12215 results for "cancer rna-seq"

in 15.01 milliseconds.

• Human and rat skeletal muscle multi-omic profiling

  Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples.

  Study EGAS00001005730

• 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

• Single-cell omics data for COVID-19 patients

  Single-cell RNA-seq, single-cell ATAC-seq, and genotypes used in the analysis for the study "Altered and allele-specific open chromatin landscape reveal epigenetic and genetic regulators of innate immunity in COVID-19". The RNA-seq and ATAC-seq are raw data in FASTQ format while the genotypes are in the VCF format which was filtered and imputed (more details are available in the main text of the study).

  Dataset EGAD00001009331

• Single cell RNA-seq, TCR-seq and bulk TCR-seq on HNSCC patients treated with ICB

  We performed single cell RNA- and TCR-sequencing (10x Genomics) on immune infiltrates (CD45+ cells) from 18 HNSCC patients enrolled in the IMCISION trial (Vos et al. 2021). Viable immune cells were isolated from pre-treatment and post-treatment primary tumor biopsies of 10 patients responding (1 partial pathological response and 9 major pathological responses) and 7 patients non-responding to anti-PD-1 and anti-CTLA4 combination immunotherapy. One patient treated with anti-PD-1 monotherapy (1 major pathological response) was included in the dataset. Bulk TCR-seq was performed on the PBMCs of responding patients, pre- and post-treatment.

  Dataset EGAD00001011311

• Enhanced cortical neural stem cell identity through SMAD/WNT inhibition in human cerebral organoids facilitates emergence of outer radial glial cells

  For scRNA-Seq, single live cells were suspended in 0.4% BSA in DPBS buffer (1000 cells/µL) and subjected for GEM generation and barcoding. Library preparation was performed according to the recommended procedures of the manufacture Chromium Single Cell 3’ reagent Kit V3.1 chemistry. 10,000 cells were targeted for capturing and 9 cycles were used for cDNA amplification, while 12 cycles were performed for library formation, and sequencing was performed on an Illumina NovaSeq 6000 sequencer. For bulk RNA-Seq, RNA was purified using the miRNeasy™ RNA MiniPrep (Qiagene) and RNA-seq libraries were generated either using the Illumina TruSeq RNA Library Preparation Kits and sequenced on the Illumina HiSeq 2500 sequencer as 76 bp paired-end reads, or using the NEBnext UltraDirectional RNA Library Preparation Kits after rRNA depletion using the NEBNext rRNA depletion kit and sequenced on an Illumina HiSeq 2500 sequencer using 50 cycles of single-end sequencing.

  Dataset EGAD00001008609

• Epigenomes and Transcriptomes of Brain Samples of Schizophrenics and Controls

  We examined the effects of antipsychotic medications on the cell-specific epigenomics and transcriptomics in the frontal cortex of schizophrenic subjects. We performed ChIP-seq (H3K4me3 and H3K27ac) and RNA-seq on neuronal and non-neuronal nuclei of postmortem frontal cortex samples from two cohorts of schizophrenics, either previously treated or not with antipsychotic medications, and control subjects individually matched by sex and age. In total, we tested 29 schizophrenics (15 untreated and 14 treated patients) and their matched control samples. Two replicates were produced on each brain sample for each assay. ChIP-seq data were generated using MOWChIP-seq (Zhu et al., PMID: 31666743) and RNA-seq data were produced using the combination of SMART-seq2 (Picelli et al., PMID: 24385147) and a Nextera XT DNA library preparation kit. The filename contains the information on the experimental group, the number of the sample within the group, the type of the brain nuclei, the epigenomic/transcriptomic data set (either H3K27ac or mRNA), and the number of replicate. For example, “SCZ-1-untreated-neuron-H3K4me3-R1” refers untreated schizophrenic sample #1, replicate 1 ChIP-seq data on H3K4me3.

  Study phs002487

• Benchmarking V(D)J Repertoire Reconstruction: Bulk RNA-Seq vs PCR-Based RepSeq Validated by SMRT Sequencing

  The aim of this study is to benchmark methods for immunoglobulin repertoire profiling using human B-cell samples. We compare targeted VDJ mRNA sequencing and repertoire reconstruction from bulk RNA-seq data to PCR-independent full-length transcript sequencing using Single-Molecule Real-Time technology. The objective is to assess methodological biases and establish a robust reference framework for immunoglobulin repertoire analysis.

  Study EGAS50000001541

• Multi-Omic Investigation of Beckwith-Wiedemann Syndrome Hepatoblastoma

  Hepatoblastoma (HB) is the most common malignant liver tumor diagnosed in children under 5 years of age. One of the most common HB predisposition syndromes is Beckwith-Wiedemann Syndrome (BWS, OMIM 130650), which affects approximately 1/10,000 live births. In this study, we perform Whole Exome Sequencing (WES), DNA methylation array, messenger RNA-Sequencing (mRNA-Seq), and microRNA-Sequencing (miRNA-Seq) to examine the genomic, methylomic, and transcriptomic signature of BWS HB. We analyzed five tumor-normal paired samples, two BWS tumor only samples, and five non-BWS control samples to identify a predisposition and oncogenic signature of BWS HB development. To further understand the new impact of 11p15 changes, specifically in the liver, we performed single-nucleus RNA sequencing (snRNA-seq) and single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) to generate paired, cell-type-specific transcriptional and chromatin accessibility profiles of both BWS-liver and nonBWS-liver nontumorous and tumor tissues.

  Study phs002614

• Uncovering Gene Regulatory Differences between Human and Chimpanzee Neural Cells

  A major challenge in human evolutionary biology is to pinpoint the genetic differences that underlie phenotypic changes in the human lineage, such as increased neuron number and a prolonged period of neuronal maturation. Here, we used human-chimpanzee tetraploid cells to distinguish changes in gene expression due to cis-acting sequence variants that change local gene regulation, from trans expression changes due to species differences in the cellular environment, in neural progenitor cells and excitatory neurons using RNA-seq and ATAC-seq. Using a CRISPR inhibition screen with scRNA-seq, transcription factor motif analyses with CUT&Tag, and downstream single-locus studies with RNA-seq, we further characterized cis-acting gene regulatory differences, including changes to FOS, TNIK, FOSL2, and MAZ, that influence neurogenesis and neuronal maturation. This study identifies specific genomic changes that may contribute to human neural specializations and provides a general framework for understanding genetic differences that underlie human traits.

  Study phs004053