10004 results for "cancer rna-seq"

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• RNA-Seq data of hepatoma (Huh7 derived) and Ph5CH cells and primary hepatocytes

  The innate immune response of cells of hepatic origin (Huh7, Huh7.5, PH5CH and primary human hepatocytes (PHH), 66 samples) was analyzed by transcriptome analysis (RNAseq) upon supernatant delivery or transfection of synthetic dsRNA (poly(I:C)). Expression of TLR3 and RIG-I was reconstituted by lentiviral transduction in Huh7 and Huh7.5 cells. The sequencing is single RNA-Seq on an Illumina HiSeq 4000 with the Illumina TruSeq stranded mRNA kit.

  Dataset EGAD00001007083

• Transcriptome profiling of three giant cell tumour of bone (GCTB) cell lines

  This dataset contains RNA-seq data of giant cell tumour of bone (GCTB) cell lines (n=3). Cell lines consist of neoplastic "stromal" cells harboring a heterozygous H3F3A p.G34W mutation. RNA-seq was performed on the BGISEQ-500 platform (PE100) and uploaded data contains fastq files, vcf files, and gene expression values (TPM). Cell lines, data generation, and data analysis are described in the following publication: Venneker et al., Histone deacetylase inhibitors as a therapeutic strategy to eliminate neoplastic “stromal” cells from giant cell tumors of bone, 2022.

  Dataset EGAD00001009074

• Transcriptome analysis of adolescents and young adults with Acute Lymphoblastic Leukemia

  The primary purpose of the research is identification of novel chromosome translocations in adolescents and young adults (AYA) with Acute Lymphoblastic Leukemia (ALL). We searched for novel chromosome translocations in 99 philadelphia-chromosome negative ALL cases (including 76 AYA cases) by RNA-seq using next-generation sequencers, and have discovered some novel chromosome translocations.

  Study JGAS000047

• Single-cell RNA-seq of immune cells from human tumor fragments after 48 hour culture ex vivo (Kaptein et al., 2024)

  Single-cell RNA-seq profiling of immune cells from human ovarian carcinoma, renal carcinoma and melanoma samples after 48h of ex vivo culture using the patient-derived tumor fragment platform (5 samples total). Samples were cultured in various conditions, including: untreated, CD8-IL2v-treated, CD8-IL2v + LCKi -treated, aPD1-treated, CD8-IL2v + aPD1 -treated, Untargeted IL2-treated, aCD3-treated and aCD3 + CD8-IL2-treated . FASTQ files contain gene expression data, feature barcode antibody capture or TCR data on immune cells from all conditions combined per patient.

  Dataset EGAD50000000377

• Genomic Profiling of Pediatric B-cell Acute Lymphoblastic Leukemia

  Pediatric leukemia is the most common type of childhood cancer and, despite tremendous progress in treatment, remains the second leading cause of cancer deaths in children. B-cell acute lymphoblastic leukemia (B-ALL) is the most common type of pediatric leukemia. Recent studies using transcriptional profiling of large cohorts of pediatric B-ALL have shown that patients can be grouped into transcriptional subtypes that are often defined by specific driver mutations. Interestingly, many of these mutational subtypes are defined by gene fusions or rearrangements that drive altered expression of transcription factors (ETV6-RUNX1, PAX5, DUX4, TCF3-PBX1, ZNF384) or in chromatin regulatory machinery (KMT2A), suggesting that transcriptional dysregulation is a major driver of B-ALL. While the transcriptional distinctions are clear, the relationship between patients in terms of their chromatin regulatory landscape remains unclear. To address this, we profiled gene expression, open chromatin, and 3D genome folding in patient derived B-ALL samples. We identified that at the level of 3D genome organization, many chromatin interactions and looping events are shared across mutational subtypes, suggesting that shared transcriptional programs, in addition to group specific driver mutations, possibly regulate the chromatin landscape in B-ALL. Using RNA-seq and ATAC-seq data, we were able to identify "latent" signatures of expression related to non-mutant transcription factors (TFs) that also contribute to expression heterogeneity across TF subtypes. These are related to patient specific patterns of 3D genome folding, and in some cases, are predictive of disease outcomes. This study helps shed light on the chromatin landscape in B-ALL and furthers our understanding of the interactions between diverse mutant TFs that drive B-ALL and non-mutant TFs that help shape the B-ALL chromatin landscape.

  Study phs003226

• PACA-CA RNASeq bam files

  Bam files for PACA-CA RNA Seq analysis, for DCC release 27

  Dataset EGAD00001003945

• SF4324 Primary Wildtype GBM Female, 57.

  Single Cell RNA-Seq of Primary GBM. Gender Female, Age, 57.

  Dataset EGAD00001006017

• Follicular T cell lymphoma

  Paired-end RNA-seq of follicular T cell lymphoma for the discovery of fusion transcripts

  Dataset EGAD00001006379

• Facioscapulohumeral muscular dystrophy (FSHD): RNA-seq of isogenic TIRM+, TIRM- muscle and PBMCs from patients and matched controls

  FASTQ files describing paired-end RNA-sequencing of isogenic TIRM+ and TIRM- muscle biopsies from 24 FSHD patients (48 samples) and vastus lateralis muscle biopsies from 11 matched control individuals. FASTQ files are also provided describing RNA-sequencing of 15 FSHD peripheral blood mononuclear samples and 14 matched controls. For muscle biopsies sequencing was at 21.7-35.5 million reads/sample. RNA was extracted from PBMCs followed by globin depletion with sequencing at 19.7-46.5 million reads/sample.

  Dataset EGAD00001011077

• RNA-seq data from 27 glioblastoma samples

  27 Fresh frozen tissue specimens were crushed by mortar and pestle, homogenized using the QIAShredder kit (Qiagen), and genomic DNA and total RNA were extracted using the AllPrep DNA/RNA Mini kit (Qiagen), according to the manufacturer’s instructions. RNA libraries were synthesized using 200 ng of total RNA using the Ilumina TruSeq Stranded RNA LT Sample Prep Kit (Illumina), and subsequently sequenced on the NextSeq550 platform to a read depth of 80 million clusters and 160 million paired end reads (75 bp X 75 bp) using V2 chemistry.

  Dataset EGAD00001008362

• RNA seq before and after cold pressor test

  The cold pressor test (CPT) is a widely used pain provocation test to investigate both pain tolerance and cardiovascular responses. Twenty-two females were phenotypically assessed before and after a CPT, and blood samples were taken for RNA-sequencing.

  Study EGAS00001006690

• 110 "KOREAN" never-smoker female adenocarcinoma RNA-seq

  All sequencing was performed within the DNAlink (Korea) by using the Solexa sequencing technology (Illumina, San Diego, CA). mRNA was isolated from total RNA using poly-T oligo-attached magnetic beads and was fragmented with fragmentation buffer to an average size of 300 bp. The libraries were prepared by using TruSeq RNA Library Prep Kit v2 (Illumina) and were sequenced on the Illumina HiSeq2000 using the manufacturer’s recommended protocols

  Dataset EGAD00001005358

• RNA-seq of atypical 3q26 samples

  RNA was isolated using phenol-chloroform extraction followed by DNase digestion or using the Qiagen Allprep DNA/RNA kit and protocol (Qiagen, #80204). cDNA synthesis was done using the SuperScript II Reverse Transcriptase kit (Invitrogen). Quantitative real-time PCR was performed by using primers as described previously13,21 on the 7500 Fast Real-time PCR System (Applied Biosystems). Relative levels of gene expression were calculated using the ΔΔCt method

  Dataset EGAD00001006106

• RNA-seq of multiple myeloma patient samples

  RNA from CD138+ plasma cells from patients with a plasma cell dyscrasia were sequenced using the TruSeq Stranded Total RNA Ribo-zero Gold kit (Illumina). Paired-end 75bp reads were generated on a NextSeq500 or HiSeq4000 (Illumina). The dataset consists of 1 MGUS sample, 5 SMM samples, 69 newly diagnosed myeloma samples, 1 relapsed myeloma sample, 1 previously treated myeloma samples, and 4 PCL samples. Matching whole genome sequencing data are available for these samples under study EGAS00001003164.

  Dataset EGAD00001004543

• Single Cell and Spatial Transcriptomic Profiling of Haemophilus ducreyi Infection

  We investigated the immune response in end-point pustules formed by Haemophilus ducreyi in volunteers using an experimental infection model. Six volunteers were infected in the skin of the upper arm at three sites with 41-85 CFU of H. ducreyi loaded on an allergy testing device; a sham-inoculated (e.g., wound) site was also performed. Five volunteers (4 men and 1 woman; 2 Asians and 3 Whites; aged 27-46 years) formed pustules 6-8 days post infection; 1 volunteer spontaneously resolved all sites. If a volunteer formed pustules, biopsies were performed to collect their pustule and wound sites. Biopsy pairs for all 5 pustule formers were subjected to single cell (sc) RNA-seq. Sequencing libraries were prepared using the 10X Genomics Single-cell 3' RNA-seq kit. Spatial transcriptomics was performed on biopsy pairs from 4 of the 5 pustule formers. Ten micron sections were placed on 10X Genomics Visium slides for fresh-frozen tissue, and libraries were prepared with the 10X Genomics Visium spatial 3' gene expression kit. All samples were sequenced on an Illumina NovaSeq 6000. Count tables were produced with CellRanger and SpaceRanger, respectively, and Seurat was used to analyze the data. We identified 13 major cell types by scRNA-seq; the proportion of some immune cell subsets was increased in pustules compared to wound sites. We also localized the major cell types within the tissue by using the scRNA-seq data to deconvolve the spatial transcriptomic data. The FASTQ files and count tables from CellRanger and SpaceRanger are provided.

  Study phs003754

• Somatic Mutations in Single Human Neurons from Patients with Congenital Neurodegenerative Diseases

  It has been hypothesized that accumulating DNA lesions in neurons contribute to aging and neurodegeneration. Despite their pathophysiological importance, the DNA lesions have not been systematically examined with effective methods. In this study, we developed a computational method for detecting genomic deletions in single-cell whole-genome sequencing (scWGS) data, and analyzed the whole genome of human single neurons. Single neurons were obtained from neurotypical individuals of various ages and from patients with three different congenital neurodegenerative diseases: Ataxia telangiectasia (AT), Cockayne syndrome (CS), and Xeroderma pigmentosum (XP). Single-neuron WGS data of AT brains are released here, and the data of other two diseases are released in a separate dbGaP study (phs001485).To understand the molecular mechanisms underlying AT, we performed single-nucleus RNA-sequencing (snRNA-seq) of postmortem cerebellar vermis and prefrontal cortex from individuals with AT and controls. To genetically confirm the diagnosis of AT, we also performed WGS on postmortem brain tissue from each individual with AT. Induced pluripotent stem cells (iPSCs) from individuals with AT and controls were differentiated into microglia, and the transcriptomes were profiled with bulk RNA-sequencing (RNA-seq).

  Study phs003005

• SF10432 Wildtype Primary GBM Female, 50

  Single Cell-RNA Seq of Wildtype Primary GBM for Female, Age 50.

  Dataset EGAD00001006019

• PDAC organoid genomic heterogeneity

  Two primary tumor-derived PDAC organoids were subjected to SNP array, RNA-seq, and single-cell WGS

  Dataset EGAD00010002408

• ChIP-seq in colorectal cancer and paired adjacent normal mucosa

  This dataset includes ChIP-seq data for H3K27ac and H3K4me1 on 20 paired samples of colorectal cancer and adjacent normal mucosa. One tumor sample that failed QC is not available.

  Dataset EGAD00001007707

• Contribution of systemic and somatic factors to clinical response and resistance in urothelial cancer: an exploratory multi-omic analysis

  Patients with metastatic urothelial cancer (n=29) were treated with atezolizumab (anti-PD-L1). All 29 patients had T-cell receptor sequencing (TCR-seq) of the pre-treatment blood; 24 also had TCR-seq on at least one post-treatment blood sample. 24 patients had TCR-seq of their pre-treatment tumors. TCR-seq data can be found at http://doi.org/10.5281/zenodo.546110. 26 patients also had RNAseq of their tumors and whole exome sequencing (WES) of their tumors and matched normal blood. WES results for one sample were excluded from our analysis after failing to meet coverage requirements.

  Study phs001743

• Validated Single-cell RNA sequencing in early breast cancer

  Single-cell RNA and VDJ sequencing of early breast cancer

  Dataset EGAD00001006608

• Immune Responses in Checkpoint Myocarditis Across Heart, Blood, and Tumor

  Immune checkpoint inhibitors (ICIs) are widely used in anti-cancer therapies, but they can cause morbid and potentially fatal immune-related adverse events (irAEs), such as ICI-related myocarditis (irMyocarditis). The pathogenesis of irMyocarditis and its relationship to anti-tumor immunity remain poorly understood. We sought to define immune responses in heart, tumor, and blood in irMyocarditis patients and controls by leveraging single‐cell RNA sequencing (scRNA‐seq) coupled with T-cell Receptor Sequencing (TCR-Seq). Our analysis demonstrated increased frequencies of cytotoxic T cells, inflammatory mononuclear phagocytes (MNPs), conventional dendritic cells (cDCs), and inflammatory fibroblasts in irMyocarditis heart tissue. Additionally, we revealed decreased frequencies of plasmacytoid dendritic cells, cDCs, and B lineage cells but an increased frequency of MNPs in the blood of irMyocarditis patients. Raw data for heart and blood can be found in dbGaP. All processed data and raw TCRseq data from heart tissue and tumor samples for this study can be found in GEO (Accession number GSE228597).Subject IDs with the prefix "SIC" were collected by the Severe Immunotherapy Complications (SIC) service at MGH due to suspicion of immune-related adverse events. Subject IDs with the prefix "donor" were collected by the MGH Melanoma Biobank at scheduled timepoints; this biobank systematically collects samples from patients at MGH at clinically relevant timepoints.

  Study phs003413

• Transcriptome sequencing of gingivo-buccal oral squamous cell carcinoma for integrative analysis: alterations in expression of genes attributable to methylation changes

  Gingivo-buccal oral squamous cell carcinoma (OSCC-GB) is the most common cancer among men in India and is associated with high mortality. Although OSCC-GB is known to be quite different from tongue cancer in its genomic presentation and its clinical behavior, it is treated identically as tongue cancer. Predictive markers of prognosis and therapy that are specific to OSCC-GB are, therefore, required. To achieve this, we have carried out transcriptome (n=72) profiling of paired tumor-normal tissues collected from OSCC-GB patients from India. RNA sequencing was performed on tumor and paired adjacent normal samples from 72 OSCC-GB patients. From each patient, total RNA was extracted from tumor and normal tissue samples using AllPrep DNA/RNA Mini Kit (QIAGEN). The quality and concentration of isolated total RNA were checked using Agilent 2100 Bioanalyzer and NanoDrop 2000 (Thermo Fisher Scientific). The OD260/OD280 ratio was ≥ 2 and RNA Integrity Number (RIN) was ≥ 7.0 for all sequenced samples. Ribosomal RNA (rRNA) was removed from the RNA samples, using Ribo-Zero Magnetic Kit (Epicentre). Sequencing libraries were prepared from rRNA depleted samples using TrueSeq RNA Sample Preparation Kit (Illumina). Each triplex cDNA library pool was sequenced as 100bp paired-end on HiSeq-2000 or HiSeq-2500 (Illumina). Protocols suggested by the manufacturers were used for all assays.

  Study EGAS00001003893

• Characterizing the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft model for RNA-based liquid biopsy in a preclinical setting

  This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n=171) derived from a DLBCL PDTX model including 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX NOD-scid IL2Rgnull mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either R-CHOP, huCD20-Fc-AFN-CHOP, or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform using the SMARTer Stranded Total RNA-seq pico v3 kit.

  Study EGAS50000000566

• Transcriptome (RNA-seq) data for the validation of the glioblastoma progression study (GBMatch).

  37 transcriptomes derived from fresh-frozen glioblastoma tumor samples. These transcriptomes have been produced for validation purposes and match the corresponding RRBS and WGS profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004076