12215 results for "cancer rna-seq"

in 19.96 milliseconds.

• RNA-seq data in hMPC, MSC_Pat and EWIma

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic and epigenetic hallmarks of EwS.

  Study EGAS50000001173

• Oropharynx cancers sequencing study (RNA-seq from FFPE)

  This is a study of transcriptomics in HPV-associated oropharynx tumors. The goals of this study were to characterize HPV+ oropharynx tumor subtypes and to examine HPV integration events and their downstream effects. HPV-host fusion transcripts and recurrent HPV integration genes were identified. Various alternative isoforms and splicing events of HPV genes were also studied. Multiple potential biomarkers of prognosis were associated with clinical outcomes.

  Study EGAS50000000893

• Transcriptomic response of miRNAs of monocytes to bacterial and viral stimuli assessed by RNA-seq in Africans and Europeans

  Leveraging the miRNA transcriptome of 977 samples, the study aims to define the levels of miRNA and isomiR diversity across individuals and populations, explore the genetic sources of miRNA expression variability and miRNA-environment interactions, evaluate the effects of immune challenges upon miRNA and isomiR expression dynamics, and quantify the relative impact of transcription and miRNA-mediated degradation on gene expression variability.

  Study EGAS00001004192

• scMultiome (snRNA + snATAC) data of 26 regionally sampled GBM tissue from 6 patients

  This dataset contains snRNA-seq data of 26 regionally sampled GBM tissue (peritumoral region, tumor edge, and tumor core). Regionally sampled GBM patient tissue was dissociated and nuclei were processed unsorted or by sorting with 7AAD to remove debris and dead cells. Single-nuclei suspension was prepared following the nuclei isolation protocol Single Cell Multiome ATAC + Gene Expression Sequencing protocol using Chromium Nuclei Isolation Kit. Single-nuclei suspension was prepared following the nuclei isolation protocol Single Cell Multiome ATAC + Gene Expression Sequencing protocol using Chromium Nuclei Isolation Kit, nuclei were barcoded and RNA and ATAC libraries were constructed, allowing for simultaneous capture of transcriptome and epigenome from the same cells.

  Dataset EGAD50000001838

• Whole blood RNAseq from a large ALS case-control study at Univ of Michigan

  This dataset consists of 694 bulk RNA-seq data (sorted aligned BAM files) from whole blood of ALS participants meeting the Gold Coast definition of ALS during their clinical visit (n=422) and healthy controls (n=272) at the University of Michigan (UM). Samples were collected as part of the UM Pranger ALS Clinic between 2011-2021, and prepared either using poly-A selection of rRNA depletion (see Experiments). RNAseq was performed on the NovSeq 6000 S4 at the UM Advanced Genomics Core, resulting in 150bp paired-end reads. Raw reads were trimmed using Cutadapt (v2.3) and aligned to hg38 using STAR (v2.5.3a). Age provided is the age at blood sample collection date.

  Dataset EGAD50000001488

• ICGC PCAWG Dataset: LIRI-JP_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: LIRI-JP.

  Dataset EGAD00001003546

• ICGC PCAWG Dataset: LIRI-JP_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: LIRI-JP.

  Dataset EGAD00001003547

• ICGC PCAWG Dataset: CLLE-ES_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: CLLE-ES.

  Dataset EGAD00001003548

• ICGC PCAWG Dataset: CLLE-ES_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: CLLE-ES.

  Dataset EGAD00001003549

• ICGC PCAWG Dataset: RECA-EU_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: RECA-EU.

  Dataset EGAD00001003558

• ICGC PCAWG Dataset: RECA-EU_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: RECA-EU.

  Dataset EGAD00001003559

• ICGC PCAWG Dataset: MALY-DE_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: MALY-DE.

  Dataset EGAD00001003560

• ICGC PCAWG Dataset: MALY-DE_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: MALY-DE.

  Dataset EGAD00001003561

• Cell line data (RNAseq, ATACseq, ChIPseq)

  Content: 2 GB RTK I cell lines (LN229, ZH487) in two conditions (NT control and shSOX10). RNAseq: single replicates per condition, polyA+ RNA sequencing, SE. ATACseq: biological replicates per condition, SE. ChIPseq (histone H3 modifications, LN229 only): all marks for each condition were pooled and sequenced on two lanes for each pool. ChIPseq (BRD4 and SOX10): SOX10 libraries were sequenced on single lanes. BRD4 samples were multiplexed and sequenced in two lanes. ChIPseq input samples are also included. Data type and technology: RNAseq: SE 50bp sequenced on HiSeq2000/4000. ATACseq: SE 50bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000.

  Dataset EGAD00001005493

• Single-cell RNA-seq of peripheral blood mononuclear cells in classic Hodgkin lymphoma

  Abstract: Classic Hodgkin lymphoma (cHL) is a largely MHC class I-negative tumor with recurrent 9p24.1/ PD-L1/ PD-L2 copy gains and the highest reported response rates to PD-1 blockade. We utilized scRNA sequencing to characterize the peripheral immune response to PD-1 blockade and more broadly define non-CD8+ dependent mechanisms of immune evasion in cHL. Peripheral blood mononuclear cells were obtained from 20 patients with relapsed/refractory (R/R) cHL treated with PD-1 blockade (nivolumab) on the CheckMate 205 clinical trial (paired samples from cycle 1 day 1 [C1D1] and cycle 4 day 1 [C4D1]), 11 patients with newly diagnosed, previously untreated cHL and 13 healthy donors.

  Dataset EGAD00001011360

• Targeted Linked-Read DNA-seq Analysis of Castration-Resistant Prostate Cancers

  Androgen receptor (AR) inhibition is standard of care for advanced prostate cancer (PC). However, its efficacy is limited by progression to castration-resistant PC (CRPC), usually due to AR re-activation via mechanisms that include AR amplification and structural rearrangement. These two classes of AR alterations often co-occur in CRPC tumors, but it is unclear whether this reflects intercellular or intracellular heterogeneity of AR. It is important to resolve the mechanisms of AR genomic rearrangements to develop new therapies and predictive biomarkers for PC. We developed a targeted linked-read DNA sequencing assay to interrogate alterations in AR and a panel of genes known to be amplified or mutated in CRPC. Linked-read DNA-sequencing libraries were generated using the 10X Genomics Chromium platform and subjected to hybridization enrichment using a custom-designed Agilent SureSelect bait panel. Post-capture DNA-seq libraries were pooled and sequenced on an Illumina HiSeq 2500 using 2x150 bp settings. This targeted linked-read DNA-seq assay was used to interrogate a set of 6 benchmarking samples harboring known AR gene rearrangements and other alterations in AR, as well a panel of 6 patient-derived xenograft CRPC tumors and 23 clinical CRPC tumors. In this cohort, we identified a subset of samples that developed complex, multiply-rearranged AR gene structures in conjunction with very high AR copy number. The data that will be made available through dbGaP are raw FASTQ files.

  Study phs003343

• Genomic Analysis of Head and Neck Cancers

  These aggregate studies focus on specimens from head and neck squamous cell carcinoma (HNSCC) patients who were treated with standard of care or window of opportunity clinical trial approaches. Specimens were interrogated with exome and RNA-Seq analysis. Patient derived xenografts (PDXs) represent a robust platform for performing co-clinical trial approaches. In the first study we generated a large panel of PDXs and compared genomic profiles between the primary tumor and matched PDX with the patients blood serving as a source of somatic variants. In the second study, we performed a window of opportunity clinical trial in oral cavity squamous cell carcinoma patients using the MEK inhibitor trametinib. In addition, PDX models were generated from these specimens also and analyzed as in the first study. Finally, the third approach used pembrolizumab, an anti-PD1 blocking antibody, in a window of opportunity setting in HNSCC patients. For the latter two studies genomic matched sample analysis was performed to define response and resistance mechanisms. Together, these genomic data will inform several therapeutic approaches for HNSCC patients.

  Study phs001623

• Characterization of Immune Evasion in Merkel Cell Carcinoma

  Merkel cell carcinoma (MCC) is a rare, neuroendocrine skin carcinoma that is caused by the Merkel cell polyomavirus (MCPyV) in 80% of cases and by ultraviolet (UV) damage in 20% of cases. MCC should theoretically elicit a strong cytotoxic T cell response due to the high neoantigen and viral antigen burden in MCPyV- and MCPyV+ MCC, respectively. However, MCC often escapes immune recognition and is associated with very poor prognosis at advanced stages. To systemically identify mechanisms of immune evasion in MCC, we established 11 robust MCC lines from either primary tumors or patient-derived xenografts (7 MCPyV+ and 4 MCPyV-). We then characterized these tumors and cell lines by whole exome sequencing (WES), RNA-sequencing, scRNA-sequencing, ATAC-seq, and whole genome bisulfite sequencing (WGBS). We also studied MCC transcriptional subtypes, utilizing bulk and scRNA-sequencing datasets of patient-derived tumors and cell lines to investigate profiles of neuroendocrine gene expression. The genes linked below define either a neuroendocrine or a non-neuroendocrine phenotype presence within MCC tumors.

  Study phs002260

• Altered Interactions between Circulating and Tissue-Resident CD8 T Cells with the Colonic Mucosa Define Checkpoint Inhibitor Colitis

  Therapeutic immune checkpoint blockade has revolutionized oncology, but treatments are limited by immune-related adverse events, including checkpoint inhibitor colitis (irColitis). To define molecular drivers of irColitis, we profiled ~300,000 cells from the colonic mucosa and blood of 29 patients and controls. Patients with irColitis showed expanded mucosal Tregs (regulatory T cells), CD8 tissue-resident memory T cells expressing CXCL13 and Th17 gene programs, and recirculating ITGB2 CD8 T cells. Cytotoxic CD4 T cells, recirculating CD8 T cells, and endothelial cells expressing hypoxia gene programs were further expanded in colitis associated with anti-PD-1/CTLA-4 compared to in the presence of anti-PD-1 therapy. Luminal epithelial cells in irColitis patients expressed PCSK9, PD-L1, and interferon-induced signatures associated with apoptosis, increased cell turnover, and malabsorption.Raw data files from both colon and PBMCs from irColitis patients and controls have been provided to dbGaP. Count matrices derived from raw RNA-Seq data will be available through GEO accession GSE206301.

  Study phs003418

• Multi-Omic Profiling of Glioma Patient Tumors and Patient-Derived Model Systems

  We have created a resource of transcriptomic (RNAseq), genomic (whole-exome seq), and lipidomic (untargeted shotgun) profiling data from over 175 molecularly diverse glioma tumors and derivative models in orthotopic mouse xenografts and gliomasphere cultures from over 110 unique patient tumor lines. Provided in this dataset are matched bulk RNA and whole-exome paired-end sequencing data from resected gliomas and derived model systems performed on Illumina HiSeq and NovaSeq sequencing instruments. This comprehensive dataset powers multiple studies aiming to derive molecular signatures of intertumoral heterogeneity and perturbation responses in glioma. Through integrative multi-omic analyses in Minami, et al., 2023, PMID: 37236196, we identified that CDKN2A deletion remodels the GBM lipidome and consequently primes CDKN2A-deleted tumors for ferroptosis. Lipidomics data related to this study are publicly available here. In another study, we used a combination of molecular profiling and functional profiling of apoptotic potential to stratify patients into groups with differential vulnerability to the current standard-of-care in gliomas, and in combination with drugs targeting intrinsic apoptosis, largely informed but not limited to TP53 mutation status.

  Study phs003286

• Immuno-genomic Profiling of Biopsy Specimens Predicts Neoadjuvant Chemotherapy Response in Esophageal Squamous Cell Carcinoma

  Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive cancers and is primarily treated with platinum-based neoadjuvant chemotherapy (NAC). Some ESCCs respond well to NAC. However, biomarkers to predict NAC sensitivity and their response mechanism in ESCC remain unclear. We introduce a model by machine learning and validated its potential to predict the NAC response in ESCC. To create this model, we performed whole genome sequencing and RNA-seq analysis on totally 141 ESCC biopsy specimens before NAC treatment and analyzed their immuno-genomic features and association with NAC response. Neutrophils infiltration could play an important role in ESCC response to NAC. We also demonstrated that specific copy number alterations and copy number signatures in the ESCC genome were significantly associated with NAC response. The interactions between the tumor genome and immune features of ESCC are likely to be a new indicator of therapeutic capability and a new therapeutic target for ESCC, and machine learning prediction for NAC response is useful.

  Study JGAS000535

• Myasthenia gravis-specific aberrant neuromuscular gene expression by medullary thymic epithelial cells in thymoma

  Myasthenia gravis (MG) is a neurological disease caused by autoantibodies against neuromuscular-associated proteins. While MG is frequently developed in thymoma patients, the etiologic factors for MG are not well understood. Here, by constructing a comprehensive atlas of thymoma using bulk and single-cell RNA-seq, we identified ectopic expression of neuromuscular molecules in MG-associated thymoma (MG-thymoma). These molecules were originated from a distinct subpopulation of medullary thymic epithelial cells (mTECs), which we named neuromuscular mTECs (nmTECs). MG-thymoma also exhibited microenvironments dedicated to autoantibody production, including ectopic germinal center formation, T follicular helper cell accumulation, and type 2 conventional dendritic cell migration. Cell-cell interaction analysis also predicted the interaction between nmTECs and T/B cells via CXCL12-CXCR4. The enrichment of nmTECs presenting neuromuscular molecules within MG-thymoma was further confirmed by immunohistochemically and by cellular composition estimation from MG-thymoma transcriptome. Altogether, this study suggests that nmTECs play a significant role in MG pathogenesis via ectopic expression of neuromuscular molecules.

  Study JGAS000482

• Single-cell analysis of airway samples identifies immune cell activation correlating with COVID-19 disease severity

  To investigate the immune response and mechanisms associated with severe COVID-19, we performed single-cell RNA-seq on nasopharyngeal and bronchial samples from 19 clinically well-characterized patients with moderate or critical disease and from 5 healthy controls. We identified airway epithelial cell types and states vulnerable to SARS-CoV-2 infection. In COVID-19 patients, epithelial cells showed an average threefold increase in expression of the SARS-CoV-2 entry receptor ACE2, which correlated with interferon signals by immune cells. Compared with moderate cases, critical cases exhibited stronger interactions between epithelial and immune cells, as indicated by ligand–receptor expression profiles, and activated immune cells , including inflammatory macrophages expressing CCL2, CCL3, CCL20, CXCL1, CXCL3, CXCL10, IL8, IL1B and TNF . The transcriptional differences in critical cases compared with moderate cases likely contribute to clinical observations of heightened inflammatory tissue damage, lung injury and respiratory failure. Our data suggest that pharmacologic inhibition of the CCR1 and/or CCR5 pathways may suppress immune hyperactivation in critical COVID-19.

  Study EGAS00001004481

• Human omentum cell atlas

  This dataset contains single-cell RNA sequencing data derived from freshly dissociated human omental tissue. The study investigates the transcriptomic landscape of the omentum by comparing samples from patients with benign conditions against those with ovarian cancer metastasis. To capture the heterogeneity of the metastatic niche, sampling was performed across distinct anatomical sites, including non-metastasized tissue, distant omental regions, peritumoral zones, and the tumor core. This comprehensive profiling aims to define the cellular remodeling associated with malignant transformation

  Dataset EGAD50000002110

• ICARUS-BREAST01 Dataset

  A phase II clinical trial (NCT04965766) of patritumab deruxtecan in 99 breast cancer patients. Whole-exome sequencing (WES) is available for 43 tumor samples and 43 blood samples collected at entry into the trial. RNA-squencing is available for 44 samples comprising 22 samples collected at entry into the trial and 22 samples collected during treatment (cycle 1 day 3, cycle 1 day 19, or cycle 2 day 3) from 22 patients.

  Dataset EGAD50000000773