6365 results for "11+1双色球多少钱一注"

in 18.95 milliseconds.

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002906

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002904

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002910

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for germinal center B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002911

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002921

• BLUEPRINT release August 2015, DNase-Hypersensitivity for Acute Myeloid Leukemia, on genome GRCh38

  DNase-Hypersensitivity data for 1 Acute Myeloid Leukemia sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820

  Dataset EGAD00001001549

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002919

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002900

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=6days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=6days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002914

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002913

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002909

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002922

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002899

• CDK4/6 inhibition in advanced chordoma: final results of the NCT PMO-1601

  Background. Chordoma is a rare bone tumor with no approved systemic therapy. Inactivation of the tumor suppressor p16 (encoded by CDKN2A) leads to aberrant cyclin D-CDK4/6-RB pathway activity, which can be inhibited by palbociclib in chordoma cell lines. Patients and Methods. We conducted a phase II single-arm, open-labeled trial on palbociclib in adult patients with advanced chordomas with p16 loss (by immunohistochemistry) or CDKN2A loss (by genomic analysis) and CDK4/6 and RB1 presence (by immunohistochemistry or RNA-Sequencing). Patients received 125mg palbociclib once daily for 21 days in a 28-day cycle. The study used a Simon optimal 2-stage design. The primary endpoint was disease control rate after six cycles. Response was evaluated according to Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Secondary endpoints included progression-free survival, overall survival, and biomarker analysis. The study was considered positive if 25% of patients reached the primary endpoint. Results. Between December 2017 and April 2023, 28 patients (median age 60 years, range 31-84) were enrolled. After a median follow-up of 28 months, the disease control rate was 39%, with 11 out of 28 patients achieving stable disease. No objective responses were observed. The median progression-free survival was 5.6 months, and the median overall survival was 24.6 months. Treatment was well tolerated without new safety signals. CDKN2A deletions were the most common genomic alterations underlying p16 loss and were accompanied by MTAP co-deletion. There was no correlation between responder phenotypes by immunohistochemistry and outcome. RNA-based analysis showed heterogeneous pathways deregulation at study entry suggesting underlying primary resistance mechanisms Conclusion. This trial met its primary endpoint with a 39% disease control rate, though antitumor activity was modest. Molecularly tailored combination therapies should be considered to improve efficacy. (ClinicalTrials.gov number, NCT03110744).

  Study EGAS00001007985

• Exome Sequencing to Define the Landscape of Plasma Cells in Systemic Light chain Amyloidosis

  Systemic light chain amyloidosis (AL) is characterized by the deposition of immunoglobulin light chains as amyloid fibrils in different organs, where they form toxic protein aggregates. The underlying disease is a plasma cell disorder, but limited whole exome data are available. We report the findings of an exome sequencing study in AL to define a plasma cell signature and compare this to monoclonal gammopathy of undefined significance (MGUS) and myeloma (MM). Twenty-four samples from unselected newly diagnosed untreated AL patients were analysed. CD138+ cells were isolated from bone marrow cells using MACSorting (Miltenyi Biotech, Bisley, UK). Cells were lysed in RLT+ buffer and DNA/RNA extracted using the AllPrep kit (Qiagen, Manchester, UK). Peripheral blood was isolated from patients, white blood cells purified by Ficoll-Pacque and DNA extracted using the QIAamp DNA mini kit (Qiagen). There were a median of 47 acquired nonsynonymous variants (range 4-253) per patient. Thirty percent of patients yielded a mutation in a myeloma driver gene. These mutations were either clonal or sub-clonal. There was evidence of MAPK activation with NRAS mutations, NF-κB activation and DNA repair pathway alterations. Exome data were used to determine the cytogenetic groups of AL samples and identified hyperdiploidy in 33% of cases and t(11;14) in 33% of cases. All translocations were generated via class switch recombination and breakpoints on chromosome 11 fell into the expected regions. A novel translocation, unlikely to be driving disease progression was identified involving RCC1. Finally, further analysis of the APCS gene encoding for the SAP protein did not show any biased genotype in the AL population in comparison to the general population. We conclude that exome sequencing identifies a genetic make-up of AL that is similar to other plasma cell disorders such as MM and MGUS. This not only includes copy number abnormalities and translocations but also nonsynonymous mutations.

  Study EGAS00001001418

• WES_of_adult_intellectual_disabilities_with_co_morbid_psychiatric_disorders

  ost adults with intellectual disabilities (ID) do not undergo genetic diagnostic investigation as part of their clinical care and have 'missed the boat' with regard to the WES and WGS genetic testing that is now being provided for children with ID. There is a dramatically increased risk of psychistric disorders in adults with ID, e.g. the risk of psychoses is 10X higher than in the general population. It remains an open question as to how much of adult ID is genetic in origin and how similar the genetic forms of adult ID are to those being diagnosed in children, in part due to survivor bias. There is also the opportunity to identify adults with treatable forms of ID, of which over 80 have been described, thus improving their clinical management. Furthermore, analysis of medical records of adults with genetic forms of ID can help to characterise the 'natural history' of individual disorders, resulting in more accurate prognoses for diagnosed children and identifying opportunities for improved management and possibly therapeutic intervention (e.g. optimal anti-epileptic therapy). Here we propose to exome sequence (to ~50X coverage) 200 adults with ID and co-morbid psychiatric disorders. This cohort has previously been assayed with chromosomal microarrays (Wolfe et al 2017 EJHG, 25, 66–72) identifying a diagnostic yield of ~11% which is comparable to the CNV diagnostic yield in various child ID cohorts (10-15%). The authors observed no substantive biases in diagnostic yield between different psychiatric diagnostic classes. The WES data will be analysed using the diagnostic workflows developed in the DDD study to ensure comparability between child and adult ID datasets. This study is intended as a pilot study to demonstrate the value of WES in adults with ID. 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 EGAS00001002962

• Single Cell Dissection of the Tumour Microenvironment Reveals Dynamic Interplay Shaping the Tumour Immunity Continuum in Ovarian Cancer

  Diverse tumour immune phenotypes with distinct T cell infiltration patterns result in different responses to cancer immunotherapies. However, the key determinants and biology underpinning these phenotypes remain elusive. Here, we provide a high-resolution dissection of the tumour microenvironment representative of different tumour immune phenotypes. By performing single-cell RNA sequencing (scRNAseq) of the tumour, immune, and stromal compartments from 15 ovarian cancer patients, we characterized the diverse cellular and functional phenotypes, as well as dynamic interplay within and between these components. Infiltrated and excluded tumours markedly differed from desert tumours in several tumour cell intrinsic features, including high interferon response, antigen presentation and oxidative phosphorylation. Moreover, these tumours were characterized by tumour associated macrophage (TAM)-like myeloid subsets, while desert tumours were enriched in myeloid derived suppressive cell (MDSC)-like myeloid subsets. Infiltrated and excluded tumours differed in their T cell composition and fibroblast subsets. While dysfunctional CD8+ GZMB T cells and IL1-activated fibroblasts (IL1 CAFs) were associated with infiltrated tumours, pre-dysfunctional CD8+ GZMK T cells and TGFB-activated fibroblasts (TGFB CAFs) were enriched in excluded tumours. These findings validated in bulk transcriptomic profiles of 1071 ovarian tumours and using in situ hybridization. Furthermore, our study revealed chemokine receptor-ligand interactions within and across compartments as potential mechanisms mediating immune cell infiltration, exemplified by the tumour cell-T cell crosstalk via a CXC16-CXCR6 axis, stromal-immune cell crosstalk via CXCL12/14-CXCR4 signalling, and TAM-like macrophage-T cell crosstalk through CXCR3-CXCL9/10/11 signalling. Our in-depth characterization of the tumour environment and intercellular interactions provides novel insights into potential molecular mechanisms that shape the distinct biology of tumour immune phenotypes. Our findings may inform novel therapeutic strategies for potentially shifting tumours along the immunity continuum to improve clinical benefit from cancer immunotherapies.

  Study EGAS00001004935

• Proteomic Analysis of Non-Muscle Invasive and Muscle Invasive Bladder Cancer Highlights Distinct Subgroups With Metabolic, Matrisomal, and Immune Hallmarks

  We present the proteome biology of bladder cancer based on a cohort comprising treatment-naïve non-muscle invasive (NMIBC, N=17) and treatment-naïve muscle-invasive bladder cancer (MIBC, N=51), as well as neoadjuvant-treated MIBC (N=11); using formalin-fixed, paraffin-embedded samples and data-independent acquisition yielding >8,000 protein identifications. The NMIBC proteome reveals two subgroups that represent cell adhesion or lipid metabolism biology. MIBC, compared to NMIBC, shows an altered metabolic proteome together with enrichment of extracellular matrix (ECM), immune response, and complement proteins; in line with three proteomic MIBC subgroups that represent ECM, metabolic, or immune signatures. The ECM and immune subgroups are enriched for markers of M2-like tumor-associated macrophages and dendritic cells, while markers for natural killer cells are exclusive for the ECM subgroup, and markers for cytotoxic T-cells are a hallmark of the immune subgroup. Infiltration of CD8+ PD1+ positive cytotoxic T cells correlated with PD-L1 expression of MIBC, as demonstrated by multiplex immunofluorescence analysis. The metabolic subgroup presents a comparably immune-depleted microenvironment. YAP1 signaling is particularly prominent in the ECM subgroup. The protein BSCL2 emerges as a prognostic marker for MIBC. We highlight increased endogenous proteolysis in MIBC alongside the upregulation of matrix metalloproteases exceeding the upregulation of their endogenous inhibitors. Genomic panel sequencing underlines prevalent FGFR3 mutations in NMIBC and prevalent TP53 mutations in MIBC, but a genomic underpinning of the MIBC subgroups remains elusive. Proteogenomic analysis yields protein-level evidence for more than 1,300 single amino acid variants. The proteomes of neoadjuvant-treated MIBC resembled treatment-naïve MIBC. Tumor-stroma interaction of MIBC was further investigated by proteomic analysis of patient-derived xenografts of MIBC. Our study adds to the proteome-level understanding of bladder cancer.

  Study EGAS00001007290

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002915

• BLUEPRINT release August 2015, DNase-Hypersensitivity for alternatively activated macrophage, on genome GRCh38

  DNase-Hypersensitivity data for 1 alternatively activated macrophage sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820

  Dataset EGAD00001001545

• BLUEPRINT release August 2014, DNase-Hypersensitivity for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  DNase-Hypersensitivity data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811

  Dataset EGAD00001000942

• BLUEPRINT release January 2015, DNase-Hypersensitivity for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  DNase-Hypersensitivity data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811

  Dataset EGAD00001001161

• BLUEPRINT release August 2016, DNase-Hypersensitivity for CD4-positive, alpha-beta T cell, on genome GRCh38

  DNase-Hypersensitivity data for 1 CD4-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002480

• BLUEPRINT release August 2016, DNase-Hypersensitivity for CD8-positive, alpha-beta T cell, on genome GRCh38

  DNase-Hypersensitivity data for 1 CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002285

• BLUEPRINT release August 2015, DNase-Hypersensitivity for CD8-positive, alpha-beta T cell, on genome GRCh38

  DNase-Hypersensitivity data for 1 CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820

  Dataset EGAD00001001475

• BLUEPRINT release August 2015, DNase-Hypersensitivity for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  DNase-Hypersensitivity data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820

  Dataset EGAD00001001524

• WGS of CTCs enriched using high-throughout microfluidic device from entire cancer patient leukopak

  Single-cell low-pass WGS analysis (illumina platform, PE150, 1-2x coverage) was performed on CTCs enriched using high-throughout microfluidic device from entire leukopak from patients with metastatic prostate cancer (GU-1 and GU-2) and metastatic hepatocellular carcinoma (HCC-1 and HCC-2).

  Study EGAS50000000723

• Brain tumor sequencing data

  This study contains tumor DNA (with matched normal) for 1 medulloblastoma and 1 ependymoma patient. Tumor RNA sequencing data is also present for the medulloblastoma patient

  Study EGAS00001006352

• BLUEPRINT release August 2014, RNA-Seq for macrophage

  RNA-Seq data for 1 macrophage sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000933

• BLUEPRINT release August 2015, Bisulfite-Seq for memory B cells, on genome GRCh38

  Bisulfite-Seq data for 1 memory B cells sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001494

• BLUEPRINT release January 2015, RNA-Seq for Leukemia

  RNA-Seq data for 1 Leukemia sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001178

• BLUEPRINT release August 2015, RNA-Seq for Leukemia, on genome GRCh38

  RNA-Seq data for 1 Leukemia sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001551

• Genomic gain of EBV's LMP-1 in NKTCL

  The study found a high recurrence of genomic gain of LMP1 locus within EBV-associated NKTCL. The pilot data set and extended dataset of 77 WGS NKTCLs found 18/77 tumoral genomes to harbour genomic gain of LMP-1 locus within the EBV viral genomes within NKTCL tumoral sequencing data. The study also found 1/10 NKTCL cell lines to be positive for LMP-1 locus gain within EBV genomes too. This dataset includes solely the confirmatory WGS data of LMP-1 gain from NKYS cell lines using Oxford Nanopore long-read sequencing technology.

  Study EGAS50000000260

• Tandem DNA Repeats Activate hTERT Gene Transcription

  Multiple independent sequence variants of the hTERT locus have been associated with telomere length and cancer risks in genome-wide association studies. Here, we identified an intronic variable number tandem repeat, VNTR2-1, as an enhancer-like element, which activated hTERT transcription in a cell and chromatin-dependent manner. VNTR2-1, consisting of 42-bp repeats with an array of E-boxes, cooperated with the proximal promoter in hTERT regulation by bHLH transcription factors and maintained hTERT expression during embryonic stem cell differentiation. Genomic deletion of VNTR2-1 in MelJuSo melanoma cells markedly reduced hTERT transcription, leading to telomere shortening, cellular senescence, and impairment of xenograft tumor growth. Interestingly, VNTR2-1 lengths varied widely in human populations.  To assess the genetic polymorphism of VNTR2-1 in human populations, we analyzed genomic DNA samples of Caucasian Americans and African Americans enrolled in the Georgia Centenarian Study.  VNTR2-1 in these genomic DNA samples were PCR amplified and subjected to sequencing analysis usinb the PacBio® SMRT method. The result showed that all VNTR2-1 alleles in Caucasian Americans contained 76 or more 42-bp repeats, whereas 32% of VNTR2-1 alleles in African Americans had fewer than 76 repeats.  

  Study phs002428

• WES

  WES was performed on 2 TURP, 6 biopsies, 1 CDX, 1 cell line, 6 CTCs, 1 DNA germline and 1WBC from prostate cancer

  Dataset EGAD00001006009

• Broccoli Sprouts Extracts Trial (BEST-COPD-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To establish a safe and tolerable dose of sulforaphane that effects in vivo antioxidants via Nrf2 for development as a potential novel treatment for participants with Chronic Obstructive Pulmonary Disease (COPD).Background: Chronic Obstructive Pulmonary Disease (COPD), caused primarily by smoking, is the third leading cause of death in the United States and world-wide. Surprisingly, there are few treatments available to address the pathobiology of COPD other than cessation of smoking. The development and progression of COPD are associated with increased inflammatory response(s) and increased oxidative stress in the lung. Thus, one approach to the development of novel therapies is the stimulation of endogenous antioxidant defense mechanisms.Nuclear factor erythroid-2-related factor 2 (NFE2L2/Nrf2) is a transcription factor activated by oxidative stress. Nrf2 activity promotes anti-oxidant enzymes, and anti-oxidant enzymes play key roles in cellular defenses. Sulforaphane, a derivative of broccoli and other cruciferous vegetables, has been shown to stimulate Nrf2 activity in both in vivo and in vitro experiments. For example, activation of Nrf2 protected mice from developing emphysema after chronic smoke exposure and decreased oxidative stress. Similarly, activation of Nrf2 in human COPD lung cells resulted in decreased oxidative stress. Therefore, this study was designed to assess whether daily ingestion of sulforaphane by COPD participants for four weeks increased Nrf2 activity in alveolar macrophages and bronchial epithelial cells. Participants: There were a total of 89 participants randomized to one of three treatment arms. Of these, 31 participants were randomized to the placebo arm, and 29 participants were randomized to the each of the sulforaphane arms. One participant withdrew from the placebo arm, therefore, a total of 88 participants completed the study.Design: Participants were assigned to receive sulforaphane at 25 micromoles (4.4mg), sulforaphane at 150 micromoles (26.6 mg), or placebo (microcellulose) once daily by mouth. Computer-generated treatment assignments were blinded to participants, clinical staff, and study staff. Doses were back-filled with methylcellulose and presented in similar capsules to compensate for appearance and weight differences in sulforaphane and placebo treatments arms.There were a total of five study visits over the six-week study period. Prior to randomization, participants were assessed for eligibility, which included baseline data collection. Participants provided medical histories, underwent a physical examination, pre-and-post bronchodilator spirometry, lung volume measurements, carbon monoxide diffusing capacity (DLCO), and pulse oximetry over the six-week study period. Follow up data and biospecimens were collected at the final visit, which was targeted for four weeks after randomization. Two fiberoptic bronchoscopies were performed under sedation to collect endobronchial brushings and bronchoalveolar lavage used to isolate alveolar macrophages and bronchial epithelial cells. The first bronchoscopy was performed on the day of randomization, and the second bronchoscopy was performed the day after the final visit. In addition, nasal brushings were obtained prior to bronchoscopy to isolate nasal epithelial cells. The primary outcomes were changes in Nrf2 target gene expression at four weeks in alveolar macrophages and bronchial epithelial cells. The target genes for the primary outcome were NQ01, H01, AKR1C1, and AKR1C3. Secondary outcomes included the evaluation of: expression of other genes in the Nrf2/Keap1 pathway (e.g. Nrf2/NFE2L2, KEAP1, and SLPI), markers of oxidative stress (e.g., isoprostane and thiobarbituric acid reactive substances) in plasma and expired breath condensate, and cytokine profiles in bronchoalveolar lavage fluid. Conclusions: Sulforaphane administered at four weeks doses of 25umoles and 150umoles to participants with COPD did not significantly increase Nrf2 target gene expression in alveolar macrophages or bronchial epithelial cells. In addition, changes in oxidative stress markers and the expression of other genes in the Nrf2/Keap1 pathway were not statistically significant between the treatment groups.Wise RA, Holbrook JT, Criner G, et al. Lack of Effect of Oral Sulforaphane Administration on Nrf2 Expression in COPD: A Randomized, Double-Blind, Placebo Controlled Trial. Vij N, ed. PLoS ONE. 2016; 11(11):e0163716. doi:10.1371/journal.pone.0163716 (PMID: 27832073; PMID: 28350841).

  Study phs004022

• Transcriptional Profiling of PD-1+ and PD-1- Teff and Treg Cells in Glioblastoma and Health

  PD-1 is an important immune checkpoint inhibitor that shows great promise in the clinic, particularly for melanoma and lung cancers. Since PD-1 is also expressed on infiltrating CD4+ Treg and Teffector cells in glioblastoma, we sought to better understand the role of PD-1 on these infiltrating CD4+ Treg and Teffector cells. To this end, we performed functional and transcriptional profiling using CD4+ Treg and Teffector cells isolated from healthy donors and glioblastoma patients (from both tumors and blood).

  Study phs001079

• scRNA-seq and scTCR-seq data IMCISION

  We performed single cell RNA and TCR sequencing (10x Genomics) on immune infiltrates (CD45+ cells) from 18 HNSCC patients enrolled in the IMCISION trial (Vos et al. 2021). Viable immune cells were isolated from pre-treatment and on-treatment primary tumor biopsies of 10 patients responding (1 partial pathological response and 9 major pathological responses) and 7 patients non-responding to anti-PD-1 and anti-CTLA4 combination immunotherapy. One patient treated with anti-PD-1 monotherapy (1 major pathological response) was included in the dataset.

  Study EGAS00001007368

• BLUEPRINT release August 2016, RNA-Seq for Acute Promyelocytic Leukemia - MC2884, on genome GRCh38

  RNA-Seq data for 1 Acute Promyelocytic Leukemia - MC2884 sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002352

• BLUEPRINT September 2016, ChIPmentation for naive B cell from tonsil, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for naive B cell from tonsil, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002937

• BLUEPRINT release January 2015, RNA-Seq for regulatory T cell

  RNA-Seq data for 1 regulatory T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001174

• BLUEPRINT release August 2016, RNA-Seq for Acute Promyelocytic Leukemia - MC2884 (24h), on genome GRCh38

  RNA-Seq data for 1 Acute Promyelocytic Leukemia - MC2884 (24h) sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002461

• BLUEPRINT release August 2016, ChIP-Seq for Acute Promyelocytic Leukemia - SAHA, on genome GRCh38

  ChIP-Seq data for 1 Acute Promyelocytic Leukemia - SAHA sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002298

• BLUEPRINT release August 2016, RNA-Seq for Acute Promyelocytic Leukemia - MC2884 (4h), on genome GRCh38

  RNA-Seq data for 1 Acute Promyelocytic Leukemia - MC2884 (4h) sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002513

• BLUEPRINT release August 2015, RNA-Seq for T-cell acute leukemia, on genome GRCh38

  RNA-Seq data for 1 T-cell acute leukemia sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001469

• BLUEPRINT release August 2016, RNA-Seq for Acute Lymphocytic Leukemia - CTR, on genome GRCh38

  RNA-Seq data for 1 Acute Lymphocytic Leukemia - CTR sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002332

• BLUEPRINT release August 2014, RNA-Seq for alternatively activated macrophage

  RNA-Seq data for 1 alternatively activated macrophage sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000937

• BLUEPRINT release January 2015, RNA-Seq for memory B cell

  RNA-Seq data for 1 memory B cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001171

• BLUEPRINT release August 2015, RNA-Seq for mature eosinophil, on genome GRCh38

  RNA-Seq data for 1 mature eosinophil sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001525

• BLUEPRINT release August 2016, RNA-Seq for Acute Promyelocytic Leukemia - MC2392, on genome GRCh38

  RNA-Seq data for 1 Acute Promyelocytic Leukemia - MC2392 sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002359