7190 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

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• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Resveratrol from donor D2, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008071

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Resveratrol from donor D2, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008072

• Transcriptome of human CD4+ T-lymphyocyte (memory-T-cells) treated with Resveratrol from donor D1, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008039

• Transcriptome of human CD4+ T-lymphyocyte (memory-T-cells) treated with Resveratrol from donor D1, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008040

• Transcriptome of human CD4+ T-lymphyocyte (memory-T-cells) treated with Rotenone from donor D1, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008041

• Transcriptome of human CD4+ T-lymphyocyte (memory-T-cells) treated with Rotenone from donor D1, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008042

• Transcriptome of human CD4+ T-lymphyocyte (memory-T-cells) treated with Oligomycin from donor D1, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008043

• Transcriptome of human CD4+ T-lymphyocyte (memory-T-cells) treated with Oligomycin from donor D1, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008044

• Transcriptome of human CD4+ T-lymphyocyte (memory-T-cells) treated with Oligomycin from donor D1, replicate 1, glucose concentration 1mM

  Dataset EGAD00001008045

• Transcriptome of human CD4+ T-lymphyocyte (memory-T-cells) treated with Oligomycin from donor D1, replicate 2, glucose concentration 1mM

  Dataset EGAD00001008046

• Transcriptome of human CD4+ T-lymphyocyte (memory-T-cells) treated with Resveratrol from donor D2, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008049

• Transcriptome of human CD4+ T-lymphyocyte (memory-T-cells) treated with Resveratrol from donor D2, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008050

• Transcriptome of human CD4+ T-lymphyocyte (memory-T-cells) treated with Rotenone from donor D2, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008051

• Transcriptome of human CD4+ T-lymphyocyte (memory-T-cells) treated with Rotenone from donor D2, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008052

• Transcriptome of human CD4+ T-lymphyocyte (memory-T-cells) treated with Oligomycin from donor D2, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008053

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Oligomycin from donor D3, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008087

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Oligomycin from donor D3, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008088

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Rotenone from donor D3, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008089

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Rotenone from donor D3, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008090

• Transcriptome of human CD4+ T-lymphyocyte (regulatory-T-cells) treated with Resveratrol from donor D3, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008078

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Oligomycin from donor D1, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008079

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Oligomycin from donor D1, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008080

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Rotenone from donor D1, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008081

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Rotenone from donor D1, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008082

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Oligomycin from donor D2, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008083

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Oligomycin from donor D2, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008084

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Rotenone from donor D2, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008085

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Rotenone from donor D2, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008086

• Transcriptome of human CD4+ T-lymphyocyte (regulatory-T-cells) treated with Resveratrol from donor D2, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008073

• Transcriptome of human CD4+ T-lymphyocyte (regulatory-T-cells) treated with Resveratrol from donor D2, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008074

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Resveratrol from donor D3, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008075

• Transcriptome of human CD4+ T-lymphyocyte (naive-T-cells) treated with Resveratrol from donor D3, replicate 2, glucose concentration 5mM

  Dataset EGAD00001008076

• Transcriptome of human CD4+ T-lymphyocyte (regulatory-T-cells) treated with Resveratrol from donor D3, replicate 1, glucose concentration 5mM

  Dataset EGAD00001008077

• Multi-Modal Single-Cell, Spatial, and Genomic Analyses of Human Non-Small Cell Lung Cancer Brain Metastases

  We performed single nuclei RNA-sequencing (snRNA-seq) with matched T cell receptor sequencing (TCR-seq), and pool matched low pass whole genome sequencing (WGS) of 12 treatment-naive non-small cell lung cancer (NSCLC) primary tumors (PTs) and 31 treatment-naive NSCLC brain metastases (BMs). In total, we recovered 277,206 cell transcriptomes in 43 samples. Single-nuclei suspension from frozen NSCLC metastases were generated using methods published in Slyper et al. (Nature Medicine, 2020, PMID:32405060) with modifications. The tissue was first cut in 20 µm sections using a cryostat and stored on dry ice until the next step. Then the tissue was put on wet ice and washed once with 5 ml PBS to remove OCT. After this step nuclei were extracted by vigorous pipetting in salt-tris buffer with Tween-20 (TST) followed by a high-volume wash in salt-tris buffer (ST). Nuclei were counted and 10,000-14,000 and were loaded using a Chromium controller (10X genomics) and Chromium Single Cell 5' Reagents (V1.1 and V2). Complementary DNA libraries were generated according to manufacturer's instructions, with the modification of one additional cycle of amplification. Matched single nuclei T cell receptor (snTCR) sequencing libraries were prepared from amplified cDNA libraries using either Chromium Single Cell V(D)J Enrichment Kit for human T cells Reagent Kit, v1.1, or single cell human TCR amplification kit. Final snTCR sequencing libraries were prepared using Single Index Kit T Set A for V1.1 libraries or Library construction kit and Dual Index Kit TT set A for V2 libraries. Sequencing libraries were quantified using Tapestation D5000 reagents and a 2200 TapeStation and pooled for sequencing. Pool matched low pass whole-genome sequencing (lp-WGS) was performed in addition to snRNA-seq to improve the identification of the malignant and non-malignant cell compartments. Nuclei from snRNA-seq sample preparations were collected by centrifugation (500g, 5 min), snap frozen after removing excess ST buffer, and stored at -200C until further processing. If insufficient nuclei (0C for 9 minutes. Adapters were not diluted, and the optional PCR (5 cycles) and cleanup were performed. After library cleanup with AMPure beads (Beckman Coulter, Brea, CA), libraries were quantified with Tapestation D5000 HS tapes (Agilent) and stored at -200C until sequencing.Using multiplexed immunofluorescence in an independent cohort of treatment-naïve pairs of primary tumors and brain metastases from the same patients with NSCLC, we validated genomic and tumor-microenvironmental findings and identified a cancer cell population characterized by neural features that strongly enriched in brain metastases. This comprehensive analysis provides insights into human NSCLC brain metastasis biology and serves as an important resource for additional discovery.

  Study phs003865

• Cryptococcosis in Previously Healthy Adults

  Cryptococcus is a fungus that causes infections most commonly in immunocompromised patients, such as those with AIDS and solid organ transplant recipients and is currently responsible for an estimated 15% of all AIDS-related deaths globally. However, in developed countries, approximately one-third of cases fall outside these groups such that cryptococcal meningoencephalitis (CM) has become the most common cause of non-viral meningitis in the U.S. Within the U.S., approximately 15-20% have no readily identifiable immune defect and cryptococcal infection in these hosts has a mortality rate of 30-50% despite optimal antifungal therapy. NIH Clinical Study Protocol 93-I-0106 (NCT00001352). The objectives of this protocol can be broadly categorized as: 1) Characterize the immunologic and genetic mechanisms predisposing to disease acquisition; 2) Understand the post-infectious inflammatory response and distinguish its consequences from those directly due to fungal growth; and 3) Management of post-infectious neuro-inflammatory syndromes associated with cryptococcal meningitis (CM). This protocol recruits patients who have microbiological evidence of cryptococcal neurologic or non-CNS disease (typically pulmonary or bone). Cerebrospinal fluid (CSF) and blood samples collected during clinical care are used to measure serum and CNS cellular and soluble cytokines as well as to perform in-situ immunohistochemistry. CSF and blood samples are also collected to measure transcriptional (gene expression), proteomic (protein), and lipidomic (lipids) changes that occur throughout disease and treatment. Observational data detailing audiological, ophthalmological and neurocognitive deficits in these patients is also recorded. We have recently described a post-infectious inflammatory syndrome (PIIRS) associated with cryptococcal meningoencephalitis (CM) which can be best described as a neuro-inflammatory state during which CM patients present with altered mental status (Montreal Cognitive Assessment Score As part of the protocol, we treat patients for either microbiological failure or neuroinflammatory sequelae by conventional therapies utilizing FDA-approved pharmaceuticals at FDA-approved doses. To understand and identify the predominant biological pathways responsible for PIIRS neuroinflammation, we examined patient CSF at baseline (at time of PIIRS diagnosis) and post-treatment with different FDA-approved pharmaceuticals at FDA-approved doses compared to CSF from non-PIIRS donors. Upstream pathway analysis of differentially expressed genes in the CSF of PIIRS patients revealed a prominent role for the JAK/STAT pathway in the pathogenesis of PIIRS and support the use of the JAK inhibitor, ruxolinib, as a pathway-instructed therapy to treat PIIRS patients. Data available through dbGaP: single cell RNA sequencing (scRNA-seq) data from CSF cells of a patient with PIIRS at the time of diagnosis and following treatment with steroids (1g solumedrol/day) and NanoString transcriptional data from CSF cells of patients with PIIRS at the time of diagnosis compared to CSF cells from non-PIIRS donors.

  Study phs003871

• Beyond BRCA deficiency: Clinical and molecular predictors of survival in patients with BRCA-deficient tubo-ovarian high-grade serous carcinoma

  Homologous recombination DNA repair deficient (HRD) tumors account for about 50% of tubo-ovarian high-grade serous carcinomas (HGSC) and are associated with a high response to platinum-based chemotherapy. However, a subset of patients with HRD tumors have unexpected resistance to chemotherapy and experience short survival. Our study compared BRCA-deficient and proficient HGSC among patients with short (<3 years, the lowest quartile of overall survival (OS)) versus longer-term (>3 year OS) to identify prognostic markers and potential therapeutic opportunities. Primary tumors from a cohort of patients with advanced-stage HGSC (n=154) enriched for those with HRD tumors and short survival (n=42) were analyzed using whole-genome sequencing, bulk RNA-sequencing, and DNA methylation profiling. A subset of HRD tumors (n=143) were characterized for immune cell densities by multiplex immunofluorescence. Clinicopathological features were assessed in 1,389 patients with HGSC, including 282 with pathogenic germline BRCA variants (gBRCApv). Findings were validated in two international HGSC cohorts: the Ovarian Tumor Tissue Analysis consortium (n=5,875) and Multisciplinary Ovarian Cancer Outcome Group (n=895). In gBRCApv-carriers, residual disease following surgical cytoreduction was not associated with shorter OS unlike in non-carriers where it was strongly associated. While most patients with gBRCApv had a more favorable OS compared to non-carriers, a survival advantage was not apparent in those with variants located outside of BRCA1 exon 10/23 and BRCA2 exon 11/27. Patient survival correlated with HRD score, such that those with a score ≥63 had significantly longer OS compared to those with HRD scores of 42-63 and <42. While higher HRD scores were associated with better survival outcomes, most gBRCApv carriers with a short survival had tumor HRD scores that exceeded the threshold typically considered predictive of a good response to carboplatin or PARP inhibitors. BRCA2-deficient HGSC with loss of the tumor suppressor NF1 was associated with exceptionally favorable outcome (median OS 17 years), whereas amplification of both PIK3CA and RAD21, was associated with poor outcome in BRCA2-deficient HGSC (median OS 2.9 years). The density of tumor-infiltrating CD8+ PD-1+ T cells was prognostic for OS in gBRCApv-carriers. In summary, rather than simply the presence or absence of a germline BRCA pathological variant influencing patient survival, the co-occurrence of specific somatic gene alterations, the extent of immune cell infiltration, the level of homologous recombination deficiency, and BRCA-variant location may modify clinical outcomes in patients with BRCA-deficient HGSC. Analysis of exceptional outcome patients, in this case gBRCApv-carriers with an atypically short survival, may identify determinants of outcome applicable to the wider HGSC patient population.

  Study EGAS00001008059

• ICGC MMML-seq Data Freeze November 2012 transcriptome sequencing

  ICGC MMML-seq Data Freeze November 2012 transcriptome sequencing

  Dataset EGAD00001000281

• Spatially resolved TME alterations in GCPM

  Whole exome sequencing of 66 gastric samples and whole transcriptome sequencing of 191 gastric samples.

  Dataset EGAD50000000715

• Whole exome and transcriptome sequencing of BPDCN

  This data set contains whole exome and transcriptome data from 47 case with BPDCN. For exome data, bam files are provided (mapped against GRCh38), for transcriptome raw fastq-files (paired-end data).

  Dataset EGAD00001008692

• ICGC MMML-seq Data Freeze March 2013 transcriptome sequencing

  ICGC MMML-seq Data Freeze March 2013 transcriptome sequencing

  Dataset EGAD00001000356

• _RNAseq___Colorectal_organoids_and_tumoroids

  Transcriptome sequencing of tumour tissue, adjacent normal tissue and derived organoids/tumoroids from colorectal cancer

  Study EGAS00001000985

• Leeds Paired Primary and Recurrent GBM RNAseq

  Whole transcriptome, strand-directional RNAseq data for paired primary dn recurrent samples from patients with glioblastoma

  Dataset EGAD00001005224

• 64 RNAseq BAMs in the HF-GBM-Tumor-Neurosphere-Xenograft study

  Whole transcriptome sequencing generated from patient, neurosphere and xenograft samples

  Dataset EGAD00001002214

• single cell transcriptome data of gluten-specific T cells

  The data contains paired-end fastq files of 1440 single cells transcriptome sequencing data from 4 Celiac disease patients. CD4+ T cells were sorted by HLA-DQ-gluten tetramers carrying four immunodominant gluten epitopes. All single cell libraries were constructed following SmartSeq2 and sequenced on Illumina NextSeq 500.

  Dataset EGAD00001007975

• Dataset for transcriptome and whole genome bisulfite sequencing of glioblastoma(GBM) tumor cells

  This dataset contains transcriptome and whole genome bisulfite sequencing for 40 samples with glioblastoma(GBM). The sequencing was performed on Illumina NextSeq 2000 and Illumina NextSeq 550, . The sequencing was always paired.

  Dataset EGAD00001015614

• Whole exome sequencing (WES), shallow whole genome sequencing (sWGS), ultra-deep targeted sequencing (TS), RNA whole transcriptome sequencing (RNAseq), targeted TCR sequencing in RNA (RNA-TCRseq) from breast cancer samples.

  Whole exome sequencing (WES), shallow whole genome sequencing (sWGS), ultra-deep targeted sequencing (TS), RNA whole transcriptome sequencing (RNAseq) bam files. Targeted TCR sequencing in RNA (RNA-TCRseq) cram files.

  Dataset EGAD00001003933

• Whole-genome and transcriptome sequencing of seven patients with gene therapy-induced T-cell acute lymphoblastic leukemia

  Dataset EGAD00001006016

• Transcriptome of (peripheral blood), from donor Sample B, replicate 2 time-course biological replicates; 10x lane replicate 3

  time-course biological replicates; 10x lane replicate 3

  Dataset EGAD00001010093

• Transcriptome of (peripheral blood), from donor Sample B, replicate 1 time-course biological replicates; 10x lane replicate 3

  time-course biological replicates; 10x lane replicate 3

  Dataset EGAD00001010092

• Transcriptome of (peripheral blood), from donor Sample B, replicate 1 time-course biological replicates; 10x lane replicate 1

  time-course biological replicates; 10x lane replicate 1

  Dataset EGAD00001010088