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• ICGC PCAWG Dataset: LAML-KR_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: LAML-KR.

  Dataset EGAD00001002119

• ICGC PCAWG Dataset: BTCA-SG_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BTCA-SG.

  Dataset EGAD00001002121

• ICGC PCAWG Dataset: BRCA-UK_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BRCA-UK.

  Dataset EGAD00001002122

• ICGC PCAWG Dataset: PAEN-IT_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PAEN-IT.

  Dataset EGAD00001002153

• Exploration of neuroblastoma xenograft models for tumor extracellular RNA profiling in murine blood plasma

  Total RNA sequencing (SMARTer Stranded Total RNA-Seq Kit v2) data of extracellular RNA (exRNA) from liquid biopsies of neuroblastoma xenograft models.

  Dataset EGAD00001010905

• Bulk RNA from sorted CD8+ T cells after 48h co-culture with human Mito-DsRed MSCs.

  For human samples, total cellular RNA was isolated from post-sorted Mito+ and Mito CD8+ cells using the RNeasy Mini Kit (Qiagen). Stranded RNA libraries were created using SMARTSeq Stranded.

  Dataset EGAD00001011082

• ICGC PCAWG Dataset: CMDI-UK_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: CMDI-UK.

  Dataset EGAD00001002664

• BLUEPRINT DNA methylation profiles of human hematopoietic progenitors

  DNA methylation was analyzed for stem/progenitor cell types and terminally differentiated cell types of the human blood lineage (HSC, MPP, CMP, MEP, GMP, CLP, MLP0, MLP1, MLP2, MLP3, MK, CD4+ Tcell, CD8+ Tcell, Bcell, NK, Neut, Mono).

  Dataset EGAD00001002732

• Benchmarking CRISPR Whole-genome Drop-out Screen - B&S (2019-08-07)

  This study is a benchmarking exercise to explore potential source of variation between different CRISPR drop out libraries. . This dataset contains all the data available for this study on 2019-08-07.

  Dataset EGAD00001005233

• SF11979 snATAC seq IDHR132H Wildtype GBM Female

  SF11979 snATAC, IDHR132H WT GBM Female, 76 Single Nuclei ATAC seq data from high grade human glioma samples. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005418

• Multi-region sequencing of a RET fusion positive cancer patient

  Deep WGS sequencing (160x) of 2 different sites of disease of a patient with a RET fusion positive cancer. Amplicon sequencing of 19 other sites of the same patients for the RET fusion.

  Dataset EGAD00001005776

• Dataset for RNA and Exome sequencing of Glioblastoma samples

  This dataset contains RNA Seq, 10x scRNA Seq and Exome sequencing of glioblastoma samples. Sequencing was performed on a Illumina NovaSeq 6000 and Illumina HiSeq 4000. The sequencing was always paired.

  Dataset EGAD00001012235

• HV31 - PacBio long-read circular consensus (CCS) senquencing

  PacBio long-read circular consensus (CCS) sequencing data for individual HV31 generated on PacBio Sequel II instrument, using size-selected (10-15 kb) DNA from CD14+ monocytes, to a sequencing depth of ~12×. Sequencing was performed at the Wellcome Sanger Institute.

  Dataset EGAD00001006979

• Kidney tumour_DNA (2018-09-19)

  This is a bulk DNA and RNA sequencing study of human renal tumours . This dataset contains all the data available for this study on 2018-09-19.

  Dataset EGAD00001004346

• Exome sequencing data for 40 cases of alopecia areata and vitiligo

  Sequencing of independent unrelated cases of alopecia areata (total/ universal) and vitiligo (>10%, affected family member). DNA obtained from blood

  Study EGAS00001003831

• Genome, epigenome and RNA sequences of monozygotic twins discordant for multiple sclerosis

  Monozygotic (MZ) twins have been widely employed for dissection of the relative contributions of genetics and environment in disease. In multiple sclerosis (MS), an autoimmune demyelinating disease that commonly causes neurodegeneration and disability in young adults, disease discordance in MZ twins has been interpreted to indicate environmental importance in pathogenesis. However, genetic and epigenetic differences between MZ twins have been described, challenging the accepted experimental paradigm in disambiguating effects of nature and nurture. Here, we report the genome sequences of one MS-discordant MZ twin pair and messenger RNA (mRNA) transcriptome and epigenome sequences of CD4+ lymphocytes from three MS-discordant, MZ twin pairs. No reproducible differences were detected between co-twins among ~3.6 million single nucleotide polymorphisms (SNPs) or ~0.2 million insertion-deletion polymorphisms (indels). Nor were any reproducible differences observed between siblings of the three twin pairs in HLA haplotypes, confirmed MS-susceptibility SNPs, copy number variations, mRNA and genomic SNP and indel genotypes, or expression of ~19,000 genes in CD4+ T cells. Only two to 176 differences in methylation of ~2 million CpG sites were detected between siblings of the three twin pairs, in contrast to ~800 differences in methylation between T cells of unrelated individuals and several thousand differences between tissues or normal and cancerous tissues. In the first systematic effort to estimate sequence variation among MZ co-twins, we did not find evidence for genetic, epigenetic or transcriptome differences that explained disease discordance. These are the first female, twin and autoimmune disease genome sequences reported.

  Study phs000239

• Genomic profiling for metastatic uveal melanoma from a phase I study of the protein kinase C inhibitor AEB071

  Up to 50% of patients with uveal melanoma (UM) develop metastatic disease, for which there is no effective systemic treatment. This study aimed to evaluate the safety and efficacy of the orally available protein kinase C inhibitor, AEB071, in patients with metastatic UM, and to perform genomic profiling of metastatic tumor samples, with the aim to propose combination therapies. Metastatic UM patients (n=153) were treated with AEB071 in a Phase I, single-arm study. Patients received total daily doses of AEB071 ranging from 450 to 1400 mg. First-cycle dose-limiting toxicities (DLTs) were observed in 13 patients (13%). These were most commonly gastrointestinal system toxicities and were dose related, occurring at doses > 700 mg/day. Preliminary clinical activity was observed, with 3% of patients achieving a partial response and 50% with stable disease (median duration 15 weeks). High-depth, targeted next-generation DNA sequencing (NGS) was performed on 89 metastatic tumor biopsy samples. Mutations previously identified in UM were observed, including mutations in GNAQ, GNA11, BAP1, SF3B1, PLCB4, and amplification of chromosome arm 8q. GNAQ/GNA11 mutations were observed at a similar frequency (93%) as previously reported, confirming a therapeutic window for inhibition of the downstream effector PKC in metastatic UM. In conclusion, the protein kinase C inhibitor AEB071 was well tolerated and modest clinical activity was observed in metastatic UM. The genomic findings were consistent with previous reports in primary UM. Together, our data allow envisaging combination therapies of PKC inhibitors with other compounds in metastatic UM.

  Study phs001953

• Rare Diseases Clinical Research Network (RDCRN) Vasculitis Clinical Research Consortium (VCRC) Longitudinal Protocol for Polyarteritis Nodosa

  The development and validation of accurate biological markers and predictors of disease activity and outcome in Polyarteritis Nodosa (PAN), a form a idiopathic vasculitis, would have a major positive impact on the clinical care of patients with this rare disease, be an important advance in the design of clinical trials and feasibility of new drug development, and provide important insight into the pathogenesis of this condition. Current measures of disease activity, including erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP), while helpful in selected settings, are mostly considered highly flawed and markers whose poor correlation with disease flares makes them inadequate to help guide therapy. Similarly, ESR and CRP are clearly unhelpful as diagnostic tests for vasculitis. The current state of clinical investigation for vasculitis relies heavily upon determination of disease status solely by clinical presentation and investigator opinion. Thus, discovery and validation of more precise markers that quantifiably measure activity, predict disease course, and correlate with an important biological process, would be of great importance. Knowledge to be gained from this study could potentially be highly important. Discovery of effective biomarkers of vasculitis and assessment of long term disease course and complications by the collection of clinical and diagnostic imaging studies proposed could lead to better care and less toxic treatment regimens. Furthermore, insight into the pathophysiology of vasculitis could be gained and this might lead to better treatments and improved outcomes in terms of reduction of vascular and treatment related complications. Ideally, excellent biomarkers reflect a sophisticated understanding of the pathophysiology of a disease.

  Study phs000590

• Non-Coding Autoimmune Risk Variant Defines Role for ICOS in T Peripheral Helper Cell Development

  Our fine-mapping of 76 non-MHC loci associated with risk for rheumatoid arthritis (RA, 11,475 cases, 15,870 controls) has recently identified rs117701653, a non-coding single nucleotide polymorphism (SNP) in the CTLA4/CD28/ICOS locus, as the variant most likely to modulate RA risk within this region, with the minor allele C showing disease protection compared to the major allele A. We found that this SNP exhibits allele-specific protein binding and transcriptional modulation, further supporting its regulatory nature. Here, we aimed to determine whether the functional non-coding variant rs117701653 modulates the expression of genes within the CD28/CTLA4/ICOS locus. To address this question, we employed low-input RNA sequencing using the Illumina SmartSeq2 platform on resting total CD4+ T cells from the blood of 24 healthy subjects (8 AA, 8 AC, 8 CC) recruited based on genotype from the Mass General Brigham biobank. We performed a targeted cis-eQTL mapping analysis for protein coding genes with transcription start sites (TSS) within a 1MB window of SNP rs117701653. These genes included WDR12, NBEAL1, CYP20A1, ABI2, RAPH1, CD28, CTLA4, ICOS, and PARD3B. Surprisingly, allelic variation at rs117701653 correlated strongly with expression of ICOS. This suggests that individuals carrying the protective allele C at rs117701653 express lower levels of ICOS, implicating ICOS as a plausible target gene influenced by this protective allele. The raw sequence data from the 24 healthy individuals are available through dbGAP. Gene expression matrices have been deposited to GEO accession GSE235868.

  Study phs003448

• Benchmarking for alignment and variant calling

  Background: Lung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and six structural variant callers comprised of four generic callers (Sniffles2, cuteSV, SVIM and DELLY in generic mode) and two somatic callers (nanomonsv and DELLY in somatic modes). Results: Different combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short read sequencing. When compared to somatic structural variants detected with short read sequencing, more events were detected with long read sequencing. The mean recall of somatic variant events identified by short read sequencing was higher for the somatic callers (64%) than generic callers (52%), with nanomonsv (69%) showing the best performance. Conclusion: Long read sequencing can identify somatic structural variants. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

  Study EGAS00001007819

• A Machine Learning Tool Integrating Circulating Cell-Free DNA Methylation with Clinical Variables for Non-Invasive Diagnosis of Liver Graft Pathology

  Liver Transplant Recipients (LTRs) with elevated liver enzymes can develop graft injury due to various etiologies, such as T-cell mediated rejection (TCMR) and NASH (NASH-LT). While liver biopsy is the gold standard method for diagnosis of graft pathology, it is invasive and is associated with risks. The goal of our study was to develop a Machine Learning (ML) tool integrating clinical variables with methylation patterns on circulating DNA in plasma as a non-invasive diagnostic tool of graft injury. We generated methylation profiles of circulating DNA in a pilot study of 43 LTRs (11 NASH-LT, 19 TCMR, and 13 Control-LT), and developed an L2 multinomial logistic regression ML approach across 101 bootstrapped models to distinguish between the graft conditions. NASH was associated with distinctive methylation patterns on genes involved in fatty acid metabolism, while methylation of platelet-derived growth factors was identified in patients with TCMR. Our ML model achieved a mean multi-classification accuracy of 0.91, with mean specificity and sensitivity of 0.94 and 0.91, respectively. The model was found to be particularly adept at detecting TCMR and Control-LT, with true positive rates (TPRs) of 95% and 90%, and areas under the curve (AUROC) of 0.992 and 0.985, respectively. For NASH-LT, the models achieved a performance with a TPR of 82% and an AUROC of 0.991. These preliminary results suggest that our newly developed ML tool, leveraging cell-free DNA methylation and clinical variables, is a promising non-invasive classifier of graft pathology.

  Study EGAS00001007171

• Pharmacogenomic Analysis Reveals New Therapeutic Options for Pleural Mesothelioma

  Background: Pleural mesothelioma (PM) urgently requires novel effective treatments. Drug repurposing is a relevant strategy to discover new therapeutic options among well-known drugs used in clinical practice. This study aimed to identify new therapies in the context of molecular heterogeneity of PM. Methods: We performed a multi-omics study of the largest cohort of patient-derived primary PM cell lines (n=58) to date, using whole exome sequencing, RNA sequencing and methylome analysis. We also conducted a large-scale drug screening of over 1300 compounds on a subset of cell lines (n=11), as well as an extension screen (n=48) for selected drugs of interest. The best candidates were validated using 3D culture and mouse models. Results: We demonstrated that the molecular landscape of the cell lines cohort recapitulates the main findings in tumours and revealed new specific features of PM. The large-scale drug screening and subsequent validations highlighted notably strong sensitivity to entinostat and fluvastatin. Importantly, both compounds displayed same efficacy in 2D and 3D culture models and single treatment prolonged survival in vivo similarly or even better than standard chemotherapy. Strikingly, combining entinostat treatment with anti-PD1 led to cures in some mice and immunized them against tumour cells. Conclusions: Among several candidates, we identified entinostat, notably in combination with immune checkpoint inhibitor, and to a lesser extent fluvastatin, as promising therapeutic options for patients. We believe our study provides a valuable resource that could contribute to advances in the field and warrants further clinical investigation.

  Study EGAS00001007866

• Implementation of pediatric precision oncology into clinical practice: The individualized Therapies for Children with cancer program “iTHER”

  iTHER is a prospective national precision oncology program aiming to define tumor molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory pediatric tumors in order to identify relevant aberrations to inform treatment. From April 2017 to April 2021, 302 samples of 253 patients were included. Comprehensive molecular profiling utilizing lcWGS, WES, RNAseq, Affymetrix, and/or 850k methylation profiling was performed for 226 samples. Germline pathogenic variants were identified in 16% of patients. At least one somatic alteration was detected in 204 (90.3%), and 185 (81.9%) were considered druggable, with priority levels very high (6.1%), high (21.3%), moderate (26.0%), intermediate (36.1%), and borderline (10.5%). Diagnosis was revised or refined in 8 patients (3.5%). Spatial and temporal heterogeneity was observed in paired samples of 15 patients, indicating the value of sequential analysis. Of 137 patients with follow-up beyond 12 months, 21 molecularly matched treatments were applied in 19 patients (13.9%) with modest response. Most relevant barriers to not applying targeted therapies included poor performance status, as well as limited access to drugs within clinical trial. iTHER demonstrates feasibility of comprehensive molecular profiling across all ages, tumor types and stages in pediatric cancers, informing of diagnostic, prognostic, and targetable alterations as well as reportable germline variants within a clinically relevant timeframe. Therefore, WES and RNAseq is implemented into standard clinical care at the Princess Máxima Center for all children. Improved access to targeted treatments within biology-driven combination trials is required to eventually improve survival.

  Study EGAS00001007099

• Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses

  Background Single-cell RNA sequencing (scRNAseq) is a powerful tool for studying complex biological systems, such as tumour heterogeneity and tissue microenvironments. However, the sources of technical and biological variation in primary solid tumour tissues and patient-derived mouse xenografts for scRNAseq, are not well understood. Here, we used low temperature (6°C) protease and collagenase (37°C) to identify the transcriptional signatures associated with tissue dissociation across a diverse scRNAseq dataset comprising 128,481 cells from patient cancer tissues, patient-derived breast cancer xenografts and cancer cell lines.Results We observe substantial variation in standard quality control (QC) metrics of cell viability across conditions and tissues. From FACS sorted populations gated for cell viability, we identify a sub-population of dead cells that would pass standard data filtering practices, and quantify the extent to which their transcriptomes differ from live cells. We identify a further subpopulation of transcriptomically “dying” cells that exhibit up-regulation of MHC class I transcripts, in contrast with live and fully dead cells. From the contrast between tissue protease dissociation at 37°C or 6°C, we observe that collagenase digestion results in a stress response. We derive a core gene set of 512 heat shock and stress response genes, including FOS and JUN, induced by collagenase (37°C), which are minimized by dissociation with a cold active protease (6°C). While induction of these genes was highly conserved across all cell types, cell type-specific responses to collagenase digestion were observed in patient tissues. We observe that the yield of cancer and non-cancer cell types varies between tissues and dissociation methods.Conclusions The method and conditions of tumour dissociation influence cell yield and transcriptome state and are both tissue and cell type dependent. Interpretation of stress pathway expression differences in cancer single cell studies, including components of surface immune recognition such as MHC class I, may be especially confounded. We define a core set of 512 genes that can assist with identification of such effects in dissociated scRNA-seq experiments.

  Study EGAS00001003753

• 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