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• Genetic Analysis of Skin Cells

  Cutaneous squamous cell carcinoma (cSCC) is a form of skin cancer originating from keratinocytes in the skin. They have high mutation burdens, primarily driven by UV-radiation-induced DNA damage. The order in which mutations undergo selection during the evolution of cSCC is not known. A subset of cSCCs grow out of benign neoplasms called actinic keratoses. To better understand the evolution of cSCC, we identified cases of cSCCs adjacent to actinic keratoses. From these cases, we separately microdissected the surrounding normal skin, the actinic keratosis, and the cSCC, and we performed targeted DNA-sequencing on the tissue from each area. We reconstructed tumor phylogenies and performed spatial transcriptomics on the 10X FFPE Visium platform on a subset of cases. Collectively, these studies revealed the mutational and gene expression changes that arise during the evolution of cSCC.

  Study phs003282

• Separation of chronic myeloid leukemia stem cells from normal hematopoietic stem cells at single-cell resolution

  Chronic myeloid leukemia (CML) is a clonal disease, initiated and sustained by a subpopulation of CML stem cells (CML-SC) containing the BCR::ABL1 oncogene. Genetic markers that enrich for CML-SC have been identified, including CD26 being most specific. Genome sequencing analysis remain yet to be performed at single cell level in order to determine differences and heterogeneity in the genetic profile of CML-SC versus normal hematopoietic stem cells (HSC). Here we show that CD26 and CD33 separate CML-SC from normal HSC in freshly isolated bone marrow samples from newly diagnosed CML patients. DNA sequencing confirms that single CML-SC derived colonies are positive for BCR::ABL1 and harbor a recurrent set of patient-specific clonal somatic mutations across different CML-SC derived colonies. In contrast, marker-negative (CD26-CD33-) HSC from the same patients are negative for the BCR::ABL1 oncogene and do not carry recurrent, clonal mutation across different colonies. These results support the concept that CD26/CD33 expression separates genetically defined, clonal mutant CML-SC from normal HSC that carry individual sets of random mutations in CML patients. We provide whole exome DNA sequencing data for 23 clinical samples of CML-SC plus two buccal swipes derived normal samples. CML samples are comprised of 4 to 8 replicates from two patients, at diagnosis and after treatment. Single CML stem cells before treatment and single non-transformed HSC at remission were selected from bone marrow samples by FACS, according to genetic markers CD33+CD26+ at diagnosis and CD33+CD26-/CD33-CD26- at remission. WES libraries of colony forming assays derived CML-SC and HSC populations were prepared using Agilent SureSelect Human All Exon V6 kit and sequenced running 150 cycles (2x 75bp paired-end) on an Illumina NextSeq 500 platform. Following GATK best practices for somatic mutation calling, novel CML variants and random mutation events during remission phase were obtained.

  Study EGAS00001006904

• Reliable detection of somatic mutations in solid tissues by laser-capture microdissection and low-input DNA sequencing

  Somatic mutations accumulate in healthy tissues as we age, giving rise to cancer and potentially contributing to ageing. To study somatic mutations in non-neoplastic tissues, we developed a series of protocols to sequence the genomes of small populations of cells isolated from histological sections. Here, we describe a complete workflow that combines laser-capture microdissection (LCM) with low-input genome sequencing, whilst circumventing the use of whole-genome amplification (WGA). The protocol is subdivided broadly into 4 steps: tissue processing, LCM, low-input library generation and mutation calling and filtering. The tissue processing and LCM steps are provided as general guidelines which may require tailoring based on the specific requirements of the study at hand. Our protocol for low-input library generation utilises enzymatic rather than acoustic fragmentation to generate WGA-free whole-genome libraries. Finally, the mutation calling and filtering strategy has been adapted from previously published protocols to account for artefacts introduced via library creation. To date, we have used this workflow to perform targeted and whole-genome sequencing of small populations of cells (typically 100-1,000 cells) in thousands of microbiopsies from a wide range of human tissues. The low-input DNA protocol is designed to be compatible with liquid handling platforms and make use of equipment and expertise standard to any core sequencing facility. However, obtaining low-input DNA material via LCM requires specialized equipment and expertise. The entire protocol from tissue reception through whole-genome library generation can be accomplished in as little as a week, though 2-3 weeks would be a more typical turnaround time.

  Dataset EGAD00001006088

• Comprehensive analyses of clinicopathological features and genomic mutations of combined hepatocellular-cholangiocarcinoma

  Combined hepatocellular and cholangiocarcinoma (cHCC-CCA) is a rare primary liver cancer. We performed whole exome sequencing to clarify the relationship between genetic mutations and clinicopathological features in cHCC-CCA.

  Study JGAS000599

• cytogenetically visibile inversions

  Pacbio Hifi whole genome sequencing data from six individuals carrying cytogenetically visible inversions. The HiFi data was produced on the PacBio Revio machine, using 1 flowcell per sample. The resulting data was aligned to hg19 using minimap2, and converted into bam using samtools.

  Dataset EGAD50000000635

• Development of a fully human glioblastoma-in-brain-spheroid model for accelerated translational research

  In glioblastoma (GBM) the intricate interplay between tumor cells and the surrounding microenvironment plays a crucial role in tumor progression, invasion, and therapeutic resistance. So far, studying these interactions in a controlled and representative model system has been challenging. Here, we report the development of hGliCS, a human glioma-cortical spheroid model that allows the elucidation of the biology of GBM cells and their interactions with a human-specific brain-like microenvironment and neurons. GBM cells efficiently invade the cortical spheroids, forming a well-connected network of communicating cells. The heterogeneous cellular states of the GBM cells within this model closely resembled findings previously observed in glioblastoma patients and in mouse xenografts. We observed a transition from predominantly mesenchymal-like cells to heterotopic states with a high diversity. In contrast to the substantial changes observed in the tumor cell population, the impact of the GBM cells on the neurons was minimal. We further demonstrate the suitability of hGliCS to test compounds targeting tumor-specific neurobiological features.

  Study EGAS50000000757

• Targeted NGS panel

  The mutational status of 121 genes recurrently altered in B-cell lymphoma was examined in 55 of 56 diagnostic and 10 of 12 relapse samples using a custom targeted NGS panel. Libraries were generated from 150 ng of DNA using molecular-barcoded library adapters (ThruPLEX Tag- seq kit; Takara) coupled with a custom hybridization capture-based method (SureSelectXT Target Enrichment System Capture strategy, Agilent Technologies). The quality of the libraries was determined using the Bioanalyzer high sensitivity DNA kit (Agilent) and quantified by PCR using the KAPA library quantification kit (KAPA Biosystems). Finally, the libraries were pooled and sequenced in the MiSeq instrument (Illumina).

  Dataset EGAD00001010842

• RNA-seq following miR-130a overexpression (OE) in human CD34+cord blood cells

  We performed RNA-seq on CD34+ human cord blood (CB) cells transduced with Control or miR-130a OE lentiviruses to identify differentially expressed genes. Sorted CD34+ cells from 3 independent cord blood pools were transduced with lentiviruses containing mOrange (mO) reporter gene. mO+ cells were sorted 3 days post-transduction and RNA was harvested for library preparation and sequencing.

  Study EGAS00001005868

• Myelodysplastic_Syndrome_Follow_Up_Series

  Agilent whole exome hybridisation capture was performed on genomic DNA derived from MDS and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to discover the prevalence of our findings using bespoke pulldown methods and sequencing the products from a larger set of patient DNA.

  Study EGAS00001000224

• Bulk RNASeq of metastatic colorectal cancer organoids treated with crenigacestat alone or in combination with cetuximab

  Bulk RNA sequencing was performed on mCRC organoids cultured under untreated conditions or treated with crenigacestat alone or in combination with cetuximab. This dataset was generated to investigate the transcriptional changes associated with combination therapy and to compare these profiles with the adaptive responses observed following cetuximab monotherapy in the corresponding ATOH1 wild-type and knockout organoid models.

  Dataset EGAD50000002061

• AML Proteogenomic Landscape Whole-transcriptome RNA-Sequencing

  Whole transcriptome RNA-sequencing of purified bone marrow blasts of 136 de novo, treatment naive AML patients. For further details, we refer to the manuscript "The Proteogenomic Landscape of AML" by Jayavelu, Wolf, Buettner et al. mRNA extraction and whole transcriptome sequencing For transcriptome analysis the TruSeq Total Stranded RNA kit was used, starting with 250ng of total RNA, to generate RNA libraries following the manufacturer’s recommendations (Illumina, San Diego, CA, USA). 100bp paired-end reads were sequenced on the NovaSeq 6000 (Illumina) with a median of 57 mio. reads per sample. RNA Data Analysis Data quality control was performed with FastQC v0.11.9. Reads were aligned to the human reference genome (Ensembl GRCh38 release 82) using STAR v2.6.1. Gene count tables were generated while mapping, using Gencode v31 annotations. All downstream analyses were carried out using R v4.0 and BioConductor v3.12 (Huber et al., 2015; R Core Team, 2020). Size-factor based normalization was performed using DESeq2 v1.28.1(Love et al., 2014).

  Dataset EGAD00001008484

• BCC HHI-ICI combination therapy

  Data of advanced basal cell carcinoma patients receiving hedgehog-inhibitor and immune checkpoint-inhibitor combination treatment. The single-cell RNA-sequencing data was generated via the Parse Biosciences platform from PBMC samples of 10 patients at 4 four timepoints each. The spatial transcriptomics dataset was generated using the 10x Visium platform (+CITE-seq) and contains altogether 10 biopsies at different timepoints during treatment from 3 patients. The processed matrices with the spatial images can be downloaded from: https://zenodo.org/records/17814765

  Dataset EGAD50000002134

• GATCI whole exome germline variants

  Exome sequences were aligned to the GRCH38 reference genome. Aligned sequence was analyzed with GATK Haplotype Caller to generate germline variant calls. Variant calls are in VCF format. Details for the call can be found in the VCF header

  Dataset EGAD00001005916

• GATCI whole exome somatic variants (MuTect)

  Exome sequences were aligned to the GRCH38 reference genome. Aligned sequence was analyzed with GATK/MuTect, to generate somatic variant calls. Somatic variant calls are in VCF format. Details for the mutect call can be found in the vcf header.

  Dataset EGAD00001005917

• GATCI whole exome somatic variants (SomaticSniper)

  Exome sequences were aligned to the GRCH38 reference genome. Aligned sequence was analyzed with GATK/SomaticSniper, to generate somatic variant calls. Somatic variant calls are in VCF format. Details for the mutect call can be found in the vcf header.

  Dataset EGAD00001005918

• Detection of Genes Predisposing to Hematologic Malignancies

  We have been conducting genetic studies on families at high risk of different hematologic malignancies, in order to define the related tumors in the families, define precursor and other related conditions, and map and identify susceptibility genes. We have focused mainly on four types of lymphoid malignancies: chronic lymphocytic leukemia (CLL), Hodgkin lymphoma (HL), non-Hodgkin lymphoma (NHL), and Waldenström macroglobulinemia (WM). A few families with a rare lymphoma subtype, hairy cell leukemia (HCL) are included. In addition, single large pedigrees with acute myeloid leukemia (AML), and juvenile myelomocytic leukemia (JMML) are included. Families are ascertained for having at least two patients with the same hematologic malignancy and are classified by the type of malignancy that predominates in the family. Multiple types of lymphoid malignancies are often found in the same family. Other data has shown that these conditions aggregate together in families. Verification of cancer diagnoses is obtained through medical records, pathology reports, and flow cytometry. Family members with precursor traits are also included, monoclonal B-cell lymphocytosis (MBL) in CLL families and IgM monoclonal gammopathy of undetermined significance (MGUS) in WM families.

  Study phs001219

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  Various peripheral blood immune cell subsets from 89 healthy volunteers and 136 systemic lupus erhythematosus (SLE) donors were collected (Naive_CD4, Mem_CD4, Th1, Th2, Th17, Tfh, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, Naive_CD8, EM_CD8, CM_CD8, TEMRA_CD8, NK, Naive_B, USM_B, SM_B, DN_B, Plasmablast, CL_Mono (or CD16n_Mono), CD16p_Mono, Int_Mono, NC_Mono, mDC, pDC, Neu, LDG). 22 SLE donors were analyzed longitudinally. RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered.

  Study JGAS000486

• Clinical and ctDNA data for IMpassion031

  Clinical and ctDNA data for IMpassion031, including survival, response, and ctDNA data from baseline through post-surgery time points. 222 samples run on Signatera assay. File type is csv.

  Dataset EGAD50000001420

• Single-nuclei ATAC sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  10x genomics single-nuclei ATAC sequencing of 7 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma, and 1 normal adrenal medulla sample. snATAC-seq was conducted using the "Van Helsing" protocol (dx.doi.org/10.17504/protocols.io.bw52pg8e). Once processed, snATAC-seq libraries were sequenced on the Illumina NextSeq 500 (Illumina, USA) using 50bp paired-end sequencing. Raw sequencing data in BCL format was demultiplexed using cellranger-atac mkfastq (V2.0.0). This dataset contains sequencing reads in FASTQ format. R1/R3 files contain the forward and reverse sequencing reads, respectively, R2 contains the 10x Barcode.

  Dataset EGAD50000000503

• The Library of Integrated Network-Based Cellular Signatures (LINCS) - NeuroLINCS

  The NeuroLINCS Center is part of the NIH Common Fund's Library of Integrated Network-based Cellular Signatures (LINCS) program, which aims to characterize how a variety of human cells, tissues and the entire organism respond to perturbations by drugs and other molecular factors. As Part of the LINCS program, the NeuroLINCS study concentrates on human brain cells, which are far less understood than other cells in the body. Our initial focus is to produce diseased motor neurons from patients by utilizing high-quality induced pluripotent stem cell (iPSC) lines from Amyotrophic Lateral Sclerosis (ALS) and Spinal Muscular Atrophy (SMA) patients in addition to unaffected normal healthy controls. Using state-of-the-art OMICS methods (genomics, epigenomics, transcriptomics, and proteomics), we intend to create a wealth of cellular data that is patient-specific in the context of their baseline genetic perturbations and in the presence of other genetic and environmental perturbagens (e.g. endoplasmic reticulum stress). The primary data will be used to build cell signatures that convey the key features that distinguish the state of a cell and determine its behavior. Ultimately, the analysis of these datasets will lead to the identification of a network of unique signatures relevant to each of these motor neuron diseases. The datasets represented in this study are generated from assays interrogating RNA expression (RNA-seq), chromatin accessibility (ATAC-seq) and whole genome sequencing.

  Study phs001231

• Single Chromatin Fiber Profiling in the Human Brain

  We developed a human postmortem brain-applicable ‘Fiber-seq' protocol for genome-scale, PCR-free single molecule sequencing of on average 8-10kb long chromatin fibers, to map nucleosome positioning and nucleosome-depleted regions which include, for example, active promoters and enhancers. We generated two Fiber-seq reference sets, one from sorted non-neuronal NeuN- prefrontal cortex (PFC) nuclei from a 32 year old female donor, with total of 11,143,795 reads/fibers, and median of 30-fold genomic coverage. The other reference set was generated on sorted prefrontal NeuN+ neurons, from two 24 year old brain donors (1 female/1 male), with a combined total read/fiber count of 4,749,556 and median of 20-fold genomic coverage. Each of the peaks in the Fiber-seq libraries seq signal correlated with the ATAC peak levels in the neuronal and non-neuronal ATAC-seq libraries, respectively (promoters, clusters 1, 3; NeuN+, r = 0.574; NeuN-, r=0.683, PHowever, Fiber-seq detected 19,978 highly significant peaks which, while showing some non-significant/near-background ATAC-Seq alignments, lacked a corresponding site-specific enrichment in conventional short-read ATAC- and ChIP-seq datasets. However, 60% of these peaks were in repetitive DNA elements. Therefore, long read single chromatin fiber sequencing, which exceed the base pair length of conventional short-read libraries by two orders of magnitude, could capture many actively regulated repeat elements at the site of specific gene loci, that otherwise would remain unmappable by conventional ATAC-, and histone- ChiP-seq.

  Study phs003771

• WGS data subfolder for normal tissue from multifocal ileal NETs study

  This dataset includes linked-read whole-genome sequencing data from the normal ileal of the patient. The normal sample was sequenced using the 10x Genomics linked-read whole-genome sequencing (WGS) approach.

  Dataset EGAD00001008491

• 18 Whole Exome Sequencing for Radiation Induced-Meningiomas

  Purpose: Majority of pediatric cancers require the irradiation of the central nervous system (CNS), and as more patients survive into adulthood from improved oncological therapy the sequelae of brain radiation are increasing in prevalence. Radiation-induced meningiomas (RIMs), one such secondary effect, demonstrate a clinically more aggressive behaviour than sporadic meningiomas (SMs). We aimed to describe the genomic mutational landscape of RIMs.Methods: We analyzed a principal cohort of 18 RIMs, with 31 RIMs overall, from patients who received childhood radiation therapy and 30 SMs, as a comparator population. We performed a multiplatform integrative genomic analysis; including methylation, whole exome and RNA sequencing. Results: RIMs exhibited a five-fold increase in copy number alterations, commonly the loss of chromosome 1p (17/18 RIMs) and 22q (17/18 RIMs), which was significantly more than observed in sporadic meningiomas. Furthermore, RNA sequencing data revealed an NF2 gene fusion event in 35.3% of RIMs. In all 6 cases, there was a complete NF2 exon spliced into a complete exon of a reciprocal gene, suggesting that the breakpoints of genomic rearrangement are intronic. All tumours with the NF2 fusion also possessed monosomy of chromosome 22q, rendering the cells with homozygous disruption of NF2. Clinically, RIMs with the NF2 fusion exhibited ill-defined borders and a tendency to develop in anatomic frontal location. Also, targeted sequencing panel confirmed that RIMs had fewer nonsynonymous NF2 mutations (6.5% vs. 30% in SM) and absence of mutations in TRAF7, SMO, KLF4, PIK3CA and AKT1, genes traditionally involved in SMs.Conclusion: Our study demonstrates that RIMs have distinct genomic drivers of oncogenesis as compared to SMs, specifically NF2 inactivation through fusion event. Radiation therapy possibly triggers genomic structural rearrangements through error-prone repair of double-stranded DNA breaks.

  Study EGAS00001002317

• The chromatin accessibility signature of human immune aging stems from CD8+ T cells

  Aging is linked to deficiencies in immune responses and increased systemic inflammation. To unravel the regulatory programsbehind these changes, we applied systems immunology approaches and profiled chromatin accessibility and the transcriptomein PBMCs, purified monocytes, and B and T cells. Analysis of samples from 77 young and elderly donors revealed a novel androbust aging signature in PBMCs, with simultaneous systematic chromatin closing at promoters and enhancers associated withT cell signaling and a potentially stochastic chromatin opening mostly found at quiescent and repressed sites. Combined analysesof chromatin accessibility and the transcriptome uncovered immune molecules activated/inactivated with aging andidentified the silencing of the IL7R gene and the IL-7 signaling pathway genes as potential biomarkers. This signature is borneby memory CD8+ T cells, which exhibited an aging-related loss in binding of NF-κB and STAT factors. Thus, our study providesa unique and comprehensive approach to identifying candidate biomarkers and provides mechanistic insights into aging-associatedimmunodeficiency.

  Study EGAS00001002605

• Proteomic predictors of individualized nutrient-specific insulin secretion in health and disease

  Population level variation and molecular mechanisms behind insulin secretion in response to carbohydrate, protein, and fat remain uncharacterized despite ramifications for personalized nutrition. We now define prototypical insulin secretion dynamics in response to the three macronutrients in islets from 140 cadaveric donors, including those diagnosed with type 2 diabetes. We leverage the insulin response heterogeneity and use transcriptomics and proteomics to identify molecular pathways of specific nutrient responsiveness. Surprisingly, we find robust insulin secretion to fatty acid stimulus in ~8% of donors, challenging the idea that fat has negligible effects on insulin release. Distinct islet proteomes with differences in metabolic signalling networks convey this hyper-responsiveness to fat relative to carbohydrate. By comparing human islets to human embryonic stem cell-derived islet clusters, we show that, unlike glucose-responsiveness, fat hyper-responsiveness is equivalent and may be a hallmark of functionally immature cells. Our study represents the first comparison of dynamic responses to nutrients and multi-omics analysis in human insulin secreting cells. Responses of different people’s islets to carbohydrate, protein, and fat lay the groundwork for personalized nutrition.

  Dataset EGAD50000000519