12528 results for ""non-traditional+communal+storytelling+approach"+novel+segment+noted+in+critical+commentary"

in 17.98 milliseconds.

• The_Genomic_Advances_in_Sepsis__GAinS__RNA_seq

  Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. This cohort comprises a subset of patients enrolled in the Genomic Advances in Sepsis (GAinS) study, an established biobank of adult sepsis patients. Patients with sepsis due to community acquired pneumonia or faecal peritonitis were recruited from 34 hospitals across the UK from 2005-2018, with samples for functional genomics and detailed clinical information collected on the first, third and/or fifth day following ICU admission. RNA was extracted from leukocytes isolated at the bedside using LeukoLOCK kits. We have previously identified sepsis response signatures (SRSs), transcriptomic endotypes that are associated with differential early mortality (Davenport et al, Lancet Respir Med, 2016; Burnham et al, AJRCCM, 2017) and response to treatment in a clinical trial (Antcliffe et al, AJRCCM, 2018). We generated RNA sequencing data on 903 samples, including 134 samples repeated from our previously released microarray data. Libraries were prepared using NEB Ultra II Library Prep kits (Illumina) and sequenced on a NovaSeq 6000. Reads were aligned to the reference genome (GRCh38) using STAR and gene counts quantified using featureCounts (annotation Ensembl v99). Counts were TMM-normalised and log-transformed. Following QC, processed data were available on 864 samples from 667 unique patients.

  Study EGAS00001003772

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities WGS

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006865

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities RNA-Seq

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006866

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities DNA-Methylation

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006881

• Detection of cancers three years prior to diagnosis using plasma cell-free DNA

  A major goal of early cancer detection is to identify subclinical disease when the tumor burden is low, so that treatments are more effective. But how early can cancers be detected prior to clinical signs or symptoms? This question can be answered only through the evaluation of participants whose clinical course has not been altered by the study itself. We here describe such an evaluation, performed on prospectively collected plasma samples from the Atherosclerosis Risk in Communities (ARIC) study, including 26 participants diagnosed with cancer and 26 matched controls. At the index time point, eight of these 52 participants scored positively with a multicancer early detection (MCED) blood test. All eight of these participants were diagnosed with cancer within 4 months after blood collection. In six of these 8 participants, we were able to assess an earlier plasma sample collected 3.1 to 3.5 years prior to clinical diagnosis. In four of these six participants, the same mutations detected by the MCED test could be identified, but at 8.6 to 79-fold lower levels. These results demonstrate that it is possible to detect circulating tumor DNA (ctDNA) more than three years prior to clinical diagnosis, and provide benchmark sensitivities required for the success of ctDNA-based tests for this purpose.

  Study EGAS00001008068

• NEI CIDR Methylation Profiling of Primary Open Angle Glaucoma in NEIGHBOR Samples

  This is a case-control study of Primary Open Angle Glaucoma (POAG). POAG is a progressive optic neuropathy that eventually leads to blindness. More than 30 million people worldwide have Primary Open Angle Glaucoma (POAG), of which greater than 3 million are blind. Gene expression changes in the retina have been observed for POAG. Several recent studies, including the NEIGHBOR consortium (NEI Glaucoma Human genetic collaboration) have used GWAS to identify correlative regions of the genome. Despite this, the genetic basis of Glaucoma is not well understood. Epigenetic variation may account for low heritability and environmental effects on human disease. Despite the significant advances being made in understanding the role of epigenetics in gene regulation in other fields, little is known about the relationship between DNA methylation patterns, retinal gene expression, and retinal disease. The goal of this study is to identify differentially methylated regions in the peripheral blood of patients with POAG. The case identification is as per the NEIGHBOR description: Cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. POAG and control samples come from two sources: Duke University and Massachusetts Eye and Ear Infirmary (MEEI). These samples were collected and genotyped as part of the NEIGHBOR study. From the 219 POAG cases contributed to NEIGHBOR by Duke, 75 samples were selected for exome sequencing by Dr. Terry Gaasterland (UCSD) as part of an ARRA grant. These samples were selected to mirror the distribution of the entire set of Duke patients for variables such as age, cup-to-disc ratio, CCT, and IOP. From these 75 patients, 43 were selected for our study and an additional seven patients chosen at random, for a total 50 patients from Duke. From the 219 Duke controls, 50 were selected to match the age (at the time of blood draw) and sex of the 50 Duke POAG patients. From the NEIGHBOR control samples from MEEI, 27 were selected who best matched the age (at blood draw), time since sample collection and sex of the POAG probands from GLAUGEN. Additional individual-level phenotype and genotype data may be obtained through the authorized access portal of phs000238 (Neighbor - Glaucoma GWAS Study).

  Study phs000458

• Center for Craniofacial and Dental Genetics (CCDG): Genetics of Orofacial Clefts and Related Phenotypes

  The purpose of this study is to investigate the genetics of orofacial clefts (OFCs) in a large study population, and importantly, to incorporate subclinical phenotypic features into these studies. Orofacial clefts (OFCs) comprise a significant fraction of human birth defects (about 1/700 live births (Rahimov et al. 2012) and represent a major public health challenge, as individuals with these anomalies require surgical, nutritional, dental, speech, medical and behavioral interventions, thus imposing a substantial economic and personal burden (Berk and Marazita 2002*). The most common forms include OFCs of the lip alone (CL, Figure 1A), CL plus cleft palate (CL+CP, Figure 1B) or of the palate only (CP, Figure 1C). Individuals born with OFC may have their first surgical repair at age 3 months, but this initial surgery is just the beginning of a lifetime of health burdens. An individual born with an OFC has a hospital use rate increased for most ages (up to 233% increase for children ages 0-10 years and 16% for middle aged adults (Wehby et al. 2012). Healthcare costs for children with OFCs are estimated to be 800% greater compared with their unaffected peers (Boulet et al. 2009). Data from Denmark show that people born with CL with or without CP (CL/P) have an increased mortality up to age 55, which may be attributed to an increased risk of suicide and/or certain cancers (Christensen et al. 2004). The focus of most OFC genetic research has been CL and/or CP. Furthermore, the majority of OFC, i.e. about 70% of CL/P and 50% of CP is considered "nonsyndromic" (Jones 1988), i.e. isolated anomalies with no other apparent cognitive or structural abnormalities. Figure 1 Sample OFC Types A: Bilateral Cleft Lip; B:Cleft Lip plus Cleft Palate; C:Cleft Palate Alone The factors leading to the majority of nonsyndromic OFCs are still unclear, particularly at an individual family level. As is true for many complex traits, substantial progress in gene identification has occurred in the OFC field in the last two years (Dixon et al. 2011; Marazita 2012). Genome Wide Association Studies (GWAS) and sequencing studies to date by our research team and others have focused on genetic risk factors for overt CL/P and CPO-and have been very successful. A major finding from this work is that OFCs exhibit significant genetic heterogeneity, i.e., multiple genetic regions have been implicated (Beaty et al. 2010; Ludwig et al. 2012). Thus, approaches are needed to understand this genetic heterogeneity. Are there GxG interactions at work? Are there subsets of families, each due to a different gene? Our research group has shown that a promising approach to dissect the etiology of OFC is to focus on subclinical phenotypic features within entire cleft families (not just in affected cases, but also in their non-cleft relatives). These subtle features are believed to represent mild manifestations of the same underlying genetic susceptibility responsible for OFCs; as such, their inclusion in case-control and family-based genetic studies can help to clarify and refine the relationship between genotype and phenotype. The study population comprises a large number of families and individuals (~12,000 individuals) from multiple populations worldwide (Caucasians from the US and Europe, Asians from China and the Philippines, Mixed Native American/Caucasians from South America, and Africans from Nigeria and Ethiopia). There are cases, case families (nuclear families and extended kindreds), as well as controls with no history of OFC nor other developmental defects. *Berk NW, Marazita ML (2002) Costs of Cleft lip and Palate: Personal and Societal Implications. In: Wyszynski DF (ed) Cleft Lip and Palate: From Origin to Treatment. Oxford University Press, Inc., New York, pp 458-467.

  Study phs000774

• How to encrypt files with EGACryptor

  File preparation Due to the processes used at the EGA for file archival the use of non-alphanumeric characters in a filename will cause issues in archival. By convention whitespaces in filenames are to be avoided and should be replaced with the underscore character (_). Before encrypting your files please make sure that any files that will be uploaded to EGA do not use special characters such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | &  Crypt4gh EGACryptor Files encrypted with EGACryptor must be uploaded via FTP EGACryptor The EGACryptor v.2.0.0 is a JAVA-based application which enables submitters to produce EGA compliant encrypted files along with files for the encrypted and unencrypted md5sum for each file to be submitted. The application will generate an output folder that will by default mirror the directory structure containing the original files. This output folder can subsequently be uploaded to the EGA FTP staging area via an FTP or Aspera client. Download EgaCryptor Download EgaCryptor Using the EgaCryptor Using the EgaCryptor Encrypting single file Encrypting multiple files Encrypting all files in folder Points to note Troubleshooting Troubleshooting Download EGACryptor The required jar files can be obtained by downloading EgaCrytptor jar file After the file has been downloaded, extraction of the zipped archive is required. The EGACryptor has been built to work with Java Runtime Environments from version 6 and above and with the OpenJDK Environment. Please refer to the relevant resources for installation guidance. Installing the latest version of the OpenJDK will include the JCE files. If your installation of Java JRE is less than 1.8.0_151 will require the manual installation of the JCE Policy Files. You can verify the version of the Java SE Runtime Environment (JRE) installed by using the command: $ java -version If you need to install the JCE please follow the instructions below: Installing the JCE policy files (due to licensing terms and conditions the required policy files must be downloaded direct from the ORACLE website) : Download the unlimited strength JCE policy files (JRE 6 / JRE 7/ JRE 8) Uncompress and extract the downloaded file. This will create a subdirectory called JCE. This directory contains the following files: README.txt, COPYRIGHT.html, local_policy.jar and US_export_policy.jar Install the two policy JAR files by replacing the existing ones in your java home directory. Install the two policy JAR files by replacing the existing ones in your directory. The standard place for JCE jurisdiction policy JAR files is: /lib/security [Unix] or \lib\security [Win32] Notes: refers to the directory where the Java SE Runtime Environment (JRE) was installed. Additional performance enhancements that have been included in the EGACryptor V2.0.0: The ability to parallelise the processing of datasets through the use of the resources on a system. Multicore systems will allow the user to specify n-1 cores for an n-core system. The use of this feature on clusters may speed up the processing of datasets that have large file numbers but consult your local cluster guide to ensure that there are not monopolising resources that are needed by other system users. The default for this process remains single threaded. 3 levels of system usage can be specified. Full usage within the limits detailed above. A limited mode that will ensure that 50% of the system resources are available for other tasks. Maximum mode is limited to 75% of system resources, this allows encryption to be prioritised but allows for the system to be usable for light alternate tasks. Finally there is a throttling mode that allows you to specify the exact number of computational threads to be used. the EGACryptor is able to ingest a structured directory and will output a directory with the same structure containing the encrypted files along with the md5checksums for the plain and encrypted files. The entire output directory can then be uploaded to the EGA for archival. as with the input path, it is now possible to specify the output path. the options have been updated inline with the upgraded functionality. The tool can only be used via the command line. The EGACryptor is designed to perform a single task, encrypting your data, for upload of these files please refer to our uploading guide Using the EgaCryptor Below are the three ways on how the EGACryptor tool can be used: Encrypting a single file : java -jar ../EGA-Cryptor_2_0_0.jar -i example1.bam Encrypting multiple files : java -jar ../EGA-Cryptor_2_0_0.jar -i "example1.bam,example2.bam" Encrypting all the files within a folder java -jar ../EGA-Cryptor_2_0_0.jar -i path/to/target/directory By default the EGACryptor v2 will create a new output directory containing all encrypted files and the relevant checksums within the target directory. If a specific directory is desired this can be specified by using the -o flag. This can be achieved in a similar manner to the following example: java -jar ../EGA-Cryptor_2_0_0.jar -i /path/to/target/directory -o /path/to/output/directory The tool will output three files per input file: file.gpg ( encrypted file ) file.md5( file md5 sum value file ) file.gpg.md5 ( encrypted file md5 sum value file ) All output files must then be uploaded to your submission account using Aspera or FTP. Further documentation on how to upload files: FTP and Aspera. Points to note Remember to provide the path to EgaCryptor.jar and run the command from within the directory the file/s are located. ECryptor writes files to the source directory of your local file system, as a result you must have write-access permissions for the source directory. Troubleshooting If in doubt about the function of the EGACryptor it is recommended to first consult the built-in documentation. This can be accessessed by using the -h flag as stated in the following table. Built-in Commands Table: list of the command line options built into EGA-Cryptor v2.0.0. Command line Option Action --------------------- ----------- -f Set this option to allow application to create maximum threads to utilise full capacity of cores/processors available on machine -h Use this option to view the bult-in help menu * -i File(s) to encrypt. Provide file/folder path or comma separated file path if multiple files in double quotes -l Set this option to allow application to create maximum threads equals to 50% capacity of cores/processors available on machine -m Set this option to allow application to create maximum threads equals to 75% capacity of cores/processors available on machine -o Path of the output file. This is optional. If not provided then output files will be generated in the same path as that of source file (default: output- files) -t Set this option if user wants to control application to create maximum threads as specified. Application will calculate no. of cores/processors available on machine & will create threads accordingly Encryption Errors UnixFileSystem.createFileExclusively (Native Method) The error is thrown by UNIX ("UnixFileSystem.createFileExclusively(Native Method)"). It appears that the user does not have write-access to the file system where the file to be uploaded is located. EGACryptor always writes MD5 checksums into files before uploading them to the server, and these files are created in the same location where the uploaded file itself resides.Solution: address your directory permission issue and re-run the command. Install JCE Unlimited Strength Jurisdiction Policy files The JCE policy unlimited strength jurisdiction files should be installed according to your current java version If you are still facing difficulty with the EGACryptor v.2 after having consulted the documentation please contact the EGA Helpdesk.

  Documentation submission/data/file-preparation/egacryptor

• The Nordic Centre of Excellence Programme in Molecular Medicine Data Access Committee

  Dac EGAC00000000006

• Expression-Based Subtypes Define Pathologic Response to Neoadjuvant Immune-Checkpoint Inhibitors in Muscle-Invasive Bladder Cancer

  Dac EGAC00001002276