genetic alterations present in the DNA molecules can then be obtained from the original and copied strands, respectively. We applied this approach to plasma from 265 individuals, including 198 with cancers of the pancreas, ovary, lung and colon, and found the expected patterns of mutations, copy number alterations, and methylation. Furthermore, we could determine which original template DNA molecules were methylated and/or mutated. MethylSaferSeqS should be useful for addressing a variety of questions relating genetics and epigenetics in the future.

Study EGAS00001006839

PGRN-RIKEN: Genetic Determinants of Clinical Cardiovascular Events in Patients Receiving Statins

Coronary heart disease (CHD) is an important public health problem in developed countries. Statins are effective in the prevention and treatment of CHD; nevertheless, many patients receiving statins still suffer cardiovascular events (CV) such as heart attack. Identifying genetic variants responsible for differential clinical responses to statins will not only allow individual patients at high residual risk to be targeted for additional therapies, but also will define new biologic pathways contributing to statin response, and thus new targets for future therapies. Accordingly, the goal of this study is to identify genetic variants associated with clinical CV in patients receiving statins. Subjects identified for study are of European descent and include 1718 subjects with CV while on statins (cases) and 4172 subjects without CV while on statins (controls). Key research resources utilized in this effort include VanderbiltD's BioVU DNA databank and associated Synthetic Derivative database of clinical information, and software tools developed to identify drugs and clinical events using Electronic Health Record-derived structured and unstructured ("free text") data. Most cases and controls identified include three data types: ICD-9 codes, medication regimens, and medical test results. Genotyping, using IlluminaD's Infinium HumanOmniExpressExome BeadChip (OmniExpressExome), was performed by the RIKEN Integrative Medical Sciences Center (IMS) and supported by the Pharmacogenomics Research Network (PGRN)-RIKEN IMS Global Alliance.

Study phs000963

FASTQ files of the polyA+ (oligo-dT) RNA-Seq dataset from the POPS SGA (Small for Gestational Age) samples and their matched controls.

FASTQ files of the polyA+ (oligo-dT) RNA-Seq dataset from the POPS SGA (Small for Gestational Age) samples and their matched controls. The POP study placental biopsies were collected within 30 minutes of birth and flash frozen in RNAlater (ThermoFisher). For each biopsy, total placental RNA was extracted from approximately 5 mg of tissue using the “mirVana miRNA Isolation Kit” (Ambion) followed by DNase treatment (“DNA-free DNA Removal Kit”, Ambion). RNA quality was assessed with the Agilent Bioanalyzer and all the samples with RIN values ≥ 7.0 were used in the downstream experiments. RNA-libraries were prepared from 1g of total placental RNA with the TruSeq Stranded mRNA Library Prep Kit (Illumina) which captures polyA-tailed transcripts by oligo-dT beads, then pooled and sequenced (single-end, 50bp) using a Single End V4 cluster kit and Illumina HiSeq2500

Dataset EGAD00001006304

NEOPREDICT-Lung: longitudinal whole exome sequencing of non-small cell lung cancers under immunotherapy

In 43 patients pretreatment tumor biopsies, resected tumors and normal tissue of sufficient quality and quantity were obtained to longitudinally explore the mutational profiles of a comprehensive set of cancer-related genes. For tumor samples, one to four FFPE sections (10 µm thickness, number depending on sample size) were lysed for genomic DNA isolation. Isolation was performed semi-automatically on the Maxwell purification system (Maxwell RSC DNA FFPE Kit, AS1450, Promega) as specified by the manufacturer. DNA was eluted in 50 µl RNase-free water and quantified fluorescently for library preparation using a Qubit 2.0 fluorometer (Life Technology) with its appertaining DNA broad-range assay. Corresponding normal DNA was isolated from blood or PBMCs using routinely available QIAGEN technology. DNA was stored at -20°C before use. Whole-exome sequencing (WES) was performed using the Twist Human Core + RefSeq + Mitochondrial Panel (Twist Bioscience), and 2 x 100 bp fragment sizes were sequenced using a NovaSeq6000 (Illumina). Demultiplexing of sequenced reads was achieved using bcl2fastq (version 2.2).

Dataset EGAD00001015362

DNA methylation-based classification of sinonasal tumors [Proteomics data]

This dataset includes raw label-free mass spectrometry proteomics data of different sinonasal tumor entities as well as normal sinonasal tissue. 72 samples were processed on a Q Exactive HF-X instrument coupled to an easy nanoLC 1200 system using one microgram of peptides and an 110 minutes gradient.

Dataset EGAD00010002381

Aligned Low pass whole genbome sequencing of cell free and tumour DNA from 5 patients with high grade serous ovarian cancer. Samples have been aligned to hg19 and bam files uploaded

This is the aligned bam files of 5 patients, with sequential sampltes from patients comprising cfDNA and FFPE extracted tumour DNA

Dataset EGAD50000001632

A mathematical model of cell-free DNA fragment size reveals cancer-specific fragmentomic patterns

This study aim to test a mathematical model of cfDNA length distribution across multiple biodiy flulids. It try to investigate biological mechanisms of cfDNA fragmentation and release.

Study EGAS50000001560

Cell-free DNA and bone marrow samples from myelodysplastic syndromes

We have assessed the molecular profile of a cohort of 70 patients with MDS by next-generation sequencing (NGS) using cfDNA and compared the results to paired bone marrow (BM) DNA. Sequencing of BM DNA and cfDNA showed a comparable mutational profile and variant allele frequencies (VAF) strongly correlated between both sample types. Our results support the analysis of cfDNA as a promising strategy for performing molecular characterization, detection of chromosomal aberrations and monitoring of MDS patients.

Study EGAS00001005992

Multimodal cell-free DNA whole-genome TAPS is sensitive and reveals specific cancer signals

This study presents a methodology for detecting circulating tumor DNA (ctDNA) using deep whole-genome TET-Assisted Pyridine Borane Sequencing (TAPS), a less destructive alternative to bisulphite sequencing. The method enables simultaneous analysis of genomic and methylomic data for multi-cancer detection and monitoring minimal residual disease. In a diagnostic accuracy study across various cancer types, it achieved 85.3% sensitivity and 88.8% specificity, with validation done using matched tumour biopsies. Additionally, in silico validation showed strong discrimination at low ctDNA levels. The approach also successfully tracks tumour burden and ctDNA shedding from precancerous lesions post-treatment, making it ready for further clinical testing.

Study EGAS50000000715

CIDR: NCI Genome Wide Predictors of Survival in Colorectal Cancer

CIDR/Molecular Correlates: This study genotyped archived blood samples from colorectal cancer cases participating in clinical trials. The goals of this project were to identify genetic variants associated with survival outcomes treatment and treatment-related severe adverse events among patients with colorectal cancer. Another goal was to examine the impact of adding information on germline genetic loci to existing prognostic models. MOSAIC: Multicenter International Study of Oxaliplatin/ 5FU-LV in the Adjuvant Treatment of Colon Cancer (MOSAIC). A randomized, open label efficacy trial to evaluate the FOLFOX regimen versus LV5FU2 in the adjuvant treatment of stage II and III colon cancer. The primary end point was disease-free survival. CPT.ES1.604: Randomized phase 3 study of weekly irinotecan plus high-dose 5-fluorouracil (FUIRI) versus biweekly irinotecan plus 5-fluorouracil/leucovorin (FOLFIRI) as first-line chemotherapy for patients with metastatic CRC. The aim of this study was to demonstrate that a regimen without leucovorin (LV) (FUIRI) is not inferior to the standard FOLFIRI (response rate). 03-TTD-01: The purpose of this phase III, multicenter, randomized, open-label study is to evaluate the safety and efficacy of combination therapy with capecitabine and oxaliplatin (XELOX) vs. oxaliplatin and 5-fluorouracil in continous infusion (5-FU CI) as first line treatment in advanced or metastatic colorectal cancer. The primary outcome measure is time to disease progression. Secondary outcome measures are to determine safety of combination, objective response rate, time to onset of response, duration of response, time to treatment failure, one year survival time, and overall survival time. 03-TTD-01: The purpose of this phase III, multicenter, randomized, open-label study is to evaluate the safety and efficacy of combination therapy with capecitabine and oxaliplatin (XELOX) vs. oxaliplatin and 5-fluorouracil in continous infusion (5-FU CI) as first line treatment in advanced or metastatic colorectal cancer. The primary outcome measure is time to disease progression. Secondary outcome measures are to determine safety of combination, objective response rate, time to onset of response, duration of response, time to treatment failure, one year survival time, and overall survival time. N0147: Randomized phase III clinical trial for adjuvant therapy in stage III colon cancer patients enrolled at institutions across North America. Originally designed to compare three different chemotherapy regimens, and then later expanded to evaluate adding cetuximab to each original arm (leading to six total arms). Further modification later added pre-screening for KRAS mutation status, with the resulting goal to assess the potential benefit of cetuximab added to the modified sixth version of the FOLFOX regimen (mFOLFOX6) in patients with resected stage III wild-type KRAS colon cancer. Main outcome of interest is disease-free survival in patients with wild-type KRAS, while secondary end points included overall survival and toxicity. N9741: Randomized phase III trial to compare the effectiveness of various combination chemotherapy regimens in treating patients who have advanced, recurrent, or metastatic colorectal cancer that cannot be treated with surgery or radiation therapy. C-08: A Phase III Clinical Trial Comparing Infusional 5-Fluorouracil (5-FU), Leucovorin, and Oxaliplatin (mFOLFOX6) Every Two Weeks With Bevacizumab to the Same Regimen Without Bevacizumab For the Treatment of Patients With Resected Stages II and III Carcinoma of the Colon. The primary aim of the trial was to compare the relative efficacy of mFOLFOX6 + bevacizumab with that of mFOLFOX6 alone in prolonging disease-free survival and the secondary aim was to compare the relative efficacy of mFOLFOX6 + bevacizumab with that of mFOLFOX6 alone in prolonging survival.

Study phs001290

NHLBI TOPMed: The Cleveland Family Study (CFS)

The Cleveland Family Study (CFS) is one cohort involved in the WGS project. The CFS was designed to provide fundamental epidemiological data on genetic and non-genetic risk factors for sleep disordered breathing (SDB). In brief, the CFS is a family-based study that enrolled a total of 2284 individuals from 361 families between 1990 and 2006. The sample was selected by identifying affected probands who had laboratory diagnosed obstructive sleep apnea. All first degree relatives, spouses and available second degree relatives of affected probands were studied. In addition, during the first 5 study years, neighborhood control families were identified through a neighborhood proband, and his/her spouses and first degree relatives. Each exam, occurring at approximately 4 year intervals, included new enrollment as well as follow up exams for previously enrolled subjects. For the first three visits, data, including an overnight sleep study, were collected in the participants' homes while the last visit occurred in a general clinical research center (GCRC). Phenotypic characterization of the entire cohort included overnight sleep apnea studies, blood pressure, spirometry, anthropometry and questionnaires. The GCRC exam (n=735 selected individuals) included more comprehensive phenotype data on a focused subsample of the larger cohort, to permit linking SDB phenotypes with cardio-metabolic phenotypes, with an interest in identifying genetic loci that are associated with these related phenotypes. In this last round of data collection, a subset of 735 individuals was selected based on expected genetic informativity by choosing pedigrees where siblings had extremes of the apnea hypopnea index (AHI). Participants underwent detailed phenotyping including laboratory polysomnography (PSG), ECG, spirometry, nasal and oral acoustic reflectometry, vigilance testing, and blood and urine collection before and after sleep and after an oral glucose tolerance test. A wide range of biochemical measures of inflammation and metabolism were assayed by a Core Laboratory at the University of Vermont. 994 individuals were sequenced as part of TOPMed Phase 1, including 507 African-Americans and 487 European-Americans. Among the sequenced individuals, 156 were probands with diagnosed sleep apnea, an additional 706 were members of families with probands, and 132 were from neighborhood control families. 298 individuals were sequenced as part of TOPMed Phase 3.5, including 169 African-Americans and 129 European-Americans. Among the newly sequenced individuals, 33 were probands with diagnosed sleep apnea, an additional 214 were members of families with probands, and 51 were from neighborhood control families. Please note: Phenotype and pedigree data are available through "NHLBI Cleveland Family Study (CFS) Candidate Gene Association Resource (CARe)", phs000284.

Study phs000954

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. The liquid biopsy sequencing (plasma cfDNA) was performed using a custom-designed targeted AmpliSeq HD Prostate Cancer cfDNA panel on all 68 patients. The sequencing on 42 matched FFPE tumor biopsy samples was performed using a custom-designed or an alternative commercial panel (ThermoFisher). Raw data underwent automated processing on the Ion Torrent Server v5.16.1 (ThermoFIsher) and were aligned to a hg19 reference genome using the Torrent Alignment Software (ThermoFihser).

Dataset EGAD50000000348

Sequence data from stage I of the CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer

The dataset for the study "Early ctDNA molecular response captures therapeutic response in the first stage of CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer", includes 134 bam files from hybrid capture targeted error-correction next-generation sequencing (PGDx Elio plasma resolve) from plasma cell-free DNA and matched white blood cell DNA from 35 individuals with non-small cell lung cancer on the BR.36 trial, alongside 11 bam files from targeted next generation sequencing (PGDx Elio tissue complete) of tumor DNA from 11 individuals with non-small cell lung cancer on the BR.36 trial.

Dataset EGAD00001011359

Profiles of extracellular miRNA in cerebrospinal fluid and serum from patients with Alzheimer's or Parkinson's disease correlate with disease status and features of pathology

We profiled the miRNA contents from cerebrospinal fluid and serum (using next generation sequencing) from postmortem patients diagnosed with Alzheimer's or Parkinson's disease, and neurologically normal controls. All biofluids were cell-free and patient matched, there was one cerebrospinal fluid and one serum sample from each of 70 patients with Alzheimer's disease, 67 patients with Parkinson's disease and 78 age-similar controls. We correlated the miRNA changes with measurements of neuropathology such as plaques, tangles and Lewy bodies.

Study phs000727

ERBB2/HER2 alterations in ctDNA and metachronous tissues of patients with metastatic urothelial cancer - WGS

Whole genome sequencing data related to the publication "ERBB2/HER2 alterations in ctDNA and metachronous tissues of patients with metastatic urothelial cancer." ERBB2 alterations, usually amplifications or activating mutations, are seen in up to 20% of urothelial carcinoma and can be targeted by monoclonal antibodies, small molecule inhibitors, and most recently, antibody-drug conjugates. Here, we perform targeted and whole-genome sequencing of cell-free DNA and archival FFPE of mUC with and without ERBB2 alterations to identify unique genomic and clinical features of ERBB2-altered cancers, accompanied by IHC, FISH, and detailed clinical outcomes.

Study EGAS50000001082

ERBB2/HER2 alterations in ctDNA and metachronous tissues of patients with metastatic urothelial cancer - Targeted

Targeted sequencing data related to the publication titled "ERBB2/HER2 alterations in ctDNA and metachronous tissues of patients with metastatic urothelial cancer." ERBB2 alterations, usually amplifications or activating mutations, are seen in up to 20% of urothelial carcinoma and can be targeted by monoclonal antibodies, small molecule inhibitors, and most recently, antibody-drug conjugates. Here, we perform targeted and whole-genome sequencing of cell-free DNA and archival FFPE of mUC with and without ERBB2 alterations to identify unique genomic and clinical features of ERBB2-altered cancers, accompanied by IHC, FISH, and detailed clinical outcomes.

Study EGAS50000001081

Whole genome sequencing data of paediatric KMT2A-rearranged acute lymphoblastic leukemia

Pediatric KMT2A-rearranged leukemia is an aggressive subtype of leukemia commonly seen in infants (less tha 1 year old) and young children. It involves rearrangements of the KMT2A gene (formerly MLL) on chromosome 11q23, resulting in fusion genes that drive uncontrolled cell growth. This subtype is most often found in acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) and is associated with a poor prognosis. In infants, the 5-year event-free and overall survival rates are around 35–40%. Despite intensive chemotherapy, outcomes remain challenging, prompting ongoing research into targeted therapies and novel treatment strategies.

Study EGAS50000001079

Non-muscle Invasive Bladder Cancer Molecular Subtypes Predict Differential Response to Intravesical Bacillus Calmette-Guérin

The recommended treatment for patients with high-risk non-muscle invasive bladder cancer (HR-NMIBC) is tumor resection followed by adjuvant Bacillus Calmette-Guérin (BCG) bladder instillations. However, only 50% of patients benefit from this therapy. In case of progression to advanced disease, patients must undergo a radical cystectomy with significant morbidity and have a poor clinical outcome. Identifying tumors least likely to respond to BCG can translate into alternative treatments, such as early radical cystectomy or novel targeted or immunotherapies. Here we present molecular profiling of 132 BCG-naive, HR-NMIBC patients, and 44 post-BCG recurrences (34 matched), which uncovered three distinct BCG Response Subtypes (BRS1-3). Patients with BRS3 tumors have reduced recurrence and progression-free survival compared to BRS1-2. BRS3 tumors expressed high EMT-basal markers and had an immunosuppresive profile, which was confirmed with spatial proteomics. Tumors which recurred post-BCG were enriched for BRS3. BRS stratification was validated in a second cohort of 151 BCG-naive HR-NMIBC patients and the molecular subtypes outperformed guideline recommended risk stratification based on clinicopathological variables. For clinical application, we validated that a commercially approved assay was able to accurately predict BRS3 tumors (AUROC 0.86). Our findings provide a potential clinical tool for improved identification of HR-NMIBC patients at the highest risk of progression, which can be used to select patients for early radical cystectomy or novel subtype-directed therapies.

Study EGAS00001006879

Poland Opole Voivodeship WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 10 samples (5 female, 5 male of Opole Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000124

Poland Podlaskie Voivodeship WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 12 samples (6 female, 6 male of Podlaskie Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000125

Poland Lubusz Voivodeship WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 19 samples (8 female, 11 male of Lubusz Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000127

Poland Holy Cross Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 6 samples (6 female of Holy Cross Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000162

Poland Warmian-Mazurian Voivodeship WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 15 samples (8 female, 7 male of Warmian-Mazurian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000128

Poland Lublin Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 24 samples (14 female, 10 male of Lublin Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000155

Poland Lodz Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 41 samples (20 female, 21 male of Lodz Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000165

Poland Lesser Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 32 samples (14 female, 18 male of Lesser Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000166

Poland Mazovia Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 43 samples (16 female, 27 male of Mazovia Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000164

Poland Greater Poland Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 37 samples (19 female, 18 male of Greater Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000161

Poland Subcarpathian Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 22 samples (11 female, 11 male of Subcarpathian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000157

Poland Pomeranian Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 25 samples (14 female, 11 male of Pomeranian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000160

Poland Lower Silesian Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 30 samples (15 female, 15 male of Lower Silesian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000156

Poland Silesian Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 47 samples (23 female, 24 male of Silesian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000163

Poland Kuyavian-Pomeranian Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 22 samples (11 female, 11 male of Kuyavian-Pomeranian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000158

Poland West Pomeranian Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 17 samples (7 female, 10 male of West Pomeranian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000129

Epidemiological study comparing rates and risk factors for dementia in African Americans in Indianapolis and Yoruba living in Ibadan, Nigeria

In 1991 collaboration between researchers at Indiana University School of Medicine and the University of Ibadan, Ibadan, Nigeria established the Indianapolis-Ibadan Dementia Project. It is a longitudinal, prospective population-based comparative epidemiological study of the prevalence and incidence rates and risk factors of Alzheimer's disease and other age associated dementias. The project compares samples of community-dwelling elderly (age > 70 years) African Americans living in Indianapolis to Yoruba living in Ibadan, Nigeria, employing the same research design, methods, and investigators. It initially reported significantly lower prevalence rates of disorders in the Yoruba compared to the African Americans. In subsequent waves of the study (1994-1995, 1997-1998) incidence rates, rates of newly diagnosed cases, were also found to be significantly lower in the Yoruba. In genetic studies, the frequency of the APOE 4 allele was about the same in the two groups. APOE 4 was a significant risk factor for Alzheimer's disease and dementia in the Americans, while no association was found for the Yoruba. The APOE 2 allele appears to be protective in the Americans, but not the Yoruba. A constellation of factors often associated with vascular risk including a history of hypertension, diabetes, and high cholesterol levels is less common in the Yoruba than in the American group. An interaction was observed between cholesterol, APOE genotype and Alzheimer's disease in both study groups. In 2001-2002 survivors of the original cohort were once again evaluated (N~800 in each site) and 2,000 additional individuals age 70 years and older were enrolled in each site. Blood samples were collected from approximately 1,500 study participants in each site for genetic studies and analysis of biochemical risk factors for vascular disease. Subsequent waves of field work were conducted in 2004, 2007, 2009, and 2011. This fieldwork followed the classic two-stage study design. The study design involves an in-home screening interview with the study participant, which includes a cognitive assessment, medical history and current medications, brief neurological examination, height and weight, blood pressure measurement and assessment of social involvement. There is also a screening interview with a close relative of the study participant to assess activities of daily living, personality change, and medical history of the study participant. On the basis of the screening interview a sample of study participants (N~500 in each site) is selected for a full clinical diagnostic dementia work up which includes a neurological test battery, extensive interview with a family member and examination by a clinician. Diagnoses are made in a consensus diagnosis conference using the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition (DSM-III R) and International Classification of Diseases 10th Revision (ICD-10) for dementia. The criteria of the National Institute for Neurological and Communicative Disease and Stroke-Alzheimer's Disease and Related Disorders Association were used to diagnose possible and probable Alzheimer's disease. The focus of the study is risk factors for dementia and Alzheimer's disease, but also of particular importance is the question of mild cognitive impairment. This refers to the condition of having some decline in cognition but the decline is not sufficient to meet the criteria for dementia. We have studied this over the course of this project. In follow up studies of individuals who have this diagnosis about one third of them are better at follow up, about a third are about the same, and about a third decline more to meet the criteria for dementia. This is a very important issue for researchers because the ultimate goal of the research is to figure out how to identify the individuals who will definitely progress to dementia. If there are clear identifiers, it would be possible to make interventions, while individuals still function well, and possibly prevent the development of dementia altogether or delay the onset significantly. This is crucial because at the moment individuals usually do not enter into the medical care system until the dementia symptoms are quite severe, and the pathological damage to the brain cannot be undone.

Study phs000378

Multi-Site Collaborative Study for Genotype-Phenotype Associations in Alzheimer's disease and Longitudinal follow-up of Genotype-Phenotype Associations in Alzheimer's disease and Neuroimaging component of Genotype-Phenotype Associations in Alzheimer's disease

GenADA is a multi-site collaborative study, involving GlaxoSmithKline Inc and nine medical centres in Canada, to develop a dataset containing 1000 Alzheimer's disease patients and 1000 ethnically-matched controls in order to associate DNA sequence (allelic) variations in candidate genes with Alzheimer's disease phenotypes. The study consists of both retrospective and prospective components, that is, patients with an existing diagnosis of Alzheimer's disease as well as newly diagnosed patients were enrolled in the study. Thus, clinical data was retrospectively or prospectively obtained on Day 1 of entry into GenADA. Where possible, biological relatives with Alzheimer's (up to third degree relationship such as cousins) and unaffected siblings of AD cases were also recruited. Note that recruitment numbers for biological relatives were lower than expected and genotypic data has not been submitted to dbGap for these subjects. The purpose of this study is: To identify DNA sequence variations (genotype) in candidate genes that are associated with the clinical symptoms and behavioural features of Alzheimer's disease (phenotype), which differ between study participants with and without the disease. To identify other genotype-phenotype associations in cognitively impaired study participants such as age of onset, family history, rate of cognitive decline, patterns of behavioural/psychiatric non-cognitive symptoms factors, response to treatment co-morbid conditions, and risks/exposure. The final subject recruitment for this study included 875 Alzheimer's disease patients, 850 ethnically-matched controls, and 37 family members. GenADA LONG is a longitudinal assessment to the original GenADA study. Eligible subjects were recruited from five of the nine memory clinics that participated in the GenADA study. Mild to moderate AD participants, a matched subset of controls, and biological related siblings (both affected and unaffected) or other blood relatives affected with AD, were initially examined a minimum of 12 months from recruitment into the original GenADA study, then at two further intervals of 12 and 18 months after time of entry into GenADA LONG. This enables an evaluation of the disease progression in AD patients and a determination of whether controls show evidence of cognitive decline. The overall goal of this extension study is to identify genetic differences and environmental influences that modulate the age of onset of the disease, the course of the disease, and/or biomarkers for neurodegenerative processes. Three of the five memory clinics that participated in the GenADA LONG study recruited eligible patients into GenADA Imaging. A concurrent neuroimaging sub-study was conducted at three of the five memory clinics participating in GenADA LONG. Eligible AD cases with mild to moderate AD, who were recruited into the original GenADA study and participated in the GenADA LONG extension study, were enrolled. Additionally, controls that showed signs of cognitive decline, as part of the assessment in GenADA LONG, were imaged at baseline, 12 and 18 month scanning intervals. The objective of this study is to find genes that: affect changes in AD brain volume measure by magnetic resonance in order to investigate how well change in brain volume predicts other key clinical measures in AD, such as neurodegenerative scales; that correlate changes in brain volume for other genotype-phenotype associations in cognitively impaired study participants; and that correlate with other clinically applicable magnetic resonance measures of pathology that can be conducted at the same time as structural volume measures, and are complementary to the volume measures. The ultimate aim of this research is to obtain a better understanding and definition of Alzheimer's Disease in order to develop new improved medicines.

Study phs000219

FASTQ files of total RNA-Seq data of POPS control samples

Placental biopsies (n = 64 female placentas, n = 67 male placentas) were selected from healthy pregnancies from the POPs cohort. These patients had no evidence of hypertension at booking and during pregnancy, did not experience pre-eclampsia, Hemolysis, Elevated Liver enzymes, and Low Platelets (HELLP) syndrome, gestational diabetes, or diabetes mellitus type I or type II and other obstetric complications. They delivered live babies with a birth weight percentile in the normal range (20-80th percentile), with no evidence of slowing in fetal growth trajectory. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

Dataset EGAD00001003457

Impact of germline pathogenic variants in 27 cancer-predisposing genes on the risk of lymphoma

The application of advanced molecular technology has significantly expanded lymphoma classification, allowing risk stratification and treatment optimization. Limited evidence suggests the presence of a genetic predisposition in lymphoma, indicating the potential for better individualized clinical management based on a novel lymphoma classification. Herein, we examined the impact of germline pathogenic variants in 27 cancer-predisposing genes with lymphoma risk and explored the clinical characteristics of pathogenic variant carriers. This study included 2,066 lymphoma patients and 38,153 cancer-free controls from the Japanese population. Following quality control of sequencing data, samples from 1,982 lymphoma patients and 37,592 controls were further analyzed. Sequencing data of controls were obtained from JGAD000721. Germline pathogenic variants in some cancer-predisposing genes were associated with a high risk of lymphoma. Furthermore, germline pathogenic variants in these genes were especially associated with the higher risk of a certain subtype. These results would provide novel insights concerning monogenic form into lymphoma classification. Some lymphoma patients may benefit from surveillance and targeted treatment like other neoplasms.

Study JGAS000347

Distinct genomic profiles and clinical outcomes in constitutional mismatch repair deficiency-associated high-grade gliomas: insights into mutational signatures and clonal evolution

Constitutional mismatch repair deficiency (CMMRD) is a rare cancer-predisposition syndrome, yet the mutational processes and clonal evolution of CMMRD-associated high-grade gliomas (HGGs) remain incompletely understood. In this study, mutational signatures and tumor evolution were analyzed in 25 CMMRD-associated HGGs. Germline biallelic mutations were most frequently identified in MSH6 (56.0%), followed by PMS2 (36.0%) and MLH1 (8.0%). Affected patients showed very early disease onset (mean 5.8 years) and poor clinical outcomes, with a mean progression-free survival of 16 months. Distinct genomic and clinical differences were observed between MSH6- and PMS2-associated tumors. MSH6-deficient HGGs were enriched for SBS6, whereas PMS2-deficient tumors showed predominance of SBS21, and these mutational signatures were correlated with prognosis. Clonal evolution analyses revealed early involvement of POLE/POLD1 mutations and persistence of the founding clone at recurrence. Overall, the study highlights the importance of mutational signatures and clonal evolution in shaping tumor behavior and clinical outcomes in CMMRD-associated HGGs.

Study EGAS50000001506

MethCORR: DNA Methylation-based Characterization, Classification and Prognostication of Colorectal Cancer using Archival Formalin-fixed, Paraffin-embedded Tissue

Transcriptional characterization and classification has potential to resolve the inter-tumor heterogeneity of colorectal cancer (CRC) and improve patient management. Yet, robust transcriptional profiling is difficult using formalin-fixed, paraffin-embedded (FFPE) samples, which complicates testing in clinical and archival material. We present MethCORR, an approach that allows uniform molecular characterization and classification of fresh-frozen and FFPE samples. MethCORR identifies genome-wide correlations between RNA expression and DNA methylation in fresh-frozen samples. This information is used to infer gene expression information in FFPE samples from their DNA methylation profiles. MethCORR was applied to methylation profiles from 877 fresh-frozen and FFPE samples and comparative analysis identified the same two major subtypes in four independent cohorts. Furthermore, subtype-specific prognostic biomarkers that better predicted relapse-free survival (HR=2.66, 95% CI [1.67-4.22], P<0.001) than TNM staging and MSI status were identified and validated using DNA methylation-specific PCR assays. The MethCORR approach is general, and may be similarly successful for other cancer types.

Study EGAS00001004293

Integrative Single-Cell Analysis of Transcriptome, Epigenome, and Lineage in HIV Latency and Activation

With the development of triple combination antiretroviral therapy, routine HIV treatment eliminates nearly all actively infected cells. Nevertheless, the small reservoir of latently infected cells, which can remain dormant for long periods of time before becoming active and producing new virus particles, represents a crucial barrier to completely curing the disease. Identifying markers that identify latently infected cells or the biochemical factors that control latency activation could enable the effective use of a “shock and kill” strategy, where specific targeting or activation of latently infected cells eliminates the viral reservoir. Our recent work suggests that the global transcriptomic and epigenomic changes during hematopoietic differentiation affect viral latency and activation. Additionally, we recently found that global inhibition of histone deacetylase activity increases viral activation in these cells, further implicating epigenomic changes during activation. These results raise fundamental questions: What are the markers of latently infected cells? How do the transcriptomic and epigenomic states of a cell affect latency and activation? How does the differentiation state relate to viral latency? Here, we leverage our experimental platform for identifying latently and actively infected cells, single-cell transcriptome and epigenome sequencing, and our recently developed computational integration methods to investigate these questions. Our interdisciplinary team combines expertise in HIV basic science, HIV clinical treatment, and bioinformatics to develop an experimental and computational framework for integrated gene expression, chromatin accessibility, and lineage into a single picture of viral latency and activation. Specifically, this project will (1) use single-cell RNA-seq and single-cell ATAC-seq to map the diversity of infected cells, (2) investigate the relationship between hematopoietic differentiation state and viral activation, (3) determine viral integration sites through single-cell RNA-seq, (4) computationally integrate single-cell transcriptome and epigenome profiles, and (5) computationally infer cell lineage relationships among viral genomes and infected cells. To accomplish these goals, we will carry out the following aims: (1) Characterize lineage, transcriptomic and epigenomic diversity of single latently and actively infected primary cells. (2) Investigate latency and activation during in vitro differentiation. (3) Survey single cell diversity of re-activated and in vitro infected cells from cART-suppressed patients. Together, these aims will produce a comprehensive, integrated transcriptomic and epigenomic atlas of the HIV reservoir, identify DNA and RNA biomarkers of latency, and characterize clonal expansion patterns. Our work also develops a broadly applicable experimental and computational framework, laying a foundation for the discovery of novel insights into HIV latency and activation.

Study phs002915

Similarity and diversity of the tumor microenvironment in multiple metastases: critical implications for overall and progression-free survival of high-grade serous ovarian cancer.

The tumor microenvironment is pivotal in influencing cancer progression and metastasis. Different cells co-exist with high spatial diversity within a patient, yet their combinatorial effects are poorly understood. We investigate the similarity of the tumor microenvironment of 192 local metastatic lesions in 61 ovarian cancer patients. An ecologically inspired measure of microenvironmental diversity derived from multiple metastasis sites is correlated with clinicopathological characteristics and prognostic outcome. We demonstrate a high accuracy of our automated analysis across multiple sites. A low level of similarity in microenvironmental composition is observed between ovary tumor and corresponding local metastases (stromal ratio r = 0.30, lymphocyte ratio r = 0.37). We identify a new measure of microenvironmental diversity derived from Shannon entropy that is highly predictive of poor overall (p = 0.002, HR = 3.18, 95% CI = 1.51-6.68) and progression-free survival (p = 0.0036, HR = 2.83, 95% CI = 1.41-5.7), independent of and stronger than clinical variables, subtype stratifications based on single cell types alone and number of sites. Although stromal influence in ovary tumors is known to have significant clinical implications, our findings reveal an even stronger impact orchestrated by diverse cell types. Quantitative histology-based measures can further enable objective selection of patients who are in urgent need of new therapeutic strategies such as combinatorial treatments targeting heterogeneous tumor microenvironment.

Study EGAS00001002065

Center for Common Disease Genomics [CCDG] - Inflammatory Bowel Disease (IBD) - Global Microbiome Conservancy Host Exomes

The human body is a complex ecosystem, hosting tens of billions of bacteria, primarily in the gut. This community, known as the 'gut microbiome', is vital to human health, affecting functions ranging from metabolism, immunity, and development, to behavior. Conversely, reduced microbiome diversity and other imbalances of the gut community (dysbiosis) are associated with many diseases of the industrialized world, such as metabolic syndrome, asthma, and inflammatory bowel diseases among others. Microbiome-based interventions thus hold the potential to revolutionize our understanding of, and therapeutic approaches to, many aspects of human health and disease. Despite many advances, current understanding of the human microbiome is largely limited to majority ethnic groups in industrialized nations, and does not reflect the full diversity of human commensal microbiota. In addition to the scientific ramifications of minority underrepresentation, there are significant translational and ethical implications as well: First, failing to capture the full diversity of healthy human microbiota may limit our ability to understand and generate effective therapeutics for many microbiome-associated diseases. Second, underrepresented groups are less likely to benefit from microbiome-based medical advances tailored to well-studied populations, propagating healthcare inequities. The window of opportunity to characterize human microbiome diversity is closing rapidly. Human gut microbial diversity is diminishing around the globe, due to the spread of Westernized diets and lifestyles, which are associated with reduced microbiome biodiversity. The Global Microbiome Conservancy (GMbC) is a non-profit collaboration between scientists and communities around the world that aims to 1) preserve the full biodiversity of the human gut microbiome, 2) characterize its evolution across populations and host lifestyles and 3) investigate its interactions with the human host. We are collecting gut microbiome and human DNA samples from diverse populations around the world, from isolated groups to urbanized populations, to culture and study this essential biodiversity and to preserve it in a living "seed bank" as a long-term safeguard against future extinctions. The National Human Genome Research Institute (NHGRI) has funded a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Called the Centers for Common Disease Genomics (CCDG), this initiative will explore a range of diseases with the ultimate goal of: Undertaking variant discovery for enough different examples of disease architectures and study designs to better understand the general principles of the genomic architecture underlying common, complex inherited diseases. Understanding how best to design rare variant studies for common disease. Developing resources, informatics tools, and innovative approaches and technologies for multiple disease research communities and the wider biomedical research community. The initial focus of the CCDGs will be in cardiovascular disease (early-onset coronary artery disease, atrial fibrillation, hemorrhagic stroke), neuropsychiatric disease (epilepsy, autism), and autoimmune/inflammatory disease (type 1 diabetes, inflammatory bowel disease). The Broad Institute is one of four selected CCDG project centers. Both exome and genotyping information of GMbC participants will help understanding how recruited human populations are structured and genetically related. This human genetic structure will be analyzed in light of gut microbiome compositional and genomic differences to illuminate associations between specific microbiome traits and human groups and the evolutionary processes involved in the co-evolution of human hosts and their gut microbiome. It will also provide variant information for critical genes shaping the composition of microbiomes, such as genes involved in innate and adaptive immunity (e.g. antimicrobial peptides) or in the regulation of the immune response (e.g. Nod2). Association studies between specific variants in these genes and microbiome features will be performed, which will then be validated with in vitro and in vivo experiments. Human data from GMbC cohorts will also increase the genetic diversity of human populations, providing additional variant information for many susceptible loci that were found to be associated with Crohn's disease and ulcerative colitis. The whole genome sequencing data generated is comprised of samples from diverse and indigenous populations. Raw sequencing data, metadata, vcf and phenotype data at the individual level for a subset of the cohort's samples are available at https://anvilproject.org/data. For questions about availability, contact help@lists.anvilproject.org. Microbiome data for the samples sequenced in this study can be found in phs002235 Global Microbiome Conservancy Sequence Data.

Study phs002205

University of Illinois at Chicago (UIC) Autism Centers of Excellence (ACE) Exome Sequencing Analysis

Autism spectrum disorder (ASD) is highly heritable with recent sibling recurrence risk estimates of 19% overall and 26% in males. The heritable phenotype of hyperserotonemia, or elevated levels of platelet serotonin (5HT), in ~35% of people with ASD is a well-established biomarker. The efficacy of drugs like risperidone and potent serotonin transporter inhibitors at treating behaviors related to Insistence on Sameness, along with evidence of the contribution of hyperserotonemia to autism susceptibility collectively support the hypothesis that dysfunction in the 5HT system is a significant etiological target for investigation of the genetic component to autism. ASD genetic architecture is complex; common variants of large effect do not contribute substantially to overall ASD risk, but there are clearly common variants with small effects and rare genetic/genomic variation of larger effect among ASD genetic risk factors. The NIH ARRA Autism Sequencing Consortium, including Dr. Sutcliffe and Dr. Cook among others, has initiated exome sequencing studies to identify more of the rare variants contributing to ASD. Data from our group and others reveal numerous rare de novo and inherited sequence mutations, and the number of de novo and other functional mutations that are found to affect molecules encoding 5HT signaling and its regulation further reinforces our hypothesis that regulation of serotonin levels is important in autism genetic susceptibility. Integrin receptor signaling pathways were prominently featured among identified de novo mutations, thus defining a set of interrelated gene networks that control 5HT signaling. We propose to extend our findings to date by conducting exome sequencing on ACE subjects, for whom we also have 5HT biochemical data, to identify rare variants (including CNVs) in 5HT-related gene networks. In total we propose to have exome sequencing completed on 523 samples. The purpose of the proposed research is two-fold: 1) we will conduct more extensive investigations to determine the support for the hypothesis that genetic variation at genes regulating platelet serotonin levels affect susceptibility to ASD and 2) we will combine the exome sequence data from these studies with sequence data for autism being accumulated in a variety of other research projects to further the goal of identifying and characterizing the genetic component to ASD.

Study phs000712

Whole Genome Association Study of Visceral Adiposity in the Health Aging and Body Composition (Health ABC) Study

The Health Aging and Body Composition (Health ABC) Study is a NIA-sponsored cohort study of the factors that contribute to incident disability and the decline in function of healthier older persons, with a particular emphasis on changes in body composition in old age. Between 4/15/97 and 6/5/98 the Health ABC study has recruited 3,075 70-79 year old community-dwelling adults (41% African-American), who were initially free of mobility and activities of daily living disability. The key components of Health ABC include a baseline exam, annual follow-up clinical exams, and phone contacts every 6 months to identify major health events and document functional status between clinic visits. The core yearly examination for HEALTH ABC includes measurement of body composition by dual energy x-ray absorptio-metry (DXA), walking ability, strength, an interview that includes self-report of limitations, and a medication survey, weight. At baseline, visceral adiposity was measured by computerized tomography (CT). Provision has been made for banking of blood specimens and extracted DNA (HealthABC repository). The overall goal of this project is to identify genetic determinants of visceral adiposity. Genetic samples from 2932 unrelated participants were evaluated with a genome-wide scan.

Study phs000169

A neoadjuvant, phase II trial demonstrates efficacy and tolerability of Talimogene laherparepvec in cutaneous basal cell carcinoma (NeoBCC trial)

We present a single arm, phase II neoadjuvant trial with the oncolytic virus Talimogene laherparepvec (T-VEC) in 18 patients with difficult-to-resect basal cell carcinomas. Six cycles of T-VEC were applied intralesionally. The primary endpoint of the study, defined as the proportion of the patients, who after six cycles of T-VEC (13 weeks) at the time point of surgery, become resectable with primary wound closure without the need for plastic reconstructive surgery like skin flaps or skin grafts, was achieved (9/18 patients; 50.0%). Secondary endpoints also included the relapse free survival rate (100%), overall survival (100%) and biological read outs in the tumor samples. T-VEC led to a significant increase of cytotoxic T cells, B cells and myeloid cells, and a decrease of Tregs within the tumor microenvironment. We observed a potent induction of antitumoral and antiviral T cell clones, as well as a strong humoral immune response. The objective response rate was 55.6% and the complete pathological response rate was 33.3%. Only mild adverse events occurred. Together, neoadjuvant T-VEC represents a viable treatment option for patients with difficult-to-resect BCCs (EudraCT Number 2018-002165-19).

Study EGAS50000000252

Childhood Cancer Data Initiative (CCDI): Pediatric In Vivo Testing Program –Sarcoma, Kidney, and Liver Cancers

The goal was to complete whole exome sequencing (WES) and RNA sequencing (RNA-Seq) on patient derived xenograft samples. Cancer in children is rare with approximately 15,700 new cases diagnosed annually in children 21 years or younger in the U.S. Through use of multimodality therapy (surgery, radiation therapy, and aggressive chemotherapy), 70% of patients will be 'cured' of their disease, and 5-year Event-Free Survival (EFS) exceeds 80%. Consequently, the number of patients that can be enrolled in phase I/II clinical trials is small, and most patients will have been extensively treated, hence drug/radiation resistant. Thus, preclinical studies that accurately translate into effective clinical therapy are an essential component of pediatric drug development. Our group has contributed to studies in the Pediatric Preclinical Testing Program (PPTP) and Pediatric Preclinical Testing Consortium (PPTC) that have led to clinical studies through Children's Oncology Group (COG). Of importance, we have developed and characterized over 330 Patient Derived Xenografts (PDX), developed from tumors both at diagnosis and relapse, that can be used to facilitate pediatric drug development as directed by FDA under the Research to Accelerate Cures and Equity for Children Act (RACE for Children Act).

Study phs003160

APOBEC3 mutagenesis drives therapy resistance in breast cancer

Acquired genetic alterations commonly drive resistance to endocrine and targeted therapies in metastatic breast cancer, however the underlying processes engendering these diverse alterations are largely uncharacterized. To identify the mutational processes operant in breast cancer and their impact on clinical outcomes, we utilized a well-annotated cohort of 3,880 patient samples with paired tumor-normal sequencing data. The mutational signatures associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) enzymes were highly prevalent and enriched in post-treatment compared to treatment-naïve hormone receptor-positive (HR+) cancers. APOBEC3 mutational signatures were independently associated with shorter progression-free survival on antiestrogen plus CDK4/6 inhibitor combination therapy in patients with HR+ metastatic breast cancer. Whole genome sequencing (WGS) of breast cancer models and selected paired primary-metastatic samples demonstrated that active APOBEC3 mutagenesis promoted resistance to both endocrine and targeted therapies through characteristic alterations such as RB1 loss-of-function mutations. Evidence of APOBEC3 activity in pre-treatment samples illustrated a pervasive role for this mutational process in breast cancer evolution. The study reveals APOBEC3 mutagenesis to be a frequent mediator of therapy resistance in breast cancer and highlights its potential as a biomarker and target for overcoming resistance.

Study EGAS50000000875

Examination of Engineered LINE-1 Integration Events in HeLa Cells

Long Interspsesed Element-1 (LINE1 or L1) encodes two proteins (ORF1p and ORF2p) required for its mobilization (i.e. retrotransposition) in the human genome. Human ORF2p, a 150kDa protein, has endonuclease (EN) and reverse transcriptase (RT) activities. L1 EN is classified as apurinic/apyrimidin-like endonuclease (APE) and is responsible for initiating target-site primer reverse transcription (TPRT) during the L1 retrotransposition cycle. During canonical TPRT, the L1 EN activity makes a single-strand endonucleolytic nick at a double-strand DNA target sequence in genomic DNA. The endonucleolytic nick is typically made at an L1 EN degnerate consensus cleavage sequence (5'-TTTT/A-3') exposing a free 3' hydroxy group that can be used as a primer by the ORF2p L1 RT activity to reverse transcribe the associated L1 RNA. Here, we characterized over 21,000 de novo engineered L1 retrotransposition events in HeLa cells to determine if L1 exhibits overt integration preferences in the human genome. Bru-seq of HeLa cells to determine actively transcribed regions of the genome was also performed. This Bru-seq data was used to determine if engineered L1 integration events preferentially integrate into transcribed regions of the genome, and to determine which strand during transcription may present itself as preferential during L1 retrotransposition.

Study phs001669

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

eIMPACT Trial: Modernized Collaborative Care to Reduce the Excess CVD Risk of Older Depressed Patients

Cardiovascular disease (CVD) is the #1 killer of American men and women, and its economic burden is substantial and on the rise. Adults with depression are at elevated risk of CVD events and poor CVD prognosis. Unfortunately, past clinical trials of depression treatments have not observed the anticipated cardiovascular benefits. A novel explanation for these null results is that the depression interventions in these trials, which all involved patients with preexisting CVD, were delivered too late in the natural history of CVD. Accordingly, the objective of this single-center, parallel-group, assessor-blinded randomized controlled trial was to determine whether successful depression treatment before, versus after, the onset of clinical CVD reduces CVD risk in depression. Primary care patients with depression and elevated CVD risk from a safety net healthcare system (N = 216, Mage = 59 years, 78% female, 50% Black, 46% with income <$10,000/year) were randomized 1:1 to 12 months of the eIMPACT intervention (a modernized collaborative stepped care program involving internet cognitive-behavioral therapy [CBT], telephonic CBT, and/or select antidepressants) or usual primary care for depression (primary care providers supported by embedded behavioral health clinicians and psychiatrists). The primary outcome was endothelial dysfunction (brachial flow-mediated dilation) at 12 months, and the secondary outcomes were self-reported depressive symptoms (Hopkins Symptom Checklist-20), autonomic dysfunction (high-frequency heart rate variability), systemic inflammation (interleukin-6 and high-sensitivity C-reactive protein), and platelet activation (β-thromboglobulin and platelet factor 4) at 12 months. The central hypothesis was that the eIMPACT intervention would improve endothelial dysfunction in depressed adults by decreasing depressive symptoms, autonomic dysfunction, systemic inflammation, and platelet activation. Primary results are posted to ClinicalTrials.gov at NCT02458690. The de-identified limited dataset available on BDC consists of only the individual phenotypic data needed to confirm this trial’s primary results – i.e., randomization status, primary and secondary outcome variables, and participant characteristics utilized in the hypothesis-testing models (age, sex, race, education, income, and systolic blood pressure). We also provide the SAS code to replicate the results of the hypothesis-testing models reported in Table 4 and Supplemental Tables 1-3 in the main outcomes paper (#2 in Selected Publications). Of note, the user will need to specify the file path for the dataset to run the SAS code. Instructions for requesting individual-level data are available on BDC at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BDC. For questions about availability, you may contact the BDC team at https://biodatacatalyst.nhlbi.nih.gov/contact.

Study phs003283

Efficacy of a Therapeutic Treatment Trial in Angelman Syndrome

This study has been designed to evaluate the possible therapeutic benefits of L-5-methyltetrahydrofolate (Metafolin), vitamin B12, creatine and betaine in children with Angelman Syndrome (AS). This study is based on the hypotheses 1) that dietary manipulation may increase global DNA methylation; 2) that increased methylation of the paternal chromosome in AS participants may increase expression of the Angelman gene causing clinical benefit; and 3) that dietary interventions with Metafolin in conjunction with creatine, betaine, and vitamin B12 would represent little risk, but some chance for benefit. The dietary regimen is felt to be quite benign and safe. The clinical response will be measured by recording: changes in seizure activity, changes in communication skills, changes in developmental skills and changes in behavioral patterns as indicated by formal developmental assessments and clinical evaluations. We will assess the progress of the participants by monitoring their changes from baseline throughout their participation in the study and measure their improvement in particular in the developmental parameters. As a secondary aim, we plan to measure the biochemical response to these compounds by obtaining levels of homocysteine, methionine, S-adenosyl-methionine (SAM), and S-adenosyl-homocysteine (SAH). The molecular response will be measured by global DNA methylation analysis. As an exploratory aim, we hope to use control data we have previously obtained from a double blind placebo-controlled trial done in the past using betaine and folic acid to compare the development of those children who have and those who have not received medications. More specifically, we wish to compare differences in the rate of development for those children who have never received study medications (from the first trial) with those who have received medications from the present trial. Developmental parameters used in the previous trial will be consistent with those used in the present trial in order to permit these comparisons. The previous trial was conducted at Baylor College of Medicine, Rady San Diego Children's Hospital and Boston Children's Hospital whereas a group of AS participants received folic acid and betaine or placebo in a randomized double-blind basis. All the participants for the study will include patients who have a documented molecular diagnosis of AS. The participants will be seen at Baylor College of Medicine, Rady Children's Hospital of San Diego, Boston Children's Hospital and the Greenwood Genetics Center at 0 months and at 12 months for follow-up. Clinical and relevant historical data will be collected during the clinical visit and examination and also by reviewing medical and laboratory records. This information will then be entered into a HIPAA compliant clinical research database.

Study phs000701

WGS data of paediatric TCF3::PBX1 acute lymphoblastic leukemia (set2)

The dataset includes FASTQ and BAM files from diagnostic and matched remission (control) samples of one TCF3::PBX1 ALL patient (ALLT-376). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using NEB Next® Ultra™ DNA Library Prep Kit. Both diagnostic (90x) and remission (30x) samples were sequenced using HiSeq X.

Dataset EGAD50000001795

WGS data of paediatric BCR::ABL1 acute lymphoblastic leukemia

The dataset includes FASTQ and CRAM files from diagnostic and matched remission (control) samples of one BCR::ABL1 ALL patient (ALLT-399). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using Novogene NGS DNA Library Prep Set Kit (Cat No. PT004). Both diagnostic (90x) and remission (30x) samples were sequenced using NovaSeqX Plus.

Dataset EGAD50000002185

WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set5)

The dataset includes FASTQ and BAM/CRAM files from diagnostic and matched remission (control) samples of two B-other ALL patients (ALLT-396, ALLK-131). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using Novogene NGS DNA Library Prep Set. Both diagnostic (90x) and remission (30x) samples were sequenced using NovaSeqX Plus.

Dataset EGAD50000002160

The dataset of Detection and characterization of lung cancer using cell-free DNA fragmentomes on NovaSeq 6000 at 1-2x coverage

The dataset contains 364 CRAM files from whole-genome next-generation sequencing on the Illumina NovaSeq 6000 at 1- 2x coverage. These are plasma samples from healthy individuals and patients with cancer.

Dataset EGAD50000001961

WGS data of paediatric hyperdiploid B cell acute lymphoblastic leukemia (set2)

The dataset includes FASTQ and BAM files from diagnostic and matched remission (control) samples of two hyperdiploid ALL patients (ALLT-315, ALLT-320). Sequencing libraries were made using PCR free-based WGS library preparation (PCR-), using TruSeq DNA PCRfree library preparation kit v1. Both diagnostic (60x) and remission (30x) samples were sequenced using Illumina HiSeq X.

Dataset EGAD50000002426

Biomodal duet +modC sequencing of endometrial cancer plasma cfDNA samples

This dataset contains biomodal sequencing data generated using the duet + modC assay from plasma-derived cell-free DNA of endometrial cancer patients and healthy donors. Sequencing was performed on an Illumina NovaSeq 6000. Dataset includes raw sequencing FASTQ files. Duet +modC output enables whole-genome profiling of both genetic variation and DNA methylation.

Dataset EGAD50000002261

TruSight Oncology 500 ctDNA targeted sequencing data from endometrial cancer patients

This dataset contains targeted sequencing data generated using the TruSight Oncology 500 ctDNA v2 assay from plasma-derived cell-free DNA of dMMR endometrial cancer patients, at baseline and C3D1 of immunotherapy. Sequencing was performed on Illumina NovaSeq600. Dataset includes aligned sequencing files in BAM format generated using the DRAGEN TruSight Oncology 500 ctDNA v2.6.0 analysis pipeline.

Dataset EGAD50000002262

De novo mutations in cell-free foetal DNA - Pulldown experiment

A pulldown experiment with Agilent SureSelect probes designed on regions that were more likely to contain de novo mutations. 266 candidate sites were selected based on whole genome sequencing data. The probes also included the exons of genes that have been identified as neurodevelopmental disorder genes in DDD (the DDG2P genes) 1,336 targets. In addition, the design included the standard iPLEX sites.

Dataset EGAD00001002265

Circulating tumour DNA abundance and potential utility in de novo metastatic prostate cancer

We set out to determine ctDNA abundance at de novo mCSPC diagnosis and whether ctDNA provides complementary clinically relevant information to a prostate biopsy. We collected and sequenced 77 plasma cell-free DNA samples from 53 newly diagnosed patients with mCSPC. Targeted sequencing was also performed on DNA from 48 diagnostic prostate tissue samples.

Dataset EGAD00001004526

lymphoma plasma cfRNA

Dataset contains total RNA sequencing data from plasma of 65 different human donors: 30 diffuse large B-cell lymphoma (DLBCL) and 13 primary mediastinal large B-cell lymphoma (PMBCL) patients, and 22 cancer-free controls. Samples were sequenced on a NovaSeq 6000 and are provided in FASTQ format.

Dataset EGAD00001010259

Programmatic submission based on XML

Programmatic submissions (XML based) For further information please check our Submission FAQs, submission quickguide as well as submission terms! Introduction Besides the Submitter Portal tool, EGA supports programmatic sequence and clinical data metadata submissions. If you are not sure what this means, you may want to explore our brief metadata introduction. Programmatic submissions are recommended for array-based submission. Moreove, it may be of help if your submission is recurrent or it is difficult to manage manually due to its sheer size. Otherwise, we highly recommend using the Submitter Portal to perform submissions. In this page we will guide you through the required steps to programmatically submit data to the EGA. Programmatic submissions require your metadata to be structured for an easy and straightforward validation and archival. It basically consists in formatting your metadata as Extensible markup language (XML) files and submitting them to the EGA using the WEBIN Before submitting metadata to the EGA, it is important to ensure that the information in your XML files is compliant with our standards. You can see further details on how these standards are maintained at EGA at our EGA Schemas documentation page. Using WEBIN, you can validate your XML files against EGA's schemas to ensure that your metadata is compliant before submission. WEBIN services WEBIN production service WEBIN test service We advise you to submit your metadata to the test service when submitting to the production service for the first time. The test service is identical to the production service except that all submissions will be discarded in the following 24 hours. This allows you to learn about the submission process without having to worry about data being submitted. Authentication Authentication is required each time a submission is made. The submission service uses HTTPS protocol for metadata encryption and identification to provide a secure submission environment. Data file upload Both Runs and Analyses reference files (e.g. FASTQ need to be uploaded to the EGA before these metadata objects are submitted. In other words, if you submit a Run that references a file that we cannot find associated with your account, the metadata submission will fail. See further details on how to upload your files in our File Upload documentation. Metadata model of the EGA Our metadata model is formed by multiple metadata objects. Check further details in our documentation at our EGA Schema documentation page. Working with EGA XMLs files Now that the basic concepts of the EGA metadata have been described, you can start preparing your programmatic submission through XML. Here you will find the guidance on how to prepare the XML files. Programmatic Submission Tutorial Video Take a look at the Programmatic Submission Tutorial Video, which explains the workflow of a programmatic submission and goes over an example metadata submission. Programmatic Submission Tutorial Video. When building your XML files, we recommend using text editors (e.g.Sublime Text or VisualStudio) that allow you to visualise the structure of the XML with ease. Furthermore, these editors constantly check the consistency of the XML structure. Alternatively, and if the submission consists of a big number of objects (specially analyses), you may find the tool star2xml handy. This tool allows for a direct conversion between metadata in a tabular format (e.g. a spreadsheet) into XMLs. Identifying objects: Aliases and center names Every EGA object must be uniquely identified within the submission account using their alias attribute. The aliases can be used in submissions to make references between EGA objects. Let us dig into EGA's use of aliases and center names: alias: every object should have a name that is unique within your submission account. Once submitted successfully, every alias will be assigned a unique and permanent accession (EGA ID). refname: when an object references another by its alias, the alias of the referenced object goes into the "refname" attribute of the referencing object. For example, if a sample has the alias "sample1", and an experiment uses this sample, then the experiment's "EXPERIMENT/SAMPLE/refname" attribute should be "sample1". center_name: The "center_name" attribute is required within the submission XML and, if not provided when the object is submitted, it will be automatically filled using your default EGA account center_name. This element is the "controlled vocabulary acronym or abbreviation that is provided to the account holder when the account is first generated". If the submitter is brokering a submission for another institute, the submitter should use their special broker account name in broker_name while the data centre acronym remains in center_name. Log-in details should have been provided when you requested a submission account. Please contact our Helpdesk team if you have any questions. run_center: Many submitting centers contract out the actual sample sequencing to another center. In these cases, the sequencing center should be acknowledged in the run_center attribute. Again, this is controlled vocabulary and the acronym should be sought from EGA helpdesk before submitting. Please contact our Helpdesk team if you have any questions. Prepare your XMLs The goal of this section is to provide sufficient information to be able to create the metadata XML documents required for programmatic submissions. Please note, the EGA utilises the XML schemas maintained at the European Nucleotide Archive (ENA). It is important due to the fact that by using a similar system, some pieces of documentation from the ENA's programmatic submission can also help you with your programmatic submission to the EGA. For example, you can submit programmatically without using a Submission XML by following the steps at Submission actions without submission XML. A submission does not have to contain all different types of XMLs. For example, it is possible to submit only a few samples; or a study that is later to be referenced. You can submit each object one by one, or submit all in a batch: you choose what method of submission works best for you. We do recommend, nevertheless, that you submit the objects to be referenced (e.g. samples or studies) first, and the objects that reference these (e.g. experiments or datasets) afterwards. You can see a graphical view of these objects and their relationships at our EGA Schemas page. Independently of the submission scenario, you will always require a Dataset XML. The entity of a dataset is what is used to control access to the given data, in the form of runs or analyses. In other words, when a requester is granted access, it is through the dataset and the objects (e.g. runs or analyses) that the dataset contains, granting access to them in one go. Given the nature of the EGA, a dataset XML will always be required for the data access. First, we will differentiate between submissions of "raw" and "processed" data: Runs and Analyses, respectively. Run data submissions Raw data derives from instruments "as is". For example, a plain sequence file (e.g. FASTQ or unaligned BAM files) would be considered raw data. A typical raw (unaligned) sequence read submission consists of 8 XMLs: Submission Study Sample Experiment Run DAC Policy Dataset When technical reads (e.g. barcodes, adaptors or linkers) are included in the submitted raw sequences, a spot descriptor must be submitted to describe the position of the technical reads so that they can be removed. The following data files can be submitted without providing spot descriptor information in the experiment/run XML: BAM files (single reads) SFF files (single reads without barcodes) FastQ files (single reads without any technical reads) Complete Genomics files Analysis data submissions Processed data is, in some way, refined raw data. This includes raw data that has been processed by some form of analysis method (e.g. alignment, noise reduction, etc.). For example, an aligned sequence (e.g. BAM file), that was created using raw FASTQ files, would be a processed file. This category includes most types of data: sequence alignment files (e.g. BAM or CRAM), clinical data (e.g. phenopackets), sequence variation files (e.g. VCF), sequence annotation, etc. A typical EGA analysis data submission consists of 7 EGA XML: Submission Study Sample Analysis DAC Policy Dataset We accept three different types of analysis data submissions: BAM files (for multiple read alignments) VCF files (for sequence variations) Phenotype files (in any format) In anycase, keep in mind that samples must be created in order to be referenced in the analyses. In other words, the provenance of the information within the BAM, VCF and phenotype files Example XMLs Below you can find a non-extensive list of example XMLs with descriptive fields (i.e. explaining what to provide in each field). Furthermore, you can also find real examples (i.e. the true value of the provided fields) in our GitHub repository. Submission XML The submission XML is used to validate, submit or update any number of other objects. The submission XML refers to other XMLs. New submissions use the ADD action to submit new objects. Object updates are done using the MODIFY action and objects can be validated using the VERIFY action. Descriptive submission XML example True values submission XML example Study XML The study XML is used to describe the study containing a title, a study type and abstract as it would appear in a publication. Descriptive study XML example True values study XML example Please use the following notation within the property "STUDY_LINKS" when including PubMed citations in the Study XML: <STUDY_LINKS> <STUDY_LINK> <XREF_LINK> <DB>PUBMED</DB> <ID>18987735</ID> </XREF_LINK> </STUDY_LINK> </STUDY_LINKS> Sample XML The sample XML is used to describe the samples used to obtain the data, whether they were sequenced, measured in any other way, or have an associated phenotype. The mandatory fields include information about the taxonomy of the sample, sex, subject ID and phenotype. For example, the mandatory attribute fields for each sample would look like these, within the array of "SAMPLE_ATTRIBUTES": <SAMPLE_ATTRIBUTES> <SAMPLE_ATTRIBUTE> <TAG>subject_id</TAG> <VALUE>free text!</VALUE> </SAMPLE_ATTRIBUTE> <SAMPLE_ATTRIBUTE> <TAG>sex</TAG> <VALUE>female/male/unknown</VALUE> </SAMPLE_ATTRIBUTE> <SAMPLE_ATTRIBUTE> <TAG>phenotype</TAG> <VALUE>Free text, EFO terms (e.g. EFO:0000574) are recommended</VALUE> </SAMPLE_ATTRIBUTE> </SAMPLE_ATTRIBUTES> Sample is one of the most important objects to be described biologically, it is highly recommended that “TAG-VALUE” pairs are generated as SAMPLE_ATTRIBUTES to describe the sample in as much detail as possible. For example, were we to give the population ancestry of the sample, we could add a new attribute to the array, in which, for example, we would indicate that the sample derives from an individual of "Mende in Sierra Leone" (MSL), with an african ancestry: <SAMPLE_ATTRIBUTE> <TAG>Population</TAG> <VALUE>MSL</VALUE> </SAMPLE_ATTRIBUTE> Given that VALUE and TAG are free text, the combinations are limitless in order to give you full flexibility on the information you want to provide. We recommend you use the Experimental Factor Ontology (EFO) to describe the phenotypes of your samples. You can provide more than one phenotype by adding more items to the array of SAMPLE_ATTRIBUTES. Phenotypes considered essential for understanding the data submission should be provided. Each phenotype described should be listed as a separate sample attribute <SAMPLE_ATTRIBUTE> </SAMPLE_ATTRIBUTE>. There is no limit to the number of phenotypes that can be submitted. If a suitable EFO accession cannot be found for your phenotype attribute, please consider using another controlled ontology database (e.g. HPO, MONDO, etc.) before using free text. Descriptive sample XML example True values sample XML example Experiment XML The experiment XML is used to describe the experimental setup, including instrument platform and model details, library preparation details, and any additional information required to correctly interpret the submitted data. Where any of these values differ between runs, a new experiment object must exist, since runs are grouped by experiments. Each experiment references a study and a sample by alias, or if previously-submitted, by accession. Pooled data must be demultiplexed by barcode for submission. Descriptive experiment ( Illumina paired read ) XML example True values experiment ( Illumina paired read ) XML example Run XML The run XML is used to associate data files with experiments and typically comprises a single data file (e.g. a FASTQ file). Please note that pooled samples should be de-multiplexed prior submission and submitted as different runs. Descriptive run XML example True values run XML example Analysis XML Given that an analysis can be used to submit any type of processed data to the EGA, we will list below an example of each of the three most common types of analysis XMLs submitted to the EGA: sequence alignments (e.g. BAM files); sequence variation (e.g. VCF files); and clinical metadata or phenotypes (e.g. phenopackets). Regardless of the type of processed data submitted in the analysis, the analysis must be associated with a Study and can reference multiple types of other objects, from samples to experiments, if they are available at the EGA. Just like with Runs, whenever a file is submitted to the EGA through an analysis object, the file MD5 checksums must be present, in order for the EGA to validate file integrity upon transfer. This also includes index files when applicable (e.g. .bai.md5 files). Ideally, any analysis that uses a reference sequence for some kind of alignment (e.g. BAM, CRAM or VCF files), would contain metadata about the alignment, such as INSDC reference assemblies and sequences, by either using accessions (e.g. CM000663.1) or common labels (e.g. GRCh37). Read alignment (BAM) Analysis XML The Analysis can be used to submit BAM alignments to EGA. Only one BAM file can be submitted in each analysis and the samples used within the BAM read groups must be associated with Samples. Descriptive bam alignments XML example True values bam alignments XML example Sequence variation (VCF) Analysis XML The Analysis can be used to submit VCF files to EGA. Only one VCF file can be submitted in each analysis and the samples used within the VCF files must be associated with Samples. Download analysis XML (VCF) Phenotype files The Analysis XML can be used to submit phenotype files to the EGA. Only one phenotype file can be submitted in each analysis and the samples used within the phenotype files must be associated with EGA Samples. Download analysis XML (Phenotype) DAC XML The DAC XML describes the Data Access Committee (DAC) affiliated to the data submission. The DAC may consist of a group or a single individual and is responsible for the data access decisions based on the application procedure described in the POLICY.XML. As with any other object, if it was already submitted to the EGA, there is no need to submit it again: you can reference an existing object within the EGA. Hence, A DAC XML does not need to be provided if your submission is affiliated to an existing EGA DAC.. Further information on DACs can be found here, and you can always contact our Helpdesk team if you have further inquiries. Descriptive dac XML example True values dac XML example Policy XML The Policy XML describes the Data Access Agreement (DAA) to be affiliated to the named Data Access Committee. Descriptive policy XML example True values study XML example Dataset XML The dataset XML describes the data files, defined by the Run.XML and Analysis.XML, that make up the dataset and links the collection of data files to a specified Policy. The dataset xml is commonly the last metadata object to be submitted, since it references multiple other entities. Please consider the number of datasets that your submission consists of. For example, a case-control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Descriptive dataset XML example True values dataset XML example Validating and submitting your EGA Validating EGA's XMLs through Webin After you have ensured that the XMLs are properly formatted and contain all the required information. You can proceed to validate and submit your data. Use the curl command to validate your XML file: Once you have prepared your XML file and asserted you have access to Webin, you can validate your XML file programmatically against EGA's schemas using the curl command. There are multiple ways in which you can validate your XMLs. This variety has to do with the fact that: (1) there are 2 instances of Webin (test and production); and (2) that validation is a default step during submission. In other words, any time that you submit your data through Webin, it will be validated automatically before being accepted. This allows for 4 possible routes of validation, all having the same validation result: validating or submitting to either the production service or the test service of Webin. For example, directly validating a "study" object XML in the testing service (wwwdev…) would look like the following: curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" In this command, you would need to replace <USERNAME> and <PASSWORD> with your EGA account username and password, respectively. You would also replace <INPUT_FILE> with the path to your XML file. A mock example would look like the following: curl -u ega-test-data@ebi.ac.uk:egarocks -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" The validation attempt can have different results depending on the given arguments: If your XML file is valid according to EGA's schemas, you will see a message indicating that your XML file is compliant. For example, see below for our mock example, where the "success" was "true" (i.e. no validation errors found). Nevertheless, notice how the "<STUDY accession=" is empty: it is because we were simply validating, so the study did not get an accession or ID. <?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="receipt.xsl"?> <RECEIPT receiptDate="2023-04-11T15:19:28.850+01:00" submissionFile="submission-EBI-TEST_1681222768850.xml" success="true"> <STUDY accession="" alias="Mock example" status="PRIVATE"/> <SUBMISSION accession="" alias="SUBMISSION-11-04-2023-15:19:28:840"/> <MESSAGES> <INFO>VALIDATE action has been specified.</INFO> <INFO>Submission has been rolled back.</INFO> <INFO>This submission is a TEST submission and will be discarded within 24 hours</INFO> </MESSAGES> <ACTIONS>VALIDATE</ACTIONS> <ACTIONS>PROTECT</ACTIONS> If there are any errors or warnings, the tool will display them, allowing you to correct them before submitting your data to EGA. For example, in the following response, it is said that the object we were trying to submit was already existing, and therefore the "success" was "false". <?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="receipt.xsl"?> <RECEIPT receiptDate="2023-04-11T15:12:35.609+01:00" submissionFile="submission-EBI-TEST_1681222355609.xml" success="false"> <STUDY alias="Example!_Human Microbiome Project SP56J" status="PRIVATE" holdUntilDate="2023-03-11Z"/> <SUBMISSION alias="SUBMISSION-11-04-2023-15:12:35:576"/> <MESSAGES> <ERROR>In study, alias: "Example!_Human Microbiome Project SP56J". The object being added already exists in the submission account with accession: "ERP127584".</ERROR> <INFO>VALIDATE action has been specified.</INFO> <INFO>Submission has been rolled back.</INFO> <INFO>This submission is a TEST submission and will be discarded within 24 hours</INFO> </MESSAGES> <ACTIONS>VALIDATE</ACTIONS> <ACTIONS>PROTECT</ACTIONS> If the curl command retrieves no response at all, please double check if your username and password are correctly provided. Also notice the "ACTION=..." argument passed to the Curl command. This specifies the action to take during the call to Webin, so we do not need a "Submission" XML just for a validation attempt. See more at submission actions without submission XML. Furthermore, validation of multiple files or objects (e.g. sample, experiment, study…) can be done in a single command by adding more arguments (i.e. '-F'). For example: curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" -F "SAMPLE=@sample.xml" -F "DATASET=@dataset.xml" As mentioned above, beside "validate" action in the test environment, you can also validate your metadata by three other methods: "Validate" in the production server. From our example above, you simply need to take the "dev" away from the URL. curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://www.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" "Add" in the development server. From our example above, you would simply need to replace the action: from "validate" to "add". Whatever is submitted to this service will be discarded in 24h, so whether something gets submitted or not would not matter in the long run. curl -u <USERNAME>:<PASSWORD> -F "ACTION=ADD" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" "Add" in the productionserver. A combination of the previous two methods, which would render this attempt into a submission. This path is just to be taken when you are sure your metadata is compliant and what you want to submit. curl -u <USERNAME>:<PASSWORD> -F "ACTION=ADD" "https://www.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" What happens after the submission of a dataset XML? Once you have completed the registration of your dataset/s please contact our Helpdesk Team to provide a release date for your study. Please note that all datasets affiliated to unreleased studies are automatically placed on hold until the authorised submitter or DAC contact contact the EGA Helpdesk for the study to be released. We strongly advise you not to delete your data until EGA Helpdesk confirms that your data has been successfully archived.

Documentation submission/metadata/submission/programmatic-submission-xml

Comprehensive molecular and clinicopathological profiling of lung adenocarcinoma in Japanese never or light smokers

Studies have yet to characterize the differences in molecular profiles of lung adenocarcinoma (LUAD) among divergent ethnic groups. Herein, we conducted comprehensive molecular profiling of LUAD in never or light smokers from Asia in order to discover novel targetable mutations and prognostic biomarkers of this distinct disease entity. Methods: We analyzed 996 cases of Asian LUAD, and performed whole-exome sequencing and/or RNA-seq in 125 cases of Asian LUAD negative for the driver oncogenes defined by conventional laboratory testing. We also investigated the clinical and pathological characteristics among the 996 cases. Results: Driver oncogenes were identified in 88 cases (70.4%) with specific hotspot mutations differing from those in The Cancer Genome Atlas (TCGA) study. Clustering based on mRNA expression profiles, but not genetic mutational ones, could predict patient prognosis. The risk score generated by the expression of a three-gene set was a strong prognostic marker for overall survival and progression-free survival in our cohort, and was further validated using TCGA cohort. Among the 996 cases, each driver alteration is distributed across all histological subtypes. Adenocarcinoma in situ was identified to harbor driver mutations, suggesting that these alterations are early events in the pathogenesis of LUAD. This study indicates the value of applying gene expression profiling for predicting the prognosis after a surgical operation, and that the identification of actionable mutations is important for optimizing targeted drugs in Japanese LUAD.

Study JGAS000215

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

Key objective Are the prognostic transcriptomic G1/G2 gene expression signature, MYC overexpression, and MYC amplification replicable stratifying biomarkers for future clinical trials in high-grade osteosarcoma? Knowledge gathered In an unselected cohort, the G2 gene expression signature and MYC overexpression, but not MYC amplification, were independently associated with poor event-free and overall survival. Relevance Transcriptomic biomarkers may serve as stratifying factors that guide the management of patients with high-grade osteosarcoma. Current data underlines the importance of prospective validation of the G1/G2 signature and MYC overexpression in an international, multicenter, study.

Dataset EGAD00001015502

Influence of the Microbiome on Epigenetic Mechanisms in IBD

Live CD4 T cells were sorted from inflamed and non-inflamed tissue samples of IBD patients or from healthy and IBD blood samples. ATAC-Seq libraries were generated from live CD4 T cells sorted from i) inflamed and non-inflamed tissue samples, ii) healthy and IBD blood samples, or from iii) CD4 T cell subsets polarised from healthy blood samples. After isolating crude nuclei, live CD4+ T cells were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry. On the other hand, single cell RNA-Seq libraries were generated exclusively from inflamed and non-inflamed tissue samples of Crohn’s disease patients. Briefly, live CD4 T cells were captured and encapsulated before cDNA amplification using the 10X Genomics Chromium Platform. Samples were prepared as outlined by 10x genomics Single Cell 3’ Reagent Kits v2 user guide. Samples were sequenced on a HiSeq 2500 with the following run parameters: Read 1 – 26 cycles, read 2 – 98 cycles, index 1 – 8 cycles.

Dataset EGAD00001011066

Tumor Fraction Guided Cell-Free DNA Profiling in Metastatic Cancer Patients

Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e cfDNA tumor fraction). We hypothesized that cfDNA tumor fraction could inform the interpretation of negative cfDNA results and guide the choice of subsequent assays of greater genomic breadth or depth. Plasma samples collected from 118 metastatic cancer patients were analyzed with cf-IMPACT, a modified version of the FDA-authorized MSK-IMPACT tumor test that can detect genomic alterations in 410 cancer-associated genes. Shallow whole genome sequencing (sWGS) was also performed in the same samples to estimate cfDNA tumor fraction based on genome-wide copy number alterations using z-score statistics. The results show that cfDNA tumor fraction can inform the interpretation of negative cfDNA results and guide the selection of subsequent sequencing platforms that are most likely to identify clinically-relevant genomic alterations.

Study phs002290

Whole genome sequencing

Whole genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from 15 patients with homologous recombination deficiencies. The dataset includes fastq files from 56 HGSC tumours (1 primary, 1 relapse, 54 end-stage) and 15 matched normals. Sequence libraries were generated from tumour and matched normal genomic DNA using the KAPA HyperPrep PCR-free library preparation kit (Roche), or the Illumina TruSeq DNA Nano kit according to manufacturer’s instructions. Sequencing was carried out by the Kinghorn Centre for Clinical Genomics Sequencing Laboratory (Sydney, Australia) on the HiSeq X Ten System (Illumina) or by the Australian Genome Research Facility (Melbourne, Australia) on an Illumina NovaSeq to a minimum base coverage of 30-fold for normal DNA and 60-fold for tumour DNA samples.

Dataset EGAD00001009746

Atherosclerosis Risk in Communities Study (ARIC-BioLINCC)

Data Access NOTE:Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. At present, the ARIC sIRB has determined that ARIC data cannot be shared with for-profit entities.Related Studies Other ARIC data available include: Imaging studies (ARIC-Imaging), Genetics and genomics (ARIC, phs000280.v8.p2), Collaborative Cohort of Cohorts for COVID-19 Research (C4R): ARIC (phs002988.v1.p1), and as a component of the Sleep Heart Health Study (SHHS-BioLINCC, phs003637.v1.p1). Available Data Data available for request include ARIC v1-v8 examination cycles, collated annual follow-up communication data for contact years 2-32, and follow-up for mortality, heart disease, and stroke events through 2019. Also included are data from ancillary studies. Objectives The objectives of ARIC are to: 1) investigate associations of factors, including those not previously measured in cohort studies, with prevalence of atherosclerosis and incidence of CHD, clinical stroke and other cardiovascular diseases; and 2) measure cardiovascular disease occurrence and trends and relate these to community levels of, and changes in, risk factors, medical care and atherosclerosis. Background At the time of project initiation, the NHLBI had long recognized the need for longitudinal studies to identify the biochemical and physiological markers and specific environmental factors which place individuals at high risk for the major atherosclerosis diseases. The development of reliable ultrasound examination of peripheral arteries enhanced the expected benefit of such studies. Community surveillance planning began for ARIC in response to recommendations of the 1978 NHLBI Workshop on the Decline in CHD Mortality and has been extended in its purpose to evaluate the large geographic differences in U.S. mortality. Participants Black and white men and women, age 45-64 at entry; sample size: 15,792. Design ARIC is a large-scale, long-term prospective study that measures associations of established and suspected coronary heart disease risk factors with both atherosclerosis and new CHD events in men and women from four geographically diverse communities. The project has two components: community surveillance of morbidity and mortality; and repeated examinations of a representative cohort of men and women in each community. The community surveillance involves abstracting hospital records and death certificates and investigating out-of-hospital deaths. The representative cohorts include approximately 4,000 persons from each community. Community surveillance data includes detailed hospital record abstraction, ECG tracings, and event adjudication. Data from out-of-hospital events in the community include physician, informant, and coroner questionnaires as well as death certificate data and event adjudication. Community surveillance ended in 2014.Cohort participants were examined four times at three year intervals between 1987 and 1998, and have been continuously contacted annually to update their medical histories. Atherosclerosis was measured by carotid ultrasonography. Risk factors studied include: blood lipids, lipoprotein cholesterols, and apolipoproteins; plasma hemostatic factors; blood chemistries and hematology; sitting, supine and standing blood pressures; anthropometry; fasting blood glucose and insulin levels; ECG findings; cigarette and alcohol use; physical activity levels; dietary aspects; and family history. Clinic visits were restarted in 2011 with ARIC visit 5.

Study phs003738

Longitudinal copy number variation analysis from plasma DNA of head and neck cancer patients under re-radiotherapy

Recurrent locally advanced head and neck cancer (HNC) patients, receiving re-radiotherapy (re-RT), are presented with short progression-free (PFS) and overall survival. Hence, biomarkers predicting therapy failure are urgently needed. We analyzed copy number variations (CNVs) in blood plasma of HNC patients collected before, during and after re-RT. Detectable CNVs after five and ten fractions of re-irradiation as well as at the end of re-RT were associated with short PFS. Furthermore, we found that CNV kinetics in longitudinally collected plasma reflected therapy response and could detect disease progression in advance of radiographic tumor assessments.

Study EGAS50000000163

Feasibility Study to Identify the Optimal Adjuvant Combination Scheme of Ipilimumab and Nivolumab (OpACIN) in resectable stage III melanoma patients

OpACIN is a feasibility study including 20 patients with palpable stage III melanoma that were 1:1 randomized to receive ipilimumab 3mg/kg and nivolumab 1mg/kg, either 4 courses after surgery (adjuvant arm), or 2 courses prior to surgery and 2 courses post-surgery (neoadjuvant arm). WES and RNA-seq was performed on baseline biopsy material and correlated with outcome of the patients (relapse free survival). TCRseq from baseline tumor samples was used to analyse the top 100 tumor resident clones and analyse their change in PBMC comparing baseline versus week 6 of immunotherapy.

Study EGAS00001003099

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Resolving the immune landscape of human prostate at a single cell level in health and cancer

GENOMIC MUTATION LANDSCAPE OF SKIN CANCERS FROM DNA REPAIR-DEFICIENT XERODERMA PIGMENTOSUM PATIENTS

Rare SNPs in receptor tyrosine kinases are negative outcome predictors in multiple myeloma

Androgen receptor blockade promotes response to BRAF/MEK-targeted therapy

FEGA Sweden Helpdesk

FASTQ files of total RNA-Seq data from the POPS SGA (Small for Gestational Age) samples

Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

Germline whole genome sequencing of patients with Li-Fraumeni syndrome

CALGB/SWOG 80405 ct DNA Biomarker Evaluation

NIBIT-EPI-MESO study samples

Whole exome sequencing of cell-free DNA reveals temporo-spatial heterogeneity and identifies treatment-resistant clones in neuroblastoma

CDK4/6 inhibition in advanced chordoma: final results of the NCT PMO-1601

VESPA: Vanderbilt Electronic Systems for Pharmacogenomic Assessment

Clinical and Genetic Evaluation of Individuals with Undiagnosed Disorders through the Undiagnosed Diseases Network (UDN)

Single Cell Transcriptomics of peripheral immune cells pre- and post-Immune Checkpoint Blockade

Copy number profiling of tissue and plasma samples from high grade serous epithelial ovarian cancer patients

DPY30 ChIP-seq

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

PCGP Ph-like ALL

NextGen Consortium: Globin Gene Expression in Sickle Cell Genotype-Specific iPS Cells

Identifying New Genetic Subtypes in Follicular Lymphoma

Microbiomic and immunogenic biomarkers of adjuvant chemotherapy efficacy in stage III colorectal cancer

FASTQ files of total RNA-Seq data from the POPS PET (pre-eclamptic) samples

Circulating RNA profiles of healthy and preeclamptic pregnancies

Prediction of homologous recombination deficiency identifies colorectal tumors sensitive to PARP inhibition

Adaptive Therapy Exploits Fitness Deficits in Chemotherapy-Resistant Ovarian Cancer to Achieve Long-Term Tumor Control Open Access

Comparative transcriptome of CD34+ hematopoietic progenitors from myeloproliferative patients and control donors

Discover Cancer Image Europe, the first release of the EUCAIM platform to fuel cancer research and data sharing

Bayesian-Based Noninvasive Prenatal Diagnosis of Single-Gene Disorders

Detection of rare mutations, copy number variation, and DNA methylation in the same template DNA molecules

PGRN-RIKEN: Genetic Determinants of Clinical Cardiovascular Events in Patients Receiving Statins

FASTQ files of the polyA+ (oligo-dT) RNA-Seq dataset from the POPS SGA (Small for Gestational Age) samples and their matched controls.

NEOPREDICT-Lung: longitudinal whole exome sequencing of non-small cell lung cancers under immunotherapy

DNA methylation-based classification of sinonasal tumors [Proteomics data]

Aligned Low pass whole genbome sequencing of cell free and tumour DNA from 5 patients with high grade serous ovarian cancer. Samples have been aligned to hg19 and bam files uploaded

A mathematical model of cell-free DNA fragment size reveals cancer-specific fragmentomic patterns

Cell-free DNA and bone marrow samples from myelodysplastic syndromes

Multimodal cell-free DNA whole-genome TAPS is sensitive and reveals specific cancer signals

CIDR: NCI Genome Wide Predictors of Survival in Colorectal Cancer

NHLBI TOPMed: The Cleveland Family Study (CFS)

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

Sequence data from stage I of the CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer

Profiles of extracellular miRNA in cerebrospinal fluid and serum from patients with Alzheimer's or Parkinson's disease correlate with disease status and features of pathology

ERBB2/HER2 alterations in ctDNA and metachronous tissues of patients with metastatic urothelial cancer - WGS

ERBB2/HER2 alterations in ctDNA and metachronous tissues of patients with metastatic urothelial cancer - Targeted

Whole genome sequencing data of paediatric KMT2A-rearranged acute lymphoblastic leukemia

Non-muscle Invasive Bladder Cancer Molecular Subtypes Predict Differential Response to Intravesical Bacillus Calmette-Guérin

Poland Opole Voivodeship WGS

Poland Podlaskie Voivodeship WGS

Poland Lubusz Voivodeship WGS

Poland Holy Cross Voivodeship - WGS

Poland Warmian-Mazurian Voivodeship WGS

Poland Lublin Voivodeship - WGS

Poland Lodz Voivodeship - WGS

Poland Lesser Voivodeship - WGS

Poland Mazovia Voivodeship - WGS

Poland Greater Poland Voivodeship - WGS

Poland Subcarpathian Voivodeship - WGS

Poland Pomeranian Voivodeship - WGS

Poland Lower Silesian Voivodeship - WGS

Poland Silesian Voivodeship - WGS

Poland Kuyavian-Pomeranian Voivodeship - WGS

Poland West Pomeranian Voivodeship - WGS

Epidemiological study comparing rates and risk factors for dementia in African Americans in Indianapolis and Yoruba living in Ibadan, Nigeria

Multi-Site Collaborative Study for Genotype-Phenotype Associations in Alzheimer's disease and Longitudinal follow-up of Genotype-Phenotype Associations in Alzheimer's disease and Neuroimaging component of Genotype-Phenotype Associations in Alzheimer's disease

FASTQ files of total RNA-Seq data of POPS control samples

Impact of germline pathogenic variants in 27 cancer-predisposing genes on the risk of lymphoma

Distinct genomic profiles and clinical outcomes in constitutional mismatch repair deficiency-associated high-grade gliomas: insights into mutational signatures and clonal evolution

MethCORR: DNA Methylation-based Characterization, Classification and Prognostication of Colorectal Cancer using Archival Formalin-fixed, Paraffin-embedded Tissue

Integrative Single-Cell Analysis of Transcriptome, Epigenome, and Lineage in HIV Latency and Activation

Similarity and diversity of the tumor microenvironment in multiple metastases: critical implications for overall and progression-free survival of high-grade serous ovarian cancer.

Center for Common Disease Genomics [CCDG] - Inflammatory Bowel Disease (IBD) - Global Microbiome Conservancy Host Exomes

University of Illinois at Chicago (UIC) Autism Centers of Excellence (ACE) Exome Sequencing Analysis

Whole Genome Association Study of Visceral Adiposity in the Health Aging and Body Composition (Health ABC) Study

A neoadjuvant, phase II trial demonstrates efficacy and tolerability of Talimogene laherparepvec in cutaneous basal cell carcinoma (NeoBCC trial)

Childhood Cancer Data Initiative (CCDI): Pediatric In Vivo Testing Program –Sarcoma, Kidney, and Liver Cancers

APOBEC3 mutagenesis drives therapy resistance in breast cancer

Examination of Engineered LINE-1 Integration Events in HeLa Cells