14982 results for "cancer studies using rna-seq"

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• Enhancer profiling to identify identifies epigenetic markers of endocrine resistance in metastatic castration resistant prostate cancer patients

  ChIP-seq and matched input data of AR, FOXA1 and H3K27ac for mCRPC patient samples taken prior to and after treatment with AR targeted therapy

  Dataset EGAD00001008688

• The dataset for Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  The dataset for “Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers” includes 409 cram files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD50000000695

• Molecular Sub-grouping of CNS-PNET

  In our study we aimed to define CNS-PNET subgroups. We performed Expression, Genotyping and/or Immunohistochemistry on 142 samples from 20 worldwide centers. Using these techniques, we have identified three molecular subgroups with distinct expression and copy number patterns, as well as, unique clinical characteristics. Specifically, these molecular subgroups were distinguished by primitive neural (group 1), oligoneural (group 2), and mesenchymal lineage (group 3) gene-expression signatures with differential expression of cell-lineage markers LIN28 and OLIG2. Our report underscores the importance of concerted, collaborative efforts to study large retrospective cohorts of tumours and patients to accelerate biological and ultimately therapeutic studies of rare tumours. The outcome of such a collaboration allowed us to identify LIN28 and OLIG2 as promising diagnostic and prognostic molecular markers for CNS PNET that warrant further assessment in prospective clinical trials.

  Study EGAS00000000116

• RNAseq Transcriptomic Analyses of European Ancestry Samples in MGS Dataset

  Schizophrenia is a common and severe psychotic disorder. While some common SNPs and rare copy number variants have been identified as being significantly associated with disease risk, the biological mechanisms remain undefined. To identify gene expression abnormalities in schizophrenia, we generated whole-genome gene expression profiles using RNAseq on lymphoblastoid cell lines from schizophrenia cases and controls of European ancestry. Subsets of these data have been used in three studies: (1) gene expression outliers (extreme tails of the distribution of transcript expression values) in 634 cases and 713 controls (PMID: 26022996); (2) baseline differential gene expression by affection status in 529 cases and 660 controls (PMID: 28418402); and (3) baseline versus dopamine stimulated differential gene expression by affection status in 514 cases and 690 controls (PMID: 30115913). Various classes of classes were enriched in the differentially expressed genes, especially brain expressed genes and genes related to immune processes.

  Study phs001932

• CRISPR-Mediated ASD Gene Knockout Reduces Neuronal Activity

  Autism Spectrum Disorder is phenotypically and genetically heterogeneous. We present a CRISPR gene editing strategy to insert a protein tag and premature termination sites creating an induced pluripotent stem cell (iPSC) knockout resource for functional studies of 10 ASD-relevant genes (AFF2/FMR2, ANOS1, ASTN2, ATRX, CACNA1C, CHD8, DLGAP2, KCNQ2, SCN2A, TENM1). Neurogenin 2 (NGN2)-directed induction of iPSCs allowed production of excitatory neurons, and mutant proteins were not detectable. RNAseq revealed convergence of several neuronal networks. Using both patch-clamp and multi-electrode array approaches, the electrophysiological deficits measured were distinct for different mutations. However, they culminated in a consistent reduction in synaptic activity, including reduced spontaneous excitatory post-synaptic current frequencies in AFF2/FMR2-, ASTN2-, ATRX-, KCNQ2- and SCN2A-null neurons. Despite ASD susceptibility genes belonging to different gene ontologies, isogenic stem cell resources can reveal common functional phenotypes, such as reduced functional connectivity.

  Study phs001816

• The Surveillance Monitoring for ART Toxicities (SMARTT) and the Women and Infants Transmission Study (WITS)

  Zidovudine (ZDV) is a nucleoside reverse transcriptase inhibitor (NRTI) which competitively inhibits HIV reverse transcriptase and is incorporated into the viral DNA, resulting in DNA chain termination. It was the first approved antiretroviral medication used for preventing HIV transmission from mother to child. However, in vitro and animal studies have suggested genotoxicity of ZDV and no study has evaluated potential impact of in utero ZDV exposure using genomic sequencing technologies. In this study, we investigate markers of genomic damage detected in peripheral blood mononuclear cell samples obtained from 91 ZDV-exposed and, for comparison, 94 NRTI-unexposed HIV-uninfected children born to HIV-infected mothers during the first week after birth. We utilize high-throughput DNA sequencing (whole exome sequencing) and genotype array methods to comprehensively identify potential clonal somatic single nucleotide variants (SNVs) and large acquired copy number alterations (SCNAs) related to ZDV exposure.

  Study phs002061

• NHLBI TOPMed: Stanford Cardiovascular Institute iPSC Biobank Study (SCVI)

  The proposed Stanford Cardiovascular Institute (SCVI) Biorepository will curate and manage an expanded collection of human induced pluripotent stem cell (iPSC) lines and provide investigators with iPSC materials generated using standardized protocols, with the overall objective of promoting the continued adoption and development of iPSC technology in cardiovascular research. Human iPSCs have revolutionized disease modeling, drug screening, and therapeutic research. However, it is also recognized that the need for specialized technical expertise and the associated cost have largely prevented individual research laboratories from adopting iPSC models in their inquiries, particularly in studies requiring multiple cell lines. To address this bottleneck, the proposed Biorepository will maintain our existing collection of iPSC lines and further expand the collection of iPSCs by recruiting 1,000 healthy, hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM) donors of both sexes and diverse racial/ethnic backgrounds (African Americans, Asians, Hispanics, and Whites).

  Study phs002338

• Genetic landscape of inherited retinal dystrophies affected cases in Spain

  Inherited retinal diseases (IRDs), defined by dysfunction or progressive loss of photoreceptors, are disorders characterized by elevated heterogeneity, both at the clinical and genetic levels. Our main goal was to address the genetic landscape of IRD in a Spanish cohort of patients. A retrospective hospital-based cross-sectional study was carried out on IRD affected individuals, referred for genetic testing from all the Spanish autonomous communities. Clinical, demographic and familiar data were collected from each patient, including family pedigree, age of appearance of visual symptoms, presence of any systemic findings and geographical origin. Genetic studies were performed to all families with available DNA using different molecular techniques. Our study provides the general landscape for IRD in Spain and our results have important implications for genetic diagnosis, counselling and new therapeutic strategies to both the Spanish population and other related populations.

  Study EGAS00001005104

• mUM patient biopsies bulk RNAseq

  Tumour biopsies were obtained from uveal melanoma patients (n = 35) pre and 16 days post treatment with tebentafusp. Biopsies, which were either snap frozen or put in RNA later, were analysed by bulk RNA sequencing (50 million reads per sample) using the Illumina NovaSeq system

  Dataset EGAD50000001225

• DNA WGS Long Read Sequence (PromethION) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"

  DNA WGS Long Read Sequence (PromethION) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"

  Dataset EGAD00001015400

• M116 scRNA-seq

  scRNA-seq was performed using Chromium Next GEM Single Cell 3’ Kit v3.1 (10X Genomics) according to the manufacturer’s instructions. Briefly, M116's PBMCs were thawed and quantified in order to calculate the number of cells to be loaded. Then, barcoded Single Cell 3ʹ Gel Beads, a master mix containing PBMCs, and Partitioning Oil were combined onto the Chromium Next GEM Chip G to generate Gel Beads-In-Emulsion (GEMs), where polyadenylated mRNAs were reverse transcribed. This way, all generated cDNAs from the same cell shared a common 10X Barcode. Following the reverse transcription, GEMs were broken and cDNAs were amplified and cleaned up with SPRIselect beads (Beckman Coulter®). Next, a portion of these cDNAs were enzymatically fragmented and subjected to adaptor ligation before using them as a PCR template for the incorporation of i5/i7 indexes. Finally, libraries were purified with SPRIselect beads, quantified and quality checked by using the 2200 TapeStation (Agilent®), and subjected to paired-end 150-bp sequencing (Novaseq systems, Illumina®) following standard practices at external facilities (Novogene®). Files types included in this dataset are raw Fastq files.

  Dataset EGAD50000001289

• Targeted sequencing of breast cancer susceptibility genes for 1,995 Japanese breast cancer patients

  In this study, we investigated pathogenic germline variants in 11 genes implicated in hereditary breast cancer, including BRCA1, BRCA2, TP53, PTEN, CDH1, STK11, NF1, PALB2, ATM, CHEK2, NBN1, in a total of 1,995 unselected Japanese women with breast cancer using targeted-capture sequencing of pooled DNA (n = 106).

  Study EGAS00001004630

• Notch Signaling and Efficacy PD-1/PD-L1 Blockade in Relapsed Small Cell Lung Cancer

  Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine (NE) cancer that accounts for approximately 15% of all lung cancer, with an annual incidence of more than 34,000 in the United States alone. SCLC is characterized by loss of function of p53 and RB and high tumor mutational burden, which suggests that these tumors could be immunogenic and respond to immune checkpoint blockade (ICB). However, the benefit from ICB in an unselected SCLC population is modest. In this study, we evaluated the genomic features associated with clinical outcomes in relapsed SCLC to gain insight into the underlying mechanisms of ICB response. Exome, RNA and TCR sequencing data from a prospective clinical trial of relapsed SCLC treated with durvalumab and olaparib and RNA-sequencing data for second cohort of relapsed SCLC cohort treated with nivolumab are included.   

  Study phs002176

• Childhood Cancer Data Initiative (CCDI): OncoKids - NGS Panel for Pediatric Malignancies

  This study aimed to systematically collect clinical, registry and genomic data on pediatric cancer patients, and to contribute to the CCDI Pediatric Data Ecosystem. Clinical, treatment and outcome data on 1,039 pediatric cancer patients whose molecular profile was characterized on OncoKids gene panel at Children's Hospital Los Angeles was abstracted and harmonized for submission to the NCI’s Cancer Data Service. The OncoKids panel was designed to detect DNA mutations and amplification in almost 200 oncogenes and tumor suppressor genes, a limited number of pharmacogenomic targets and 1,700 disease-associated gene fusions at the RNA level. The panel encompasses the vast majority of FDA’s relevant pediatric molecular target list, as well as additional genes associated with ultra-rare pediatric tumors. The final data elements included DNA/RNA sequence data, OncoKids test results, clinical data on demographics, diagnosis, comorbidity and adverse events and treatment data.

  Study phs002518

• Ongoing_mutagenesis_RNAseq

  One of the key questions to be explored is whether the biological processes generating specific mutational signatures continue to operate in the human cancer cell lines or simply reflect past mutagenic activity which is no longer operative. To address this question, we have extracted mutational signatures from 1,000 cancer cell lines of diverse cancer types. Several cell lines with mutational signatures of interest were selected, subcloned over a defined period of time and their genomes sequenced. The increased load of the mutations representative of a specific mutational signature within the genome of a subclone when compared to its parental clone was informative of the on-going mutational processes. To further study the recent observation that some of the clones belonging to a same cell line acquired differencet numbers of mutations over a set period of time, their RNA will be subjected to RNA-sequencing to study their differences.

  Study EGAS00001002364

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Oesophageal_squamous_cell_carcinoma

  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 (Illumina HiSeqX, 40X and 20X depth respectively). 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.

  Study EGAS00001002725

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__pancreas

  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 (Illumina HiSeqX, 40X and 20X depth respectively). 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.

  Study EGAS00001002726

• Validated Single-cell RNA sequencing in early breast cancer

  Single-cell RNA and VDJ sequencing of early breast cancer

  Dataset EGAD00001006608

• 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

• Hepatitis B virus integrations promote local and distant oncogenic driver alterations in hepatocarcinogenesis

  This study contain the WGS and WEX aligned bam files and RNA-seq fastq files for human liver tumors.

  Dataset EGAD00001006426

• SARS-CoV2 mRNA-vaccination-induced Immunological Memory in Human Non-Lymphoid and Lymphoid Tissues

  This dataset includes combined single-cell RNA-Seq and T cell receptor profiling data for SARS-CoV-2 spike protein-reactive CD4+ T cells and NK cells from blood, liver, lungs, and bone marrow of human donors.

  Dataset EGAD50000000062

• Oxidative DNA damage and ubiquitin proteasome system dysfunction underpins neurodegeneration in young adults with a DNA repair disorder

  Deposited here are time series bulk RNA-seq data generated from XP patients and controls as well as rescued patient hiPSC cells during cortical neuronal differentiation.

  Dataset EGAD50000000230

• Oxidative DNA damage and ubiquitin proteasome system dysfunction underpins neurodegeneration in young adults with a DNA repair disorder

  Deposited here are time series bulk RNA-seq data generated from isogenic wild-type (WT), XPA and XPG gene knockouts hiPSC cells during cortical neuronal differentiation.

  Dataset EGAD50000000228

• Tumor Profiler Project - AML scRNA data

  The dataset contains single-cell RNA seq data from 23 patients with Acute Myeloid Leukemia (AML). Samples were collected from bone marrow or blood. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format.

  Dataset EGAD50000000823

• DAC for "Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas"

  This DAC will be created for sequencing data for the manuscript "Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas." The dataset includes Illumina-based exome sequencing of tumor specimens, paired blood specimens, bulk RNA-seq, and Visium FFPE.

  Dac EGAC50000000579