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• Induced Pluripotent Cells Derived from Differentiated Rod Photoreceptors Undergo Efficient Retinogenesis in Three-Dimensional Cultures

  "Embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) are used to study lineage-specific differentiation in culture. We developed a standardized quantitative protocol called STEM-RET to compare eye field specification, optic cup formation, and retinal differentiation across stem cell populations. We reprogrammed individual rod photoreceptors into iPSCs by inducible expression of Oct3/4, Klf4, Sox2, and Myc. We also developed ESC lines from rods by somatic cell nuclear transfer. Using the STEM-RET protocol, we compared the abilities of ESCs, fibroblast-derived iPSCs (f-iPSCs), rod photoreceptor-derived iPSCs (r-iPSCs), and rod photoreceptorderived ESCs to form retinae using STEM-RET. r-iPSCs were the most efficient at producing differentiated retina. Retinae derived from f-iPSCs lacked an inner nuclear layer (INL) and had a concomitant reduction in amacrine cells and other INL cell populations. The INL-specific LIM homeobox gene, Lhx9, was hypermethylated in fiPSCs and concomitantly downregulated in retinae derived from those stem cells. ChIP-seq analysis for H3K36me3, H3K4me1, H3K4me3, H3K9/14Ac, H3K27me3, H3K9me3, CTCF and 5 hydroxymethyl cytosine showed that the major difference between the r-iPSCs and the f-iPSCs were in the genes marked by the CTCF insulator protein. Importantly, CTCF binding enrichment at rod photoreceptor specific genes was at least 10-fold higher in r-iPSCs relative to f-iPSCs. Taken together, our data suggest that both inhibitory and permissive epigenetic marks important for retinal development can be retained in iPSCs and such marks can be exploited to select the most favorable stem cell population to study retinal development or produce photoreceptor precursors for cell transplantation."

  Study EGAS00001001288

• DSRCT RNA genomic sequencing

  Purpose: To further understand the molecular pathogenesis of desmoplastic small round cell tumor (DSRCT), a rare but often fatal malignancy occurring primarily in young males, we used next-generation RNA sequencing to investigate the gene expression profiles intrinsic to this disease.Experimental Design: RNA from DSRCT tumor samples were obtained from the Cooperative Human Tissue Network biorepository. RNA sequencing was completed using the Illumina HiSeq 2000 system. Presence of the EWSR1-WT1 fusion was verified using both RNA-sequencing and PCR. Validation studies, including WT1 ChIP-seq, RNA sequencing, and EWS-WT1 knockdown experiments, were performed on an established DSRCT cell line, JN-DSRCT-1. Protein expression of clinically relevant genes determined by RNA sequencing was confirmed using immunohistochemistry. A panel of immune signature genes was also evaluated to identify possible immune therapeutic targets. Results: We analyzed the RNA from 14 tumor samples, of which two were confirmed negative for the diagnostic EWSR1-WT1 translocation. Principal component analysis of the sequencing data indicated that fusion-negative and fusion-positive tumors are transcriptionally distinct entities. Overlapping the significant ChIP-seq peaks with genes found to be highly expressed in the RNA sequencing data revealed that IGF2 and FGFR4 were both highly expressed, and targets of the EWS-WT1 fusion gene. This finding has potential clinical relevance for targeted therapeutic intervention. In addition, we identified the immune checkpoints CD200 and CD276 as potentially targetable genes whose expression is independent of the EWS-WT1 fusion gene in vitro.Conclusions: Despite the transcriptional complexity of this disease, we were able to identify IGF2, FGFR4, CD200, and CD276 as potential therapeutic targets for patients suffering from DSRCT.

  Study EGAS00001002770

• 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

• Single_cell_measurements_to_characterise_B_cell_repopulation_in_SLE_after_rituximab_therapy__a_pilot_study

  Systemic lupus erythematosus (SLE) is a systemic autoimmune disease characterised by autoantibodies against DNA and nuclear proteins. Kidney involvement (lupus nephritis) is one of the most serious manifestations and is the leading determinant of long-term prognosis. Therapies targeting B cells (e.g. rituximab) are used in the treatment of severe lupus, including lupus nephritis. Rituximab is a monoclonal antibody that targets the CD20 surface protein on the surface of B cells. Following rituximab treatment, there is near complete depletion of B cells in peripheral blood. Peripheral blood B cells slowly return over a period of months. The speed of repopulation varies but typically B cells have returned to baseline levels between 9 and 12 months post rituximab therapy. Return of B cells may be associated with increased disease activity, but this is not always the case. For example, some patients remain in clinical remission for several years following one cycle of rituximab, despite B cell repopulation, whilst others relapse as soon as the B cell number reaches the normal range. The reasons for the different response remain unclear. The B cell subpopulations that return following B cell depleting therapy have been previously studied using flow cytometry but have never been characterised using single cell -omic technologies and thus no data on their molecular signatures are available. Previous studies have shown that naïve B cells were the predominant repopulating B-cells, indicating de novo production of B cells. Obtaining an integrated understanding of the molecular programs of these cells at the single cell level will enhance our ability to predict disease outcome, to identify patients with poorer B-cell drug responses, understand disease heterogeneity and design more effective B-cell targeted therapies approach.

  Study EGAS00001006798

• 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

• Center for Common Disease Genomics [CCDG] - Cardiovascular: Genetics of Coronary Heart Disease - Characterizaton of Coronary Prone Pedigrees

  The primary cohort includes samples from 499 men and 154 women who survived a myocardial infarction, percutaneous transluminal angioplasty, or coronary artery bypass grafting (CABG) by age 55 years for men or age 65 years for women. Patients were seen at least six months after their acute event. Samples from another 488 men and 541 women that showed a nearly identical age, gender, and measured blood pressure distribution were collected as population-based controls. These controls tended to live in urban Salt Lake City, where the vast majority of the population is Caucasian. Blood samples were collected in the morning after 12h to 16h of fasting and prepared according to guidelines of the Lipid Research Clinic's program Manual of Laboratory Operations. All samples have serum, DNA and/or white blood cells, and a host of measurements (e.g. standard clinical chemistries, LDL and HDL cholesterol, triglycerides, glucose, HbA1C, insulin, blood pressures, anthropometric data, information on medical conditions and drug use, etc.). Additional details about the cohort or sample preparation were published previously. Here we present in total 1,475 patients that were successfully sequenced. This number includes 228 women, 419 men, and 7 of unreported gender survivors as well as 339 women and 482 men that served as population-based controls.

  Study phs001901

• Transcriptome sequencing of gingivo-buccal oral squamous cell carcinoma for integrative analysis: alterations in expression of genes attributable to methylation changes

  Gingivo-buccal oral squamous cell carcinoma (OSCC-GB) is the most common cancer among men in India and is associated with high mortality. Although OSCC-GB is known to be quite different from tongue cancer in its genomic presentation and its clinical behavior, it is treated identically as tongue cancer. Predictive markers of prognosis and therapy that are specific to OSCC-GB are, therefore, required. To achieve this, we have carried out transcriptome (n=72) profiling of paired tumor-normal tissues collected from OSCC-GB patients from India. RNA sequencing was performed on tumor and paired adjacent normal samples from 72 OSCC-GB patients. From each patient, total RNA was extracted from tumor and normal tissue samples using AllPrep DNA/RNA Mini Kit (QIAGEN). The quality and concentration of isolated total RNA were checked using Agilent 2100 Bioanalyzer and NanoDrop 2000 (Thermo Fisher Scientific). The OD260/OD280 ratio was ≥ 2 and RNA Integrity Number (RIN) was ≥ 7.0 for all sequenced samples. Ribosomal RNA (rRNA) was removed from the RNA samples, using Ribo-Zero Magnetic Kit (Epicentre). Sequencing libraries were prepared from rRNA depleted samples using TrueSeq RNA Sample Preparation Kit (Illumina). Each triplex cDNA library pool was sequenced as 100bp paired-end on HiSeq-2000 or HiSeq-2500 (Illumina). Protocols suggested by the manufacturers were used for all assays.

  Study EGAS00001003893

• Patient-derived tumor organoids for personalized medicine in a rare case of hepatocellular carcinoma with neuroendocrine differentiation.

  We report the case of a 74-year-old man with a very rare subtype of hepatocellular carcinoma with neuroendocrine differentiation (HCC-NED). The patient presented with two independent tumors, a gastrointestinal stromal tumor in the stomach and a hepatocellular carcinoma in the liver. Both tumors were surgically removed in curative intent. Histopathological work-up of the liver tumor revealed poorly differentiated hepatocellular carcinoma (Edmondson-Steiner grade IV) with diffuse expression of neuroendocrine markers synaptophysin (SYP) and chromogranin (CHGA). Three months after resection, multifocal recurrence of the HCC with neuroendocrine differentiation (HCC-NED) was observed. In the meantime, tumor organoids have been generated from the resected HCC-NED and extensively characterized. Sensitivity to a number of drugs approved for the treatment of HCC or neuroendocrine carcinomas was tested in vitro. Based on their in vitro efficacy, etoposide and carboplatin were used as first line palliative combination treatment. Because genomic analysis revealed a NTRK1-mutation (kinase domain) and tumor organoids were sensitive to entrectinib, a pan-TRK inhibitor, the patient received entrectinib as second line therapy. After only two weeks, treatment had to be discontinued due to deterioration of the patient’s general condition. In conclusion, we demonstrate for the first time that preclinical drug testing using organoids is feasible in selected HCC cases.

  Study EGAS00001005887

• Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007451

• Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007545

• Sequencing data (BAM files) from - A mutation in VPS15 (PIK3R4) causes a ciliopathy and affects IFT20 release from the cis-Golgi. The Data Access Committee (DAC) is responsible for sequencing data release to external requestors based on consent and/or National Research Ethics terms.

  Dac EGAC00001000552

• EGAD00010000744

  Subset 2 of osteoarthritis cases genotyped on Illumina 610k from the arcOGEN Consortium (http://www.arcogen.org.uk/) with consent for osteoarthritis studies only.

  Dataset EGAD00010000744

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Transcriptomic sequencing on pre-immunotherapy melanoma patients.

  Dataset EGAD00001007710

• OncoScan SNP data set for localized follicular lymphoma (lFL)

  149 unpaired initial tumor samples (133/149 FFPE and 16/149 fresh frozen samples) of lFL patients measured with OncoScan SNP microarrays, Affymetrix CEL intensity data file types (Thermo Fisher Scientific, Waltham, Massachusetts, USA)

  Dataset EGAD00010002593

• SECRETO Oral metagenome

  The dataset comprises data for n=329 participants who underwent saliva sampling. Shotgun metagenomic paired-end sequencing was conducted using the Illumina NovaSeq 6000 platform, and the resulting files are in FASTQ format.

  Dataset EGAD50000000283

• Multi time/space shallow whole genome sequencing of esophageal adenocarcinoma's

  Shallow whole genome sequencing of 170 samples from 24 esophageal adenocarcinoma's. DNA was obtained from FFPE stored material. Illumna Hiseq 400 was used for sequencing.

  Dataset EGAD50000000318

• Multimodal epigenetic sequencing analysis for colon cancer

  Targeted methylation sequencing (enzymatic conversion) data of plasma samples collected from colon cancer patients and non-cancer subjects.

  Study EGAS50000000052

• AmsterdamUMC Data Access Committee for the EPIC-CD study

  The current data access committee reviews and assesses data requests of researchers that seek to gain access to data acquired as part of the EPIC-CD project as performed at the AmsterdamUMC, Amsterdam, Netherlands.

  Dac EGAC50000000097

• ATAC Dataset for 19 T-ALL patient samples and 1 normal control sample

  19 ATAC-seq from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference

  Dataset EGAD50000000024