11925 results for "cancer rna-seq"

in 189.68 milliseconds.

• BLUEPRINT September 2016, RNA-Seq Acute Lymphocytic Leukemia for precursor B cell from bone marrow, on Genome GRCh38

  RNA-Seq data for 8 sample(s) Acute Lymphocytic Leukemia for precursor B cell from bone marrow, on Genome GRCh38. 8 run(s), 8 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002953

• BLUEPRINT September 2016, RNA-Seq for monocyte T=0day from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=0day from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002955

• BLUEPRINT September 2016, RNA-Seq T-cell lymphoma for helper T cell from venous blood, on Genome GRCh38

  RNA-Seq data for 2 sample(s) T-cell lymphoma for helper T cell from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002956

• BLUEPRINT September 2016, RNA-Seq for monocyte T=2day_RANK_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=2day_RANK_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002957

• BLUEPRINT September 2016, RNA-Seq for monocyte T=1day_M-CSF_S100A9_4hr_RANL from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=1day_M-CSF_S100A9_4hr_RANL from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002959

• BLUEPRINT September 2016, RNA-Seq for monocyte T=6day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=6day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002960

• BLUEPRINT September 2016, RNA-Seq for monocyte T=10day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=10day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002961

• BLUEPRINT September 2016, RNA-Seq Acute Myeloid Leukemia for blast cell from bone marrow, on Genome GRCh38

  RNA-Seq data for 1 sample(s) Acute Myeloid Leukemia for blast cell from bone marrow, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002962

• BLUEPRINT September 2016, RNA-Seq Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38

  RNA-Seq data for 6 sample(s) Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38. 6 run(s), 6 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002963

• BLUEPRINT September 2016, RNA-Seq for monocyte T=1day_4hr_RANK from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=1day_4hr_RANK from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002964

• BLUEPRINT September 2016, RNA-Seq for monocyte T=2day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=2day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002965

• BLUEPRINT September 2016, RNA-Seq for monocyte T=10day_RANK_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=10day_RANK_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002966

• BLUEPRINT September 2016, RNA-Seq for monocyte T=6day_RANK_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=6day_RANK_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002967

• BLUEPRINT September 2016, RNA-Seq Acute Myeloid Leukemia for myeloid cell from venous blood, on Genome GRCh38

  RNA-Seq data for 2 sample(s) Acute Myeloid Leukemia for myeloid cell from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002968

• The role of MALT1 in driving IBN resistance in MCL

  The bulk RNA-seq dataset was generated for the cell lines below and used for two major purposes: 1. DEG analysis and GSEA analysis comparing IBN-R and IBN-S cells 2. DEG analysis and GSEA analysis comparing MCL cells with/without MI-2 treatment.

  Study EGAS00001006832

• BLUEPRINT release August 2014, RNA-Seq for CD8-positive, alpha-beta T cell

  RNA-Seq data for 1 CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 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 EGAD00001000912

• BLUEPRINT release January 2015, RNA-Seq for CD14-positive, CD16-negative classical monocyte

  RNA-Seq data for 8 CD14-positive, CD16-negative classical monocyte sample(s). 8 run(s), 8 experiment(s), 8 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 EGAD00001001148

• BLUEPRINT release January 2015, RNA-Seq for effector memory CD4-positive, alpha-beta T cell

  RNA-Seq data for 1 effector memory CD4-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 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 EGAD00001001163

• BLUEPRINT release January 2015, RNA-Seq for central memory CD4-positive, alpha-beta T cell

  RNA-Seq data for 1 central memory CD4-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 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 EGAD00001001172

• BLUEPRINT release August 2015, RNA-Seq for class switched memory B cell, on genome GRCh38

  RNA-Seq data for 1 class switched memory B cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001531

• BLUEPRINT release August 2015, RNA-Seq for memory B cell, on genome GRCh38

  RNA-Seq data for 1 memory B cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001542

• BLUEPRINT release August 2016, RNA-Seq for colony forming unit erythroid, on genome GRCh38

  RNA-Seq data for 1 colony forming unit erythroid sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002509

• Comparison of 3 protocols for deriving pancreatic progenitors from hPSCs (RNA-seq)

  This dataset contains 26 mapped bam files. The samples were generated with 3 different protocols for deriving pancreatic progenitors from hPSC. Three parallel differentiations were performed, all done in a hPSC NKX6.1-GFP reporter line. For each protocol there are three cellular populations: total (presort), GFP+ and GFP- . In summary: 3 differentiations x 3 protocols x 3 cellular populations. We prepared Smart-Seq2 RNA-seq libraries for the 27 samples, 1 sample failed library preparation and is not therefore included in this dataset.

  Dataset EGAD00001004823

• Multidimensional and Longitudinal Immune Profiling of Sepsis in Uganda

  We conducted a prospective, observational cohort study of adults (RESERVE-U-2-TOR) admitted to Tororo General Hospital in eastern Uganda with severe, undifferentiated infection (i.e., suspected sepsis). Briefly, whole-blood samples were collected in PAXgene blood RNA tubes (PreAnalytiX, Qiagen, Germantown, MD, USA), from which RNA was extracted using PAXgene Blood RNA Kits (cat. no. 762164) (Qiagen). Sequencing libraries were constructed with the NEBNext Ultra II RNA Library Preparation Kit for Illumina, after which libraries were multiplexed and sequenced on the Illumina NovaSeq X Plus platform (Illumina, Inc, San Diego, CA). Data from this study available through dbGaP include raw RNA-Seq data generated from whole-blood samples collected upon RESERVE-U-2-TOR study enrollment (N=274).

  Study phs003914

• RNA-seq of hepatocellular carcinoma xenografts established from needle biopsies

  RNA-sequencing of human hepatocellular carcinoma biopsies (n=14), 44 HCC xenografts derived from 11 HCC biopsies and 3 lymphoma xenografts derived from 3 HCC biopsies. RNA-sequencing was performed using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Gold (lllumina). SR126 sequencing was performed on an Illumina HiSeq 2500 using v4 SBS chemistry according to the manufacturer’s guidelines.

  Dataset EGAD00001004541

• The RNA, ChIP and whole exome sequencing analysis of human colorectal cancer organoids and normal colon organoids treated with (+)-JQ1

  To reveal the mechanism of anti-tumor effect of (+)-JQ1, we performed RNA, ChIP and whole exome sequencing using human colorectal cancer and normal colon organoids.

  Study JGAS000378

• Whole Exome Sequencing of Localized Prostate Cancer Patients

  We performed whole-exome sequencing on localized prostate cancer patients to validate tumor content as part of a single-cell RNA sequencing study of localized prostate cancer patients.

  Study EGAS00001005685

• Short-read RNA-seq of doxycycline-inducible DUX4 human myoblast cell lines

  The dataset includes the short-read RNA sequencing data of DUX4i myoblasts (Clone-5 and Clone-7) with and without 16-hour DOX-treatment (n=1 in each condition).

  Dataset EGAD50000000719

• RNA-seq in endometrial healthy and tumor tissues

  RNA has been extracted by Rneasy mini kit from around 30mg of flash frozen tissue derived from 3 healthy and 3 tumor endometrial tissues of post-menopausal patients. Raw paired-end fastq.gz files are provided.

  Dataset EGAD50000000200

• single cell RNA seq

  A selection of samples was analyzed using single-cell RNA sequencing to explore cellular heterogeneity. 4 inflammatory diseases were chosen for this purpose: Still’s disease, recurrent pericarditis, familial Mediterranean fever (FMF), and chronic non-bacterial osteomyelitis (CNO).

  Dataset EGAD50000002022

• Performance assessment of total RNA sequencing of human biofluids and extracellular vesicles

  SMARTer Stranded Total RNA-Seq method of human platelet-rich plasma, platelet-free plasma, urine, conditioned medium, and extracellular vesicles (EVs) from these biofluids. Including a titration experiment with spikes.

  Dataset EGAD00001006150

• Richter Syndrome RNA-seq dataset

  Raw FASTQ files for 77 RS + DLBCL + CLL samples. RNA-sequencing with single-end 50 nt reads.

  Dataset EGAD00001007922

• Bulk RNA data from Wilms Tumors

  Bulk RNA-seq data of pediatric Wilms tumors

  Dataset EGAD00001009298

• RNA-seq samples

  Raw FASTQ files obtained by RNA sequencing of tumor samples from patients (age 12-29) with newly diagnosed, recurrent intermediate or high-grade sarcoma.

  Dataset EGAD00001008393

• Genetic landscape of Extranodal NK/T-cell lymphoma

  Whole-exome sequence (WES) data of tumor-normal pairs from 40 ENKTCL patients and RNA sequence (RNA-seq) data of tumors from 20 ENKTCL patients.

  Dataset EGAD00001009852

• IL1R1+ cancer-associated fibroblasts drive tumor development and immunosuppression in colorectal cancer

  180502: RNA-Sequencing data of cocultured matched CRC patient (P4) derived normal fibroblasts (NFs), cancer associated fibroblasts (CAFs) and tumor spheroids. 200503_coculture: RNA-Sequencing data of cocultured CRC patient derived normal fibroblasts (NFs) or cancer associated fibroblasts (CAFs) (P16, P19, P22, P32, P41, P42) and tumor spheroids (HT29). 200503_il1b: RNA-Sequencing data of IL-1β stimulated fibroblasts (NFs and CAFs) Cole: scRNA-sequencing of matched CRC tumour samples and normal tissue counterparts derived from 3 patients. 220501: RNA-Sequencing of FACS sorted IL1R1 high and IL1R1 low CT5.3 CAFs

  Dataset EGAD00001010322

• Single-cell RNA sequencing of SarBC-01 treated with Dexamethasone vs DMSO, with or without Matrigel.

  This dataset contains raw FASTQ files from single cell RNA sequencing of SarBC-01 cells treated with Dexamethasone vs DMSO, with or without Matrigel, processed with MULTI-seq. Cells from 4 different culture conditions (+Mat/Dex, +Mat/DMSO, -Mat/Dex, -Mat/DMSO) were harvested, processed for multiplexing using the MULTI-seq protocol and loaded in a Chromium Single Cell 3ʹ GEM Library and Gel Bead Kit v3 (10x Genomics). Gene expression (cDNA) and MULTI-seq libraries were prepared according to the manufacturers’ protocol of Chromium Next GEM Single Cell 3’ reagents Kits v3.1 (Dual Index). Finally, cDNA and MULTI-seq libraries were analyzed using an Agilent Bioanalyzer (DNA High Sensitivity kit) and sequenced on a NovaSeq6000 (S2 flow cell) platform. MULTISEQ BARCODES: TTAGCCAG => Matrigel/DMSO CCACAATG => Matrigel/Dexamethasone GCACACGC => noMatrigel/DMSO AGAGAGAG => noMatrigel/Dexamethasone

  Dataset EGAD00001011155

• Datasets of RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial

  RNA-seq analyses were performed on tumor tissue samples of 115 advanced clear cell renal cell carcinoma patients who participated in the NIVOREN GETUG-AFU-26 trial. The samples were obtained prior to treatment initiation. RNA-seq was performed to evaluate previously published gene expression signatures. These included: the IMmotion T effector (CD8A, EOMES, PRF1, IFNG and CD274) and the IMmotion Myeloid (IL-6, CXCL1, CXCL2, CXCL3, CXCL8, and PTGS2) gene signatures represent gene expression patterns associated with T effector cells and myeloid cells, respectively, while JAVELIN Renal 101 Immuno (T-cell receptor signaling: CD3G, CD3E, CD8B, THEMIS, TRAT1, GRAP2, CD247; T-cell activation, proliferation, and differentiation: CD2, CD96, PRF1, CD6, IL7R, ITK, GPR18, EOMES, SIT1, NLRC3; Natural killer cell mediated cytotoxicity: D2, CD96, PRF1, CD244, KLRD1, SH2D1A; Chemokine: CCL5, XCL2; and Other immune response genes: CST7, GFI1, KCNA3, PSTPIP1) represents gene expression patterns associated with both innate and adaptive immune response.

  Dataset EGAD50000001541

• Genomic, epigenomic and transcriptomic profiling of GCTB

  This dataset contains primary raw data of whole-genome sequencing, whole-genome bisulfite sequencing, ATAC-seq, ChIP-seq (ChIP-mentation) of histone variants and modifications, as well as RNA-seq of giant cell tumor of bone tissue and primary cell line samples.

  Dataset EGAD00001005109

• G_WTS_001 data

  RNA-seq data from Korean CRC samples

  Dataset EGAD00001006985

• 20200417_PNET_methylation_paper

  Illumina platform RNA-seq data from 47 Pancreatic neuroendocrine tumour samples

  Dataset EGAD00001006063

• Single cell RNA seq component of ATAC-RNA multiome analysis of a four weeks post conception embryo head

  Four single-cell RNA libraries were generated from an unbiased sample of cells of a human four weeks post conception embryo using the 10X Chromium Single-Cell Instrument and NextGEM Single Cell Multiome ATAC+Gene Expression kit (10X Genomics) according to the manufacturer’s protocol.

  Dataset EGAD50000001501

• RNA-seq of cultured human hematopoietic stem and progenitor cells from umblical cord blood in cytokine-rich ex vivo culture conditions following sphingolipid modulation

  To elucidate the biological pathways altered by sphingolipid modulation with N-(4-hydroxyphenyl) retinamide (4HPR) treatment in human HSPC that may contribute to the restraint in proliferation while promoting persistence of HSC self-renewal as well as determine the mechanism of synergy in enhancement of HSC self-renewal with CB CD34+ agonists UM171 and StemRegenin 1 (SR1), we performed RNA-sequencing (RNA-Seq) of 3 pools of lin-CB cells following 2 or 4 days with DMSO, 4HPR, UM171+SR1 or 3-Factor (4HPR+UM171+SR1). We identified modulation of sphingolipid metabolism regulates self-renewal through activating coordinated stress pathways that coalesce on endoplasmic reticulum stress and autophagy programs.

  Study EGAS00001003756

• Discovery of cancer prognostic markers based on comparison of gene expression in colorectal cancer samples.

  Here, we analyse bulk mRNA-seq data derived from normal tissues adjacent to tumors (NATs) and tumour tissues of colorectal cancer (CRC), including 80 NAT samples and 80 tumour samples.

  Study EGAS00001005068

• The coding and non-coding transcriptional landscape of subependymal giant cell astrocytomas

  Tuberous sclerosis complex (TSC) is an autosomal dominantly inherited neurocutaneous disorder caused by inactivating mutations in TSC1 or TSC2, key regulators of the mechanistic target of rapamycin complex 1 (mTORC1) pathway. In the central nervous system TSC is characterized by cortical tubers, subependymal nodules and subependymal giant cell astrocytomas (SEGAs). SEGAs may lead to the impaired circulation of cerebrospinal fluid resulting in hydrocephalus and raised intracranial pressure in patients with TSC. Currently, surgical resection and mTORC1 inhibitors are the recommended treatment options for patients with SEGA. Here, we performed RNA-Seq and small RNA-Seq on SEGAs (n=19) and periventricular controls (n=8) to gain a better understanding of the underlying molecular basis of SEGAs, so that novel treatment targets could be identified.

  Study EGAS00001003787

• scRNA-seq of total bone marrow and T cells from multiple myeloma long-term survivors

  scRNA This dataset contains 50 scRNA-seq samples from bone marrow aspirates of 11 multiple myeloma patients experiencing long-term survival and 3 healthy donors. For each donor, total bone marrow and CD3+ T cells were sequenced. For multiple myeloma patients, paired samples were collected at initial diagnosis and between 7-17 years after first-line therapy. Bone marrow mononuclear cells were isolated by Ficoll density gradient centrifugation. For sorting of total bone marrow cells singlet, live cells were gated and sorted, for sorting of T cells CD45+, CD3+ cells were gated and sorted on either FACSAria Fusion or FACSAria II. Single-cell RNA sequencing were generated using 10x Genomics single-cell RNAseq technology (Chromium Single Cell 3’ Solution v2) according to the manufacturer’s protocol and sequenced on an Illumina HiSeq4000 (paired end, 26 and 74 bp). Bulk RNA Singlet, live CD3+CD4- CXCR3+CD8+ and CD3+CD4- CXCR3-CD8+ cells were sorted from 7 bone marrow and 3 peripheral blood samples of 7 multiple myeloma patients using a FACSAria Fusion machine. Bulk-RNA sequencing libraries were generated using the SMART Seq Stranded Total RNA-Seq kit (Takara) and sequenced using the Illumina NovaSeq 6000 platform (2 x 100 bp).

  Dataset EGAD00001010025

• Targeted_gene_fusion_sequencing__Fus_seq__in_mesothelioma

  This is a small pilot data set to test the feasibility of cDNA exomes across 1200 cancer cell line panel. cDNA exomes or Fus-seq is further explained in this studies Abstract.

  Study EGAS00001000390

• Single MII oocyte mRNA expression from women

  This dataset contains 14 paired-end FASTQ sequences from mRNA-Seq on single human M-II stage oocytes that were collected from ovarian tissue from unstimulated patients undergoing fertility preservation treatments due to cancer diagnoses, which did not influence ovarian function. Cumulus-oocyte-complexes were matured in vitro according Gruhn et al (Science 365: 1466-1469) and short term flash frozen prior to lysis, RNA extraction, full length cDNA preparation and amplification using the Ultra-low-input SMART-Seq2 v4 kit from Takara Clonetech. Further, these cDNA were used to prepare libraries for sequencing according the Nextera XT DNA library preparation kit from Illumina

  Dataset EGAD00001005971

• The Role of E2F4 in Controlling Resistance to Irinotecan (CPT-11) in Human Colon Cancer

  This study reports the results of RNA sequencing (RNA-seq) experiments performed on three isogenic clones of the human HT29 colon cancer cell line, genetically engineered to achieve the selective inactivation of the adenovirus early 2 (E2) gene transcription factor 4 (E2F4) protein, a key functional component of the multimeric transcriptional repression complex known as the dimerization partner (DP), retinoblastoma-like (RB-like), E2F and multi-vulva class B (MuvB) complex (DREAM). In previous studies, we identified E2F4 as a key regulator of colorectal cancer (CRC) resistance to irinotecan (CPT-11), a cytotoxic agent that stands at the backbone of multiple chemotherapy regimens for the treatment of metastatic CRCs. The molecular mechanisms linking E2F4 to irinotecan resistance, however, remain poorly understood. The present study was designed to identify which genes are under the transcriptional control of E2F4, either at baseline or following exposure to SN38 (i.e., the active metabolite of irinotecan, generated in vivo by biotransformation in the liver) in order to clarify the role played by E2F4 in shaping colon cancer resistance to chemotherapy. The cell line used for this study (HT29) is aneuploid and contains three copies of the E2F4 gene, because of a trisomy of chromosome 16, where the E2F4 gene is located (Kawai et al., Genes, Chromosomes & Cancer, 34:1-8, 2002; PMID: 11921276). HT29 cells were infected with lentivirus vectors encoding for CRISPR/Cas9 constructs designed to selectively inactivate the E2F4 gene, using three distinct guide-RNAs (gRNAs), each targeting a different sequence within the proximal exons of the E2F4 gene (exon 1, exon 2). Lentivirus-infected cells were sub-cloned by single-cell fluorescence-activated cell sorting (FACS), based on the differential expression of a fluorescent reporter (EGFP) expressed in tandem with the gRNAs. Isogenic clones (EGFP+) were then screened to identify those with a tri-allelic knock-out, as revealed by both genetic sequencing of the E2F4 gene (revealing the presence of three distinct frameshift mutations) and Western blot (revealing complete loss of E2F4 protein expression). The study includes twelve (n=12) RNA-seq experiments, representative of 3 experimental replicates (i.e., three distinct isogenic clones of the HT29 cell line, each displaying complete loss of E2F4 expression) and 3 negative controls (i.e., three independent preparations of the parent HT29 cell line, infected with a lentivirus vector encoding for a non-targeting gRNA) exposed to 2 distinct in vitro cell culture conditions: a) treatment with SN38 resuspended in dimethyl sulfoxide (DMSO); or b) treatment with DMSO alone (negative control). The in vitro treatment regimen used for SN38 (32 nM, 24 hours) was designed so that the exposure to SN38 experienced in vitro by HT29 cells would mirror the exposure to SN38 experienced in vivo by malignant tissues, as measured, for example, in metastatic CRC patients receiving a standard dose of irinotecan (180 mg/m2) administered by intravenous infusion over 90 minutes (Deyme et al., Cancer Chemotherapy and Pharmacology, 88:247-258, 2021; PMID: 33912999).

  Study phs003560

• 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).

  Dataset EGAD50000000105