12304 results for "cancer rna-seq"

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• Systematic comparative analysis of single-nucleotide variants detection methods from single-cell RNA sequencing data

  Systematic interrogation of single nucleotide variations (SNVs) is one of the most promising approaches to delineate the cellular heterogeneity and phylogenetic relationships at the single cell level. While SNV detection from abundant single cell RNA sequencing (scRNA-seq) data is applicable and cost-effective in identifying expressed variants, inferring sub-clones, and deciphering genotype-phenotype linkages, there is a lack of computational methods specifically developed for SNV calling in scRNA-seq. Although variant callers for bulk RNA-seq have been sporadically used in scRNA-seq, the performances of different tools have not been assessed. Here, we performed a systematic comparison of seven tools including SAMtools, the GATK pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, using both simulation and scRNA-seq datasets, and identified multiple elements influencing their performance. Our study provided the first benchmarking to evaluate the performances of different SNV detection tools for scRNA-seq data.

  Study EGAS00001003883

• Defining and Overcoming Intrinsic T Cell Dysfunction to Enable Pediatric Immunotherapy

  T-cells from 71 children and young adults with B-cell malignancies on trial to receive anti-CD19 CAR T-cell therapy were analyzed. These T-cells represent the pre-manufacture T-cells that were subsequently used for CAR T manufacture. Bulk RNA-Seq was performed on sorted T-cell subsets for all patients, in addition to CITE-Seq and single-cell ATAC-Seq on a subset of 6 patients. The primary clinical outcome was duration of B-cell aplasia, a surrogate measure of functional CAR T-cell persistence. From these data, molecular signatures associated with long and short-term CAR T-cell persistence were identified. This data submission includes bulk RNA-Seq, CITE-Seq, and single-cell ATAC-Seq data from this study.

  Study phs002323

• Identification of Recurrent SMO and BRAF Mutations in Ameloblastomas

  RNA-seq data from two cases of ameloblastoma was analyzed for candidate gene fusions and point mutations. Recurrent point mutations identified in the RNA-seq data, as well as mutations identified with limited panel targeted deep sequencing, were validated as somatic. Expanding to a larger cohort of 28, one of two activating mutations was found in 80% of cases. No recurrent gene fusions events were identified.

  Study phs000739

• Transcriptome analysis of iPSC-derived hepatocytes from Wilson's Disease patients and healthy controls

  To identify the differences in global gene expression patterns in WD-specific hepatocytes, we performed RNA-seq analysis. Six WD-specific hepatocytes and 6 healthy-donor (HD) hepatocytes were compared in total. The data suggested that our RNA-seq data were partially validated in the context of ATP7B deficiency and that these overlapped genes might be regulated by ATP7B deficiency among mammalian species in common.

  Study JGAS000382

• Transcriptomic subgroups in soft tissue tumors correlate with morphologic subtype, genomic features, and outcome

  We assessed gene expression (GGE) profiles and gene fusions as detected by transcriptome sequencing (RNA-seq) of 704 soft tissue tumors (STT) representing 56 different tumor types. Comparison with follow-up data identified transcriptional subclusters among sarcomas with complex genomes and among adipocytic tumors that correlated with metastasis-free survival and local recurrences, respectively. Thus, RNA-seq analysis of STT provides clinically important information.

  Study EGAS50000001472

• Discriminating Th17.1 cell driven sarcoidosis-like inflammation from relapse after anti-BCMA CAR T cells in multiple myeloma

  We present a case study on sarcoidosis-like flare-up after Idecabtagen Vicleucel (Ide-cel), a BCMA targeting CAR T cell therapy, and identified a Th17.1 driven autoimmune mechanism as the biological underpinning of this phenomenon using single-cell RNA-seq analysis. Furthermore, single-cell RNA-seq allowed to discriminate between immune-mediated changes and true relapse after CAR T cell treatment.

  Study EGAS00001006133

• Whole-exome and RNA sequencing data from a uveal melanoma patient with multi-regional sampling

  This dataset includes whole-exome sequencing (WES) and RNA sequencing (RNA-seq) data from a uveal melanoma patient. Tumor samples were obtained from three distinct regions, each with matched RNA-seq and WES data. Additionally, WES data from the patient’s peripheral blood mononuclear cells (PBMCs) is provided as a germline reference.

  Dataset EGAD50000001422

• TIRE-seq: an Integrated Sample Extraction and Transcriptomics Workflow for High Throughput Perturbation Studies

  TIRE-seq is a novel RNA sequencing method that integrates mRNA purification directly into library preparation, eliminating separate RNA extraction. The technique demonstrated utility across three biological applications, including capturing transcriptional changes in human T cells, identifying genes driving murine dendritic cell differentiation, and analyzing the dose-response effects of temozolomide on patient-derived neurospheres. With its simplified approach and high sequencing efficiency, TIRE-seq offers a cost-effective solution for large-scale gene expression studies.

  Study EGAS50000000867

• Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

  To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

  Dataset EGAD00001007872

• Tissue Sampling and Biorepository to improve Cancer Cell Therapy

  This study focuses on the elucidation of determinants of response and resistance to anti-CD19 CAR T-cells in large B-cell lymphoma. Plasma samples were collected prior to treatment and serially post CAR T-cell infusion. Pre-treatment and relapse tumor samples were also obtained as available. Germ-line DNA isolated from Peripheral Blood Mononuclear Cells (PBMCs) was collected for all patients when available. Circulating tumor DNA (ctDNA) and tumor DNA were sequenced using a target hybrid capture oligonucleotide pool. RNA-Seq was also performed on tumor isolated RNA. The authors identified several recurrent genomic alterations associated with relapse, and identified molecular thresholds that were predictive of response.

  Study phs003145