20311 results for "Fc coins Buyfc26coins.com is EA Sports official for FC 26 coins They are efficient and quick always..Z2Xg"

in 44.64 milliseconds.

• Evaluating the immune response in treatment-naive hospitalised patients with influenza and COVID-19

  Clinical characteristics and peripheral blood were acquired upon hospital admission from two well characterised cohorts, a cohort of patients infected with influenza and a cohort of patients infected with SARS-CoV-2 during the first wave of the pandemic and prior to availability of COVID-19 treatments and vaccines.

  Study EGAS00001005971

• Genomic Alterations and Transcriptional Phenotypes in Circulating Tumor DNA and Matched Metastatic Tumor

  We analyzed a prospective cohort of 49 plasma samples obtained before, during, and after treatment from 20 patients with recurrent small cell lung cancer. We conducted cfDNA low-pass whole genome sequencing (0.1X coverage) and exome sequencing (130X coverage) in comparison with time-point matched tumor characterized using whole-exome (130X) and transcriptome sequencing. A direct comparison of cfDNA and tumor biopsy revealed that cfDNA not only mirrors the mutation and copy number landscape of the corresponding tumor, but also identifies clinically relevant resistance mechanisms and cancer driver alterations not detected in matched tumor biopsies. Longitudinal cfDNA analysis reliably tracks tumor response, progression, and clonal evolution. Sequencing coverage of plasma DNA fragments around transcription start sites showed distinct treatment-related changes and captured the expression of key transcription factors n the corresponding SCLC tumors.

  Study phs003689

• Integrative Profiling of T790M Negative EGFR Mutated NSCLC Reveals Pervasive Lineage Transition and Therapeutic Opportunities

  We performed whole exome and transcriptome analysis of 59 first- and second-generation EGFR TKI resistant metastatic EGFR mutated patients to characterize and compare molecular alterations mediating resistance in T790M positive and negative disease. Transcriptomic analysis revealed ubiquitous loss of adenocarcinoma lineage gene expression in T790M negative tumors, orthogonally validated using multiplex immunohistochemistry. There was enrichment of genomic features such as TP53 alterations, 3q chromosomal amplifications, whole genome doubling and non-aging mutational signatures in T790M negative tumors. Almost half of resistant tumors were further classified as Immunehot, with clinical outcomes conditional on immune cell infiltration state and T790M status. Finally, using a Bayesian statistical approach, we explored how T790M negative and positive disease might be predicted using comprehensive genomic and transcriptomic profiles of treatment-naïve patients.

  Study EGAS00001005389

• NIH Undiagnosed Diseases Program (UDP) Genotypic and Phenotypic Study

  The NIH Undiagnosed Diseases Program collects phenotypic and genomic data from patients with medical conditions that have eluded diagnosis in order to provide explanations and to advance medical and scientific understanding.

  Study phs000721

• Aging and viral evolution impair immunity against dominant pan-coronavirus-reactive T cell epitope

  In this project we have analysed gene expression and Tcell repertoires of CD40L+41bb+ and CD40L-41bb- Tcells from young and old donors after stimulation with the iCope peptide.

  Study EGAS50000001150

• Integrated Genomic and Transcriptomic Analysis of Small Cell Lung Cancer Reveals Inter- and Intratumoral Heterogeneity and a Novel Chemotherapy-Refractory Subtype

  We integrated histology, transcriptome, exome, and treatment outcomes of small cell neuroendocrine cancer (SCNC) from a range of metastatic sites, revealing complex intra- and intertumoral heterogeneity of neuroendocrine (NE) differentiation and transcriptomic subtypes (ASCL1, NEUROD1, POU2F3, YAP1 and ATOH1). High NE SCNCs were more likely to benefit from replication stress-targeted therapies, in contrast to non-NE tumors which were more likely to respond to immune response-targeted therapies.

  Study phs002541

• RNA Sequencing of Control and Myotonic Dystrophy Type 1 Cells During Myogenic Differentiation

  Immortalized control, patient-derived and CRISPR/Cas9-edited patient-derived myoblasts (known in the literature as C25, DM11, and DM11_1E6 cells, respectively) were grown confluent and were fused to myotubes in differentiation medium. Samples were collected at day -2 before initiation of differentiation (i.e. proliferation stage), at day 1 and at day 5 of differentiation in lysis buffer and stored at -70 degrees until all samples were collected.

  Study EGAS50000001152

• Transcriptomic profiling of Hedgehog-high and Hedgehog-low HPV-negative HNSCC

  This study investigates transcriptomic differences between Hedgehog-high and Hedgehog-low HPV-negative head and neck squamous cell carcinoma (HNSCC). Tumors were stratified based on pathway-level genomic alteration scores and imaging-associated Hedgehog activity. RNA sequencing was performed on archival FFPE tumor samples to assess pathway activation and transcriptional programs associated with Hedgehog signaling. The dataset supports integrative radiogenomic and functional analyses of tumor-intrinsic signaling pathways.

  Study EGAS50000001549

• WGS and WES of pediatric osteosarcoma

  Despite being the most common childhood bone tumor, the genomic characterization of osteosarcoma remains incomplete. Very few metastatic cases have been sequenced to date, a required step to better understand the progression and evolution of this tumor. Here, we present an integrative analysis of whole genome and whole exome sequencing (WGS and WES) of a cohort of primary and metastatic pediatric osteosarcoma, in order to identify recurrent genomic alterations between and within patients.

  Study EGAS00001003342

• ST dataset of subcortical MS

  Spatial transcriptomics from subcortical white matter controls and MS lesions, specifically chronic active (CA) and chronic inactive (CI), that paired with single-nuclei RNA-sequencing from the same samples , was used to identify spatial niches and key cell interactions driving inflammation and disease progression

  Study EGAS50000000353

• Human_Evolution_3B

  The mtDNA and Y chromosome of up to 15 Australian Aborigines, concentrating on individuals with indigenous lineages will be sequenced using the standard whole-genome sequencing followed by filtering out autosomal and X sequences, so that only mtDNA and the Y chromosome would be analysed and released.

  Study EGAS00001000718

• 1. Identidication of molecular biological mechanism associated with the development and prognosis of uterine cancer, uterine sarcoma, and endometrial hyperplasia / 2. Identification of molecular biological mechanism associated with the development of endometriosis and malignant transformation, ovarian cancer, fallopian tubal cancer, peritoneal cancer, and other malignant tumors in gynecological organs

  To clarify the biological difference between clear cell carcinoma and other histological subtypes in ovarian carcinomas by comparing copy number variants, and to identify molecular subtypes and carcinogenesis in clear cell ovarian carcinomas by whole-exome sequencing and RNA-sequencing. Then, characterize high-grade serous carcinomas by NGS-based, integrative genomic analyses, with focus on homologous recombination deficiency, molecular subtypes, prognostic factors and effectiveness of PARP inhibitor. Based on the results of whole-exome sequencing, an investigator-initiated, phase 2 clinical trial will be conducted to evaluate the efficacy and safety of the PARP inhibitor olaparib in HRD-positive cases.

  Study JGAS000789

• Understanding_the_multicellular_dynamics_of_clear_cell_renal_cell_carcinoma___DNA_sequencing

  This study will reconstruct the single cellular phylogeny of tumour and immune cells in relation to both genomic, functional, and spatial location. 20 tumours in total will be studied, including non-progressing small renal masses, progressing small renal masses, relatively indolent larger tumours, and high risk tumour with metastatic sampling. We aim to: Generate a focused, comprehensive phylogenetic characterisation of tumour cells Understand the dependencies of the cancer genome, transcriptome, tissue architecture and the single cellular micro-environment Quantify the single cellular composition and functional intra- and inter- tumoural heterogeneity Determine the phylogeny of tumour associated lymphocytes and their relationship to neo-epitopes and the immune microenvironment Investigate the mechanisms by which the tumour-normal interface constrains tumoural growth

  Study EGAS00001003517

• Understanding_the_multicellular_dynamics_of_clear_cell_renal_cell_carcinoma___single_cell_RNA_sequencing

  This study will reconstruct the single cellular phylogeny of tumour and immune cells in relation to both genomic, functional, and spatial location. 20 tumours in total will be studied, including non-progressing small renal masses, progressing small renal masses, relatively indolent larger tumours, and high risk tumour with metastatic sampling. We aim to: Generate a focused, comprehensive phylogenetic characterisation of tumour cells Understand the dependencies of the cancer genome, transcriptome, tissue architecture and the single cellular micro-environment Quantify the single cellular composition and functional intra- and inter- tumoural heterogeneity Determine the phylogeny of tumour associated lymphocytes and their relationship to neo-epitopes and the immune microenvironment Investigate the mechanisms by which the tumour-normal interface constrains tumoural growth

  Study EGAS00001003519

• Cancer and germline exomes, and cancer RNA-seq consisiting of FASTQ paired-end reads from melanoma and lung cancer samples

  Cancer and germline exomes, and cancer RNA-seq consisiting of FASTQ paired-end reads from melanoma and lung cancer samples

  Dataset EGAD00001005097

• Exploring_the_landscape_of_somatic_mutations_in_normal_tissue___GI___LYNCH___WGS

  Somatic mutations (burdens and signatures) and clonal dynamics in normal human tissues from the gastrointestinal tract of individuals with tumour predisposition syndromes and DNA damage repair defects.

  Study EGAS00001003882

• Exploring_the_landscape_of_somatic_mutations_in_normal_tissue___GI___MAP___WGS

  Somatic mutations (burdens and signatures) and clonal dynamics in normal human tissues from the gastrointestinal tract of individuals with tumour predisposition syndromes and DNA damage repair defects.

  Study EGAS00001004122

• Intra-tumor heterogeneity and clonal evolution of papillary renal cell carcinoma

  Limited knowledge of intratumor heterogeneity (ITH), and clonal evolution of papillary renal cell carcinoma (pRCC) and rare kidney tumor subtypes hinders understanding of tumorigenesis and therapeutic efficacy. We conducted an integrative genomic and epigenomic ITH analysis and studied clonal evolutionary history of pRCC and rare kidney tumor subtypes. We dissected multiple consecutive samples from the center of the tumor towards the tumor's periphery, a normal sample ~5 cm distant from the tumor, and, where feasible, metastatic regions in the adrenal gland. Specifically, we performed 60X multi-region whole-genome sequencing (mWGS), both genome-wide methylation and SNP array profiling, and deep targeted sequencing (average 500X coverage) of 254 cancer driver genes (PMID:24390350). The study population comprises 39 patients with kidney cancers, including 23 with papillary type 1 (pRCC1), 12 with papillary type 2 (pRCC2), one of which also had areas of clear cell, and one each with collecting duct tumor (cdRCC), renal fibrosarcoma rSRC, mixed pRCC1/pRCC2, and an unclassified renal cancer with mixed features of pRCC2 and cdRCC. Based on DNA sample availability, we conducted whole genome sequencing (WGS) on 124 samples from 29 subjects, deep targeted sequencing on 139 samples from 38 subjects, SNP array genotyping on 101 samples from 38 subjects, and genome-wide methylation profiling on 139 samples from 28 subjects. All assays were performed on tumor, metastasis and normal tissue samples, with the exception of the SNP array genotyping, which was conducted only on tumor samples.

  Study phs001573

• Somatic Mosaicism in Amyotrophic Lateral Sclerosis and Frontotemporal Dementia

  The study was designed to investigate the role of somatic mosaic mutations in the pathogenesis of sporadic amyotrophic lateral sclerosis (sALS) and frontotemporal dementia (sFTD). A panel of molecular inversion probes (MIP) were used to target the exons and exon-intron junctions of 88 neurodegeneration-related genes. The panel included 34 ALS/FTD genes, 10 Alzheimer's disease genes, 28 Parkinson's disease genes, and 16 genes associated with other rare neurodegenerative disorders. The panel was used to perform ultra-deep sequencing on postmortem brain and spinal cord from 404 individuals with sALS or sFTD and 144 age-matched neurotypical controls. Known pathogenic germline mutations were found in 20.6% of ALS cases and 26.5% of FTD cases. Predicted pathogenic somatic mutations were observed in 2.7% of sALS and sFTD cases that did not have known germline mutations. The somatic variants had low variant allele fraction and region-specific enrichment, particularly in the primary motor cortex of sALS cases and prefrontal cortex of sFTD cases.

  Study phs003530

• Deciphering RBP - alternative splicing networks in ALS iPSC-MN: patient and control datasets

  We produce RNA-seq datasets of iPSC-derived motor neurons (iPSC-MN) from healthy controls and sporadic ALS patients and controls and familial ALS patients with pathogenic variants in TARDBP.

  Study EGAS00001005879

• Colorectal cancer genomics with primary and metastatic samples

  We performed whole genome sequencing of metastatic colorectal cancer from 16 patients. Normal adjacent tissue, primary tissue, and metastatic tissue were analyzed to uncover metastatic progression and difference between primary and distant metastatic lesions.

  Study EGAS00001006465

• Colorectal cancer transcriptomics with primary and metastatic samples

  We performed RNAseq analysis of metastatic colorectal cancer from 16 patients. Normal adjacent tissue, primary tissue, and metastatic tissue were analyzed to uncover metastatic progression and difference between primary and distant metastatic lesions.

  Study EGAS00001006464

• HuBMAP: High Resolution 3D Mapping of Cellular Heterogeneity Within Multiple Types of Mineralized Tissues

  The overall goal of the study was to generate 3D single cell maps of healthy human knee cartilage. Articular cartilage from the weightbearing and non-weightbearing regions of the femoral condyles in healthy knees from young donors (n=12) was analyzed by bulk RNA-sequencing (RNA-Seq), single nuclei RNA (snRNA-seq) and ATAC-sequencing and by spatial transcriptomic methods (GeoMx, MERFISH and Xenium). These multimodal data and additional single cell RNA-sequencing (scRNA-seq) data were integrated to generate a comprehensive molecular, genomic and function annotation of chondrocyte populations. Regulatory mechanisms were derived by linking motifs in expressed genes, transcription factors and chromatin organization.

  Study phs003721

• Identifying and Reducing Disparities in Patient-Reported Outcomes Among African American Prostate Cancer Survivors

  This research study aimed to identify disparities in prostate cancer symptom burden and their contributors among African American, Hispanic, and non-Hispanic White prostate cancer survivors. We collected patient-reported outcomes data, focusing on various aspects of the survivors' health and well-being, clinical data, demographics data, and germline genomic data.

  Study phs003745

• Profiling of H3K27ac landscape in immune cells from rheumatoid arthritis patients and healthy controls

  We collected peripheral blood mononuclear cells (PBMC) from 6 RA patients and 4 healthy controls, as well as synovial fluid from the same RA patients. We then sorted B cells, CD4+ and CD8+ T cells, regulatory T cells and monocytes using flow cytometry and profiled regions marked with H3K27ac using CUT&Tag.

  Study EGAS00001005085

• RNA-seq analysis of human primary keratinocytes and skin

  Bulk and single cell RNA-seq analysis of human keratinocyte and human skin

  Study EGAS00001002981

• Paired diagnostic and relapse medulloblastoma sequencing

  Whole exome and targeted panel sequencing in a cohort of paired diagnostic and relapse medulloblastoma samples.

  Study EGAS00001007120

• NHLBI Recipient Epidemiology Donor Evaluation Study (REDS)-III - Brazil Sickle Cell Disease Cohort (REDS-BSCDC)

  The Recipient Epidemiology and Donor Evaluation Study (REDS)-III program established a Brazilian Sickle Cell Disease (SCD) Cohort to identify molecular determinants of response to transfusions, alloimmunization and risk factors associated with HIV infection. The Brazil population presents a complex admixture of African, European, Asian and Indigenous heritage and will provide insights into genetic, demographic, social, and healthcare system determinates of SCD outcomes. The REDS-III Brazil SCD cohort began in the Fall of 2013 and aimed to: Establish a cohort of SCD patients with a comprehensive centralized electronic database of detailed clinical, laboratory and transfusion information, as well as establish a repository of blood samples to support biological studies relevant to SCD pathogenesis and transfusion complications; Characterize changes in markers of inflammation in response to transfusion by analyzing chemokine/cytokine panels in serial post transfusion specimens; Identify single nucleotide polymorphisms (SNPs) that contribute to the risk of red blood cell alloimmunization in SCD by performing a genome-wide association (GWA) study in transfused SCD patients; Characterize risk of HIV and HIV outcomes in the Brazilian SCD population and compare SCD outcomes among HIV sero-positive and sero-negative SCD patients.

  Study phs001972

• Cross-tissue transcriptomic analysis of human secondary lymphoid organ residing ILC3 reveals a default quiescent state in the absence of inflammation

  A cross tissue transcriptional comparison of human ILC3 isolated from non-inflamed lymph nodes (LN) and spleens, inflamed tonsils and the peripheral blood (PB). Using uniform gating and high-purity cell-sorting, ILC3 were sorted as Lineage(CD3,CD19,CD34,CD14,CD94)-CD45intCD127+CRTH2-CD117+. From LN, spleen, tonsils and PB, NKp44- ILC3 were isolated and, in addition, NKp44+ ILC3 were sorted from spleen and tonsils. RNA quality was measured on a RNA 6000 Pico Kit (Agilent Technologies) using a 2100 Bioanalyzer (Agilent Technologies). 100 pg high-quality RNA was isolated and cDNA was generated using the SMART-Seq (v3) Ultra Low Input RNA Kit (Clontech) with 15 cycles of amplification. Amplified and Covaris-fragmented cDNA was quality-checked on a High Sensitivity DNA chip (Agilent Technologies) and further processed according the TruSeq Nano DNA Library Preparation Kit (Illumina). Data was processed as follows: SMARTer adapters were trimmed with cutadapt and the resulting sequences were aligned to the human RefSeq transcriptome using 14 TopHat2 (Kim et al., 2013). Normalization and quantification was performed using Cufflinks (Trapnell et al., 2012). FPKM counts were determined per gene with HTSeq-count.

  Study EGAS00001002636

• Clinical significance of novel subtypes of acute lymphoblastic leukemia in the context of minimal residual disease-directed therapy

  We evaluate clinical significance of recently identified subtypes of acute lymphoblastic leukemia (ALL) in 598 children treated with minimal residual disease (MRD)-directed therapy. Among the 16 B-ALL and 8 T-ALL subtypes identified by next generation sequencing, ETV6-RUNX1, high-hyperdiploid and DUX4-rearranged B-ALL had the best five-year event-free survival rates (95% to 98.4%); TCF3-PBX1, PAX5alt, T-cell, ETP, iAMP21, and hypodiploid ALL intermediate rates (80.0% to 88.2%); and BCR-ABL1, BCR-ABL1-like and ETV6-RUNX1-like and KMT2A-rearranged ALL the worst rates (64.1% to 76.2%). All but three of the 142 patients with day-8 blood MRD <0.01% remained in remission. Among new subtypes, intensified therapy based on day-15 MRD≥1% improved outcome of DUX4-rearranged, BCR-ABL1-like, and ZNF384-rearranged ALL, and achievement of day-42 MRD<0.01% did not preclude relapse of PAX5alt, MEF2D-rearranged and ETV6-RUNX1-like ALL. Thus, new subtypes including DUX4-rearranged, PAX5alt, BCR-ABL1-like, ETV6-RUNX1-like, MEF2D-rearranged and ZNF384-rearranged ALL have important prognostic and therapeutic implications.

  Study EGAS00001005084

• Long-term Impact and Intervention with Micronutrients in Brazil, Parque Universitário, Community-Based Study

  The Parque Universitário Zinc-Vitamin A cohort was a prospective, double-blind, randomized placebo-controlled trial with 324 children enrolled between 2000 and 2004 and randomized into 8 treatment arms: Placebo, Vitamin A, Glutamine, Vitamin A + Glutamine, Zinc + Glutamine, Zinc, Vitamin A + Zinc, Vitamin A + Zinc + Glutamine.The Parque Universitário Zinc-Arginine study conducted between 2006 and 2010 enrolled 349 infants from the Parque Universitário favela in Fortaleza. Participants were randomized into Placebo, Zinc, and Zinc + Arginine arms.This submission includes genetic and corresponding anthropometric data on a subset of 210 participants from the Zinc-Vitamin A (96) and Zinc-Arginine cohorts (114). More information on this project and its related projects can be found here: Studies of diarrheal susceptibility, growth, and development, in pediatric populations in Northeastern Brazil

  Study phs003175

• Clonal Evolution and Transcriptional Plasticity Shape Metastatic Dissemination Routes in Prostate Cancer

  This study provides comprehensive insights into the genetic and transcriptomic landscape of prostate cancer, highlighting significant clonal heterogeneity, transcriptional plasticity, and metastatic spread patterns. We examined the clonal evolution and metastatic dissemination of prostate cancer by integrating single-nuclei RNA sequencing (snRNA-seq) and low-pass whole-genome sequencing (WGS) data from 43 spatially distinct tumour samples in five patients with locally advanced disease. By reconstructing the evolutionary trajectories of each tumour, we identified distinct patterns of tumour evolution, including both monophyletic and polyphyletic metastatic dissemination, as well as ongoing primary tumour clonal evolution after metastatic spread. We observed converging changes leading to metastatic potential, such as androgen receptor independence and increased activity in the estrogen, WNT, and JAK/STAT pathways in identified seeding areas. These findings enhance our understanding of the disease's progression and may inform future therapeutic strategies.

  Study EGAS50000000927

• Genomic and transcriptional landscape of P2RY8-CRLF2-positive childhood acute lymphoblastic leukemia

  The mutational and transcriptional landscape of P2RY8-CRLF2-positive ALL was defined in 41 major clone fusion-positive cases including 19 matched diagnosis and relapse pairs by an integrated analysis of whole-exome and RNA sequencing. We detected a variety of frequently subclonal and highly unstable JAK/STAT but also RTK/Ras pathway activating mutations in 76% of cases at diagnosis and virtually all relapses. Unlike P2RAY8-CRLF2 that was lost in 32% of relapses, all other genomic deletions affecting lymphoid development and cell cycle remained stable. Only IKZF1 alterations predominated in relapsing cases and increased from initially 36 to 58% in matched cases. IKZF1¹s transcriptional signature revealed compromised stem cell features with signs of impaired lymphoid differentiation, enhanced focal adhesion, activated hypoxia pathway, deregulated cell cycle and increased drug resistance.

  Study EGAS00001001847

• Whole exome and RNA sequencing of patient-derived and COPA-engineered human intestinal organoids

  We performed whole exome and RNA sequencing of COPA-mutated and COPA-engineered human intestinal organoids to analyze the impact of COPA mutation.

  Study JGAS000881

• Identification of Novel Immunotherapy Targets in Myeloma

  RNA sequencing (RNA-Seq) was performed on 94 multiple myeloma (MM) patient samples. We used genomic subgroup and high-risk markers to identify therapeutic targets, including TNFRSF17, GPRC5D, ITGA4, and LAX1, with low predicted toxicity and high specificity to MM and genomic subgroups such as those with TP53 alterations.

  Study phs003772

• Stratified Medicine Paediatrics (SMPaeds): molecular profiling of relapsed paediatric cancer

  We profiled a large heterogenous cohort of matched diagnostic-relapse tumour tissue and plasma-derived cell free DNA (cfDNA) from patients with relapsed and progressive solid tumours of childhood. Tumour DNA and cfDNA were analysed by targeted panel sequencing and low coverage whole genome sequencing.

  Study EGAS50000000549

• snRNA-seq of subcortical MS

  Single-nuclei RNA-sequencing (snRNA-seq) from subcortical white matter controls and MS lesions, specifically chronic active (CA) and chronic inactive (CI), that paired with the spatial transcriptomics from the same samples, was used to identify spatial niches and key cell interactions driving inflammation and disease progression.

  Study EGAS50000000354

• Human_Evolution_3

  The mtDNA and Y chromosome of up to 15 Australian Aborigines, concentrating on individuals with indigenous lineages, will be sequenced using the standard whole-genome sequencing followed by filtering out of autosomal and X sequences, so that only mtDNA and the Y chromosome will be analysed and released.

  Study EGAS00001000315

• Integrated Exome-seq analysis of tumor thrombus

  We prospectively enrolled 83 patients with a renal mass and TT scheduled to undergo surgical resection. To accurately integrate genomic and transcriptomic findings and enable histological co-registration, simultaneous isolation of DNA and RNA was performed from individual samples characterized histologically through immediately flanking sections

  Study EGAS00001005511

• Integrated RNA-seq analysis of tumor thrombus

  We prospectively enrolled 83 patients with a renal mass and TT scheduled to undergo surgical resection. To accurately integrate genomic and transcriptomic findings and enable histological co-registration, simultaneous isolation of DNA and RNA was performed from individual samples characterized histologically through immediately flanking sections

  Study EGAS00001005512

• Genomic Analysis of Nucleic Acid Sequences from Pancreatic Cancer

  Our study aims to perform multi-omics analysis of pancreatic ductal adenocarcinoma. We performed dual single-cell RNA sequencing and whole genome sequencing on fresh tumor specimens and dual bulk RNA-sequencing and 16S amplicon sequencing on frozen tumor specimens to identify human and non-human nucleic acid sequences. Additionally, we identified microbial sequences and found that bacterial taxonomic profiles from the same sample strongly correlated across technologies.

  Study phs003035

• Spatially resolved single-nucleus RNA sequencing of Choroid Plexus Tumours reveals clinically relevant hypoxia- and stress-driven dedifferentiation programs that sculpt an immunosuppressive and pro-angiogenic microenvironment

  Our study leverages single-nucleus RNA sequencing (~124,500 nuclei) and spatial transcriptomics (~40,650 spots) to dissect the molecular architecture of CPTs. We generated a comprehensive transcriptomic atlas of 45 CPT samples spanning all three methylation groups and a reference cohort of 16 non-neoplastic choroid plexus (ChP) samples, spanning foetal, paediatric and adult specimens. Key discoveries from this investigation include that paediatric B tumorus exhibit a dedifferentiated state and enrichment of stress-related metaprograms, including hypoxia, TGFß signaling, Interferon I signaling and early stress response, that correlate with poor clinical outcome and antagonise multiciliogenesis. On a spatial level, these stress-linked programs co-localise with immunosuppressive, pro-angiogenic microenvironment, suggesting a link between developmental arrest, microenvironmental remodelling and aggressive behaviour.

  Study EGAS50000001617

• Multi-omics analysis of serial samples from metastatic TNBC patients on PARP inhibitor monotherapy provide insight into rational PARP inhibitor therapy combinations

  In a pilot study, we evaluated the safety and efficacy of olaparib/durvalumab combination treatment in mTNBC patients and the feasibility of real-time deep analysis of serial tumor samples from triple negative breast cancer patients to identify mechanisms of resistance and treatment opportunities. This study used the SMMART analytic platform at OHSU KCI and incorporated comprehensive multi-omic analysis of serial liquid and tumor biopsies. Deep analysis of longitudinal biopsies combined with a robust computational biology pipeline identified multiple PARPi-induced changes in immune activation, DNA damage checkpoint activation, apoptosis and signaling pathways including RTK, PI3K-AKT and RAS-MAPK. These emergent tumor and immune state changes could act as biomarker targets to be used in selecting patient specific combination therapies.

  Study EGAS00001005479

• Whole-exome and targeted sequencing of pediatric hyperdiploid B-cell precursor acute lymphoblastic leukemia

  High hyperdiploidy defines the largest genetic entity of childhood acute lymphoblastic leukemia (ALL). Despite its relatively low recurrence risk, this subgroup generates a high proportion of relapses. The cause and origin of these relapses remains obscure. We therefore explored the mutational landscape in high hyperdiploid (HD) ALL with whole-exome (n=19) and subsequent targeted deep sequencing of 60 genes in 100 relapsing and 51 non-relapsing cases. We identified multiple clones at diagnosis that were primarily defined by a variety of mutations in receptor tyrosine kinase (RTK)/Ras pathway and chromatin-modifying genes. The relapse clones consisted of reappearing as well as new mutations, and overall contained more mutations. Although RTK/Ras pathway mutations were similarly frequent between diagnosis and relapse, both intergenic and intragenic heterogeneity was essentially lost at relapse. CREBBP mutations, however, increased from initially 18-30% at relapse, then commonly co-occurred with KRAS mutations (P<0.001) and these relapses appeared primarily early (P=0.012). Our results confirm the exceptional susceptibility of HD ALL to RTK/Ras pathway and CREBBP mutations, but, more importantly, suggest that mutant KRAS and CREBBP might cooperate and equip cells with the necessary capacity to evolve into a relapse-generating clone.

  Study EGAS00001001113

• Combined – whole blood and skin fibroblasts - transcriptomic analysis in Psoriatic arthritis.

  Whole blood RNA sequencing was performed longitudinally in 27 subjects with PsA at the beginning, one month and six months after treatment and response to therapy was defined at 6 months. As control groups 7 healthy individuals and 9 subjects with rheumatoid arthritis were recruited combined with public RNA-sequencing datasets from patients with psoriasis and systemic lupus erythematous. Differential expression analysis and weighted gene co-expression network analysis were performed to identify gene expression signatures, while deconvolution and flow cytometry to characterize the peripheral blood immune cell profile. RNA sequencing of skin fibroblasts was performed in a subset of affected (n=3) and healthy individuals (n=3) combined with CellChat to identify the blood-skin fibroblasts interaction network.

  Study EGAS00001006288

• Integrative Genomic and Transcriptomic Analyses of Refractory Multiple Myeloma

  This study reports results from integrative sequencing analyses that combine capture transcriptome sequencing with a comparative analysis of exome capture between the malignant plasma cells and normal cells of patients with relapsed and refractory multiple myeloma (RRMM). This approach has enabled the detection of point mutations, insertions/deletions, gene fusions and rearrangements, amplifications/deletions, and outlier expressed genes among other classes of alterations that contribute to disease progression and drug resistance in the RRMM patients. 

  Study phs002498

• WGS of breast cancer diagnosed during pregnancy and matched control

  The aim of this study was to compare the mutational landscape of breast cancer diagnosed during pregnancy (BCP) and breast cancer from age/stage non-pregnant patients (controls). We present whole genome sequencing data (Illumina HiSeq X ten platform) of tumor and matched normal tissues from 35 BCP patients and 20 controls. This work provides important novel biological insights and a unique resource to study the biology of breast cancer in young women and how pregnancy could modulate tumor biology.

  Study EGAS00001002685

• RNAseq metadata

  Meta-data/patient information for the bulk RNAseq data

  Dataset EGAD00001008815

• Fecal WMS HV metadata

  Metadata for fecal WMS data from NCT02749630 healthy volunteers.

  Dataset EGAD00001008819

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0170_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0170_003 for Follicular lymphoma patient sample TFRI_Cont_5

  Dataset EGAD00001010207

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0167_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0167_003 for Follicular lymphoma patient sample TFRI_Cont_2

  Dataset EGAD00001010204

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0168_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0168_003 for Follicular lymphoma patient sample TFRI_Cont_3

  Dataset EGAD00001010205

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0169_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0169_003 for Follicular lymphoma patient sample TFRI_Cont_4

  Dataset EGAD00001010206

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0171_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0171_003A for Follicular lymphoma patient sample TFRI_Cont_6

  Dataset EGAD00001010208

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0178_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0178_003A for Follicular lymphoma patient sample TFRI_Cont_8

  Dataset EGAD00001010209

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0187_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0187_003A for Follicular lymphoma patient sample TFRI_Cont_10

  Dataset EGAD00001010211

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0188_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0188_003A for Follicular lymphoma patient sample TFRI_Cont_11

  Dataset EGAD00001010212

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0197_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0197_003A for Follicular lymphoma patient sample TFRI_Cont_12

  Dataset EGAD00001010213

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0198_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0198_003A for Follicular lymphoma patient sample TFRI_Cont_13

  Dataset EGAD00001010214

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0167_001

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0167_001 for Follicular lymphoma patient sample TFRIPAIR2_FL

  Dataset EGAD00001010215

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0168_001

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0168_001 for Follicular lymphoma patient sample TFRIPAIR3_FL

  Dataset EGAD00001010216

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0169_001

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0169_001 for Follicular lymphoma patient sample TFRIPAIR4_FL

  Dataset EGAD00001010217

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0170_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0170_001A for Follicular lymphoma patient sample TFRIPAIR5_FL

  Dataset EGAD00001010218

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0171_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0171_001A for Follicular lymphoma patient sample TFRI_Pair_6_FL

  Dataset EGAD00001010219

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0178_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0178_001A for Follicular lymphoma patient sample TFRIPAIR8_FL

  Dataset EGAD00001010220

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0183_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0183_001A for Follicular lymphoma patient sample TFRIPAIR9_FL

  Dataset EGAD00001010221

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0188_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0188_001A for Follicular lymphoma patient sample TFRIPAIR11_FL

  Dataset EGAD00001010223

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0197_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0197_001A for Follicular lymphoma patient sample TFRIPAIR12_FL

  Dataset EGAD00001010224

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0198_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0198_001A for Follicular lymphoma patient sample TFRI_Pair_13_FL

  Dataset EGAD00001010225

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0167_002

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0167_002 for Diffuse large B-cell lymphoma patient sample TFRIPAIR2_DLBCL

  Dataset EGAD00001010226

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0168_002

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0168_002 for Diffuse large B-cell lymphoma patient sample TFRIPAIR3_DLBCL

  Dataset EGAD00001010227

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0063_000

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0063_000 for Triple negative breast cancer patient-derived xenograft SA609X3XB01584

  Dataset EGAD00001011209

• 10x Single Cell Gene Expression Library TENX068

  10x Single Cell Gene Expression library TENX068 for Triple negative breast cancer patient-derived xenograft SA609X4XB03080

  Dataset EGAD00001011210

• 10x Single Cell Gene Expression Library TENX069

  10x Single Cell Gene Expression library TENX069 for Triple negative breast cancer patient-derived xenograft SA609X4XB03083

  Dataset EGAD00001011211

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0150_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0150_001 for Triple negative breast cancer sample SA609X5XB03230

  Dataset EGAD00001011212

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0150_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0150_002 for Triple negative breast cancer sample SA609X5XB03231

  Dataset EGAD00001011213

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0146_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0146_002 for Triple negative breast cancer patient-derived xenograft SA609X5XB03223

  Dataset EGAD00001011214

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0152_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0152_001 for Triple negative breast cancer patient-derived xenograft SA609X6XB03401

  Dataset EGAD00001011215

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0152_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0152_002 for Triple negative breast cancer sample SA609X6XB03404

  Dataset EGAD00001011216

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0172_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0172_001 for Triple negative breast cancer sample SA609X6XB03447

  Dataset EGAD00001011217

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0163_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0163_002 for Triple negative breast cancer sample SA609X7XB03510

  Dataset EGAD00001011218

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0163_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0163_001 for Triple negative breast cancer patient-derived xenograft SA609X7XB03505

  Dataset EGAD00001011219

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0172_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0172_002 for Triple negative breast cancer sample SA609X7XB03554

  Dataset EGAD00001011220

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0148_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0148_001 for Triple negative breast cancer patient-derived xenograft SA535X4XB02498

  Dataset EGAD00001011221

• 10x Single Cell Gene Expression Library TENX048

  10x Single Cell Gene Expression library TENX048 for Triple negative breast cancer sample SA535X5XB02895

  Dataset EGAD00001011222

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0146_006

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0146_006 for Triple negative breast cancer sample SA535X6XB03099

  Dataset EGAD00001011223

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0175_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0175_001 for Triple negative breast cancer patient-derived xenograft SA535X6XB03101

  Dataset EGAD00001011224

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0182_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0182_001 for Triple negative breast cancer patient-derived xenograft SA535X7XB03304

  Dataset EGAD00001011225

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0189_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0189_001 for Triple negative breast cancer patient-derived xenograft SA535X7XB03448

  Dataset EGAD00001011226

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0184_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0184_001 for Triple negative breast cancer sample SA535X7XB03305

  Dataset EGAD00001011227

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0146_004

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0146_004 for Triple negative breast cancer sample SA535X7XB03305

  Dataset EGAD00001011228

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0189_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0189_002 for Triple negative breast cancer patient-derived xenograft SA535X8XB03663

  Dataset EGAD00001011229

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0182_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0182_002 for Triple negative breast cancer sample SA535X8XB03431

  Dataset EGAD00001011230

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0184_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0184_002 for Triple negative breast cancer patient-derived xenograft SA535X8XB03434

  Dataset EGAD00001011231

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0173_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0173_002 for Triple negative breast cancer patient-derived xenograft SA535X9XB03617

  Dataset EGAD00001011232

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0173_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0173_001 for Triple negative breast cancer patient-derived xenograft SA535X9XB03616

  Dataset EGAD00001011233

• Transcriptomic changes in placenta associated with anesthesia, delivery mode and maternal diabetes

  The goal of this study was to analyse the impact of maternal diabetes and other maternal factors such as birth mode and anaesthesia on placental transcriptomics. Placental tissue samples from both, the villous and the decidua were prepared and RNAseq was conducted; samples were from mothers with Type1 Diabetes or gestational diabetes or from control mothers.

  Study EGAS50000000489

• Spatial Dynamics of the Developing Heart (single-cell)

  Heart development relies on a topologically defined interplay between diverse cardiac cells. We finely curated spatial and single-cell measurements with high-resolution imaging-based transcriptomics validation to explore spatial dynamics during early human cardiogenesis. Analyzing almost 80,000 individual cells and 70,000 spatially barcoded tissue regions between the 5.5th and 14th postconceptional weeks, we identified 31 coarse- and 72 fine-grained cell states and mapped them to highly resolved cardiac cellular niches. We provide novel insight into the development of the cardiac pacemaker-conduction system, heart valves, and atrial septum, and decipher heterogeneity of the hitherto elusive cardiac fibroblast population. Furthermore, we describe the formation of the cardiac autonomic innervation and present the first spatial account of chromaffin cells in the fetal human heart. Our study, supported by an open-access, spatially centric interactive viewer, delineates the cellular and molecular architecture of the developing heart, offering links to genetic causes of heart disease.

  Study EGAS50000001029

• Spatial Dynamics of the Developing Human Heart

  Heart development relies on a topologically defined interplay between diverse cardiac cells. We finely curated spatial and single-cell measurements with high-resolution imaging-based transcriptomics validation to explore spatial dynamics during early human cardiogenesis. Analyzing almost 80,000 individual cells and 70,000 spatially barcoded tissue regions between the 5.5th and 14th postconceptional weeks, we identified 31 coarse- and 72 fine-grained cell states and mapped them to highly resolved cardiac cellular niches. We provide novel insight into the development of the cardiac pacemaker-conduction system, heart valves, and atrial septum, and decipher heterogeneity of the hitherto elusive cardiac fibroblast population. Furthermore, we describe the formation of the cardiac autonomic innervation and present the first spatial account of chromaffin cells in the fetal human heart. Our study, supported by an open-access, spatially centric interactive viewer, delineates the cellular and molecular architecture of the developing heart, offering links to genetic causes of heart disease.

  Study EGAS50000001122

• Whole genome sequencing, DNA methylation, and gene expression data from gastrointestinal stromal tumor 30 patients

  We performed WGS along with genome-wide DNA methylation and gene expression analyses in 30 GIST cases to determine the genomic and epigenomic differences between KIT exon 11 557���558 deletions and other KIT exon 11 mutations.

  Study JGAS000604