12373 results for ""statistically+reactive"+taxa+in+microbial+community"

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• Combination_Immune_Checkpoint_Inhibition_in_Australian_Rare_Cancers_WES

  Combination immune checkpoint inhibition (ICI) with anti-CTLA-4 and anti-PD-1 blockade has demonstrated significant clinical activity across tumour types. Rare cancer patients have limited treatment options due to the scarcity of studies of novel treatment options, so they are often offered chemotherapies untested in their disease. ONJ2016-001/CA209-538 is a prospective, multicentre clinical trial of combination ICI (ipilimumab and nivolumab) in patients with advanced rare cancers, including biliary tract, adrenocortical, rare gynaecological and neuroendocrine cancers (https://clinicaltrials.gov/ct2/show/NCT02923934). The primary endpoint is clinical benefit rate (complete response + partial response + stable disease >3 months) by RECIST 1.1. This study involves generation and analysis of pre-treatment formalin fixed paraffin embedded (FFPE) tumour DNA sequencing data, paired with germline DNA sequencing data, to potentially identify genomic biomarkers that may associate with clinical benefit or other clinical efficacy / toxicity metrics.

  Study EGAS00001005709

• Beacon v2

  Beacon v2: a tool for data discovery Motivation In the era of data-driven health research and personalised medicine, human genomic data has become extremely valuable. These are also identifiable data, as they carry information pointing to a specific individual as well as their own family; and as such, they must be protected. This makes data discovery particularly challenging: this is where ?Beacon? comes in. A ?Beacon? is an API aiming to enable the search of genomic variants and associated information without jeopardising the privacy of the dataset. Here, we refer to its current version, namely version 2 (v2). Definition Beacon v2 is a term that can refer to different aspects. The EGA is playing a central role in the following aspects: The Beacon v2 protocol is a Global Alliance for Health and Genomics standard. The Beacon v2 Reference Implementation (B2RI) is an ?out-of-the-box? Beacon instance developed with ELIXIR, which facilitates Beacon deployment. The EGA Beacon(s) are Beacons following the v2 standard and using the B2RI, deployed on top of data hosted at the EGA and allowing for their discovery. Resources Depending on whether you are visiting us a stakeholder (you need more general information about Beacon), a deployer /implementer (you want to have your own Beacon instance), or an EGA user (you want to query Beacon and start browsing data), you will be interested in the following resources: Your role Beacon aspect Documentation type Stakeholder Beacon v2 protocol Beacon website Beacon page on the GA4GH website Deployer/Implementer Beacon v2 protocol Read the docs: Beacon v2 standard technical description GitHub repository Beacon v2 standard Beacon v2 Reference Implementation Read the docs: B2RI technical description GitHub repository B2RI Guide to deploy Beacon using B2RI EGA user EGA Beacon EGA AF Browser

  Documentation about/projects-and-funders/beacon

• PDX_models_from_Latin_America_WES_

  Acral melanoma (AM) is a subtype of cutaneous melanoma that occurs on glabrous skin of the hands and feet (palms, soles and nail apparatus) and which is relatively more common in non-European descent populations such as those of Latin America. Compared to other subtypes, it is poorly studied and experimental models that faithfully reproduce human AM features are urgently needed. We report the generation and preliminary characterisation of a collection of patient-derived xenografts of acral melanomas (AM-PDX) from Latin-American patients. PDX came from Brazilian and Mexican patients cared for at the Instituto Nacional de Câncer (INCA) and the Instituto Nacional de Cancerologia (INCan). The majority of the samples are acral lentiginous melanomas, ulcerated, with > 4mm Breslow depth and > 2 mitosis / mm2. Samples were mechanically fragmented and subcutaneously implanted in NSG mice and then collected for molecular analysis.

  Study EGAS00001005663

• PDX_models_from_Latin_America_RNAseq

  Acral melanoma (AM) is a subtype of cutaneous melanoma that occurs on glabrous skin of the hands and feet (palms, soles and nail apparatus) and which is relatively more common in non-European descent populations such as those of Latin America. Compared to other subtypes, it is poorly studied and experimental models that faithfully reproduce human AM features are urgently needed. We report the generation and preliminary characterisation of a collection of patient-derived xenografts of acral melanomas (AM-PDX) from Latin-American patients. PDX came from Brazilian and Mexican patients cared for at the Instituto Nacional de Câncer (INCA) and the Instituto Nacional de Cancerologia (INCan). The majority of the samples are acral lentiginous melanomas, ulcerated, with > 4mm Breslow depth and > 2 mitosis / mm2. Samples were mechanically fragmented and subcutaneously implanted in NSG mice and then collected for molecular analysis.

  Study EGAS00001008150

• PDX_models_from_Latin_America_Xenofiltered_WES

  Acral melanoma (AM) is a subtype of cutaneous melanoma that occurs on glabrous skin of the hands and feet (palms, soles and nail apparatus) and which is relatively more common in non-European descent populations such as those of Latin America. Compared to other subtypes, it is poorly studied and experimental models that faithfully reproduce human AM features are urgently needed. We report the generation and preliminary characterisation of a collection of patient-derived xenografts of acral melanomas (AM-PDX) from Latin-American patients. PDX came from Brazilian and Mexican patients cared for at the Instituto Nacional de Câncer (INCA) and the Instituto Nacional de Cancerologia (INCan). The majority of the samples are acral lentiginous melanomas, ulcerated, with > 4mm Breslow depth and > 2 mitosis / mm2. Samples were mechanically fragmented and subcutaneously implanted in NSG mice and then collected for molecular analysis.

  Study EGAS00001008231

• PDX_models_from_Latin_America_RNAseq_Xenofiltered

  Acral melanoma (AM) is a subtype of cutaneous melanoma that occurs on glabrous skin of the hands and feet (palms, soles and nail apparatus) and which is relatively more common in non-European descent populations such as those of Latin America. Compared to other subtypes, it is poorly studied and experimental models that faithfully reproduce human AM features are urgently needed. We report the generation and preliminary characterisation of a collection of patient-derived xenografts of acral melanomas (AM-PDX) from Latin-American patients. PDX came from Brazilian and Mexican patients cared for at the Instituto Nacional de Câncer (INCA) and the Instituto Nacional de Cancerologia (INCan). The majority of the samples are acral lentiginous melanomas, ulcerated, with > 4mm Breslow depth and > 2 mitosis / mm2. Samples were mechanically fragmented and subcutaneously implanted in NSG mice and then collected for molecular analysis.

  Study EGAS00001008232

• miRNA expression data from primary tumors, metastasis and matched normals.

  MicroRNAs (miRs) have been recognized as promising biomarkers. It is unknown to what extent tumor-derived miRs are differentially expressed between primary colorectal cancers (pCRCs) and metastatic lesions, and to what extent the expression profiles of tumor tissue differ from the surrounding normal tissue. Next-generation sequencing (NGS) of 220 fresh-frozen samples, including paired primary and metastatic tumor tissue and non-tumorous tissue from 38 patients, revealed expression of 2245 known unique mature miRs and 515 novel candidate miRs. Unsupervised clustering of miR expression profiles of pCRC tissue with paired metastases did not separate the two entities, whereas unsupervised clustering of miR expression profiles of pCRC with normal colorectal mucosa demonstrated complete separation of the tumor samples from their paired normal mucosa. Two hundred and twenty-two miRs differentiated both pCRC and metastases from normal tissue samples (false discovery rate (FDR) <0.05). The highest expressed tumor-specific miRs were miR-21 and miR-92a, both previously described to be involved in CRC with potential as circulating biomarker for early detection. Only eight miRs, 0.5% of the analysed miR transcriptome, were differentially expressed between pCRC and the corresponding metastases (FDR <0.1), consisting of five known miRs (miR-320b, miR-320d, miR-3117, miR-1246 and miR-663b) and three novel candidate miRs (chr 1-2552-5p, chr 8-20656-5p and chr 10-25333-3p). These results indicate that previously unrecognized candidate miRs expressed in advanced CRC were identified using NGS. In addition, miR expression profiles of pCRC and metastatic lesions are highly comparable and may be of similar predictive value for prognosis or response to treatment in patients with advanced CRC.

  Dataset EGAD00001001644

• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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/ . This dataset contains all the data available for this study on 2018-10-23.

  Dataset EGAD00001004413

• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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/ . This dataset contains all the data available for this study on 2018-10-23.

  Dataset EGAD00001004416

• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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/ . This dataset contains all the data available for this study on 2018-10-23.

  Dataset EGAD00001004414

• Molecular risk stratification in patients with T1 colorectal cancer_WES

  The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have 'born-to-be-bad' aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world's largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3' RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

  Dataset EGAD00001010890

• H3K27ac ChIP-seq in primary inflammatory macrophages from 2 minor allele homozygotes and 2 major allele homozygotes at rs2836882

  This dataset consists of H3K27ac ChIP-sequencing in inflammatory (TPP) macrophages from 2 minor allele homozygotes and 2 major allele homozygotes at rs2836882. Monocytes were positively selected from PBMC using CD14 Microbeads and inflammatory macrophage differentiation performed using conditions that model chronic inflammation (TPP): 3 days GM-CSF (50ng/mL) followed by 3 days GM-CSF, TNFa (50ng/mL), PGE2 (1mg/mL), and Pam3CSK4 (1mg/mL). After harvesting, cells were cross-linked, quenched, lysed, and sheared. Immunoprecipitation of histone-DNA complexes was performed overnight at 4C with rotation using an anti-H3K27ac antibody and the SimpleChIP Plus Sonication ChIP kit (Cell Signaling Technology). Following reverse cross-linking, 50ng of immunoprecipitated DNA or input DNA were used to prepare sequencing libraries using the iDeal Library Preparation kit (Diagenode), according to manufacturer instructions. 10 PCR cycles were used for the amplification step and size selection was not performed. The quality and molarity of all libraries was assessed using a BioAnalyzer 2100 (Agilent) and the libraries were sequenced in pools of 8, with each pool being sequenced in 2 lanes of an Illumina HiSeq2500 high output flow-cell (50bp, single-end reads). Raw data are provided as raw and aligned single-end sequencing reads from H3K27ac-bound DNA and the input chromatin. Raw reads were trimmed using Trim Galore and aligned to the reference human genome (hg19) using Burrows-Wheeler Aligner (v0.7.12) with default parameters. Aligned reads were converted to BAM files, sorted, and technical duplicates merged before indexing – all using SAMtools (v1.4). PCR duplicates were identified using Picard tools (v2.18.1) and removed together with unmapped reads using SAMtools (v1.4). The resulting BAM files were re-sorted and indexed after filtering.

  Dataset EGAD00001011351

• Raw mRNA expressions

  WG mRNA profiling in FFPE primary melanoma

  Dataset EGAD00010001562

• Kenya_GWAS-2.5M_b37

  Genome-wide study of resistance to severe malaria in eleven worldwide populations:Kenya

  Dataset EGAD00010000904

• Malawi_GWAS-2.5M_b37

  Genome-wide study of resistance to severe malaria in eleven worldwide populations:Malawi

  Dataset EGAD00010000903

• Gambia_GWAS-2.5M_b37

  Genome-wide study of resistance to severe malaria in eleven worldwide populations:Gambia

  Dataset EGAD00010000902

• ChIP-Seq files for RMS.

  ChIP-Seq files accompanying the paper titled "Identification of Therapeutic Targets in Rhabdomyosarcoma Through Integrated Genomic, Epigenomic, and Proteomic Analyses".

  Dataset EGAD00001006398

• postQC Genotypes

  postQC genotype data from the Affymetrix AxiomTM HGCoV2 1 array in plink binary format. QC was carried out using PLINK v1.9

  Dataset EGAD00010002436

• cfDNA methylation dataset for colon cancer

  Enzymatic conversion-based methylation sequencing data (EM-seq) for colon cancer used in the MESA study

  Dataset EGAD50000000075

• GLASS-NL Transcriptomic data

  This dataset contains RNA-sequencing data of 169 IDH-mutant astrocytoma samples included in the GLASS-NL cohort

  Dataset EGAD50000000408

• TOAPR-B patient cell-free DNA WGS and WES

  Sequencing files for TOPARP-B patients as described in manuscript

  Dataset EGAD50000000407

• ECL_onc_biology_DAC

  This DAC can be used by biology members of the oncology-related domain and function of ECL when depositing data. (DAA was reviewed by the legal department in March 2024.)

  Dac EGAC50000000275

• University of Hull

  Tumour Regulatory Molecules in Early Pancreatic Cancer Detection (TEM-PAC) and EARLY DIAgnosis of PAncreatic Cancer by combined proteomics and genomics testing of pancreatic cyst fluid (DIA-PAC) studies.

  Dac EGAC50000000402

• Rucaparib in patients presenting a metastatic breast cancer with Homologous Recombination Deficiency, without germline BRCA1/2 mutation, pronostic value of high LOH genomic score and predictive value of HRDetect (WGS)

  Study EGAS00001004756

• Walter and Eliza Hall - Aix-Marseille Université

  Data Access Committee for the Liao et al. 2025 study, D4Z4End2End: complete genetic and epigenetic architecture of D4Z4 macrosatellites in FSHD, BAMS and reference cohorts.

  Dac EGAC50000000655