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• DNA and RNAseq of serial biopsies from 75 DLBCL patients

  This data set includes serial biopsies from 75 patients with DLBCL. Tumour tissue was preserved either in FFPE or frozen. Each biopsy was sequenced with either whole genome or exome. A custom targeted sequencing data set is available to match most whole genome samples. RNAseq data were available for a subset of biopsies.

  Dataset EGAD00001011816

• RNA expression profiling of melanoma patient-derived xenograft

  Patient-derived xenografts (n=96) were derived from metastatic melanoma patients. RNA expression profiling will be preformed to study 1. HLA-typing and 2. the effect of the tumour microenvironment on tumour growth 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 EGAD00001002230

• Whole Genome Sequencing of Human Organoid Lines (2020-02-20)

  The study will use WGS to aid in benchmarking different culture conditions in a set of genetically annotated human organoid lines. The data will be used to assess whether there is any clonal differences introduced when culturing these lines in different conditions. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005995

• 47 urothelial cancer patients WES and 38 RNAseq

  We performed a global mutational landscape analysis using tumor samples from the 47 urothelial cancer patients included in MATCH-R or MOSCATO studies, with advanced metastatic disease and WES available (RNAseq is included for 38 patient samples).

  Dataset EGAD00001011063

• Type 1 Diabetes Genetics Consortium (T1DGC): Multi-Ethnic ImmunoChip Study

  Type 1 diabetes (T1D) is characterized by an autoimmune attack that destroys the insulin-producing pancreatic beta cells and is driven by diverse genetic and environmental factors. Between 8-100 chromosome regions are known to contain variants that alter T1D risk, substantially fewer than many other common diseases. Less is known about the contribution of T1D risk alleles in non-European populations, despite recent increases in T1D diagnoses in multiple non-European ancestry groups. To address these gaps in T1D genetics, we doubled the sample size from the previous largest T1D association study, genotyped ancestrally diverse T1D cases, controls, and affected families with the Illumina ImmunoChip array, and imputed additional variants using a large haplotype reference panel. After quality filtering, a total of 61,427 participants and 140,333 genotyped ImmunoChip variants were included in analysis, providing dense coverage in 188 autosomal regions ("ImmunoChip regions") and sparse genotyping in other regions of the genome. Each participant was assigned to one of five ancestry groups using k-means clustering of ImmunoChip genotype principal components: European (EUR, N = 47,319), African Admixed (AFR, N = 4,290), Finnish (FIN, N = 6,991), East Asian (EAS, N = 588) and Other Admixed (AMR, N = 2,239). In total, 16,159 T1D cases, 25,386 controls (unrelated) and 6,143 trio families (i.e., an affected child and both parents) were genotyped and included in association analyses. Imputation with the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) multi-ethnic reference panel was used to improve discovery power and fine-mapping resolution. After imputation, the number of variants in ImmunoChip regions with imputation R-squared > 0.8 and MAF > 0.005 in each ancestry group was 322,084 (AFR), 166,274 (EUR), 163,612 (FIN), 137,730 (EAS) and 188,550 (AMR). Imputed genotypes were compared in the same participants who have whole genome sequencing data, resulting in high concordance. Unrelated cases and controls (N = 41,545) were analyzed initially, assuming an additive inheritance model. T1D trio families (N = 6,143 trios, some trio families were multiplex and analyzed as multiple trios) were analyzed separately, with meta-analysis of case-control and trio results used for discovery of regions associated with T1D (p < 5×10-8). Summary-level data at each SNP (genotype and imputed) for type 1 diabetes (outcome) are provided in dbGaP.

  Study phs002468

• UK10K RARE COLOBOMA

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. Ocular coloboma is the most common significant developmental eye defect with an incidence of ~1 in 5,000 live births. It results from failure of optic fissure closure during embryogenesis. The position and extent of the fusion failure dictates the clinical appearance and functional effect. ~30% of coloboma cases are associated with other systemic malformations. These UK10K samples will mostly comprise isolated coloboma cases without systemic involvement (aka non-syndromal coloboma). There is strong evidence from family studies that coloboma has a major genetic component with autosomal dominance being the most common pattern of inheritance. However, many cases are isolated or show complex patterns of familial clustering. The genes responsible for isolated coloboma are largely unknown, but in a small number of families mutations in SHH, CHX10, and PAX6 have been identified indicating marked genetic heterogeneity. Thus in addition to the clinical benefits of achieving a molecular diagnosis there are also major scientific advantages to identifying coloboma genes, as these are likely to provide insights into the complex process of optic fissure closure, that is critical to normal eye development. In the longer term, understanding the molecular basis of the disease may provide clues to therapeutic strategies.For further information with regard to this cohort please contact David Fitzpatrick (david.fitzpatrick@ed.ac.uk).

  Study EGAS00001000127

• Understand Paratyphoid Disease - host responses to human challenge with S. Paratyphi A (2019-08-28)

  This project aims to evaluate the transcriptional response to disease measured in whole blood of participants who developed enteric fever after challenge and, importantly, those who were challenged but stayed well throughout the challenge period. This data will provide unique coverage of the transcriptome and will yield invaluable insight after integration with a wealth of clinical data collected during this trial. 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/ . This dataset contains all the data available for this study on 2019-08-28.

  Dataset EGAD00001005298

• RNAseq dataset for MALT1 in MCL

  Manuscript Title: Co-targeting of BTK and MALT1 overcomes resistance to BTK inhibitors in mantle cell lymphoma Journal: Journal of Clinical Investigation Authors Vivian Changying Jiang1, Yang Liu1, Junwei Lian1, Shengjian Huang1, Alexa Jordan1, Qingsong Cai1, Fangfang Yan3, Joseph Mitchell McIntosh1, Yijing Li1, Yuxuan Che1, Zhihong Chen1, Jovanny Vargas1, Maria Badillo1, JohnNelson Bigcal1, Heng-Huan Lee1, Wei Wang1, Yixin Yao1, Lei Nie1, Christopher Flowers1, and Michael Wang1, 2* Abstract Bruton’s tyrosine kinase (BTK) is a proven target in mantle cell lymphoma (MCL), an aggressive subtype of non-Hodgkin lymphoma. However, resistance to BTK inhibitors is a major clinical challenge. We here report that MALT1 is one of the top overexpressed genes in ibrutinib-resistant MCL cells, while expression of CARD11, which is upstream of MALT1, is decreased. MALT1 genetic knockout or inhibition produced dramatic defects in MCL cell growth regardless of ibrutinib sensitivity. Conversely, CARD11 knockout cells showed anti-tumor effects only in ibrutinib-sensitive cells, suggesting that MALT1 overexpression could drive ibrutinib resistance via bypassing BTK-CARD11 signaling. Additionally, BTK knockdown and MALT1 knockout markedly impaired MCL tumor migration and dissemination, and MALT1 pharmacological inhibition decreased MCL cell viability, adhesion, and migration by suppressing NF-κB, PI3K-ATK-mTOR, and integrin signaling. Importantly, co-targeting MALT1 with safimaltib and BTK with pirtobrutinib induced potent anti-MCL activity in ibrutinib-resistant MCL cell lines and patient-derived xenografts. Therefore, we conclude that MALT1 overexpression associates with resistance to BTK inhibitors in MCL, targeting abnormal MALT1 activity could be a promising therapeutic strategy to overcome BTK inhibitor resistance, and co-targeting of MALT1 and BTK should improve MCL treatment efficacy and durability as well as patient outcomes. Dataset description: The bulk RNA-seq dataset was generated for the cell lines below and used for two major purposes: 1. DEG analysis and GSEA analysis comparing IBN-R and IBN-S cells 2. DEG analysis and GSEA analysis comparing MCL cells with/without MI-2 treatment. sample Cell MI-2 Ibrutinib (IBN) Venetoclax (VEN) Used for IBN-R vs IBN-S comparison Used for MI-2 vs untreated (DMSO) H9 Granta519 - R S yes H21 Granta519 - R S yes H33 Granta519 - R S yes H10 Granta519-VEN-R - R R yes H22 Granta519-VEN-R - R R yes H34 Granta519-VEN-R - R R yes H3 JeKo BTK KD_1 - R R yes yes H15 JeKo BTK KD_1 - R R yes yes H27 JeKo BTK KD_1 - R R yes yes H5 JeKo BTK KD_2 - R R yes yes H17 JeKo BTK KD_2 - R R yes yes H29 JeKo BTK KD_2 - R R yes yes H1 JeKo-1 - S R yes yes H13 JeKo-1 - S R yes yes H25 JeKo-1 - S R yes yes H7 Mino - S S yes H19 Mino - S S yes H31 Mino - S S yes H8 Mino-VEN-R - S R yes H20 Mino-VEN-R - S R yes H32 Mino-VEN-R - S R yes H11 Rec-1 - S S yes H23 Rec-1 - S S yes H12 Rec-VEN-R - S S yes H24 Rec-VEN-R - S R yes H36 Rec-VEN-R - S R yes H35 Rec-1 -- S R yes H4 JeKo BTK KD_1 + MI-2 + yes H16 JeKo BTK KD_1 + MI-2 + yes H28 JeKo BTK KD_1 + MI-2 + yes H6 JeKo BTK KD_2 + MI-2 + yes H18 JeKo BTK KD_2 + MI-2 + yes H30 JeKo BTK KD_2 + MI-2 + yes H2 JeKo-1 + MI-2 + yes H14 JeKo-1 + MI-2 + yes H26 JeKo-1 + MI-2 + yes

  Dataset EGAD00001009771

• Uncovering Inversion Formation in the Human Genome and its Impact to Disease

  The relevance of inversions for disease causation, speciation and adaptation is broadly recognized, although the prevalence of inversions is unknown. In humans, de novo inversions are associated with congenital anomalies in approximately 9.6% of patients. Yet, despite the biological relevance of inversions, their molecular features, formation mechanism, impact to the genomic structure of carriers, as well as their contribution to clinical phenotypes, have not been further explored. Inversions are typically classified as balanced reciprocal events generated by ectopic recombination, although recent studies reveal a distinct picture whereby inversions originate from mechanisms that concomitantly generate copy number variants (CNVs). Surprisingly, those complex inversions underlie as much as 30% of neurodevelopmental-associated CNVs. The hypothesis of this project are: inversions are often generated de novo by mechanisms other than ectopic recombination a relevant fraction of inversions are associated with complex genomic rearrangements (CGRs), often overlooked in sporadic diseases, and inversions are a "hidden" type of structural variation for which contribution to a clinical phenotypes has been under assessed due to the lack of appropriate detection tools. A combined strategy using multiple genomic tools will be applied to characterize inversions and associated genomic alterations in individuals with neurodevelopmental disorders and controls: whole genome sequencing (WGS) with short-and long-reads; genome mapping; classical cytogenetics; and array CGH. This project will establish common ground to bridge studies of rare and common diseases, human evolution, and population genetics.

  Study phs002999

• Multi-omics bulk and single-cell profiling of epithelioid sarcoma

  Epithelioid sarcoma (EpS) is an aggressive sarcoma, characterized by the loss of SMARCB1 expression. EpS is traditionally classified as distal or proximal according to clinicopathological features, but its molecular characteristics remain largely unknown. To establish an EpS molecular classification and uncover determinants of inter- and intra-patient heterogeneity in EpS, we used multi-omics profiling and integrated the genomic, transcriptional and methylome landscapes with single-cell RNA sequencing on fresh samples as well as spatial transcriptomics. We identified two molecular subtypes of EpS: “distal-like” and “proximal-like”, which were distinct from the histological subtypes. Distal-like tumors include all morphological distal subtypes and a subset of proximal and hybrid EpS. They express a specific molecular single-cell derived epithelial-to-mesenchymal transition signature, which associates with improved patient survival and includes Desmoglein 2 (DSG2), which we identify as a potential routine immunohistochemical biomarker to improve diagnosis. Distal-like EpS also display increased peri-tumoral CD8+ T cell infiltrates and specific tumor-immune cell interactions. Conversely, proximal-like EpS harbor a higher inter-tumoral molecular heterogeneity with some cases resembling other SMARCB1-deficient tumors by DNA methylation profiling, and increased intra-tumoral pro-tumoral macrophage infiltrates. Our study introduces a novel molecular classification of EpS with prognostic value, associated diagnostic biomarkers and distinct tumor immune microenvironments, which extends beyond traditional clinicopathological classification. This paves the way for precision medicine-based therapeutic strategies for patients with EpS.

  Study EGAS50000000973

• RB1 Gene Inactivation by Chromothripsis in Human Retinoblastoma

  Retinoblastoma is a rare childhood cancer of the developing retina. Most retinoblastomas initiate with biallelic inactivation of the RB1 gene through diverse mechanisms including point mutations, nucleotide insertions, deletions, loss of heterozygosity and promoter hypermethylation. Recently, a novel mechanism of retinoblastoma initiation was proposed. Gallie and colleagues discovered that a small proportion of retinoblastomas lack RB1 mutations and had MYCN amplification [1]. In this study, we identified recurrent chromosomal, regional and focal genomic lesions in 94 primary retinoblastomas with their matched normal DNA using SNP 6.0 chips. We also analyzed the RB1 gene mutations and compared the mechanism of RB1 inactivation to the recurrent copy number variations in the retinoblastoma genome. In addition to the previously described focal amplification of MYCN and deletions in RB1 and BCOR, we also identified recurrent focal amplification of OTX2, a transcription factor required for retinal photoreceptor development. We identified 10 retinoblastomas in our cohort that lacked RB1 point mutations or indels. We performed whole genome sequencing on those 10 tumors and their corresponding germline DNA. In one of the tumors, the RB1 gene was unaltered, the MYCN gene was amplified and RB1 protein was expressed in the nuclei of the tumor cells. In addition, several tumors had complex patterns of structural variations and we identified 3 tumors with chromothripsis at the RB1 locus. This is the first report of chromothripsis as a mechanism for RB1 gene inactivation in cancer.

  Study EGAS00001000598

• Identification_of_synthetic_lethal_genes_by_CRISPR_Cas9_library

  Sequencing is performed on PCR products from the amplification of gRNA segments introduced into cell lines (some are commercial, some are derived by collaborators, as described in HMDMC 13/076). Cellular DNA or RNA are not sequenced. This data is defined as "Other Biological/Biochemical Assay Data" under the WTSI datasharing guidelines and consequently will be released at the time of publication and/or through faculty websites. SEQUENCING DETAILS: in October 2016 3 DNA samples will be submitted for PCR amplification and purification through CGP pipeline using Thompson's custom primer set and PCR settings and sequencing with Hiseq using a custom protocol (with 3 forward reads to read sgRNA1, sgRNA2 and the index, optimized with Illumina Bespoke Sanger team); read length 50bp. The following set of samples will be submitted in later 2016 and ealry 2017 as cell pellet to be processed through CGP Cas9 pipeline (Thompson's oligos and protocols) and sequences on Hiseq (same custom sequencing protocol described above) We are utilizing a custom CRISPR/Cas9 library to identify synthetic lethal gene pairs. Cells will be transduced with LV expressing Cas9, then infected with LV expressign the library of 42'000 sgRNA pairs. Cell pellet will be collected from the cell population at different timepoints. The samples will be processed by CGP pipeline customized for the specific protocol and then sequenced to identify the 19bp of the sgRNA and quantify their representation.

  Study EGAS00001002117

• ICU_transcriptomics__Assessing_the_role_of_the_host_immune_response_in_patients_with_ventilator_associated_pneumonia

  The aim of the proposed project is to provide transcriptomic sequencing data analysis of cells isolated from bronchioalveolar lavage and blood samples from critically ill patients with pneumonia on an intensive care unit in order to investigate the host contribution to disease. The lung microbiome of these patients will be analysed in parallel by deep sequencing and 16S sequencing. These data will provide important information to the development of strategies aimed at improving patient outcomes, reducing the development of antimicrobial resistance and facilitating infection control measures in hospital. Specifically, the proposed work will be a proof of principle study of 100 patients. We will use transcriptomic data to define the host contribution to the symptoms of these critically ill patients diagnosed with pneumonia. The data will be correlated with cytokine/chemokine concentrations, routine microbiology analysis and pathogen genomic data from the same samples to determine the ecology of the lungs of these patients. We will look for associations between clinical features, host response and pathogen genomics in order to identify new diagnostic markers. This study should provide important information to improve the speed and accuracy of diagnosis - resulting in more targeted and successful treatment of critically ill patients in the ICU. 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/

  Study EGAS00001003074

• A novel orthotopic patient-derived xenograft model of radiation-induced glioma following medulloblastoma

  Radiation-induced glioma (RIG) is a highly aggressive brain cancer arising as a consequence of radiation therapy. We report a case of RIG that arose in the brain stem following treatment for paediatric medulloblastoma, and the development and characterisation of a matched orthotopic patient-derived xenograft (PDX) model (TK-RIG915). Patient and PDX tumours were analysed using DNA methylation profiling, whole genome sequencing (WGS) and RNA sequencing. While initially thought to be a diffuse intrinsic pontine glioma (DIPG) based on disease location, results from methylation profiling and WGS were not consistent with this diagnosis. Furthermore, clustering analyses based on RNA expression suggested the tumours were distinct from primary DIPG. Additional gene expression analysis demonstrated concordance with a published RIG expression profile. Multiple genetic alterations that enhance PI3K/AKT and Ras/Raf/MEK/ERK signalling were discovered in TK-RIG915 including an activating mutation in PIK3CA, upregulation of PDGFRA and AKT2, inactivating mutations in NF1, and a gain-of-function mutation in PTPN11. Additionally, deletion of CDKN2A/B, increased IDH1 expression, and decreased ARID1A expression were observed. Detection of phospho-S6, -4EBP1 and -ERK via immunohistochemistry confirmed PI3K pathway and ERK activation. Here, we report one of the first PDX models for RIG, which recapitulates the patient disease and is molecularly distinct from primary brain stem glioma. Genetic interrogation of this model has enabled the identification of potential therapeutic vulnerabilities in this currently incurable disease.

  Study EGAS00001004709

• Whole Genome Scan for Pancreatic Cancer Risk in the Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case-Control Consortium (PanScan)

  Within the framework of the NCI-sponsored Cohort Consortium, investigators from 12 prospective epidemiologic cohorts formed the Pancreatic Cancer Cohort Consortium in 2006. This study, also known as "PanScan", is funded by the National Cancer Institute (NCI) and involves conducting a genome-wide association study (GWAS) of common genetic variants to identify markers of susceptibility to pancreatic cancer. In 2007, the study was expanded to include 8 case-control studies. The study team includes scientists from the cohorts comprising the Consortium, the NCI and the Pancreatic Cancer Case Control Consortium (PanC4). PanScan I and II were conducted in 12 cohort studies and 8 case-control studies, leading to the discovery of four novel regions in the genome associated with risk for pancreatic adenocarcinoma. The third phase of PanScan (PanScan III) was conducted using recently identified incident pancreatic cancer cases drawn from fourteen cohorts from the cohort consortium, including nine prospective cohorts who participated in PanScan I, and five newly joined cohorts. The nine cohort studies that participated in PanScan I and had new genotyping of cases in PanScan III include ATBC, CPS-II, EPIC, HPFS, NHS, PHS, PLCO, SMWHS, and WHI; the five newly joined cohort studies include the Agricultural Health Study (AHS), the Multiethnic Cohort Study (MEC), the Melbourne Collaborative Cohort Study (MCCS), the Vitamins and Lifestyle Study (VITAL), and Selenium and Vitamin E Cancer Prevention Trial (SELECT). In addition to the cases from cohorts, we also included cases from the Gastrointestinal Cancer Clinic of Dana-Farber Cancer Institute Study (DFCI-GCC); from the University Hospital in Heidelberg, Germany, which is part of a larger European clinical case-control study (PANDoRA); and from clinic-based cases from eastern Spain (PANKRAS-II). The dbGaP datasets available include all subjects previously made available from PanScan I and II, plus 1,582 new incident pancreatic cancer cases of European descent from prospective cohorts, case-control studies or case series (genotyped as part of PanScan III). Also included are 61 pancreatic cancer cases and 67 control subjects from PanScan I as well as 173 pancreatic cancer cases from PanScan III of Asian ancestry from the Shanghai Men's and Women's Health Study (Supplemental Table 10, Wolpin et al. (Nat Genet, 2014)). The control population used in the analysis for the Wolpin et al. manuscript included cancer-free individuals from the prospective cohorts that contributed pancreatic cancer cases to PanScan III and controls from the Spanish Bladder Cancer SBC/EPICURO study that were previously genotyped using the OmniExpress, Omni 1M or Omni 2.5M SNP arrays. The data from these control subjects were posted to dbGaP under the GWAS in which they were initially genotyped and will not be made available in duplicate under this dbGaP study.The summary statistics for PanScan I-III were generated as detailed in Wolpin BM. et al., Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer, Nature Genetics 2014; 46(9):994-1000 (https://www.nature.com/articles/ng.3052), and Klein, A. et al., Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer, Nature Communications, 2018;9(1):556 (https://www.nature.com/articles/s41467-018-02942-5). The dataset includes results from an association study of 5,117 individuals diagnosed with pancreatic ductal adenocarcinoma (PDAC) and 8,845 control individuals, or a total of 13,962 subjects of European ancestry (as compared to the genotype and phenotype information under this project that includes 9,437 individuals (PanScan I and II PDAC case and control individuals and PanScan III PDAC cases only). This is due to the fact that PanScan III “borrowed” GWAS data from control individuals genotyped separately from the PanScan GWAS project and are therefore not included as raw genotypes in phs000206.v5.p3. Association analysis was performed separately for PanScan I-II and PanScan III, followed by a meta-analysis of the two datasets. Results were filtered based on a minor allele frequency (MAF) < 0.01, an imputation INFO score < 0.3 and a heterogeneity P-value < 1x10-10 leaving a total of 9,758,390 variants. Columns in the summary statistics dataset are as follows: ID: variant rsIDChr: chromosome numberPosition: position in the chromosome, genome build GRCh37/hg19MarkerName: variant identifierAllele1: reference alleleAllele2: alternative alleleFreq1: allele frequency for allele2FreqSE: standard error of the allele frequencyMinFreq: the minimal allele frequency across studiesMaxFreq: the max allele frequency across studiesEffect: effect size for allele2StdErr: standard errorP-value: meta-analysis p-valueDirection: summary of effect direction for each studyHetISq: I^2 statistic which measures heterogeneity on scale of 0-100%HetChiSq: chi-squared statistic in simple test of heterogeneityHetDf: degrees of freedom for heterogeneity statisticHetPVal: P-value for heterogeneity statistic

  Study phs000206

• ENOC WGS for the study Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes

  For ENOC cohorts, OvCaRe cases were reviewed, including frozen material, by at least two expert gynecopathologists prior to inclusion in the sequencing cohort who provided the confirmation on final selected cohort. Frozen H&E from Tokyo were also used for evaluation along with representative H&E photos and review done at the Jikei School of Medicine. For ENOC, DAH985 and DG1288 are recurrent and both were treated with chemotherapy after their first surgery. DAH123 is a untreated sample, metastasis from an primary endometrial tumour. All HGSC, GCT, CCOC and the rest ENOC tumours are primary tumour samples. Library construction and sequencing Frozen specimens with >50% tumour cellularity (based on initial slide review) were used for cryosectioning and subsequent nucleic acid extraction. Patient tumour and normal blood samples derived from primary, untreated fresh frozen tumour specimens harvested at diagnosis during standard of care debulking surgery. Germline DNA was provided from peripheral blood buffy coat on all specimens except 13 from Tokyo, where non-cancer frozen tissue was used as a germline source. DNA extraction from both matched normal (blood) and tumour samples (frozen tissue) were performed using the QIAamp Blood and Tissue DNA kit (Qiagen) and quantified using a Qbit fluorometer and reagents (high-sensitivity assay). Three lanes of Illumina HiSeq 2500 v4 chemistry for normal samples and five lanes for tumour samples were obtained. The PCR-free protocol was adopted to eliminate the PCR-induced bias and improve coverage across the genome.

  Dataset EGAD00001003266

• Randomized Phase II 2 x 2 Factorial Trial of the Addition of Carboplatin +/- Bevacizumab to Neoadjuvant Weekly Paclitaxel Followed by Dose-Dense AC in Hormone Receptor-Poor/HER2-Negative Resectable Breast Cancer

  This randomized phase II trial studies how well paclitaxel with or without carboplatin and/or bevacizumab followed by doxorubicin and cyclophosphamide works in treating patients with breast cancer that can be removed by surgery. Drugs used in chemotherapy, such as paclitaxel, carboplatin, doxorubicin, and cyclophosphamide, work in different ways to stop the growth of tumor cells, either by killing the cells or by stopping them from dividing. Bevacizumab may stop the growth of tumor cells by blocking blood flow to the tumor. Giving chemotherapy together with bevacizumab before surgery may make the tumor smaller and reduce the amount of normal tissue that needs to be removed. All participants in this study were female.

  Study phs001863

• Filtering and Annotation of Variants That Are Rare (FAVR)

  The project developed a suite of new methods (FAVR) designed to assist the shortlisting of genetic variants under a rare variant-phenotype/disease model. The methods were designed to work with commonly used massively parallel sequencing analysis pipelines, such as the GATK or ANNOVAR, and have been made publically available as a suite of software tools (https://github.com/bjpop/favr). The FAVR methods use signatures in comparator sequence alignment files to facilitate the filtering of mapping artifacts and common genetic variants, and annotation of genetic variants based on evidence of co-occurrence in individuals. As relevant, FAVR methods can also be used to filter out artifacts derived from imbalanced paired-end sequencing. Pope et al., BMC Bioinformatics, accepted Dec 2012.

  Study phs000601

• Clinical Outcomes of 344 Diffuse Large B-Cell Lymphoma patients

  This study examines clinical outcomes of patients with diffuse large B-cell lymphoma (DLBCL). We analyzed a cohort of 344 patients from the German High-Grade Non-Hodgkin Lymphoma Study Group (DSHNHL). To protect patient confidentiality, all samples were pseudonymized. The dataset includes clinical key characteristics, such as patient age at diagnosis, sex, ECOG performance status, disease stage, serum lactate dehydrogenase levels, bulky disease, bone marrow involvement, extranodal involvement, and B-symptoms. We used these data alongside proteomic and transcriptomic profiles to explore relationships between clinical features and molecular signatures, reconstructing regulatory networks. Insights from this integrative analysis aim to identify key pathological drivers and biomarkers of DLBCL progression, ultimately informing improved risk stratification and targeted therapeutic approaches.

  Study EGAS50000001054

• Gabriella Miller Kids First Pediatric Research Program in Craniofacial Microsomia

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Craniofacial microsomia (CFM), also termed hemifacial microsomia or oculo-auricular-vertebral spectrum, is the third most common congenital craniofacial condition. CFM comprises a variable phenotype and the most common features include malformations of the ear (i.e. microtia) and lower jaw (i.e. mandibular hypoplasia) on one or both sides. Microtia in the absence of other anomalies is believed to represent the mildest form of CFM. The cause of CFM is unknown for most affected individuals. We have established a cohort through previous studies and collected DNA to identify the genetic contributions to CFM, which could facilitate diagnosis, tailored treatments and guide prevention strategies. Successful completion of this proposal will advance knowledge in the genetic architecture of susceptibility to CFM and will provide insight about the biological mechanisms underlying craniofacial development. The results from this study have the potential to further research on the etiology of other craniofacial conditions, and the pathogenesis of typical and atypical craniofacial development.

  Study phs002130

• Longitudinal Multi-Omic Immune Resource Reveals Dynamic Responses in Healthy Human Aging

  The generation and maintenance of protective immunity is a dynamic interplay between host and environment that is impacted by age. Understanding fundamental changes in the healthy immune system that occur over a lifespan is critical in developing interventions for age-related susceptibility to infections and diseases. Here, we use multi-omic profiling (scRNA-seq, proteomics, flow cytometry) to examine human peripheral immunity in over 300 healthy adults, with 96 young and older adults followed over two years with yearly vaccination. The resulting resource includes scRNA-seq datasets of >16 million PBMCs, interrogating 71 immune cell subsets from our new Immune Health Atlas. This study allows unique insights into the composition and transcriptional state of immune cells at homeostasis, with vaccine perturbation, under Cytomegalovirus (CMV) infection and across age. We find that T cells specifically accumulate age-related transcriptional changes more than other immune cells, independent from inflammation and chronic perturbation. Moreover, impaired memory B cell responses to vaccination are linked to a Th2-like state shift in older adults' memory CD4 T cells, revealing possible mechanisms of immune dysregulation during healthy human aging. This extensive resource is provided with a suite of exploration tools at https://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/ to enhance data accessibility and further the understanding of immune health across age. Please note that the Sound Life Cohort raw data are spread across three dbGap submissions: phs003841.v1 (this study), phs003944.v1, and phs003400.v1.

  Study phs003841

• Evolutionary origin and methylation status of human intronic CpG islands that are not present in mouse

  Imprinting of the human RB1 gene is due to the presence of a differentially methylated CpG island (CGI) in intron 2, which is part of a retrogene derived from the PPP1R26 gene on chromosome 9. The murine Rb1 gene does not have this retrogene and is not imprinted. We have investigated whether the RB1/Rb1 locus is unique with respect to these differences. For this we have compared the CGIs from human and mouse by in silico analyses and found out that there are at least 2033 human intronic CGIs that are not present in the mouse. Among these CGIs, 104 show sequences similarities elsewhere in the human genome, which suggests that they arose by retrotransposition. We could narrow down the time points when most of these CGIs appeared during evolution. Their methylation status was analysed in two monocyte methylome datasets from whole genome bisulfite sequencing and in 18 published methylomes. Five CGIs appear to be differentially methylated, which suggests that they are subject of genomic imprinting. They are located in introns of the following genes: RB1, ASRGL1, PARP11, PDXDC1 and MYO1D. Four of these CGIs are parts of retrogenes. Our study supports the notion that imprinting builds on host defence mechanisms by which the genome protects itself against retrotransposed and foreign DNA and that the epigenetic fate of the retrotransposed DNA depends on selective forces at the integration site.

  Study EGAS00001000719

• Tissue-specific mutation accumulation in human adult stem cells during life

  Gradual accumulation of mutations in human adult stem cells during life is associated with various age-related diseases, including cancer. The number of stem cell divisions throughout life is believed to be a major determinant for mutation accumulation and could explain the extreme variation of cancer incidence across different organs. Yet, mutation patterns and rates of healthy adult stem cells remain unknown. Here, we determined genome-wide mutation patterns in primary adult stem cells of the small intestine, colon and liver of human donors with ages ranging from 3 to 87 years. We find that the number of mutations increases linearly with age up to several thousand mutations per cell at 87 years of age, while mutation spectra remain constant throughout life. Small intestine and colon stem cells have a 2-fold higher mutation rate per year compared with liver stem cells. These differences could be exclusively attributed to the mutagenic action of spontaneous deamination of cytosine residues and may reflect the high stem cell division rate in these tissues. The genomic distribution of somatic mutations is non-random and predominantly associated with DNA replication dynamics in the small intestine and colon, and with transcription in the liver. These results indicate that a stable balance between various mutagenic and DNA repair processes is maintained throughout life and that the activity of these processes in adult stem cells varies between tissues.

  Study EGAS00001001682

• Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR01

  As a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Paired DNA samples – isolated from the tumor tissue and from the blood of fifty patients – have been analyzed to catalog germline and somatic mutations. Association between each observed genomic alteration and exposure to environmental risk factors is being explored.Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from blood and tumor tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Exome capture and deep resequencing are being performed at the National Institute of Biomedical Genomics, Kalyani. We have analyzed the exomes of paired blood and tumor DNA samples using two orthogonal platforms – exome capture by Roche-Nimblegen SeqCap Ez kit followed by sequencing on Roche-454 GS FLX, and exome capture by Illumina TrueSeq Exome Enrichment kit followed by sequencing on Illumina HiSeq-2000. Each exome is being sequenced at a mean depth of 30x. In addition, we have used Illumina Omni Quad SNP-chips to generate genotype data at 1.14 million genomic markers. The average concordance between SNP-chip and sequence data is 99.8%.

  Study EGAS00001000249

• A Clone's Genomic Stability as a Biomarker of Its DNA-Damage Resilience

  A main problem in the treatment of advanced cancers, including gastric cancers and glioblastoma, is the incertitude at which we predict how individual patients will respond to DNA-damaging agents, especially on the long run. Knowing the mechanism behind a patient's response, or the lack thereof, will help us depart from the oversimplified “more-is-better” and “one-size-fits-all” principles according to which DNA-damaging agents are administered. This will improve clinical outcome by allowing us to pinpoint those who would respond better and longer to lower doses than to higher doses of DNA-damaging agents. Under the assumption that the success of DNA-damaging therapy increases with the proliferation rate of a relatively homogeneous tumor population, there was little reason to assume anything other than monotonic dose-response relations. With the recent paradigm shift that most cancers are in fact DNA mosaic products of ongoing evolution, comes the urgency to reconsider these fundamental principles behind DNA-damaging therapy administration. As the developers of one of the first DNA deconvolution methods and with access to technologies to profile the transcriptomes of up to 10,000 cells simultaneously, we are equipped to embark on first personalized dose-finding strategies for DNA-damaging therapies. We will test the potential of the very long-term legacy that DNA-damage entails on a cell “genomic instability” as new biomarker of DNA-damage response. Our preliminary studies showed that, for most cancer types, DNA-damaging agents change a clone's genomic instability and that clones succumb to a limit in the amount of genomic instability they can tolerate. In particular, our results showed that patients with intermediate genomic instability have a very poor outcome and that this relation is only evident among treatment-naive patients, but not among patients treated with DNA-damaging agents. Further they show that we can measure genomic instability per clone and that clones with extreme genomic instability typically don't grow large. Our hypothesis that genomic instability, rather than proliferation rate, determines how sensitive a tumor is to DNA-damaging agents on the long-term, is founded on two unexpected findings. Patients with extremely high genomic instability per tumor clone have an exceptionally good outcome. Aim 1 will integrate exome- and single cell RNA-Seq (scRNA-Seq) data to characterize clones and to measure how much genomic instability they can tolerate. Low genomic instability is associated with reduced benefit from DNA-damaging agents. Aim 2 will use comet assays and treatment history to quantify DNA damage per clone, relating it to the clones' ability to tolerate DNA damage and to changes in the genomic instability of therapy-surviving clones.

  Study phs003762