14983 results for "cancer studies using rna-seq"

in 25.87 milliseconds.

• ctDNA multigenic panel for non-small cell lung cancer

  Detection of actionable mutations in liquid biopsies constitute an important tool for management of non-small cell lung cancer (NSCLC) patients in the era of oncology precision medicine. We aimed to evaluate the actionable alterations using a commercial multi-gene panel in circulating tumor DNA (ctDNA) derived from plasma samples of treatment naïve and prior-treated non-small cell lung cancer (NSCLC) patients. For this, we analyze plasma samples of 30 subjects with non-small cell lung cancer.

  Study EGAS50000000643

• Whole exome and Transcriptome sequencing of treatment-naïve esophageal adenocarcinoma biopsies and matched peripheral blood mononuclear cells

  Exome sequencing was performed on n=28 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. WES was performed on EAC biopsies at 120X average coverage, with autologous PBMCs used as germline controls at 80X average coverage. Libraries were prepared from 30 ng of input DNA using the SureSelect QXT Human All Exon V7 kit (Agilent Technologies) and sequenced on the NextSeq 550 (Illumina), 2x150 bp. BCL files were demultiplexed to FastQ files using bcl2fastq2 software (Illumina). Three paired end sequencing batches were analyzed independently (Batch1: samples 8, 10, 11, 12, 15, 17, 18; Batch2: samples 20, 24, 25, 26, 27, 29, 30, 31, 33, 34 ; Batch3: samples 35, 37, 39, 40, 41, 43, 45, 48, 54, 55, 57). RNA sequencing was performed on n=26 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. RNAseq libraries were prepared on 50 ng of total RNA (with RNA integrity index RIN >=7) with the TruSeq Stranded mRNA library preparation kit (Illumina) in accordance with low-throughput protocol. After PCR enrichment (15 cycles) and purification of adapter-ligated fragments, the concentration and length of DNA fragments were measured using D1000 Screen Tape System (Agilent), obtaining a median insert size of 311 nucleotides. Then, RNAseq libraries were sequenced using the Illumina NovaSeq platform, 1x100 bp, obtaining on average 100 million single reads per sample.

  Dataset EGAD00001010876

• Whole exome sequencing of papillary thyroid carcinoma in the Chinese population

  Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Here we submitted the sequencing results for PTC using 91 tumor-normal pairs through exome sequencing in the Chinese Han population.

  Study EGAS00001001268

• DAC for Studies of "Genetics and Genomics of Cardiovascular Diseases" Group at MDC Berlin, Germany

  DAC for Studies of "Genetics and Genomics of Cardiovascular Diseases" Group at MDC Berlin This is an umbrella DAC.

  Dac EGAC50000000481

• Targeted replication of LVOTO genes

  Non-syndromic cases of congenital heart defects (CHD) exhibit variable modes of inheritance (Mendelian and non-Mendelian). Several studies have identified strong candidates in humans by taking a candidate gene approach as well as by using whole exome next generation sequencing (NGS). So far these studies could only explain a minor fraction of the observed phenotype in humans, most of them in syndromic cases and no single study has focused on the subset of cases with left ventricular outflow tract obstruction (LVOTO). To discover novel disease-causing genes a large cohort of patients with LVOTO, approximately 100 cases, 25 families and 100 trios have been exome sequenced. This study based on NGS sequencing data yielded several known and novel compelling candidate genes, such as MYH6, NR2F2 and MYH11, but also novel ones, such as ITGB4. To evaluate the significance of our findings in a replication cohort we assembled another 1614 cases with an LVOTO phenotype from our collaborators in Toronto, Berlin and Amsterdam. Targeted resequencing in this additional cohort will help to find additional cases with mutations in the identified candidate genes to strengthen genotype-phenotype association. We will use control data from the INTERVAL project for case/control analyses The pulldowns will be performed as 24-plex ISC with 192 or greater indexes, and the sequencing will be performed with 192 samples per lane, requiring 9 lanes of sequencing.

  Dataset EGAD00001002212

• Using human induced pluripotent stem cell-derived oligodendrocytes to explore cellular phenotypes associated with t(1;11) translocation.

  Although the underlying neurobiology of major mental illness (MMI) remains unknown, emerging evidence implicates a role for oligodendrocyte-myelin abnormalities. Here, we took advantage of a large family carrying a balanced t(1;11) translocation, which substantially increases risk of MMI, to undertake both diffusion tensor imaging (DTI) and cellular studies to evaluate the consequences of the t(1;11) translocation on white matter structural integrity and oligodendrocyte-myelin biology (this translocation disrupts among others the DISC1 gene which plays a crucial role in brain development). At a cellular level, we observe dysregulation of key pathways controlling oligodendrocyte development and morphogenesis in induced pluripotent stem cell (iPSC) case derived oligodendrocytes.

  Study EGAS00001004595

• RNA sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001000285

• Dataset for head_and_neck_cancer-EXON

  Rare cancer sequencing data of 86 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008880

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Kidney (1)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Dataset EGAD00001006427

• Single-cell RNA sequencing of blood immune cells before and after interleukin-2 immunotherapy

  Single-cell RNA sequencing of flow cytometry sorted human CD45+ immune cells from 3 systemic lupus erythematosus patients (SLE_002, SLE_004, and SLE_006) collected at baseline (day 0, before interleukin-2 immunotherpay) and day 5 (after 1 treatment cycle of interleukin-2 immunotherapy). Sorted immune cells were hash tagged and then stained with TotalSeq Human Universal Cocktail (Biolegend) before further processing for single-cell RNA sequencing using the 10X-Genomics platform. Samples from all 3 patients were pooled and loaded on 3 lanes of the chromium controller, resulting in 1 raw sequncing file for each lane.

  Dataset EGAD50000000662

• ATAC-Seq of CD4 T cell subsets

  Blood samples were taken from 4 age-matched healthy volunteers (two males and two females), and naïve CD4 T cells were isolated using the naïve CD4+ T Cell Isolation Kit II, human (Miltenyi Biotec). Two hundred thousand cells were plated in a 96-well plate, activated with Dynabeads Human T-activator CD3/CD28 (bead-to-cell ratio of 1:1, as recommended by the manufacturer) (ThermoFisher Scientific) and polarized towards CD4 T cell subtypes (Teff, Th1, Th2, rTh17, pTh17, and Treg cells) with specific cocktails of recombinant cytokines and neutralizing antibodies (see details in the material and methods) for each subset. At day 4 post-stimulation, forty thousand cells were used to perform ATAC-Seq on CD4 T cell subtypes. Again, crude nuclei of live CD4+ T cell subsets were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry.

  Study EGAS00001007345

• Unraveling the transcriptomic profile of utero-tubal lavage fluid of ovarian cancer patients

  mRNA capture seq of uterotubal lavage samples

  Dataset EGAD00001007933

• HGSOC-celllines-SmartSeq3

  Smart-seq3 scRNA-seq of cells from primary (OV2295) and metastatic (OV2295R2) high-grade serous ovarian cancer cell-line

  Dataset EGAD00001009798

• Chordoma_Sequencing_Project_RNAseq

  This is a continuation of the Chordoma Sequencing Project. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. RNA Sequencing/Methylation and SNP6 and an additional sequencing of three cancer cell lines will be added to this work.

  Study EGAS00001000410

• To profile the landscape of sebaceous tumours_RNAseq

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract RNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted RNA will be used for RNA sequencing.

  Dataset EGAD00001015368

• Gene-Environment Interactions in COCCaINE Use Disorder: Collaborative Case-Control Initiative in Cocaine Addiction

  Drug addiction is a phenotype that has high heritability estimates. In recent years, association studies of candidate genes and some genome-wide association studies (GWAS) have identified a large number of SNPs associated with substance use, abuse or dependence, particularly in phenotypes related to alcohol and nicotine use. Regarding snorted or smoked cocaine dependency, only one GWAS has been conducted so far. In addition, genetic association studies that specifically evaluated smoked cocaine dependence (e.g. crack) are rare, because of characteristics related to the route of administration and duration of the effect of the drug. Thus, the main aim of this GWAS was to identify genetic variations that modulate the risk for the cocaine dependence.

  Study phs001810

• Neurogenetic Investigations of Obsessive-Compulsive Disorder

  Obsessive-compulsive disorder (OCD) is a disabling early-onset neuropsychiatric disorder with a clear genetic contribution to risk but unclear underlying pathophysiology, which has hindered the development of new treatments and interventions. This study uses high-throughput sequencing approaches to identify OCD risk genes, detect gene expression differences in OCD, and determine epigenetic signatures driving gene expression in OCD brain. These studies will improve our understanding of the underlying mechanisms of OCD and identify points of traction for mechanistic studies in model systems, ultimately leading to novel therapeutics, and reducing the significant morbidity and mortality associated with this disabling illness. Furthermore, insights gained in these studies can inform gene discovery approaches to other complex neuropsychiatric disorders.

  Study phs001929

• Sweden-Schizophrenia Population-Based Case-Control Exome Sequencing

  Current findings of the genetic risk of schizophrenia and bipolar disorder emerging from genome wide association studies (GWAS) support a highly polygenic model displaying the full spectrum of causal alleles that includes the extremes of rare, penetrant alleles as well as common alleles of small effect. Lower frequency polymorphism, rare variants and private mutations have eluded measurement by GWAS studies and thus association with disease. In order to create a comprehensive catalogue of low frequency or rare coding variation in individuals with psychiatric disease and to build a foundation for future genetic studies of schizophrenia and bipolar disorder, we have obtained whole exome DNA sequence from a population-based schizophrenia and bipolar disorder Swedish case-control cohort.

  Study phs000473

• T2D-GENES Project 2: San Antonio Mexican American Family Studies

  The Type 2 Diabetes (T2D) Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) Consortium is a collaborative international effort to identify genes influencing susceptibility to T2D in multiple ethnic groups using next generation sequencing. T2D-GENES Project 2 is a complex pedigree-based study designed to identify low frequency or rare variants influencing susceptibility to T2D, using whole genome sequence (WGS) information from 1,043 individuals in 20 Mexican American T2D-enriched pedigrees from San Antonio, Texas. The major objectives of this study are to identify low frequency or rare variants in and around known common variant signals for T2D, as well as to find novel low frequency or rare variants influencing susceptibility to T2D. The sampled individuals are obtained from two studies: the San Antonio Family Heart Study (SAFHS) and the San Antonio Family Diabetes/Gallbladder Study (SAFDGS), collectively referred to as the San Antonio Mexican American Family Studies (SAMAFS). The strategy is to sequence approximately 600 individuals at an average of 50x coverage across the entire genome, then impute genome wide genotypes for about 440 additional family members. The 600 sequenced individuals are specifically chosen for their value in imputing sequence information into other family members. By studying large pedigrees, we expect to find multiple individuals carrying each genetic variant, even if this variant is very rare in the population at large. Thus, a pedigree-based approach provides an excellent opportunity for identifying rare novel variants influencing risk of T2D and quantitative variation in T2D-related phenotypes. The whole genome sequencing has been done commercially by Complete Genomics, Inc. (CGI). The final data set includes whole genome sequence data for 607 individuals. After quality control, 585 sequenced individuals provide data for family based imputation, using Merlin linkage analysis software, into approximately 440 additional family members for whom chip based genotypes are available to indicate which parental haplotype is transmitted. Extensive phenotype data is provided for 1048 individuals. These include 5 sequenced individuals who do not belong to any of the 20 large pedigrees. Phenotype information was collected between 1991 and 2011 in the two contributing longitudinal studies. SAFHS participants may have information from up to 5 visits, and SAFDGS participants may have up to 4 visits. The clinical variables reported are coordinated with T2D-GENES Project 1 (multi-ethnic exome sequencing) and include T2D status and age at diagnosis, glycemic traits (fasting and 2 hour glucose and insulin), blood pressure, blood lipids (total cholesterol, HDL cholesterol, calculated LDL cholesterol and triglycerides), clinical chemistry (cystatin c, glutamic acid decarboxylase antibody titer (GadAb), creatinine, adiponectin and leptin). Glycated hemoglobin (HbA1c) was not measured for these individuals and insulin C-peptide is not included in this data set. Additional phenotype data include the medication status at each visit, classified in four categories as any current use of diabetes, hypertension or lipid-lowering medications, and, for females, current use of female hormones. Anthropometric measurements include age, sex, height, weight, hip circumference, waist circumference and derived ratios. Each phenotype variable has an initial summary column containing the most recent non-missing measurement for each individual, followed by the five potential time points for each individual, the number of non-missing measurements, and the age and year for the most recent non-missing measurement. For historical reasons, the order in which variables are presented on the dbGaP web site differs from their order in the data download file. When reading the comment fields for each variable, please note that commas are omitted to support data exchange in .csv format.

  Study phs000462