11979 results for "cancer rna-seq"

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• CRUK Accelerator: Non-small cell lung cancer whole exome and RNA sequencing

  Whole exome and RNASeq raw sequencing data for a cohort 24 patients with non-small cell lung cancer, 15 adenocarcinoma (8 female, 7 male) and 9 squamous cell carcinoma(5 female, 4 male). Median age at diagnosis was 69. Tumour tissue and PBMCs were used for whole exome sequencing and RNA sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

  Dataset EGAD00001007934

• HiDEF-seq Single-Molecule Sequencing of Single-Strand Mismatches and Damage

  Our study sought to resolve, with single-molecule resolution, the mismatches and damage events that precede DNA mutations. Using a novel single-molecule, long-read sequencing method (HiDEF-seq) we detected base substitutions when present in either one or both DNA strands. We compared the fidelity for dsDNA mutations to that of the same samples profiled by NanoSeq duplex sequencing. We also detected cytosine deamination, a common type of DNA damage, with single-molecule resolution. We profiled 134 samples from diverse tissues, including from individuals with cancer predisposition syndromes. These samples revealed single-strand mismatch and damage signatures. Since double-strand DNA mutations are only the endpoint of the mutation process, our approach enables new studies of how mutations arise in a variety of contexts, especially in cancer and aging.The data available via dbGaP includes raw HiDEF-seq sequencing files (Pacific Biosciences subreads in BAM format), raw NanoSeq sequencing files (Illumina FASTQ format), and raw germline sequencing files (Illumina FASTQ format).The HiDEF-seq main publication contains a supplementary table with a list of accession IDs for each sample's files.

  Study phs003604

• LEF1 knockdown effects on human T cell transcriptome and chromatin accessibility profiles.

  LEF1 (Lymphoid Enhancer-Binding Factor 1) is a key transcription factor in T cell development and function, and its dysregulation has been implicated in various immune-related disorders. This study aimed to comprehensively characterize the transcriptional and epigenetic changes induced by LEF1 knockdown in human T cells. CD3+ T cells isolated from three healthy donors were transfected with either LEF1-specific siRNA or control siRNA, followed by activation with CD3/CD28 Dynabeads and culture in IL-2-containing media. Cells were harvested at 24, 48 and 72 hours post-transfection for multi-omics analysis including bulk RNA-seq, bulk ATAC-seq, single-cell CITE-seq (For CITE-seq, 48 and 72 hours only). This dataset provides insights into LEF1-dependent gene regulatory networks and chromatin accessibility patterns in activated human T cells, contributing to our understanding of T cell biology and potential therapeutic targets. This dataset is part of a comprehensive study investigating functional roles of risk polymorphisms in autoimmune diseases, particularly focusing on the rs58107865 variant at the LEF1 locus.

  Study JGAS000818

• A Phase Ib/II Study of Regorafenib and Paclitaxel in Beyond First-line Advanced Esophagogastric Carcinoma (REPEAT)

  Regorafenib showed promising results in gastric cancer. We aimed to assess the tolerability of regorafenib and paclitaxel in advanced esophagogastric cancer (EGC) patients refractory to first-line treatment and explore potential biomarkers.. We performed enzyme-linked immunosorbent assay measurements of galectin-1, RNA sequencing, and shallow wholegenome sequencing of metastatic tumor biopsies for biomarker analyses.

  Study EGAS00001006054

• RNA sequencing in primary inflammatory (TPP) macrophages following deletion of a disease-associated gene desert at chr21q22, disruption of ETS2, or treatment of ETS2-edited macrophages with a HIF1α stabiliser.

  This dataset comprises raw RNA sequencing data (FASTQs) from primary inflammatory (TPP) macrophages that were unedited (non-targeting control, NTC), edited to delete the disease-associated chr21q22 enhancer region (n=5), or edited to disrupt ETS2 with 1 of 2 independent gRNAs (n=9). We also performed RNA-sequencing in NTC or ETS2-edited TPP macrophages that were treated for 12 hours with vehicle (DMSO) or roxadustat (30 uM, n=3). Macrophages were detached using Accutase and lysed. RNA was extracted from cell lysates using an AllPrep DNA/RNA Mini Kit (Qiagen). Sequencing libraries were prepared from 10ng RNA using the SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian (Takara) following the manufacturer’s instructions. The quality and molarity of all libraries was assessed using a BioAnalyzer 2100 and the libraries were sequenced on a NextSeq500. Raw data are provided as 50 bp paired-end Illumina reads.

  Dataset EGAD00001011338

• Pooled scRNA-seq of iPSC-derived neural stem cells from ADHD and control individuals

  This dataset comprises paired-end FASTQ files from single-cell RNA sequencing (scRNA-seq) of neural stem cells (NSCs) derived from induced pluripotent stem cells (iPSCs). The iPSCs were reprogrammed from somatic cells (keratinocytes, PBMCs, or lymphoblastoid cell lines) collected from individuals diagnosed with attention-deficit hyperactivity disorder (ADHD) and age-matched healthy controls (ages 6–18 years). Reprogramming was carried out using the non-integrative Sendai virus system (CytoTune-iPS 2.0, Thermo Fisher Scientific), introducing OCT3/4, SOX2, KLF4, and cMYC. iPSCs were cultured in Essential 8 medium on vitronectin and underwent rigorous quality control including immunocytochemistry, qRT-PCR, mycoplasma testing, and SNP genotyping (Illumina Global Screening Array). NSCs were generated using a standardized neural induction protocol and validated via qRT-PCR and immunostaining for markers including PAX6, SOX2, NESTIN, TUJ1, and FOXG1. Two independent scRNA-seq multiplexed experiments were performed: Experiment 1 (ADHD: n = 7; Control: n = 6) and Experiment 2 (ADHD: n = 9; Control: n = 7). Samples were pooled and demultiplexed using the Ensemblex algorithm, incorporating prior genotype data. After quality control filtering (>500 unique RNA molecules per cell), 30,433 single-cell transcriptomes were retained. Differential gene expression analysis was conducted to identify transcriptional signatures associated with ADHD compared to controls.

  Study EGAS00001008169

• Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis

  This dataset contains raw sequencing files associated with the paper "Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis" (https://doi.org/10.1038/s41590-023-01490-5). It is composed of two experiments, which are as follows: 1. Single-cell profiling of whole blood leukocytes: This experiment comprises sequencing files generated using the BD Rhapsody single-cell multi-omics profiling (RNA + protein) platform. This platform was used to profile the whole blood leukocyte population in a cohort of sepsis patients, cardiac surgery controls and healthy controls. There are 48 samples and four files per sample: two paired-end FASTQ files (R1 and R2) corresponding to the RNA-seq library, and two paired-end FASTQ files (R1 and R2) corresponding to the protein profiling (ADT-based AbSeq) library. 2. Single-cell profiling of circulating HSPCs: This experiment comprises sequencing files generated using the 10X single-cell multi-omics (RNA-seq + ATAC-seq) profiling platform. This platform was used to profile circulating HSPCs in a cohort of sepsis patients and healthy controls. There are 5 samples (or plexes), each of which consists of a pool of individuals for whom cells were multiplexed and sequenced as a single sample. There are four files per sample: two paired-end FASTQ files (R1 and R2) corresponding to the RNA-seq library, and two paired-end FASTQ files (R1 and R2) corresponding to the ATAC-seq library. Because these samples consists of multiplexed pools, index files are also provided. These can be used for sample deconvolution using the Cell Ranger pipeline. NOTE: Due to EGA's constrains in the number of files permitted per sample, index files (I1 and I2) for the HSPC data set are provided as a separate experiment named "FASTQ index files (I1 and I2) for deconvolution of 10X single-cell multiomics libraries".

  Dataset EGAD00001010927

• Strand-specific mRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  Strand-specific mRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001227

• Fastq data for stranded mRNA-Seq assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for stranded mRNA-Seq assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001402

• ChIP-Seq (Input) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (Input) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001235

• Molecular Characterization for Nasopharyngeal Carcinoma (NPC)

  Total RNA was isolated from 50 formalin-fixed paraffin-embedded nasopharyngeal cancer (NPC) specimens using the RecoverAll Total Nucleic Acid Isolation kit (Ambion). Tumor RNA libraries were prepared with 200ng RNA using the Illumina TruSeq Stranded Total RNA kit with Ribo-Zero Gold, and sequenced with >80 million 100 bp paired-end reads.

  Dataset EGAD00001009047

• Enzymatic Methyl-Seq Rectal Mucus

  Enzymatic methyl sequencing of rectal mucus samples from patients suspected to have colorectal cancer. This is 1 of 4 sequencing experiments on the same sample type.

  Study EGAS50000001314

• Data for noninvasive lung cancer subtyping study

  This dataset included cfMethyl-Seq data of 15 plasma cfDNA samples from 15 lung cancer patients and RRBS data of 58 lung tumor tissue samples from 58 lung cancer patients. The data were generated following the standard protocols.

  Dataset EGAD00001015344

• 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

• Indonesian RNA-seq data

  Transcription data were collected to study patterns of functional variation across the broad geography of Indonesia. The region has extremely diverse populations, with very different demographic histories and multiple genetic ancestries. This dataset reports high-throughput RNA-sequencing data for individuals from three islands spanning this geographical region: Mentawai, Sumba and West Papua.

  Study EGAS00001003671

• High-Throughput RNA Isoform Sequencing using Programmable cDNA Concatenation

  MAS-ISO-seq is a novel technique for programmably concatenating cDNAs into single molecules for optimal long-read sequencing. In practice, this boosts throughput >15 fold to nearly 40 million cDNA reads per run on the PacBio Sequel IIe sequencer. We have validated this method via application to synthetic RNA isoforms and single-cell sequencing of tumor-infiltrating T cells. Results demonstrated a >30 fold boosted discovery of differentially spliced genes and robust cell clustering, as well as canonical PTPRC splicing patterns across T cell subpopulations and the concerted expression of the associated hnRNPLL splicing factor.

  Study phs003200

• Neuroblastoma patient Total RNA Seq data

  Tumor Total RNA Seq data of primary neuroblastomas. This is an update of the „Berlin Neuroblastoma Dataset” (EGAS00001004022). This data was used for the analysis of circular RNA expression and regulation in neuroblastoma.

  Dataset EGAD00001008124

• Effects of 2DG, Galactose, or Oligomycin on the epigenome remodeling induce by T cells activation.

  T cell activation is known to require a metabolic shift towards glycolysis, triggered by TCR-engagement . To substantiate the role of glycolysis in transcriptional reprogramming during antigen-driven T cell activation, we utilized a well-established ex-vivo model to recapitulate the process of antigen stimulation without the requirement for additional antigen-presenting cells . We initially explored and validated the conditions for both metabolic and epigenetic reprogramming. Antigen-mediated CD4+ T cells activation initiates context-specific gene-expression programs that drive effector functions and cell fates through changes in the epigenetic landscape . To evaluate global changes in histone modifications, we isolated CD4+ T cells from peripheral blood (PB) of healthy control (HC) human donors and either maintained them in resting conditions or stimulated with anti-CD3/CD28 for 24h. Rapid changes in the CD4+ epigenome and transcriptome were observed within 24h as measured by RNA-sequencing (RNA-seq) and H3K27ac chromatin immunoprecipitation followed by DNA-sequencing (ChIP-seq).To explore the requirement for metabolic reprogramming in regulating transcriptional responses after initial TCR engagement, CD4+ T cells from PB of healthy donors were isolated and activated in either the presence or absence of oligomycin (inhibitor of ATP synthase blocking the production of ATP by OXPHOS), 2-deoxyglucose (2DG; competitively inhibiting production of glucose-6-phosphate from glucose), or replacement of glucose with galactose. Galactose is metabolized through glycolysis, utilizing the Leloir pathway which is energy neutral, forcing cells to use all the pyruvate production to sustain the TCA cycle for OXPHOS and ATP synthesis at the expense of lactate production. Employing ChIP-seq and RNA-seq, inhibition of OXPHOS-mediated ATP production by oligomycin had only a limited effect on H3K27-acetylation or activation-induced transcription during the first 24h of activation. In contrast, inhibition of glycolysis by 2DG treatment compromised both H3K27-acetylation and transcriptional changes. However, under conditions of galactose-metabolism where lactate production is abrogated, activated CD4+ T cells were still able to globally remodel H3K27 acetylation and reprogram the transcriptome.

  Study EGAS00001007115

• COVID_Methyl_scRNA

  DAC for the study of whole-genome enzymatic DNA methylation sequencing and single-cell RNA sequencing of nasal cells from COVID-19 patients. Nasal swabs were collected from COVID-19 patients during the acute phase of infection as well as 3 and 12-months post-infection. Cells isolated from nasal swabs were subjected to whole-genome enzymatic DNA methylation sequencing (n=33) and scRNA-seq (n=24). For n=12 former COVID-19 pateints, follow-up samples were collected at 3 and 12 months post-infection and subjected to scRNA-seq.

  Dac EGAC50000000197

• ZFHX4 is necessary for dopaminergic neuron differentiation and controls cell cycle by regulating LIN28A

  ZFHX4 as a transcription factor specifically induced during the in vitro differentiation of iPSC-derived mDANs. Depletion of ZFHX4 during neuronal differentiation led to a significant reduction in the number of mDANs while its overexpression did not lead to any changes in mDAN count. Identification of ZFHX4 target genes using CUT&Tag profiling and RNA-seq upon ZFHX4 knock-down (KD) revealed its involvement in cell cycle regulation during mDAN differentiation

  Dataset EGAD50000001605

• Monosomy 7 delineates a primitive acute myeloid leukemia with adverse prognosis and responsiveness to epigenetic therapy

  The dataset comprises 27 single-cell multiome (ATAC + GEX) datasets generated from 13 patients with AML, collected across different stages of disease progression. In addition, matched long-read sequencing data from 5 samples were used to enable longitudinal analyses throughout the manuscript. Finally, bulk RNA-seq and ATAC-seq datasets from the cell line used in this study are also included.

  Dataset EGAD50000002359

• Stromal and dendritic cells from lymph nodes: single-cell RNA-seq

  Although cross-species transcriptional analysis has been generated for DCs, transcriptomic conservation between mouse and human FRCs at single-cell resolution has been unclear. To test whether GREM1+ FRCs might also play a role in DC homeostasis in humans, we performed scRNA-seq of CD45–PDPN+ stromal cells, as well as CD45+CD11c+ immune cells from healthy human LNs of three human donors. Data was generated using the 10x platform.

  Dataset EGAD00001008731

• FOXM1 is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer that is detectable using metabolic imaging (RNA-seq data)

  PIK3CA, encoding the PI3Kα isoform, is the most frequently mutated oncogene in estrogen receptor-positive breast cancer. Isoform-selective PI3K inhibitors are used clinically but intrinsic and acquired resistance limits their utility. Improved selection of patients that will benefit from these drugs requires novel predictive biomarkers. We show here that persistent FOXM1 expression following drug treatment is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer. Since the transcription factor drives expression of lactate dehydrogenase (LDH) but not hexokinase 2 (HK-II), changes in FOXM1 expression can be detected using magnetic resonance imaging of LDH-catalyzed hyperpolarized 13C label exchange between pyruvate and lactate but not by PET measurements of HK-II-mediated trapping of the glucose analog 2-deoxy-2-[18F]fluorodeoxyglucose.

  Study EGAS00001004452