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• Whole Exome Sequencing Analysis of Carfilzomib-Related Cardiotoxicity in Multiple Myeloma Patients

  This study investigated the contribution of germline genetic variants in protein-coding genes in carfilzomib-related cardiovascular adverse events among patients with multiple myeloma using whole-exome sequencing (WES) analysis. We analyzed 247 patients with multiple myeloma who had been treated with carfilzomib at the Moffitt Cancer Center. We identified a missense mutation in the TMSB10/TRABD2A locus that appeared to be associated with a higher risk for cardiovascular adverse events in these patients. In this submission, we will provide all the genotype data along with the phenotype data of whether or not a patient developed cardiovascular adverse events after carfilzomib treatment and all the covariates used in this analysis.

  Study phs003308

• WES analysis of DMD-ASD, DMD-ID and DMD-Control individuals for de novo and rare risk variants analysis

  This project generated a whole-exome sequencing (WES) dataset of 83 boys with a pathogenic variant in the DMD gene, along with WES data from the parents of 38 of them, totaling 159 samples. In addition to DMD, 12 boys also had ID (12 DMD-ID samples), 36 boys had ASD (DMD-ASD samples) and 35 did not present ID or ASD diagnosis (DMD-Control samples).

  Dataset EGAD50000001113

• ChIP-Seq files for RMS.

  ChIP-Seq files accompanying the paper titled "Identification of Therapeutic Targets in Rhabdomyosarcoma Through Integrated Genomic, Epigenomic, and Proteomic Analyses".

  Dataset EGAD00001006398

• Sequencing data for oesophageal and related samples - Ogden et al (WGS, RNA)

  Data supporting: "Widespread reorganisation of the regulatory chromatin landscape facilitates resistance to inhibition of oncogenic ERBB2 signalling" Ogden et al. WGS for tumour and normal samples. RNAseq for tumour samples.

  Dataset EGAD00001007496

• DAC of "Gene expression adaptation of metastases to their host tissue"

  The DAC consists of Prof. Axel Hillmer, University of Cologne, Faculty of Medicine and University Hospital Cologne, Institute of Pathology, Cologne, Germany, e-mail: ahillmer@uni-koeln.de and Prof. Andreas Beyer, University of Cologne, Faculty of Mathematics and Natural Sciences, Cologne Excellence Cluster for Aging and Aging-Associated Diseases (CECAD), Cologne, Germany, e-mail: andreas.beyer@uni-koeln.de

  Dac EGAC50000000514

• snRNA-seq dataset and atlas from subcortical white matter MS lesions (CA & CI) and controls

  Dataset including FASTQ files for all snRNA-seq samples from subcortical Multiple Sclerosis (MS) lesions and controls (n=15), together with the curated and annotated snRNA-seq atlas.

  Dataset EGAD50000000521

• Hermansky-Pudlak syndrome type 1 causes impaired anti-microbial immunity through a pathogenic lipid metabolism-mTOR circuit

  Mendelian diseases that present with immune-mediated disorders can provide insights into the molecular mechanisms that drive inflammation. Hermansky-Pudlak syndrome (HPS) types 1 and 4 are caused by defective vesicle trafficking involving the BLOC-3 complex. The presence of inflammatory complications such as Crohn’s disease-like inflammation and lung fibrosis in these patients remains enigmatic. Using mass cytometry we observe an augmented inflammatory monocyte compartment in HPS1 patient peripheral blood that may be associated with a TNF - and IL-1α-dominated cytokine dysregulation. HPS1 patient monocyte-derived macrophages express an inflammatory TNF-OSM mRNA gene signature and changes in lipid metabolism. Using stimulation experiments and lysosomal proteomics we show that defective lipid metabolism drives RAB32-dependent mTOR signaling, facilitated by the accumulation of mTOR on lysosomes. This pathogenic circuit translates into aberrant bacterial clearance, which can be rescued with mTORC1 inhibition. We reveal that a pathogenic lipid-mTOR signaling circuit acts as a metabolic checkpoint for defective anti-microbial activity. This mechanism may be relevant to the complex pathology of HPS1 patients featuring macrophage lipid accumulation, granuloma formation, defective anti-microbial activity and tissue inflammation. Lastly, this circuit may be present in a wider group of disorders with defective lipid metabolism and cholesterol accumulation.

  Study EGAS00001005053

• Hermansky-Pudlak syndrome type 1 causes impaired anti-microbial immunity through a pathogenic lipid metabolism-mTOR circuit - 10x Genomics scRNAseq

  Mendelian diseases that present with immune-mediated disorders can provide insights into the molecular mechanisms that drive inflammation. Hermansky-Pudlak syndrome (HPS) types 1 and 4 are caused by defective vesicle trafficking involving the BLOC-3 complex. The presence of inflammatory complications such as Crohn’s disease-like inflammation and lung fibrosis in these patients remains enigmatic. Using mass cytometry we observe an augmented inflammatory monocyte compartment in HPS1 patient peripheral blood that may be associated with a TNF - and IL-1α-dominated cytokine dysregulation. HPS1 patient monocyte-derived macrophages express an inflammatory TNF-OSM mRNA gene signature and changes in lipid metabolism. Using stimulation experiments and lysosomal proteomics we show that defective lipid metabolism drives RAB32-dependent mTOR signaling, facilitated by the accumulation of mTOR on lysosomes. This pathogenic circuit translates into aberrant bacterial clearance, which can be rescued with mTORC1 inhibition. We reveal that a pathogenic lipid-mTOR signaling circuit acts as a metabolic checkpoint for defective anti-microbial activity. This mechanism may be relevant to the complex pathology of HPS1 patients featuring macrophage lipid accumulation, granuloma formation, defective anti-microbial activity and tissue inflammation. Lastly, this circuit may be present in a wider group of disorders with defective lipid metabolism and cholesterol accumulation.

  Study EGAS00001005098

• A new subgroup of hepatocellular adenomas with sonic hedgehog pathway activation

  Using sequencing and gene expression analyses, we identified a subgroup of HCA characterized by fusion of the INHBE and GLI1 genes and activation of sonic hedgehog pathway. Molecular subtypes of HCAs associated with different patients’ risk factors for HCA, disease progression, and pathology features of tumors. This classification system might be used to select treatment strategies for patients with HCA. Related Publication: Molecular Classification of Hepatocellular Adenoma Associates With Risk Factors, Bleeding, and Malignant Transformation Nault, Jean-CharlesLaurent, Christophe et al. Gastroenterology , Volume 152 , Issue 4 , 880 - 894.e6 http://dx.doi.org/10.1053/j.gastro.2016.11.042

  Dataset EGAD00001003092

• Sequencing data for the manuscript "Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas"

  Mapping the spatial organization of DNA-level somatic copy number changes in tumors can provide insight to understanding higher-level molecular and cellular processes that drive pathogenesis. We describe an integrated framework of spatial transcriptomics, tumor/normal DNA sequencing, and bulk RNA sequencing to identify shared and distinct characteristics of an initial cohort of eleven gliomas of varied pathology and a replication cohort of six high-grade glioblastomas.

  Dataset EGAD50000001394

• Human normal esophagus and Barrett's esophagus mtDNA sequencing

  BAM files containing paired-end mtDNA sequencing data from human esophageal samples of individuals that had progressed to dysplasia or developed Barrett's esophagus (BE) post-esophagectomy. BE biopsies and the background mucosa were analysed. Each patient (JE*) has associated mtDNA sequencing data from biopsies of stroma, BE and squamous and cardia tissue. Two technical replicates, denoted "A" and "B", were analysed for each biopsy. Libraries were sequenced via the Illumina MiSeq platform v2 (Illumina, San Diego, CA, USA) 300 cycles (150 nt paired-end).

  Dataset EGAD00001008310

• Lam-ESC&Lam-Recombination data

  This dataset includes all data produced in the study describing "Lam-ESC&Lam-Recombination", a method for sequencing of signal joints and coding joints generated from human light chain antigen receptor loci during V(D)J recombination in B-cell precursor acute lymphoblastic leukaemia (BCP-ALL) patients. This dataset includes: - Amplicon Lam-ESC for a total of 86 BCP-ALL patients - fastq files - Amplicon Lam-Recombination for a total of 43 BCP-ALL patients - fastq files

  Dataset EGAD50000000597

• Validation for human early embryonic substitutions (2017-05-11)

  PCR and MiSeq validation for early embryonic substitution candidates from 400 Breast cancer patients This dataset contains all the data available for this study on 2017-05-11.

  Dataset EGAD00001003332

• RNA sequencing and Illumina 2.5M SNP array data collected from 675 commonly used human cancer cell lines.

  Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic response1. Although substantial effort has been directed to defining the genomic constitution of cancer cell line panels2–4, the transcriptome – which represents the active program of a cell – remains understudied. Here, we describe RNA sequencing and SNP array analysis of 675 commonly used human cancer cell lines. We explore numerous transcriptome features including coding and non-coding gene expression, transcribed mutations, gene fusion and expression of non-human sequences. Aside from many known aberrations we find new surprising characteristics, including more than 2200 unique fusion gene pairs representing a vast, testable repertoire of oncogenic fusions, many of which have analogs found in primary human tumors. We show that a combination of multiple genome and transcriptome features in a novel pathway-based approach enhances prediction of response to various targeted therapeutics. Our results provide valuable new insights into these critical pre-clinical models and provide added context for interpreting the numerous studies that employ these widely used cell lines.

  Study EGAS00001000610

• 10X CD4 auto-antigens

  Ex vivo CD4 T-cells from 4 donors were stimulated with antigen-coupled beads to aCD3, ABD, EBNA1, ANO2 or CRYAB and the LiveCD3+CD4+CFSEdim cells were sorted by flow cytometry. Cells were labelled with barcoded antibodies to identify the original stimulus. All stimulations from each donor were pooled into four reactions, i.e. one reaction per donor. Libraries were assembled with the 10X Chromium Next GEM Single Cell 5’ Kit for TCR and transcriptome with feature barcodes. Dataset contains raw fastq reads as well as supplementary information needed to link fastq files to modality, i.e. gene-expression, protein or VDJ, and includes supplementary information to de-multiplex the reactions by stimulation condition.

  Dataset EGAD50000002201

• GSA pilot raw data

  Unfiltered genotype data for a pilot study (Batch 1) of 1,140 DDD Study participants (and 12 "Empty" samples). Samples include 380 mothers, 382 fathers and 378 probands, and form 376 trios. Most of the probands have been previously genoyped on the llumina HumanCoreExome BeadChip (EGAD00010001598) or the Illumina InfiniumCoreExome Beadchip (EGAD00010001600). All samples were genotyped on the Illumina Global Screening Array.

  Dataset EGAD00010002567

• Whole Transcriptome Sequencing

  RNA-seq data of 15 snap-frozen tissue of peritoneal mesothelioma. The strand specific RNA library prepared using TruSeq (Illumina) and pair-end sequencing performed in Illumina HiSeq 4000. The datasets contains paired fastq files for each of 15 tumor samples.

  Dataset EGAD00001004504

• sWGS of cfDNA from metastatic CRC patients

  Paired end shallow whole genome sequencing (sWGS) data (FASTQ) for the identification of genomewide somatic copy number alterations (SCNA) and the estimation of tumor fractions.

  Dataset EGAD00001010293

• Data for noninvasive lung cancer subtyping study

  This dataset included cfMethyl-Seq data of 15 plasma cfDNA samples from 15 lung cancer patients and RRBS data of 58 lung tumor tissue samples from 58 lung cancer patients. The data were generated following the standard protocols.

  Dataset EGAD00001015344

• Dynamics of neoantigen landscape during immunotherapy

  Immune checkpoint inhibitors have shown significant therapeutic responses against tumors containing increased mutation-associated neoantigen load. We have examined the evolving landscape of tumor neoantigens during the emergence of acquired resistance in non-small cell lung cancer patients after initial response to immune checkpoint blockade with anti-PD1 or anti-PD-1/anti-CTLA4 antibodies. Analyses of matched pretreatment and resistant tumors identified genomic changes resulting in loss of 7 to 18 putative mutation-associated neoantigens in resistant clones. Peptides generated from the eliminated neoantigens elicited clonal T cell expansion in autologous T cell cultures, suggesting that they generated functional immune responses. Neoantigen loss occurred through elimination of tumor subclones or through deletion of chromosomal regions containing truncal alterations and were associated with changes in T cell receptor clonality. These analyses provide insights into the dynamics of mutational landscapes during immune checkpoint blockade and have implications for development of immune therapies that target tumor neoantigens.

  Study EGAS00001002704

• A Genomics-Based Classification of Human Lung Tumors

  We characterized genome alterations in 1255 clinically annotated lung tumors of all histological subgroups to identify genetically defined and clinically relevant subtypes. More than 55% of all cases had at least one oncogenic genome alteration potentially amenable to specific therapeutic intervention, including several personalized treatment approaches that are already in clinical evaluation. Marked differences in the pattern of genomic alterations existed between and within histological subtypes, thus challenging the original histomorphological diagnosis. Immunohistochemical studies confirmed many of these reassigned subtypes. The reassignment eliminated almost all cases of large cell carcinomas, some of which had therapeutically relevant alterations. Prospective testing of our genomics-based diagnostic algorithm in 5145 lung cancer patients enabled a genome-based diagnosis in 3863 (75%) patients, confirmed the feasibility of rational reassignments of large cell lung cancer, and led to improvement in overall survival in patients with EGFR-mutant or ALK-rearranged cancers. Thus, our findings provide support for broad implementation of genome-based diagnosis of lung cancer.

  Study EGAS00001000647

• Chromatin accessibility (ATAC-seq) of human acute leukemias and healthy donors

  ATAC-seq of 79 primary samples obtained from human acute leukemias, namely AML, T-ALL and mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP). ATAC-seq of CD34+ HSPCs from 3 healthy donors is also included.

  Dataset EGAD00001011050

• Somatic mutation and clonal evolution in the human bladder_WGS (2020-05-05)

  In this study, we aim to characterise the landscape of mutation and clonal selection in the human bladder. The data in this study will be generated by whole-genome sequencing of laser-dissected microbiopsies from the bladder. The samples utilised in this study will include urothelium from transplant donors with no history of bladder cancer and cystectomy specimens from patients with bladder cancer. . This dataset contains all the data available for this study on 2020-05-05.

  Dataset EGAD00001006113

• Somatic mutation and clonal evolution in the human bladder Novaseq (2020-05-05)

  In this study, we aim to characterise the landscape of mutation and clonal selection in the human bladder. The data in this study will be generated by whole-genome sequencing of laser-dissected microbiopsies from the bladder. The samples utilised in this study will include urothelium from transplant donors with no history of bladder cancer and cystectomy specimens from patients with bladder cancer. . This dataset contains all the data available for this study on 2020-05-05.

  Dataset EGAD00001006116

• Somatic mutation and clonal evolution in the human bladder_WES (2020-05-05)

  In this study, we aim to characterise the landscape of mutation and clonal selection in the human bladder. The data in this study will be generated by whole-exome sequencing of laser-dissected microbiopsies from the bladder. The samples utilised in this study will include urothelium from transplant donors with no history of bladder cancer and cystectomy specimens from patients with bladder cancer. . This dataset contains all the data available for this study on 2020-05-05.

  Dataset EGAD00001006115

• Achilles tendinopathy exome data

  Exemplar asymptomatic controls (n=10, 6 males) and exemplar cases with chronic Achilles tendinopathy (n=10, 6 males), representing divergent extremes of the phenotype spectrum were selected for WES. Individual samples were sequenced at paired ends on the Illumina HiSeq 2000/2500 platform at 30X coverage using the Agilent V5+UTR (71Mbp) capture kit.

  Dataset EGAD00001004362

• GWAS for atrial fibrillation in the Japanese population

  We performed a genome-wide association study (GWAS) that utilized 8,180 atrial fibrillation cases and 28,612 controls and followed up in an additional 3,120 cases and 125,064 controls in the Japanese population. We replicated previously reported loci and identified six novel loci. Five of the six novel loci were specifically associated with atrial fibrillation in the Japanese population after comparing our data to individuals of European ancestry, suggesting there might be different susceptibility genetic factors across ancestries. Our study has discovered variants in genes HAND2, KCND3 and NEBL that are relevant to atrial fibrillation susceptibility. The involvement of PPFIA4 and SH3PXD2A in axon guidance also suggested its role in the disease pathogenesis. Our findings may contribute to a better understanding of atrial fibrillation susceptibility and pathogenesis.

  Study JGAS000101

• Single Cell Targeted Sequence Capture

  This study is to ascertain whether it is feasible to extract single cell from a tumour, perform amplification, generate a library and sequence a targeted pulldown.

  Dataset EGAD00001001450

• MOSAIC Window Glioblastoma Data

  This dataset will include Spatial Transcriptomics, Single-Cell RNA-Seq, Bulk RNA-Seq, Clinical data, WES, and H&E data from 10 Glioblastoma (GBM) Cancer patients. Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001352

• Bulk RNA-sequencing data from five lines of human iPSC-derived (hiPSC-derived) astrocytes, both alone and in co-culture with neurons, to define the molecular response of astrocytes to misfolded alpha-synuclein.

  Samples were derived from five lines of human iPSC-derived (hiPSC-derived) astrocytes, both alone and in co-culture with neurons +/- alpha-synuclein oligomer treatment. Paired-end FASTQ files for each of the samples are provided.

  Dataset EGAD50000001109

• Exome sequencing of relapsed/refractory DLBCL

  This dataset consists of the exome sequencing data for 30 tumour and germline DNA pairs derived from relapsed/refractory DLBCL.

  Dataset EGAD00001003395

• ChIP-Seq files for RMS.

  ChIP-Seq files accompanying the paper titled "Identification of Therapeutic Targets in Rhabdomyosarcoma Through Integrated Genomic, Epigenomic, and Proteomic Analyses".

  Dataset EGAD00001004312

• Raw ONT R10 data: Rapid brain tumor classification from sparse epigenomic data

  This dataset contains 207 samples sequenced using rapid-multiplexed barcoded library preparation on Nanopore PromethION R10 flow cells on P2 Solo and P24 systems. One unaligned BAM file per sample is provided.

  Dataset EGAD50000000791

• PML complete dataset

  We generated single-cell transcriptomics, single-nuclei chromatin accessibility, CITE-seq and Multiomics of patients with PML. Pools are genetically multiplexed across donors, genotypic variation is included in this dataset to enable demultiplexing.

  Dataset EGAD50000000197

• Whole-genome sequencing of BCR-ABL1 lymphoblastic leukemia

  This dataset is derived from whole-genome sequencing (WGS) of DNA from 57 BCR-ABL1 lymphoblastic leukemias (53 diagnostic, 4 relapse) and 53 germline samples.

  Dataset EGAD00001010323

• De novo modeling of chromoplectic Ewing sarcoma tumors from patient-derived mesenchymal stem cells

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic (RNA-seq) and epigenetic (ChIP-seq) hallmarks of EwS.

  Dataset EGAD50000001673

• DDD_1 hypermutated individual

  CRAM files and VCF for DDD_1 and their parents. Also de novo mutations file for hypermutated DDD_1 child as described in the manuscript ‘Genetic and chemotherapeutic influences of germline hypermutation’ by Kaplanis et al. which will be published in Nature shortly.

  Dataset EGAD00001008497

• Helleday_HRAS Project

  This experiment is looking at the mutational signatures generated by engineered HRAS mutations by using whole genome sequence generated on massively parallel next generation sequencers.

  Dataset EGAD00001000302

• Mucosal RNAseq data

  This is the RNAseq data from mucosal biopsies.

  Dataset EGAD00001008214

• Single-cell RNA sequencing of chronic-phase chronic myeloid leukemia patients

  Single-cell RNA sequencing of viably frozen cells from 12 samples from four chronic-phase chronic myeloid leukemia patients. The raw data is available as fastq files.

  Dataset EGAD00001009086

• Genomic Landscape of Multiple Myeloma and of its Precursor Conditions, and its Clinical Implications

  Reliable strategies to capture patients at risk of progression from precursor stages of multiple myeloma (MM) to overt disease are still missing. In this study, we generated whole-genome sequencing (WGS) data from matched tumor and normal samples from 98 individuals from the PCROWD study (Precursor Crowd, NCT02269592). These individuals have either a precursor condition for MM, which can be a monoclonal gammopathy of undetermined significance (MGUS) or smoldering multiple myeloma (SMM), or an active multiple myeloma (MM). To do so, we enriched tumor plasma cells from the bone marrow by magnetic bead selection (CD138+), sequenced the DNA of these samples to a target depth of 60X (tumor), and analyzed them against normal white blood cells (peripheral blood mononuclear cells) from the same individuals sequenced to a target depth of 30X (normal). In our first publication [Alberge, Dutta, Poletti, et al., 2025], we integrated and homogeneously analyzed these data together with data from mostly publicly available datasets (phs003084 and phs000748) to reach 1,030 total samples. We used these data to identify recurrent coding and non-coding candidate drivers, as well as significant hotspots of structural variation, and used those drivers to define and validate a simple “MM-like” score which we could use to place patients' tumors on a gradual axis of progression toward active disease. Our MM precursor genomic map provides new insights on the time of initiation and cell of origin of the disease, on the order of acquisition of genomic alterations, and on mutational processes found across stages of the transformation. Taken together, we highlight here the potential of genome sequencing to better inform risk assessment and monitoring of MM precursor conditions.

  Study phs003846

• Genomics-based personalized oncology in cancer of unknown primary (CUP, project H021)

  To perform a comprehensive genomic characterization of 70 patients suffering from cancer of unknown primary (CUP) we used whole-exome, whole-genome, transcriptome and methylome analysis. We detected a substantial mutational heterogeneity with genes most commonly affected by SNVs, indels and fusions being TP53, TTN, MUC16, ABCA13, COL6A3, KRAS, LRP1B, XIRP2 and CSMD3. The most common fusion involved FGFR2, the most common focal deletion affected CDKN2A. A molecular tumor board recommended genomics-based therapies in 56/70 (80%) patients which were applied in 20/56 (35.7%) cases. Entity predictions based on transcriptome and methylome data could be made in up to 62/70 (88.6%) cases but were conclusive in only 16/48 (33.3%) cases. Germline analysis revealed 6 (likely) pathogenic mutations in 5 patients. Recommended therapies translated into a mean PFS2/1 ratio of 3.61 (median=2.25) with a median PFS1 of 89 days (n=17) compared to a median PFS2 of 182.5 days (n=20). Our data emphasize the clinical benefit of comprehensive genetic approaches in diagnostic and therapeutic management and underline the need for innovative, mechanism-based clinical trials in this heterogeneous group of diseases.

  Study EGAS00001004786

• DNA methylation in rhabdomyosarcoma PDX and PDX-derived primary cells

  Conditions to maintain primary tumor cells in culture are largely unknown for most tumor entities including rhabdomyosarcoma. In this collaborative study with Dr. Beat Schäfer's laboratory, we performed DNA methylation profiles of rhabdomyosarcoma patient-derived xenograft (PDX) and their matching PDX-derived primary cells (PPC), where the PPCs were developed and maintained under optimized culture conditions. We further compared DNA methylation profiles between these PDXs and PPCs. Exome sequencing and copy number analysis between these rhabdomyosarcoma PDXs and PPXs were also carried out. These analyses may help us to evaluate a feasibility of in vitro profiling of primary rhabdomyosarcoma cells from a genomic perspective.

  Study phs002051

• Stand Up To Cancer East Coast Prostate Cancer Research Group

  Most prostate cancer deaths are caused by metastatic, castration resistant disease (mCRPC). To develop a precision medicine framework for mCRPC, we established a multi-institutional, international clinical sequencing infrastructure to enroll and carry out prospective whole exome and transcriptome sequencing of tumors from a cohort of mCRPC patients. We obtained high quality DNA and RNA sequence data from 150 bone or soft tissue biopsies. Central pathology revealed high-grade adenocarcinoma with only four cases (3.6%) showing neuroendocrine differentiation. Aberrations of AR, ETS genes, TP53 and PTEN were frequent (40-60% of cases), with TP53 and AR alterations being the most enriched in mCRPC compared to primary prostate cancer. We identified novel genomic alterations in PIK3CA/B (fusions and mutations); R-spondin, BRAF and RAF1 (fusions); APC (inactivating mutations); delta-catenin (missense mutations); and ZBTB16/PLZF (homozygous deletions). Aberrations of BRCA2, BRCA1 and ATM were observed at substantially higher frequencies (19.3% overall) than seen in primary prostate cancers, with 56% of these being exclusively somatic. Putative driver gene alterations were identified in nearly all patients, and over half also harbored driver gene fusions, homozygous deletions and/or amplifications. Moreover, 89% of patients harbored a clinically actionable aberration including 62.7% with aberrations in AR, 65% in other cancer-related genes, and 8% with actionable pathogenic germline alterations. Overall, integrative clinical sequencing analysis can be safely and efficiently performed in mCRPC, yields findings that may be actionable for enrolling patients in clinical trials of targeted therapies, and may inform the basis of individual clinical responses.

  Study phs000915

• Targeted sequencing of cell free DNA samples from oligometastatic colorectal cancer patients

  In order to discover specific mutations that correlate with prognosis, target sequencing was performed using cell-free DNA samples from oligometastatic colorectal cancer patients.

  Study JGAS000196

• The ALT pathway generates telomere fusions that can be detected in the blood of cancer patients

  Telomere fusions (TFs) can trigger the accumulation of oncogenic alterations leading to malignant transformation and drug resistance. Despite their relevance in tumour evolution, our understanding of the patterns and consequences of TFs in human cancers remains limited. Here, we characterize the rates and spectrum of somatic TFs across >30 cancer types using whole-genome sequencing data. TFs are pervasive in human tumours with rates varying markedly across and within cancer types. In addition to end-to-end fusions, we find novel patterns of TFs that we mechanistically link to the activity of the alternative lengthening of telomeres (ALT) pathway. We show that TFs can be detected in the blood of cancer patients, which enables cancer detection with high specificity and sensitivity even for early-stage tumours and cancers of high unmet clinical need. Overall, we report a novel genomic footprint that enables characterization of the telomere maintenance mechanism of tumours and liquid biopsy analysis.

  Dataset EGAD00001012101

• HipSci expression microarray for embryonic stem cell control lines

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we use commercially available embryonic stem cell lines as control samples against which to compare HipSci's iPS cell lines. We performed expression analysis using the Illumina HumanHT -12 Expression BeadChip.

  Study EGAS00001001729

• Naive TCR V, D and J gene usage frequencies

  This dataset contains gene usage matrices calculated from the processed productively rearranged bulk TCR sequences from peripheral blood CD4+ T cells from 103 subjects with celiac disease and 103 control donors. The files contain per sample V, D and J gene usage frequencies for TRA and TRB sequences. Unique rearrangements were quantified with Alakazam in gene mode. More details about processing steps are found in the linked publication. The dataset also contains an accompanying metadata file (csv).

  Dataset EGAD50000002726

• Naive BCR V, D and J gene usage frequencies

  This dataset contains gene usage matrices calculated from the processed productively rearranged bulk BCR sequences from peripheral blood B cells from 102 subjects with celiac disease and 102 control donors. The files contain per sample V, D and J gene usage frequencies for IGH, IGK and IGL sequences. Unique rearrangements were quantified with Alakazam in gene mode. More details about processing steps are found in the linked publication. The dataset also contains an accompanying metadata file (csv).

  Dataset EGAD50000002727

• Spatial and temporal intra-tumoural heterogeneity in advanced High-Grade Serous Ovarian Cancer: implications for surgical and clinical outcomes

  Limited evidence exists on the extent and impact of spatial and temporal heterogeneity of high grade serous ovarian cancer (HGSOC) on tumour evolution and patients surgical and clinical outcome. We investigated this through systematic mapping of multi-site tumours at initial presentation and matched relapse from 49 chemo-naïve HGSOC patients with high tumour load, operated upfront. Our data provides a unique insight into the tumour evolution and metastatic pathways of HGSOC across time and space, how this complexity relates to surgical and clinical outcome and its consequences on clinical decision-making.

  Study EGAS00001007164