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• Genetic diversity and continuity of the population of the UAE

  With high consanguinity rates on the Arabian Peninsula, it would not have been unexpected if the population of the UAE was shown to be relatively homogenous. However, this study of 1,000 UAE nationals, provided a contrasting perspective, one of a relatively heterogeneous population. Located at the apex of Europe, Asia and Africa, the observed diversity could be explained by a plethora of migration patterns since the first Out-of-Africa movement. A strategy to explore the extent of genetic variation of the population of the UAE is presented. The first step involved a comprehensive population stratification study that was instructive for subsequent Whole Genome Sequencing (WGS) of suitable representatives (which is described elsewhere). When this UAE data was compared to previous smaller studies from the region, the findings were consistent with a population that is a diverse and admixed group of people. However, rather than sharp and distinctive clusters, a continuous genotype distribution was observed. The analysis showed a continuous gradient of ancestral populations, suggesting that admixture on the south eastern tip of Arabian Peninsula occurred gradually. When visualized using a unique technique that combined admixture ratios and Principal Component Analysis (PCA), unappreciated diversity was revealed while mitigating projection bias of conventional PCA. The analytical strategy used here highlights the complementary nature of data from genotype array and WGS for anthropological studies. Specifically, genotype array data was instructive to select representative subjects for WGS. Furthermore, from the 2.3 million allele frequencies obtained from genotype arrays, we identified 46,481 loci with allele frequencies that were significantly different with respect to other world populations. This comparison of allele frequencies facilitates variant prioritization in common diseases. In addition, these loci bear great potential as biomarkers in anthropological and forensic studies.

  Study EGAS00001004362

• Matching of actionable mutations with therapies in cancer patients: comparison of three commercial decision support platforms

  Purpose: In oncology, precision medicine centers on tailoring the most appropriate therapy to a patient according to their tumor molecular profile. We addressed the question whether there is a consensus in the classification of actionability of somatic variants and their alignment to treatment recommendations. To this end, we evaluated three commercial clinical decision support tools to assess their variant classification and drug matching strategies.Methods: In this two centers study 48 patients with metastatic breast (n=12), colorectal (n=17) or non-small cell lung cancer (n=19) were recruited based on circulating tumor DNA levels in peripheral blood. In individual patients’ plasma samples, we established somatic copy number alterations and somatic mutations across a 77 cancer-associated gene panel and exposed the obtained molecular profiles to the decision support packages NAVIFY Mutation Profiler (NMP; Roche), Qiagen Clinical Insight (QCI) Interpret (Qiagen) and CureMatch Bionov (CureMatch).Results: In the plasma samples, altogether 492 somatic alterations were assessed. Each decision support platform varied in their format of data input, mode of variant classification and strategies for identifying druggable targets and clinical trials, which resulted in discrepancies in tier classification as well as designations of actionability. The frequency of concordant actionable events for tier I-A or tier I-B classifications, i.e. those with the strongest clinical evidence, was only 4.3%, 9.5% and 28.4% when comparing NMP with QCI, NMP with CureMatch, and CureMatch with QCI, respectively. As a consequence, the obtained treatment recommendations differed drastically, and alignment of treatment recommendations was limited to established predictive markers.Conclusions: The lack of standards for the extraction of treatment recommendations from comprehensive tumor molecular profiling data challenge the promising concepts of precision oncology.

  Study EGAS00001004383

• Post_Mortem_Tissue_COVID19_spatial

  Single cell analysis of post mortem tissue samples from SARS-CoV2-infected patients We aim to directly identify the human cell types infected by SARS-CoV-2 and measure the cellular response to COVID19 infection across 20 different tissues from infected patient autopsies. We have examined the expression pattern of viral entry receptors across healthy human tissues to predict several candidate target cell types across the airway and heart. In addition, high prevalence of cardiac failure and abnormal renal function in COVID19 patients implicates heart and kidney involvement, but the pathogenesis of organ specific damage - whether via a direct cytopathic mechanism or an indirect inflammatory response - remains unknown . Currently, we lack confirmation of target cell types and cellular processes in infected tissues as autopsies are discouraged in most countries due to health and safety risks. Our collaborators Drs Michael Osborn and Brian Hanley (Imperial College) have outlined guidelines to perform post-mortem in COVID19 patients (Hanley et al., 2020) and have established a programme of autopsies for research to be performed in a high-risk facility at Westminster Public Mortuary. Here, we propose to identify infected cell types and aberrant molecular pathologies in this precious tissue resource using single cell and spatial genomics. We will prioritise three organ systems: the human airway, heart and the kidney. We will directly examine the cellular identities of SARS-CoV-2 infected cell types and identify the cellular responses to infection across these organs. This fundamental knowledge will help guide future treatment choices for COVID19. 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 EGAS00001004441

• Whole genome sequencing of a breast cancer cohort with known functional homologous recombination status

  Optimal patient selection for PARP inhibitors and double strand break (DSB) inducing chemotherapy is of great clinical importance. In principle, the use of these therapies can be extended beyond germline BRCA1/2 mutated cancers. Although several methods for detection of BRCA-like tumors have been developed, a golden standard is lacking. We have developed the RECAP test, a functional HR assay exploiting the formation of RAD51 foci in proliferating cells after ex vivo irradiation of fresh primary breast cancer (BrC) tissue. The RECAP test seems robust and has an advantage over genetic tests, due to its functional character for exploring the HR phenotype. Another type of HRD test is the BRCAness classifier, which is based on specific genomic patterns derived from copy number data of BRCA1/2 mutated BrCs that also occur in sporadic cancers. The BRCAness classifier is a robust test that is easily applicable in the clinic and has also been validated to predict in vivo response to high dose chemotherapy in clinical trials. More recently, a new HRD test based on genomic signatures which can be extracted from whole genome sequencing has been published, HRDetect. Studies comparing these different HRD tests within the same cohort of patients do not yet exist. Here, we have the unique opportunity to compare three HRD tests within the same cohort. We aim to compare three different HRD tests (RECAP, BRCAness classifier and HRDetect) within the same cohort of primary BrCs (n=41). As a secondary aim, we will analyze additional genetic alterations in HRD tumors (both BRCA-deficient and BRCA-proficient HRD tumors).

  Study EGAS00001005572

• The clinical utility of genomics in childhood cancer extends beyond targetable mutations

  Survival of children with relapsed cancer remains unacceptably low. Cancer genomic profiling may identify new therapeutic options, enhance diagnostic accuracy, and improve understanding of tumors’ origins and continued evolution. We deeply sequenced 864 cancer-associated genes and the complete genomes and transcriptomes for 300 pediatric and adolescent/young adult (AYA) patients with poor prognosis or rare tumors. Using integrative somatic-germline analyses, we assessed the clinical utility of cancer genomics in this population. We analyzed tumor mutational signatures and burden to interrogate the relevance of germline variants in DNA repair genes and the impact of therapeutic exposures on tumor evolution. We also evaluated the frequency of changes to tumor drivers and therapeutic targets at relapse in those with serial samples. Integrative analysis yielded clinically actionable variants in a majority of patients. Improved diagnostic accuracy led to modified management in a subset. Therapeutically targetable variants were of unanticipated timing and type, with many of these derived from the germline. Enrichment in corroborating mutational signature 3 (‘BRCAness’) in patients with germline homologous recombination defects suggests they are drivers of pediatric cancers and potential targets for PARP inhibition. We show that mutation burden, which may in part be driven by prior therapeutic exposures, was significantly elevated in a minority of patients. Over one-third of patients with sequential samples analyzed showed a change in therapeutically-targetable drivers. Comprehensive somatic-germline cancer genomic profiling is useful at multiple points in the care trajectory for pediatric/AYA patients, supporting its integration into early clinical management. Re-biopsy at the time of relapse should be considered, and specific attention to mutational burden is indicated. Defective DNA repair genes in the germline may represent important targetable drivers.

  Study EGAS00001006034

• ctDNA monitoring using patient-specific sequencing and integration of variant reads - Breast cohort

  Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

  Study EGAS00001004446

• Integrative analysis of exome-seq, RNA-seq, ATAC-seq (bulk and single-cell), and Hi-C data generated from 3-D spatially mapped samples acquired during surgical resection from 10 patients diagnosed with IDH-WT glioblastoma

  Glioblastoma (GBM), the most common primary brain cancer in adults, remains incurable with no targeted therapies approved despite decades of investigation into its molecular landscape. Treatment failure is attributed to intratumoral heterogeneity in the GBM genome and epigenome, which foster tumor evolution and selection of resistant clones. However, tumor evolution and intratumoral heterogeneity remain poorly understood on the level of the whole tumor as most studies are based on single samples per patient and lack spatial context. Here, we have used 3-D neuronavigation during surgical resection for 10 primary IDH-WT GBM patients to collect 102 samples representing maximal tumor diversity, each mapped by 3-D spatial coordinates. We have applied a strategic set of genomic and epigenomic assays spanning multiple levels of resolution to discover, orthogonally validate, and functionally assess drivers of tumor evolution and intratumoral heterogeneity. These include extrachromosomal DNA amplifications, chromothripsis events, inversions, and translocations that disrupt both the GBM genome and epigenome while generating fusion transcripts and opportunities for therapeutic intervention. We define epigenomic programs that contribute to GBM evolution and intratumoral heterogeneity, revealing their 3-D spatial patterning within whole tumors and their cell type(s) of origin in single-cell data from the same tumor samples. Notably, we distinguish neuronal, glial, and immune programs aberrantly active in tumor cells from their counterparts in normal cells and discover NEUROD1, JUN/FOS, and NF1 transcription factors as key drivers of GBM evolution and growth. Collectively, these data provide unprecedented insight into GBM evolution and intratumoral heterogeneity from single-cell to whole-tumor resolution, redefining current understanding and providing a rich resource of targets for therapeutic investigation.

  Study EGAS00001006785

• cfDNA dataset from the urine supernatant of ovarian cancer patients and healthy controls

  Background Ovarian cancer is the deadliest gynecological malignancy worldwide, due to frequent diagnosis at advanced stage. Simple and non-invasive methods for earlier and accurate detection are urgently needed. Here, the presence of tumor-derived DNA in home-collected urine, cervicovaginal self-samples and clinician-taken cervical scrapes of ovarian cancer patients was explored by DNA methylation and copy number analysis. Methods A total of 428 samples (urine, cervicovaginal self-samples, and clinician-taken cervical scrapes) of 110 healthy controls and 54 patients with benign (n=25) or malignant (n=29) ovarian masses were analyzed. Different urine fractions were examined (full void urine, urine supernatant, and urine sediment). All samples were tested for 12 methylation markers by quantitative methylation-specific PCR. Shallow whole-genome sequencing was performed to detect copy number aberrations and verify the presence of tumor-derived DNA. Results Full void urine was most discriminatory between healthy controls and ovarian cancer patients (C2CD4D, p=0.008; CDO1, p=0.022; MAL, p=0.008), followed by cervical scrapes (C2CD4D, p=0.001; CDO1, p=0.004). A significant difference between benign and malignant ovarian masses was only observed for GHSR in the urine sediment (p=0.024). Methylation levels in cervicovaginal self-samples did not discriminate between healthy controls, benign and malignant ovarian masses. Copy number changes were identified in 17% of urine supernatant samples and smaller fragment sizes were seen in urine supernatant samples with a high tumor fraction. Conclusions This study demonstrates the presence of ovarian cancer-derived DNA in home-collected urine. Additional studies are warranted to further explore the clinical applicability of this approach.

  Study EGAS00001007238

• Whole genome sequencing of tumor samples from advanced pre-treated NSCLC patients recruited in a phase I/II single-arm trial utilising CVA21, an oncolytic coxsackie virus, in combination with pembrolizumab.

  Acquired or de novo resistance to immune checkpoint inhibitors occurs in the majority of advanced non-small cell lung cancers (NSCLC). There is an unmet need to improve outcomes for patients with this condition. Oncolytic viruses represent an attractive treatment approach due to their dual activity in inducing tumor cell lysis directly and potentially augmenting anti-tumor immunity. Here, we present the safety, efficacy and translational findings from a phase I/II single-arm trial utilising CVA21, an oncolytic coxsackie virus, in combination with pembrolizumab in patients with advanced pre-treated NSCLC. We performed paired biopsies pre- and post-treatment in 10 patients who received intravenous CVA21 and pembrolizumab, 8 of whom had prior treatment with immune checkpoint inhibitor (ICI) therapy. Whole genome sequencing and spatial proteomics were performed to comprehensively characterise the response to CVA21. Combination CVA21/pembrolizumab (anti PD-1) therapy was well tolerated with no serious treatment-related adverse events. Partial responses were seen in two patients with prior acquired anti-PD-1 resistance and disease stabilisation in 6 patients, giving a clinical benefit rate of 80%. High baseline tumor mutational burden and PD-L1 expression were observed in patients with better response to treatment. Interestingly, an increase in antigen presentation and CD8+ T cell infiltration was observed on treatment compared with baseline in patients with better progression-free survival. This study demonstrates the potential of CVA21 to modulate the immunogenicity of tumor cells and remodelling the tumor microenvironment, providing novel insights for patient selection for trials involving novel immunotherapeutic approaches.

  Study EGAS00001008258

• UniKilinikum Wuerzburg MSNZ AGRasche/AG Riedel EMD DAC

  This is a Data access committee for the Data presented in the paper tilted "Spatially resolved transcriptomics reveals profound subclonal heterogeneity and T cell dysfunction in extramedullary myeloma"

  Dac EGAC50000000173

• Transcriptome analysis of Hepatitis B for drug discovery and clinical applications

  We analyzed blood transcriptome of HBV positive untreated patients (men) using the CAGE technology.

  Study JGAS000053

• RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Transcriptomic analysis of K7M2 murine osteosarcoma cells stably modified to overexpress or repress CYR61

  Study EGAS50000000526

• SEARCH FOR BACTERIA IN NEURAL TISSUE FROM AMYOTROPHIC LATERAL SCLEROSIS

  The study aims to find bacteria in neural tissue from patients with amyotrophic lateral sclerosis

  Study EGAS00001003295

• RNA sequencing of mCRPC patient biopsies

  RNA sequencing of mCRPC patient biopsies obtained for the profiling of the prevalence of immune transcripts. Manuscript can be found at PMID: 35491356

  Dataset EGAD50000001811

• Optimized large-scale longitudinal biorepository of gastroesophageal adenocarcinoma patient-derived organoids: High-fidelity models for personalized treatment to overcome resistance

  Whole exome sequencing of patient tumour samples and matched patient derived organoids.

  Dataset EGAD50000002315

• ERDERA WES reanalysis - DPF1 Batch 1

  Processed data for 100 WES from the Data Processing Freeze 1

  Dataset EGAD50000002187

• Sequencing data for filanesib-treated hepatoblastoma samples

  This dataset contains RNA sequencing data of two hepatoblastoma PDX cell models. Cells were either treated with KSP inhibitor filanesib or with DMSO (controls).

  Dataset EGAD50000001314

• Patient TSO500 VCF files

  Tumours from MMRd EC patients treated with 2 cycles neoadjuvant ICI. TruSight Oncology 500 (TSO 500) panel for all 10 tumour samples from patients included in the trial.

  Dataset EGAD50000000694

• Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types

  Raw bam file for bulk RNA-seq of checkpoint-blockade treated lung cancer cohorts

  Dataset EGAD50000000469

• Profiling of human fecal microbiota for succinate consumption

  Enrichments of human stool samples in culture medium containing succinate as the main carbon source and the corresponding stool samples.

  Dataset EGAD50000000740

• WGS and WXS for mismatch repair-deficient human colon organoids

  Whole genome/exome sequencing to detect spontaneous acquired mutations in mismatch repair-deficient human colon organoids.

  Dataset EGAD50000000159

• GCAT| SNParray GSA TopMed

  2746 samples issued from GCAT cohort, genotyped with GSA Array, with data for Cr1-23. Plink files with QC and imputed using TOPMed.

  Dataset EGAD00010002758

• OncoScan SNP data set for systemic follicular lymphoma (sFL)

  122 unpaired initial tumor samples (122 FFPE samples) of sFL patients measured with OncoScan SNP microarrays, Affymetrix CEL intensity data file types (Thermo Fisher Scientific, Waltham, Massachusetts, USA)

  Dataset EGAD00010002592

• Hostage_1_genotype

  Cohort: Raw genotype files for Hostage1 cohort. Genotype Chip: Illumina’s (Illumina Inc., San Diego, U.S.) Global Screening Array-24 Multi Disease (GSA) Version 2.0 B1 genomic build: b37

  Dataset EGAD00010002180

• Richter Syndrome Methylation dataset

  Raw idat files for 90 RS + DLBCL + CLL samples.

  Dataset EGAD00010002194