14982 results for "cancer studies using rna-seq"

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• Total RNA sequencing from the TNT trial (NCT00532727)

  Primary tumours from 186 TNT participants (13 matched recurrences) were profiled using total RNA-sequencing. Four transcriptional DDR-related and 25 immune-related signatures were evaluated. We assessed their association with objective-response-rate (ORR) and progression-free-survival (PFS) and performed conditional inference forest clustering to integrate multi-modal data.

  Study EGAS00001007398

• Single-cell profiling of co-cultures of GSCCs and macrophages

  This dataset contains scRNA-seq data from 8 co-cultures of GSCCs and macrophages, and 1 monoculture of macrophages. Samples were individually labeled and pooled using MULTI-seq technology and processed with 10x Genomics Technology.

  Dataset EGAD00001011275

• WGS and WTS data of patient diagnosed with HSTCL

  WGS and WTS data of a single patient diagnosed with HSTCL. Whole-genome sequencing (WGS) was performed for the tumor-normal sample. Genomic DNA from tumor tissue was extracted with QIAamp DNA Mini Kit. The DNA for the matching normal was obtained from blood or buccal swabs and purified by Blood and Cell Culture DNA Mini kit or E.Z.N.A. Tissue DNA Kit (Omega Bio-tek) according to manufacturer’s instructions. The quantity and quality were assessed by Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen) and agarose gel electrophoresis. All sequencing libraries were prepared using TruSeq Nano DNA Library Prep Kit (Illumina). Paired-end sequencing was performed on Illumina HiSeq 4000 2x151 bp read length. Whole-transcriptome sequencing (WTS): Total RNA from snap frozen EITL tumor samples was extracted using TRIzol (Invitrogen) and purified with RNeasy Mini Kit (Qiagen) according to manufacturer’s instructions. The integrity of RNA was determined by electrophoresis using 2100 Bioanalyzer (Agilent Technologies). 500 ng of total RNA was reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). Quantification was performed using SsoFast EvaGreen Supermix and CFX96 Real-Time PCR System (both Bio-Rad). Sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero (Illumina) and WTS was performed on Illumina HiSeq 2500 with 2x101 bp read length.

  Dataset EGAD00001005229

• The Environmental Determinants of Diabetes in the Young Study (TEDDY)

  Study Overview The Environmental Determinants of Diabetes in the Young (TEDDY) Study is a longitudinal study that investigates genetic and genetic-environmental interactions, including gestational events, childhood infections, dietary exposures, and other environmental factors after birth, in relation to the development of islet autoimmunity and type 1 diabetes (T1D). A consortium of six clinical centers assembled to participate in the development and implementation of the study to identify environmental triggers for the development of islet autoimmunity and T1D in genetically susceptible individuals. Beginning in 2004, the TEDDY study screened over 400,000 newborns for high-risk HLA-DR, DQ genotypes from both the general population and families already affected by T1D. The TEDDY study enrolled around 8,676 participants across six clinical centers worldwide (Finland, Germany, Sweden and three in the United States) in the 15-year prospective follow-up. Participants are followed every three months for islet autoantibody (IA) measurements with blood sampling until four years of age and then at least every six months until the age of 15. After the age of four, autoantibody positive participants continue to be followed at three month intervals and autoantibody negative participants are followed at six-month intervals. In addition to the analysis of autoantibodies, additional data and sample collection are performed at each visit. Parents collect monthly stool samples in early childhood. The parents also fill out questionnaires at regular intervals in connection with study visits and record information about diet and health status in the child's TEDDY Book between visits. Continued long-term follow-up of the currently active TEDDY participants will provide important scientific information on early childhood diet, reported and measured infections, vaccinations, and psychosocial stressors that may contribute to the development of type 1 diabetes and islet autoimmunity. Additional information on the TEDDY study is available in the following articles: Rewers et al., 2008, PMID: 19120261 and Hagopian et al., 2006, PMID: 17130573. Details of the TEDDY protocol can be found in Hagopian et al., 2011, PMID: 21564455. TEDDY data currently available in dbGaP include: gene expression, SNPs, exome, microbiome (gut, nasal, and plasma), RNA sequencing, and whole genome sequencing. For more information on TEDDY Study version history please refer to TEDDY Study dbGaP README File. ImmunoChip SNP DNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for SNP genotyping. Genotyping was performed by the Center for Public Health Genomics at the University of Virginia using the Illumina ImmunoChip SNP array, which contains around 196,000 SNPs from 186 regions associated with 12 autoimmune diseases (Hadley et al., 2015, PMID: 26010309). Data cleaning and validation included the removal of subjects with a low call rate (< 5% SNPs missing) and differences in reported sex and prior genotyping at the TEDDY HLA laboratory. Additionally, SNPs with a low call rate or Hardy-Weinberg equilibrium P value < 10-6, except for chromosome 6 due to HLA eligibility requirements, were removed from the final dataset (Törn et al., 2015, PMID: 25422107).TEDDY-T1DExome ArrayDNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for genotyping. Genotyping was performed by the University of Virginia using the Illumina TEDDY-T1DExome array. The TEDDY-T1DExome array is a custom chip that contains 550,601 markers from the Infinium CoreExome-24 v1.1 BeadChip and an additional 90,214 tagSNPs specifically selected by the TEDDY investigators based on their associations with nutrients, vitamins, type 2 diabetes, autoimmune diseases, body-mass index, or other exposures and phenotypes measured by TEDDY study.The Illumina GenTrain2 algorithm was used for genotype calling. Sample quality control metrics included sample call rate, heterozygosity rate and concordance of gender between the information reported and genotyped. Gene Expression The TEDDY study collected peripheral blood for the extraction of total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA (200 ng) was further used for cRNA amplification and labeling with biotin using Target Amp cDNA synthesis kit (Epicenter catalog no. TAB1R6924). Labeled cRNA was hybridized to the Illumina HumanHT-12 Expression BeadChips based on the manufacturer's instructions. The HumanHT-12 Expression BeadChip provides coverage for more than 47,000 transcripts and known splice variants across the human transcriptome. Microbiome The TEDDY microbiome study aimed to characterize the longitudinal development of the microbiome, including bacteria, viruses and other microorganisms in the gut, plasma, and nasal cavity of prediabetic and diabetic subjects compared to autoantibody negative non-diabetic subjects. Stool samples used were collected monthly from 3 to 48 months, after which stool samples were collected every 3 months. Nasal swab samples were collected every 3 months starting at 9 months of age until 48 months, after which nasal swabs were collected every 6 months. Plasma samples were collected every 3 months starting at 3 months of age until 48 months, after which plasma samples were collected every 6 months. If the subject was autoantibody positive at 48 months then they remained on the 3 month collection interval for nasal swab and plasma samples. Samples underwent 16s rRNA gene sequencing, DNA and viral RNA metagenomics shotgun sequencing, and sequencing of the internal transcribed spacer (ITS) regions. Additional information on the TEDDY microbiome data is available in the following articles: Vatanen et al., 2018, PMID: 30356183, Stewart et al., 2018, PMID: 30356187, and Vehik et al., 2020, PMID: 31792456. RNA Sequencing The TEDDY study aimed to characterize the transcriptome in subjects with islet autoimmunity and type 1 diabetes compared to matched control subjects. Peripheral blood was collected to extract total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA was then sent to the Broad Institute for the generation of the TEDDY RNA sequencing (RNA-Seq) data. The RNA samples were prepped using Superscript III reverse transcriptase and Illumina's TruSeq Stranded mRNA Sample Prep Kit. The TruSeq libraries were run on the Illumina HiSeq2500 platform. Whole Genome Sequencing The TEDDY study aimed to conduct deep whole genome sequencing and examine the genomic variations in subjects with islet autoimmunity and type 1 diabetes compared to matched autoantibody negative and non-diabetic children. DNA from whole blood was obtained from TEDDY children for whole genome sequencing. The WGS data were generated on the Illumina HiSeq X Ten system.

  Study phs001442

• Pathogenic Neurofibromatosis type 1 (NF1) RNA splicing resolved by targeted RNAseq

  Neurofibromatosis type 1 (NF1) is caused by loss-of-function variants in the NF1 gene. Approximately 10% of these variants affect RNA splicing and are either missed by conventional DNA diagnostics or are misinterpreted by in silico splicing predictions. Therefore, a targeted RNAseq-based approach was designed to detect pathogenic RNA splicing and associated pathogenic DNA variants. an in-house developed tool (QURNAS) was used to calculate the enrichment score (ERS) for each splicing event. RNA enrichment of NF1 and SPRED1 was done using SPET (NUGEN - NF1 only) and using SureSelect (Agilent - NF1 and SPRED1).

  Dataset EGAD00001007978

• Transcriptome analysis of kidney organoids lacking NPHP1gene

  To explore the molecular mechanisms of cyst formation in kidney organoids lacking NPHP1, we performed RNA-seq transcriptome experiments. Because the potential for cyst formation by suspension culture should already be derived from kidney organoids at the adherent culture, we compared the global gene expression pattern of kidney organoids on day 18 between healthy group and NPHP1-deficient group

  Study JGAS000683

• RNA-seq data of proliferative vitreoretinal diseases and healthy human retinal pigment epithelium

  This Data Access Committee (DAC) evaluates access requests for RNA-seq data generated from: - Membranes from proliferative vitreoretinal diseases, including proliferative vitreoretinopathy and epiretinal membranes. - Retinal pigment epithelial cells isolated from healthy ocular globes obtained from deceased donors. Collection and analysis of these residual human materials were conducted with the approval of the ULB-Erasme Ethical Committee (P2019/066 A2022/136) and of the Eye Bank (CHU Liège), with no need for informed consent in compliance with Belgian law. All data are pseudonymised, and access is restricted to qualified researchers whose proposed use of the data is consistent with the applicable ethical approval and legal requirements, including the General Data Protection Regulation (GDPR).

  Dac EGAC50000000721

• RNA-Seq data of hepatoma (Huh7 derived) and Ph5CH cells and primary hepatocytes

  The innate immune response of cells of hepatic origin (Huh7, Huh7.5, PH5CH and primary human hepatocytes (PHH), 66 samples) was analyzed by transcriptome analysis (RNAseq) upon supernatant delivery or transfection of synthetic dsRNA (poly(I:C)). Expression of TLR3 and RIG-I was reconstituted by lentiviral transduction in Huh7 and Huh7.5 cells. The sequencing is single RNA-Seq on an Illumina HiSeq 4000 with the Illumina TruSeq stranded mRNA kit.

  Dataset EGAD00001007083

• RNA-Seq data for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  RNA-Seq data for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  Dataset EGAD00001003433

• Multi-omic dataset of neuroendocrine neoplasm organoids

  This dataset corresponds to one of the first biobanks for the understudied neuroendocrine neoplasms from multiple grades and body sites (lung, pancreas, small intestine). It contains whole-genome sequencing data for original tumors, patient-derived tumor organoids at multiple passages, and matched normal tissue, and RNA-seq data for the original tumor and patient-derived tumor organoids.

  Study EGAS00001005752

• 28 RNA-Seq from CAF-S1, CAF-S4 and EPCAM cells coming from Primary tumors and Lymph nodes of 5 patients)

  Dataset EGAD00001005744

• RNAseq RPKM

  RNA-seq data from ILC samples. This dataset includes counts normalized for sequencing depth and gene length.

  Dataset EGAD50000000828

• scRNA primaries

  Single cell RNA-seq for primary samples

  Dataset EGAD00001006135

• PACA-CA RNASeq fastq files

  Fastq files for PACA-CA RNA Seq analysis, for DCC release 27

  Dataset EGAD00001003972

• Covacta RNAseq merged EGA metadata

  Sample metadata for the RNA-seq dataset. This dataset includes subject-level data and longitudinal visit day information for the corresponding samples.

  Dataset EGAD00001011162

• ChIP-seq in colorectal cancer and paired adjacent normal mucosa

  Chip-seq samples for 20 colorectal patients with paired adjacent normal mucosa to characterize H3K27ac and H3K4me1.

  Study EGAS00001005303

• Glioma International Case Control Study (GICC)

  The main goals of the GICC Study were: 1) to identify novel genetic risk variants for glioma, as well as validate variants implicated by previous genome-wide association studies of glioma; and 2) to explore biologically relevant gene-gene and gene-environment interactions in glioma susceptibility. The GICC Study includes participants from the following centers: Brigham and Women's Hospital (Boston, Massachusetts), Case Western Reserve University (Cleveland, Ohio), Columbia University (New York, New York), the Danish Cancer Society Research Centre (Copenhagen, Denmark), Duke University (Durham, North Carolina), the University of Texas MD Anderson Cancer Center (Houston, Texas), Memorial Sloan Kettering Cancer Center (New York, New York), the Mayo Clinic (Rochester, Minnesota), NorthShore HealthSystem (Chicago, Illinois), Umea University (Umea, Sweden), the University of California, San Francisco (San Francisco, California), the University of Southern California (Los Angeles, California), and the Institute of Cancer Research (London, United Kingdom).

  Study phs001319

• comparing the snRNA-seq from placentas of mothers with or without obesity

  Obesity poses risks to maternal health and increases the likelihood of short- and long-term adverse pregnancy outcomes in the offspring. The placenta, a key organ at the maternal-fetal interface, responds to maternal obesity and regulates fetal growth. To investigate the molecular features of physiological adaptation, we perform single-nuclei RNA-seq on human placentas and compared the transcriptomic profiles of women with obesity delivering appropriate- or large-for-gestational age (i.e., AGA and LGA) babies with those from normal-weight healthy controls with AGA babies. The snRNA-seq libraries were generated with Chromium Single Cell 3’ kit v3.1 (10X Genomics) and sequenced on Illumina NovaSeq 6000 at Novogene.

  Study EGAS50000000834

• Bulk RNAseq from in vitro generated macrophages and T cells, and mUM tumour biopsies

  Monocyte derived macrophages were polarised into M1 or M2 using IFNg+ ILP or IL-4 respectively (n =4) . Pan T cells were cultured with or without IL-2 for 4 days (n=4 - 6). Pan T cells were co-cultured with THP1 tumour cells for 20 hours in the presence or absence of ImmTAC molecules and in the presence or absence of M2 macrophages. Sorted T cells and macrophage populations prior and post co-culture were analysed by bulk RNA sequencing (60 million reads per sample) using the Illumina NovaSeq system. 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

  Dac EGAC50000000518