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• RNA-seq of oropharynx cancer cases from University of Michigan

  This dataset consists of 67 bulk RNA-seq data (sorted aligned BAM files) from formalin-fixed paraffin-embedded (FFPE) oropharynx tumor samples from the University of Michigan (UM). Samples were collected as part of the UM Head and Neck SPORE between 2008-2014. Library preparation was performed using the ribo-depletion method with the FastSelect kit and sequenced on the NovaSeq 6000 at the UM Advanced Genomics Core, resulting in 150bp paired-end reads. Raw reads were trimmed using Cutadapt (v3.4) and aligned to hg38 and high-risk HPV genomes using STAR (v2.7.9a). 62 of 67 samples were determined to be HPV RNA-positive.

  Dataset EGAD50000001306

• COVID-19: Post-Hospital Thromboprophylaxis A Multicenter, Adaptive, Prospective, Randomized Trial Evaluating the Efficacy and Safety of Antithrombotic Strategies in Patients with COVID-19 Following Hospital Discharge (ACTIV-4C)

  This study is an adaptive, prospective, randomized trial designed to compare the effectiveness and safety of antithrombotic therapy with no antithrombotic therapy after hospitalization for 48 hours or longer for COVID-19. For Stage 1 of this study, participants will be randomized to either prophylactic anticoagulation or no anticoagulant therapy for 30 days, and then followed for an additional 60 days after the completion of treatment (total duration of follow-up, approximately 90 days). Biobanking of samples for future biomarker and mechanistic studies will be available for centers able to participate and collect samples from eligible participants. Samples will be collected at the time of enrollment and after the completion of 30 days of therapy.

  Study phs003063

• Epigenome-wide association study of asthma remission in whole blood and nasal epithelium

  Clinical remission (ClinR) was defined as the absence of asthma symptoms and medication for at least 12 months, and complete remission (ComR) was defined as ClinR with normal lung function and absence of airway hyperresponsiveness. We analyzed differential DNA methylation of ClinR and ComR comparing to persistent asthma (PersA) in whole blood samples (n=72) and nasal brushing samples (n=97) in a longitudinal cohort of well characterized asthma patients.

  Dataset EGAD00010002026

• Indonesian Genome Diversity Project 3

  Low coverage whole genome sequences (1-3x) were collected to study human genetic history across Wallacea archipelago and West Papuan Region of Indonesia . We collected 254 newly sequenced genomes mostly from previously undocumented populations including 9 communities in Wallacea and 3 in West Papuan regions. Out of 254, there are 8 high coverage whole genome sequences were produce in the study (L4).

  Dataset EGAD50000000647

• Anti-MPO BCR sequences described in 'Anti-myeloperoxidase IgM B cells in anti-neutrophil cytoplasmic antibody-associated vasculitis'

  FASTA files from quality-checked Sanger Sequencing results from BCR-specific PCR products. B cells from 4 different MPO+ AAV patients were single cell sorted and processed to sequence the specific BCR, resulting in 51, 175, 12 and 3 heavy chain BCR sequences for AAV1, 2, 3, and 5 respectively. Sequence names indicate patient ID and isotype (IgG, IgM or IgA).

  Dataset EGAD50000001112

• scRNAseq of endothelial cells from human iPSC-derived kidney organoids transplanted in the coelomic cavity of chicken embryos compared to untransplanted controls

  This dataset includes scRNA-seq fastq files and Seurat counts and metadata for 6 samples of endothelial cells enriched from hiPSC-derived kidney organoids cultured in vitro or transplanted in chicken embryos. Samples were obtained at 2 timepoints: d7+13 (1 day after transplantation) and day 7+20 (8 days after transplantation).

  Dataset EGAD50000001555

• WES analysis in identifying additive genetic factors that may contribute to the occurrence of moyamoya in neurofibromatosis type 1

  Five subjects from pedigree with co-occurrence of neurofibromatosis type 1 and moyamoya were sequenced in duplicate (0 and1). Kinship and phenotype: NF025, NF026 and NF027 were sibling all affected by neurofibromatosis type 1. NF026 also presented moyamoya. NF0262 and NF0263 were sibling both affected by neurofibromatosis type 1. NF0262 also presented moyamoya. NF026 and NF0262 were first cousins.

  Dataset EGAD00001004157

• Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

  Despite progress in immunotherapy, identifying patients that respond has remained a challenge. Through analysis of whole-exome and targeted sequence data from 5,449 tumors, we found a significant correlation between tumor mutation burden (TMB) and tumor purity, suggesting that low tumor purity tumors are likely to have inaccurate TMB estimates. We developed a new method to estimate a corrected TMB (cTMB) that was adjusted for tumor purity and more accurately predicted outcome to immune checkpoint blockade (ICB). To identify improved predictive markers together with cTMB, we performed whole-exome sequencing for 104 lung tumors treated with ICB. Through comprehensive analyses of sequence and structural alterations, we discovered a significant enrichment in activating mutations in receptor tyrosine kinase (RTK) genes in non-responding tumors in three immunotherapy-treated cohorts. An integrated multivariable model incorporating cTMB, RTK mutations, smoking-related mutational signature, and HLA status provided an improved predictor of response to immunotherapy that was independently validated.

  Study EGAS00001003892

• Copy numbers in resectable gastric cancer treated with surgery alone

  Purpose: Gastric cancer is a heterogeneous disease requiring stratification to recognize its underlying biology and variable clinical outcome. The Cancer Genome Atlas (TCGA) recognizes four molecular subgroups: Epstein-Barr virus positive (EBV+) and microsatellite instable (MSI) with superior survival compared to genomically stable (GS) and chromosomal instable (CIN). Since classification criteria to distinguish GS from CIN were not defined, alternative markers such as Lauren’s histopathology or CDH1/p53 immunohistochemistry are commonly applied. Here we compared survival of gastric cancer subgroups determined by four methods. Experimental Design: EBV- and microsatellite stable tumors from a total of 309 patients treated with surgery alone were assigned to subgroups by: (i) specific copy number aberrations as determined by TCGA (GS or CIN), (ii) genome instability index (GII; high or low), (iii) Lauren’s classification (diffuse or intestinal), and (iv) CDH1/p53 immunohistochemistry (IHC; aberrant CDH1, normal-, or aberrant p53 expression). Subgroups were associated with cancer-related survival (CRS). Results: Five-year CRS was 42.0% for diffuse and 49.5% for intestinal type tumors, and 57.8% for GS and 41.6% for CIN tumors. Classification by GII or CDH1/p53 IHC did not correlate with CRS. The combination of TCGA and Lauren classifications resulted in four distinct subgroups. Five-year CRS for GS-intestinal (n=24), GS-diffuse (n=57), CIN-intestinal (n=142) and CIN-diffuse (n=86) was 61.4%, 56.5%, 47.6%, and 31.5%, respectively. Conclusions: TCGA’s GS and CIN have additional prognostic value to Lauren’s diffuse and intestinal subgroups in gastric cancer. GS-intestinal, GS-diffuse, CIN-intestinal and CIN-diffuse constitute biologically distinct entities and are suggested as stratification variables for future studies.

  Study EGAS00001007394

• Phase 1/2 Study of the Indoleamine 2,3-Dioxygenase 1 Inhibitor Linrodostat Mesylate Combined With Nivolumab or Nivolumab and Ipilimumab in Advanced Solid Tumors or Hematologic Malignancies

  Purpose: To evaluate the safety, efficacy, pharmacokinetics, pharmacodynamics, and biomarker data of linrodostat mesylate, a selective, oral indoleamine 2,3-dioxygenase 1 (IDO1) inhibitor, combined with nivolumab ± ipilimumab in advanced solid tumors and hematologic malignancies. Patients and Methods: In this phase 1/2 study, patients received once-daily (QD) linrodostat (part 1 [escalation], 25-400 mg; part 2 [expansion], 100 or 200 mg) plus nivolumab (480 mg every [Q] 4 weeks [W] or 240 mg Q2W) or triplet therapy (part 3, linrodostat 20-100 mg QD; nivolumab 360 mg Q3W or 480 mg Q4W; ipilimumab 1 mg/kg Q6W or Q8W). Endpoints included safety and efficacy (co-primary; parts 2, 3), pharmacokinetics, pharmacodynamics, biomarkers, and efficacy (part 1). Results: Fifty-five, 494, and 41 patients were enrolled in parts 1, 2, and 3, respectively. Linrodostat exposures exceeded predicted therapeutic target concentrations starting at 50 mg. Rates of grade 3/4 adverse events were 50.1%-63.4%. The maximum tolerated linrodostat dose was 200 mg; dose-limiting toxicities were primarily immune related. Responses were observed across different cohorts, study parts, and tumor types, particularly in immunotherapy-naive patients. Kynurenine decreased with linrodostat + nivolumab, regardless of response. In contrast, interferon gamma (IFN-γ) gene expression signature was associated with response; in nonmelanoma patients, a composite of low tryptophan 2,3-dioxygenase (TDO2) gene expression plus high IFN-γ signature was associated with response. Conclusions: Linrodostat + nivolumab ± ipilimumab demonstrated a manageable safety profile. Kynurenine changes supported IDO1 pathway inhibition but did not correlate with response. A composite biomarker of low TDO2 expression plus high IFN-γ gene expression may predict response to linrodostat + nivolumab.

  Study EGAS50000000710

• Automated machine-learning approach for next generation profiling of sequence alterations, mutation burden, microsatellite instability, and structural variants in human cancers

  Sequence and structural alterations together with tumor mutation burden (TMB) and microsatellite instability (MSI) have been identified as biomarkers for the determination of response to targeted and immune checkpoint inhibitor therapies. However, widespread clinical adoption of these biomarkers has historically been limited due to barriers such as evidence of clinical utility and reimbursement. We have developed 2.2 Mb targeted NGS system and an automated machine-learning analysis approach (PGDx elio™ tissue complete, ETC) that has been FDA cleared for examination of 500+ cancer-related genes and 68 mononucleotide repeats for identification of sequence and structural alterations, TMB, and MSI in solid cancers in a clinical setting. We designed and trained this approach using sequence data from 4,174 cancers and >124,000 in silico alterations and evaluated the methodology in >2,550 tumor or non-cancerous normal samples. Independent analyses of ETC sequence changes in 440 formalin fixed paraffin embedded (FFPE) tumor or cell line samples using MSK-IMPACT™, FoundationOne®, and ddPCR revealed a positive percent agreement (PPA) >97% with high sensitivity as low as 3% mutant allele fraction. We observed high concordance between panel-wide and whole-exome TMB for 307 pan-cancer FFPE tumors (Pearson r=0.95, p < 0.0001) using samples with ≥20% tumor cellularity. Comparison of the mutation context and repeat-based MSI approach in ETC with a multiplex MSI PCR assay in 223 samples revealed a PPA of 99% and negative predictive agreement (NPA) >99%. We confirmed the accuracy and precision of TMB and MSI measurements across three independent laboratories (CV of <5% and average PPA >99%, respectively). Finally, evaluation of amplifications and translocations against DNA and RNA-based approaches exhibited >98% NPA and PPA of 86% and 82% respectively. These results demonstrate high analytical performance for determination of sequence and structural changes, TMB, and MSI using a targeted NGS panel and provide a scalable and facile approach for evaluating these biomarkers in a clinical laboratory.

  Study EGAS00001005556

• Chromatin Accessibility Landscape of Human Pancreatic Ductal Adenocarcinoma (PDAC)

  Therapeutic options in pancreatic ductal adenocarcinoma (PDAC) are largely limited to cytotoxic chemotherapy without the benefit of molecular markers predicting response. By ATAC-seq analyses of EpCAM+ PDAC malignant epithelial cells sorted from 54 freshly resected human tumors, we discovered a signature of 1092 chromatin loci displaying differential accessibility between patients with disease-free survival (DFS) < 1 year and patients with DFS > 1 year. Using this signature, we further develop a chromatin accessibility microarray methodology termed “ATAC-Array”, an easy-to-use platform obviating the time and cost of next-generation sequencing. PDAC prognosis can be predicted by ATAC-array, which represents a low-cost, clinically feasible technology for assessing chromatin accessibility profiles.

  Study phs002394

• Clonal tracing with somatic epimutations reveals dynamics of blood aging

  In this study, we generated comprehensive single-cell multi-omic datasets from bone marrow samples collected from 13 donors spanning a wide age range. We applied the scTAMseq protocol to profile DNA methylation and nuclear mutations obtained from 7 total bone marrow aspirates (donors A.1-A.7) and 6 CD34+-enriched bone marrow samples ((donors B.1-B.5 & X.1). Complementary surface marker expression data were acquired by integrating CITE-seq into the scTAMseq workflow (scTAMseq_prot). Targeted RNA sequencing (scTAMARA_rna) was performed alongside scTAMARA_DNA on one CD34+-enriched sample (X.1). Additionally, a dedicated mitochondrial panel (TAMITO_seq) was employed on a peripheral blood sample from a healthy donor (X.2) to assess mitochondrial heterogeneity and facilitate lineage tracing.

  Study EGAS00001008056

• Identifying_Novel_Fusion_Genes_in_Myeloma

  To identify novel fusion genes in Myeloma samples

  Study EGAS00001000220

• Single-cell transcriptomic analyses of peritoneal metastases from patients with colorectal cancer metastasized to the peritoneum

  The data published here contains single-cell RNA-sequencing (scRNAseq) data as obtained using the 3' scRNAseq using Chromium Single Cell 3’ Reagent from 10X Genomics on peritoneal metastases (PM) from patients with colorectal cancer (CRC) and PM. Sequencing was performed in a paired-ended fashion on the NovaSeq6000.

  Dataset EGAD50000000249

• Finding structural variation and functional consequences from the Skin fibroblast at the single-cell level

  In this study, we aimed to identify somatic structural variation of Skin fibroblast at the single-cell level and investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of skin fibroblast sample from male donor.

  Dataset EGAD00001009307

• 25 metastatic cutaneous squamous cell carcinoma WGS VCF

  whole genome sequencing on lymph node metastases and blood DNA from 25 cSCC patients with regional metastases of the head and neck. We designed a multifaceted computational analysis at the whole genome level to provide a more comprehensive perspective of the genomic landscape of metastatic cSCC. This study contains the majority of 15 samples which are previously submitted in EGAC00001001100.

  Dataset EGAD00001009004

• Finding structural variation and functional consequences from the primary leukemia cells (CLL) at the single-cell level

  In this study, we aimed to identify somatic structural variation of chronic lymphocytic leukemia (CLL) at the single-cell level and investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of primary leukemia samples from 63-year-old female patient.

  Dataset EGAD00001006822

• Finding structural variation and functional consequences from the primary leukemia cells (AML) at the single-cell level

  In this study, we aimed to identify somatic structural variation of acute myeloid leukemia (AML) at the single-cell level and investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of primary leukemia samples from 32-year-old male donor.

  Dataset EGAD00001006782

• Integrated Genetic and Pharmacologic Interrogation of Rare Cancers

  Due to the paucity of patient derived models in rare cancers, identification of therapeutic targets remains challenging. We developed a patient derived model, CLF-PED-015-T, from a patient with an undifferentiated sarcoma. From this model, we performed pooled RNAi and CRISPR-Cas9 negative selection screens and integrated that with a small molecule screen. Integration of these data identified CDK4 and XPO1 as potential therapeutic targets.

  Study phs001121

• cfDNA methylation profiling on longitudinally collected blood plasma of patients with esophageal adenocarcinoma

  Esophageal adenocarcinoma (EAC) is an aggressive cancer characterized by a high risk of relapse post-surgery. Analyzing cell-free DNA (cfDNA) from blood plasma emerges as a promising avenue for therapy response monitoring. This study aims to evaluate the cost-effective and genome-wide cell-free reduced representation bisulfite sequencing (cfRRBS) method combined with computational deconvolution for effective disease monitoring in EAC patients.

  Study EGAS50000000514

• Single-Cell RNA-Sequencing of Bone Marrow and Circulating Tumor Cells from Patients with Multiple Myeloma and its Precursor Conditions

  We performed single-cell RNA and V(D)J-sequencing of tumor cells from bone marrow and peripheral blood specimens and patients with Monoclonal Gammopathy of Undetermined Significance (MGUS), Smoldering Multiple Myeloma (SMM), and Multiple Myeloma (MM), as well as healthy donors. In this study we aimed to shed light on the mechanisms underlying tumor cell circulatory capacity and dissemination.

  Study phs003855

• Analysis of Large Cell Neuroendocrine Carcinoma Expressing HNF4alpha Using WGS

  Lung LCNEC (Large Cell Neuroendocrine Carcinoma) has a poor prognosis, and no effective treatment has yet been established. We have found that the gastrointestinal marker HNF4alpha is specifically expressed in some LCNEC cases. By performing Whole Genome Sequencing (WGS) on samples from 10 LCNEC patients, we aim to identify changes characteristic of LCNEC expressing HNF4alpha and explore new classifications and treatment options for LCNEC.

  Study JGAS000732

• Exome_sequencing_of_Congenital_Heart_Disease_families_from_the_Competence_Network_Berlin

  This project aims to study exomes from families and trios withcongenital heart disease (CHD). The samples have been collected underthe Competence Network - Congenital Heart Defects in Berlin, Germany.The phenotypes are mainly left ventricular outflow obstruction (aorticstenosis, bicuspd aortic valve disease coarctation and hypoplasticleft heart), but will also include samples with hypoplastic rightheart and atrioventricular septal defects. We will perform whole exomesequencing using Agilent sequence capture and Illumina HiSeqsequencing.

  Study EGAS00001000368

• Dissecting intratumor heterogeneity of nodal B cell lymphoma on the transcriptional, genetic, and drug response level

  Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

  Study EGAS00001004335