12300 results for "cancer rna-seq"

in 28.32 milliseconds.

• Genomic and transcriptomic analysis of baseline PDAC patients' tumors from the OXIRI phase 1b clinical trial

  This study was aimed at investigating the genomic and transcriptomic features associated with response to the OXIRI regimen (oxaliplatin, irinotecan, capecitabine) in pancreatic ductal adenocarcinoma (PDAC) tumors. We performed whole-exome sequencing (WES) and RNA sequencing (RNA-seq) on baseline tumor samples obtained from 8 patients recruited in the OXIRI phase 1b clinical trial (NCT02368860).

  Study EGAS00001006073

• Cancer and germline exomes, and cancer RNA-seq consisiting of FASTQ paired-end reads from melanoma, lung and colon cancer samples

  Discovery of patient-specific tumor antigens usually requires in vitro-expanded autologous tumor infiltrating lymphocytes (TILs), among which tumor antigen-specific T cells are however often rare, thus limiting sensitivity. We designed in vitro culture conditions to improve the identification of rare tumor antigen-specific CD8 TILs. This innovative yet accessible pipeline allows highly-sensitive identification of tumor antigens and cognate T cell receptors (TCRs), greatly improving the selection of candidates for personalized cancer vaccines and TCR-based cellular immunotherapies.

  Study EGAS00001005513

• RNA-seq analysis of metastatic prostate cancer solid tumor biopsies

  The prevalence and features of treatment-emergent small-cell neuroendocrine prostate cancer (t-SCNC) are not well characterized in the era of modern androgen receptor (AR)–targeting therapy. We sought to characterize the clinical and genomic features of t-SCNC in a multi-institutional prospective study. Patients with progressive, metastatic castration-resistant prostate cancer (mCRPC) underwent metastatic tumor biopsy and were followed for survival. t-SCNC is present in nearly one fifth of patients with mCRPC and is associated with shortened survival.

  Study EGAS00001006369

• Data Access Commitee Hidradenitis suppurativa RNA-Seq

  Dac EGAC00001002270

• Pheochromocytoma and paraganglioma single nuclei RNA-seq

  Dac EGAC00001002657

• COVID-19 RNA-seq Data Access Commitee

  Dac EGAC00001002979

• RNA-seq data of HGG PDOX study

  Study EGAS00001004633

• RNA-Seq Pair End

  RNA analysis of two patients 11 and 15 with WGS done on Illumina HiSeq2000. For research purpose and authorised user only.

  Dataset EGAD00001003429

• Novel genome editing strategies to uncover genotype-phenotype correlations in Polycystic Kidney Disease: a proof-of-concept

  Bulk RNA-seq of genome-edited HEK293T cell lines engineered to model specific PKD1 variants. This dataset enables the exploration of genotype-phenotype correlations in Polycystic Kidney Disease (PKD)

  Study EGAS50000001188

• Dopaminergic neuron differentiation of human embryonic stem cells

  2 replicates of dopaminergic neuron differentiation of human embryonic stem cells from timepoints day 17 and day 28, performed with 10X Genomics single cell RNA-seq. Part of the Ásgrimsdottir et al. (Arenas Lab).

  Study EGAS50000001099

• ABCB1 expression in HCC biopsies

  We analyzed the ABCB1 expression in RNA-seq data of 134 HCCs (120 of these were previously published), including the biopsies from which the 3 doxorubicin-sensitive and 3 doxorubicin-resistant HCCOs were derived.

  Study EGAS50000000041

• Patient-derived organoids cohort raw FASTQ from SGMedical

  Raw FASTQ files for a glioblastoma multiforme organoid study, including exome sequencing and RNA-seq. 29 runs (paired-end), 58 FASTQ.c4gh files (R1/R2). Short-read Illumina; library strategies include exome capture and stranded total RNA-seq (see Experiment records for kit/instrument details). No processed results are included; access is controlled under the selected Policy.

  Dataset EGAD50000001741

• Deciphering RBP - alternative splicing networks in ALS iPSC-MN: patient and control datasets

  We produce RNA-seq datasets of iPSC-derived motor neurons (iPSC-MN) from healthy controls and sporadic ALS patients and controls and familial ALS patients with pathogenic variants in TARDBP.

  Study EGAS00001005879

• Nascent transcriptome in T-ALL bone marrow

  Nascent RNA expression profiles were generated with Global Run-On sequencing (GRO-seq) from T-ALL patient samples to measure primary transcription genome-wide and to summarize the transcriptional activity at gene loci and enhancers.

  Study EGAS00001005864

• BLUEPRINT release January 2015, RNA-Seq for common myeloid progenitor

  RNA-Seq data for 3 common myeloid progenitor sample(s). 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001169

• BLUEPRINT release August 2014, RNA-Seq for common myeloid progenitor

  RNA-Seq data for 3 common myeloid progenitor sample(s). 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000907

• The effect of anti-HER2/CD3 TDB on transcription in human PBMCs (single-cell RNA-seq)

  Single-cell RNA-seq libraries were generated from human PBMCs that were incubated with anti-HER2/CD3 TDB in the presence of KPL-4 cells. This dataset is linked with the following ArrayExpress Experiment: E-MTAB-8212 - The effect of anti-HER2/CD3 TDB on transcription in human PBMCs (single-cell)

  Dataset EGAD00001005188

• RNA-seq from PDAC samples

  Bam and fastq files from RNA-seq of PDAC samples used in the PCSI mismatch repair study

  Dataset EGAD00001006261

• Acute myeloid leukemia bulk RNA-seq (Diagnosis and Relapse)

  To gain insight into the clonal heterogeneity of diagnosis (Dx) and relapse (Re) pairs, we employed RNA-seq to longitudinally profile two t(8;21) (AML1-ETO = RUNX1-RUNX1T1), and four FLT3-ITD AML cases. All the samples are bone marrow aspirates.

  Dataset EGAD00001008374

• RNA-Seq data for Academic and For-Profit researchers.

  RNA-Seq data for both Academic and For-profit use

  Dataset EGAD00001009676

• Paired-end RNA-seq analysis of the 3D evolution of glioma cell populations. Part 2.

  Dataset contains paired-end RNA-seq sequencing data from 221 glioma samples.

  Dataset EGAD00001009497

• Paired RNA-Seq data of 65 samples of chemo-naïve and post-chemotherapy pancreatic ductal adenocarcinoma (PDAC)

  130 runs/ 65 samples of paired RNA-Seq data of chemo-naïve and post-chemotherapy pancreatic ductal adenocarcinoma (PDAC). The sequencing was done on Novaseq 6000 with Illumina TruSeq stranded mRNA Kit.

  Dataset EGAD00001010883

• Childhood Cancer Data Initiative (CCDI): Pediatric In Vivo Testing Program –Sarcoma, Kidney, and Liver Cancers

  The goal was to complete whole exome sequencing (WES) and RNA sequencing (RNA-Seq) on patient derived xenograft samples. Cancer in children is rare with approximately 15,700 new cases diagnosed annually in children 21 years or younger in the U.S. Through use of multimodality therapy (surgery, radiation therapy, and aggressive chemotherapy), 70% of patients will be 'cured' of their disease, and 5-year Event-Free Survival (EFS) exceeds 80%. Consequently, the number of patients that can be enrolled in phase I/II clinical trials is small, and most patients will have been extensively treated, hence drug/radiation resistant. Thus, preclinical studies that accurately translate into effective clinical therapy are an essential component of pediatric drug development. Our group has contributed to studies in the Pediatric Preclinical Testing Program (PPTP) and Pediatric Preclinical Testing Consortium (PPTC) that have led to clinical studies through Children's Oncology Group (COG). Of importance, we have developed and characterized over 330 Patient Derived Xenografts (PDX), developed from tumors both at diagnosis and relapse, that can be used to facilitate pediatric drug development as directed by FDA under the Research to Accelerate Cures and Equity for Children Act (RACE for Children Act).

  Study phs003160

• Breast Cancer Single-Cell RNA-Seq Dataset

  Single-cell RNA-Sequencing of 26 primary breast cancers from Wu et al. (2021) study. Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq 500 platform.

  Dataset EGAD00001007495

• Nasal MicroRNA during Bronchiolitis and Age 6y Asthma: MARC-35 Cohort

  We analyzed data from the 35th Multicenter Airway Research Collaboration (MARC-35) study to examine the relationship between nasal airway microRNAs (miRNAs) and the risk of developing childhood asthma. MARC-35 is a multicenter prospective cohort study which enrolled infants (age Structured interviews of the parents/guardians were performed by site investigators and clinical details were collected via emergency department and hospital inpatient chart reviews. Following the index hospitalization, trained study personnel conducted telephone interviews with parents/legal guardians at six-month intervals. Participants also underwent nasal swab sampling conducted by trained site personnel during the index bronchiolitis hospitalization and during an in-person follow-up examination at about age 6 years. Total RNA was extracted from nasal swab specimens using Trizol LS reagent (ThermoFisher Scientific, Waltham, MA) and the Direct-zol RNA Miniprep Kit (Zymo Research, Irvine, CA). Small RNA-seq was performed using the PerkinElmer NEXTFLEX® small RNA-seq v3 kit with Unique Dual Indexes (PerkinElmer, Waltham, MA) and sequenced on an Illumina NovaSeq6000 sequencer using an S2 50bp PE Flowcell (Illumina, San Diego, CA). Through dbGaP, limited de-identified phenotypic data (e.g., demographics) and RNA-seq FASTQ files will be made available. Among a cohort of infants hospitalized with bronchiolitis, we applied a small RNA sequencing approach and found miRNAs were associated with asthma risk factors, and highly expressed in lung tissue and immune cells (e.g., TH cells, neutrophils). They also played key roles in mechanisms relating to asthma, such as innate immunity, airway remodeling, and IgE regulation.

  Study phs003564

• GEP-NEN Bulk-RNA-seq dataset

  This dataset entails 40 Bulk-RNA sequenced patient-derived gastro-intestinal neuroendocrine (GEP-NEN) neoplasms.

  Dataset EGAD00001006657

• Leiden University Medical Center Adipose tissue RNA-seq

  Dac EGAC00001000503

• Board considering access to BELOB RNA-seq data

  Dac EGAC00001001686

• RNA-seq data from 27 glioblastoma samples

  Study EGAS00001005807

• Whole transcriptome profiling of liquid biopsies from tumour xenografted mouse models: validation cohort

  Total RNA sequencing (SMARTer Stranded Total RNA-Seq Kit v2) data of extracellular RNA (exRNA) from liquid biopsies of the validation PDX/CDX cohort

  Dataset EGAD00001009413

• Genomic, transcriptomic and epigenomic profiling of GCTB

  Giant cell tumor of bone is a rare bone neoplasm driven by oncogenic hotspot G34W/L/V mutations in the non-canonical histone variant H3.3. This study provides primary data of genomic (WGS), transcriptomic (RNA-seq) and epigenomic (histone mark ChIP-seq, WGBS, ATAC-seq) profiling of primary GCTB samples from several cohorts in Germany and Korea. We confirm the H3.3-G34 mutations as sole genetic drivers of GCTB, and describe the epigenetic alterations in mutant GCTB stromal cells.

  Study EGAS00001003730

• Exploration of coding and non-coding variants in cancer using GenomePaint.

  GenomePaint (https://proteinpaint.stjude.org/genomepaint) is a dynamic visualization platform for whole-genome, whole-exome, transcriptome, and epigenomic data, featuring a novel design that captures the inter-relatedness between DNA variations and RNA expression. Regulatory non-coding variants can be inspected and discovered along with coding variants, and their functional impact further explored by examining 3D genome and/or ChIP-seq data generated from cancer cell lines. Further, GenomePaint correlates mutation and expression patterns with patient outcomes, and can display external data such as adult cancer datasets and user-provided custom tracks. We used GenomePaint to analyze multi-omics data from 3,652 pediatric cancers representing 16 histotypes, and demonstrate the visualization features through examples, including two that led to new insights into oncogenic mechanisms in pediatric cancer. The first is the discovery of a new class of pathogenic recurrent variants that cause aberrant splicing, disrupting the RING domain of CREBBP, a driver gene frequently mutated in relapsed pediatric leukemia. The second is the cis-activation of the MYC oncogene in a subset of B-lineage acute lymphoblastic leukemia (B-ALL) via duplication of the NOTCH1-MYC enhancer (N-ME), previously discovered only in T-lineage ALL. The regulatory impact of N-ME enhancer amplification was initially confirmed by allelic imbalance in published gene expression and ChIP-seq data and verified by additional Capture-C and fluorescence in situ hybridization data generated by follow-up experiments. These examples demonstrate the power of GenomePaint in enabling not only data visualization but also integrative genomic analysis that can lead to novel biological insight for follow-up experimental validation.

  Study EGAS00001004669

• Mapping the lineage-retained antigen landscape in neuroblastoma

  Neuroblastoma is among the deadliest pediatric solid tumors, and relapse is frequently driven by lineage plasticity between adrenergic (ADRN) and mesenchymal (MES) cell states that escape conventional and targeted therapies. This project aims to identify tumor antigens that are retained across both lineage states and are therefore suitable for T-cell–based immunotherapy resistant to lineage switching, including non-canonical antigens derived from the "dark proteome." To support this aim, we generated paired RNA-sequencing and ribosome profiling (Ribo-seq) data from neuroblastoma cell lines, patient-derived tumor organoids, and primary patient tumors spanning ADRN and MES states. The RNA-seq data enable custom transcriptome assembly to recover non-reference and non-canonical transcripts, while Ribo-seq maps actively translated canonical and non-canonical open reading frames at codon resolution. Together these data provide the molecular substrate for systematic discovery of lineage-retained, translation-supported neuroblastoma antigens.

  Study EGAS00001008445

• RNA-seq of pcALCL

  RNA sequencing of frozen tumor biopsies from patients with primary cutaneous anaplastic large cell lymphoma. 12 samples. Illumina HiSeq 4000.

  Dataset EGAD00001006178

• rna-seq data of multiple myeloma patients

  6 samples from individuals with multiple myeloma with selective elimination of immunosuppressive T cells, rna sequencing

  Dataset EGAD00001006866

• RNA-seq data from the EUROBATS Project in four tissues: Fat, LCL, Skin and whole Blood.

  EUROBATS consists of RNA-seq data for female twins in lisphoblastoide cell lines (LCL), abdominal adipose tissue (Fat), abdominal skin tissue (Skin) and whole blood (Blood). The samples are a combination of MZ twins, DZ twins and singletons. The goal of the project is to find biomarkers related with the ageing process and cellular senescence.

  Study EGAS00001000805

• single-cell RNA-seq Case-Control study of children progressing to Type1 diabetes

  It was a single-cell RNA sequencing study on the PBMC samples from four Finnish children at risk of developing Type 1 diabetes and their gender age and HLA matched control children. All four Case children were positive for multiple islet specific autoantibodies and two of them also progressed to clinical disease during the follow up whereas the control children remain negative for all autoantibodies. Single-cell analysis confirmed some of the signatures obtained from the bulk data. It identified that high IL32 in case samples in the bulk RNA-seq was contributed mainly by activated T cells and NK cells. Trajectory analysis of the scRNA-seq data suggested that IL32 expression increased as the T cells moved towards activated state.

  Dataset EGAD00001005768

• SATB1 KO Treg and Teff cells: RNA-seq

  We expanded human Treg and CD4+ Teff cells for 9 days, re-activated the cells and performed CRISPR/Cas9 RNP-mediated KO at day 11. The cells were treated with a pro-inflammatory cytokine IL-12 on day 12. 4 days after editing, living cells were FACS-sorted, the RNA was extracted and prepared for RNA-seq. AAVS1 KO served as control. The transcription factors SATB1 and two other targets (included to increase the robustness of the dataset) were knocked-out. Three biological replicates have been applied.

  Dataset EGAD50000001277

• Single-cell RNA and DNA sequencing data obtained after genome-and-transcriptome separation.

  This dataset contains single-cell RNA and DNA sequencing data (fastq, n=928) obtained after genome-and-transcriptome separation. The RNA-seq data was obtained by Smart-seq2 amplification and Nextera XT library preparation. The DNA-seq data was obtained either by Gtag library preparation and amplification or by PicoPlex whole-genome amplification followed by Nextera XT library preparation. The single cells originate from a human PDX melanoma model and from HCC38 and HCC38 BL cell lines. The sequencing libraries were sequenced with Illumina instruments.

  Dataset EGAD00001010096

• DAC for RNA-Seq Transcriptomic CD4+ T data from EGAS00001004152

  Dac EGAC00001001462

• FIMM AML Single-Cell RNA-seq Data Access Committee

  Dac EGAC00001001709

• RNA-Seq of clonal endocrine therapy resistant cell lines

  Study EGAS00001007123

• Sequencing Lymphoma

  This repository contains sequencing data to describe the genomic profiles of several B-cell lymphomas including follicular lymphoma and Hodgkin lymphoma. We have used several different high throughput sequencing technologies to interrogate genomic DNA and RNA from tumor cells obtained from lymph node biopsies and normal cells obtained from skin biopsies and peripheral blood mononuclear cells. A number of sequencing platforms for DNA, RNA, and protein were used to generate the data. These platforms include exome sequencing and a custom capture panel (NimbleGen) that targets 7.05 MB corresponding to the exons and splice sites of 1716 genes related to lymphoma biology (WUSM-LP). Other platforms include single-cell RNA-seq and Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), which was used to describe transcriptional and proteomic changes in immune cell subsets within lymphoma patients pre- and post-therapy.

  Study phs001229

• RNA-seq analysis of human skin

  RNA sequencing analysis comparing epidermal subpopulations in normal and inflamed skin.

  Study EGAS00001002927

• H005 RNA-seq CLL

  Paired-end RNA sequencing using total RNA from 136 primary lymphoma samples. Sequencing was performed on the Illumina HiSeq2000 with 300bp insert size. The dataset contains FASTQ files.

  Dataset EGAD00001002056

• Transcriptional profiling and clonality analysis of peripheral blood B cells and small intestinal plasma cells in celiac disease

  Single-cell RNA-seq and BCR sequencing and/or inference of sorted IgA+ peripheral blood B-lineage cells and small intestinal plasma cells of untreated celiac disease patients.

  Study EGAS50000000229

• ALS-FTD brain motor cortex single-nucleus RNA-seq of NeuN+ nuclei sorted for TDP-43 low vs. high

  A dataset of single-nucleus RNA-seq data of nuclei from the post-mortem human primary motor cortex from patients with ALS-FTD. The nuclei were sorted by flow cytomotetry into NeuN+ (neuronal) TDP-43 low vs. TDP-43 high fractions.

  Dataset EGAD50000002243

• RNA-seq for 8 samples

  This dataset contains RNA-seq data from 8 acute leukemia cases (diagnosis or relapse) belonging to a newly identified subtype, termed FOXF1/FENDRR ALL. All the 8 samples are in bam file type.

  Dataset EGAD50000001789

• InsPIRE islets

  We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors and 26 FAC sorted beta-cells.

  Study EGAS00001003997

• Transcriptome profiling of 25 prostate tumor samples by RNA-Seq

  Transcriptome profiling of 25 prostate tumor samples by RNA-Seq

  Dataset EGAD00001003344