11625 results for "cancer rna-seq"

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• 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

• Single cell RNA seq of breast cancer stem cells

  RNA sequences of breast cancer have been investigated for many patients. Recently it has been shown that there are intra-heterogeneity in tumor tissues. When the tumor cells were sequenced in bulk condition, only the major populations' mRNA will be detected. With respect to breast cancer, it has been also reported that cancer cells can sub-gropued into cancer stem cells and non-cancer stem cells. Although the mRNA expressions' difference between this two groups has been profoundly investigated, whether each group is composed by unique cell or not is yet to be elucidated. Since cancer stem cells are the thought to be the major contributor of metastasis and/or recurrence, we focused on cancer stem cells in this study. We separated cancer cells into cancer stem cells and non-cancer stem cells exploiting cancer stem cell specific surface markers. Thereafter, we sequenced mRNA of cancer stem cells in single cell resolution. From this result, we examined whether these cells can be sub-grouped or not.

  Study JGAS000305

• 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

• Dana-Farber Cancer Institute (DFCI) Wu Lab/Avicenne CLL RNA-Seq Study

  Chronic Lymphocytic Leukemia (CLL) is a hematological malignancy characterized by accumulation of CD5+ B cells in peripheral lymphoid organs, bone marrow and blood. Recently, the advent of large-scale whole-exome sequencing of hundreds of CLL samples has led to gain a comprehensive understanding of the mutational landscape of this clonal B cell malignancy, but the functional effects of the putative driver mutations thus discovered are largely unknown. In this study, we analyze RNA-seq data from CLL patients to characterize dysregulated biological pathways regarding the presence of recurrent mutations. Source of tumor is patients' PBMC isolated from peripheral blood using the Ficoll method. Purity was confirmed using flow cytometry flow (>80% in all cases).

  Study phs002335

• Single cell RNA-seq profiling of CD8 T cells from elder adults

  Single cell RNA-seq profiling of ~62k purified CD8+ T cell transcriptomes, from six healthy older adult donors using 10X genomics. Cells from each donor were separated based on their IL-7R protein expression (i.e. CD8+ IL7R+ and CD8+ IL7R- T cells).

  Study EGAS00001004255

• BLUEPRINT RNA-seq data for rare cells in the haematopoietic lineages, from adult and cord blood samples.

  RNA-seq data for rare cells in the haematopoietic lineages, from adult and cord blood samples.

  Study EGAS00001000284

• Indonesian RNA-seq dataset

  This dataset contains 4 batches of Indonesian RNA-seq data from Mentawai, New Guinea and Sumba islands. One RNA-seq batch was prepared without Globin depletion, and three batches were Globin depleted using the Illumina Globin-Zero Gold Kit. There are 179 runs in total, including 119 unique samples. Dataset includes multiple batch control samples.

  Dataset EGAD00001005053

• Comparison of the single-cell and single-nucleus hepatic myeloid landscape within decompensated cirrhosis patients

  In-patient comparison of single-cell RNA-sequencing (scRNA-seq) and single-nucleus (snRNA-seq) technologies and accompanying tissue processing protocols on transjugular liver biopsy from decompensated cirrhosis patients (n = 3).

  Study EGAS50000000073

• ATAC-seq and RNA-seq datasets of CD14+ monocytes from healthy donors

  This dataset consists of functional genomic data from 6 healthy donors taken from CD14+ monocytes upon different immune stimulations. It contains 150 paired end fastq files consisting of 30 total RNA-seq samples across 4 runs and 30 ATAC-seq samples. The samples were sequenced on Illumina HiSeq4000 platform.

  Dataset EGAD00001011113

• RNA-seq data for genomic determinants of response and resistance to inotuzumab in B-ALL

  RNA-seq data for 101 samples with B-cell acute lymphoblastic leukemia

  Dataset EGAD50000000095