11769 results for "cancer rna-seq"

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• Single-cell RNA sequencing of RCC patients

  Single-cell RNA sequencing was performed on viable frozen tumor dissociated cells from three RCC patients. The raw data is available as fastq files.

  Dataset EGAD00001011045

• Single-nucleus transcriptome sequencing of the human motor cortex

  Single-nucleus RNA-sequencing of the human motor cortex in patients with ALS, C9ORF72-ALS-FTD, ALS-FTD and unaffected controls.

  Study EGAS50000001562

• Count Me In (CMI): The Angiosarcoma (ASC) Project (CMI-ASCproject)

  Count Me In - The Angiosarcoma Project: A Patient-Partnered Research Initiative to Accelerate Research in a Rare Sarcoma The Angiosarcoma Project (ASCproject) is a research study that directly engages angiosarcoma patients online and empowers them to accelerate cancer research by sharing medical information and clinical samples. Angiosarcoma is an exceedingly rare soft tissue sarcoma with an incidence of ~300 newly diagnosed cases per year in the United States. This low incidence has impeded large-scale research efforts in this disease that are strongly needed to catalyze research and improve clinical outcomes. The Angiosarcoma Project, launched in March 2017, has demonstrated the feasibility of directly engaging geographically dispersed patients to democratize research and establish a large patient cohort to characterize the genomic and clinical landscape of a rare disease. Angiosarcoma patients living in the US or Canada can access the study and consent online through an online portal (ASCproject.org). Enrolled patients are mailed saliva and blood draw kits, which can be used to extract germline DNA and cell-free DNA (cfDNA), respectively. The study team contacts participants' healthcare institutions to obtain medical records and a portion of archived tumor samples. All received tumor samples are subjected to centralized histological re-review by an expert pathologist to confirm a diagnosis of angiosarcoma. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing is performed on tumor RNA. De-identified data, including linked genomic, clinical, and patient-reported data, are shared via public databases on a recurring pre-publication basis. Participants are regularly provided updates on the study.

  Study phs001931

• Evaluation of EBUS-TBNA Aspirates from Advanced NSCLC for Comprehensive Sequencing Platforms Including Whole Genome Sequencing

  Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is often the only source of tumor tissue from patients with advanced, inoperable lung cancer. EBUS-TBNA aspirates are used for the diagnosis, staging, and genomic testing to inform therapy options. Here we extracted DNA and RNA from 220 EBUS-TBNA aspirates to evaluate their suitability for whole genome (WGS), whole exome (WES), and comprehensive panel sequencing. For a subset of 40 cases, the same nucleic acid extraction was sequenced using WGS, WES, and the TruSight Oncology 500 assay. Genomic features were compared between sequencing platforms and compared with those reported by clinical testing. A total of 204 aspirates (92.7%) had sufficient DNA (100 ng) for comprehensive panel sequencing, and 109 aspirates (49.5%) had sufficient material for WGS. Comprehensive sequencing platforms detected all seven clinically reported tier 1 actionable mutations, an additional three (7%) tier 1 mutations, six (15%) tier 2–3 mutations, and biomarkers of potential immunotherapy benefit (tumor mutation burden and microsatellite instability). As expected, WGS was more suited for the detection and discovery of emerging novel biomarkers of treatment response. WGS could be performed in half of all EBUS-TBNA aspirates, which points to the enormous potential of EBUS-TBNA as source material for large, well-curated discovery-based studies for novel and more effective predictors of treatment response. Comprehensive panel sequencing is possible in the vast majority of fresh EBUS-TBNA aspirates and enhances the detection of actionable mutations over current clinical testing.

  Study EGAS00001007708

• Small Genomic Insertions Form Enhancers that Misregulate Oncogenes

  ChIP-Seq data from 102 cell lines were processed to identify insertions relative to the human reference genome. To confirm the ability of a computational pipeline to identify insertions that are actually present in these genomes, we PCR-amplified and deeply sequenced regions where insertions were predicted to exist in MOLT4 T-cell acute lymphoblastic leukemia cells. The current study release makes available sequences of amplicons from a tumor cell genome (MOLT4) where a computational pipeline predicted small insertions from orthogonal data.

  Study phs001242

• Decade-Long Leukemia Remissions with Persistence of CD4+ CAR T-Cells

  Two patients with chronic lymphocytic leukemia (CLL) were treated with CD19 targeted CAR T therapy and followed over several years. Peripheral blood from both patients at multiple time points was collected, and 5' CITE-Seq with TCR profiling was performed on sorted CD3+CAR+ T cells at multiple time points. Here, we deposit the raw sequencing data for these single-cell experiments. Processed and de-identified data (e.g. cellranger output, Seurat objects) have been made available on a separate public data repository.

  Study phs002931

• High-throughput determination of the antigen specificities of T cell receptors in single cells

  High-throughput linking of T cell receptor (TCR) sequences to their binding antigens is vital for immune profiling, yet challenging. We present Tetramer associated TCR Sequencing (TetTCR-Seq) to address this challenge. Binding is determined using a library of DNA-barcoded antigen tetramers that are rapidly and inexpensively generated using an in vitro transcription/translation platform. We included CMV+ donors (CMV seropositive donors who are infected with Cytomegalovirus) to screen for CMV specific TCRs.

  Study phs001678

• Single nuclei ATAC-Seq data from the human ganglionic eminences

  Data generated through single nuclei ATAC sequencing on whole ganglionic eminences from 3 human fetuses (two of 16 and one of 17 gestational weeks). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource with ethical approval. snATAC-Seq libraries were prepared from ~8,000 nuclei per sample using Chromium Next GEM Single Cell ATAC (v1.1) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 617 million read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Schizophrenia Bulletin 2024, https://doi.org/10.1093/schbul/sbae083. Please note that 10X generated BAM files, rather than FASTQ files, have been uploded. FASTQ files can be regenerated using the 10X Genomics bamtofastq tool. https://support.10xgenomics.com/docs/bamtofastq

  Dataset EGAD50000000601

• LCM-ATACseq on human lung macrophages

  In this study we employed Laser Capture Microdissection (LCM) for the multimodal profiling of lung macrophages cell populations as a function of location within the healthy tissue. In detail, macrophage mini-bulks (~100 cells) were collected from 4 healthy human donors in 5 different locations of the airways (a total of 20 biopsies), including parenchyma (L1 – lower left lobe (LLL); L6 – 80% distance from LLL tip), trachea (L2), bronchi (L3 – 1st/2nd generation; L5 – 3rd/4th generation), and processed for ATAC-seq.

  Study EGAS00001006167

• COVID_19_Challenge_Project_Single_Cell_Profiling

  Single-cell profiling of sero-negative and sero-positive humans that were inoculated with SARS-CoV-2. The cellular response during SARS-CoV-2 is profiled using single-cell transcriptomics, CITE-seq and single cell immune profiling, by sampling PBMCs and nasal swabs before and at multiple time points during SARS-CoV-2 infection. This one-of-a-kind cellular map will give unique temporal resolution of how nasal and immune cells respond to SARS-CoV-2 exposure and infection

  Study EGAS00001005696

• cfMethyl-Seq

  cfMethyl-Seq libraries were generated for 479 cfDNA samples and were sequenced with 150 bp paired-end reads.

  Dataset EGAD00001009003

• Smart-seq 2 single cell sequencing of CD4 and CD8 T cells from the blood and synovial fluid of 4 psoriatic arthritis patients.

  This dataset was used to characterise T cell gene expression and clonality at sites of active inflammation within the joints of psoriatic arthritis (PsA) patients, and to compare these results with T cells from the peripheral blood of those same patients. Freshly sorted CD45RA negative CD3+CD4+ and CD3+CD8+ single cells from four patients were individually flow sorted into 96-well full-skirted plates (Eppendorf) containing 10µL of a 2% Dithiothreitol (DTT, 2M Sigma-Aldrich), RTL lysis buffer (Qiagen) solution. Cell lysates were sealed, mixed and spun down before storing at -80 ºC. Paired-end multiplexed sequencing libraries were prepared following the Smart-seq 2 protocol using the Nextera XT DNA library prep kit (Illumina). A pool of barcoded libraries from four different plates were sequenced across two lanes on the Illumina HiSeq 2500.

  Dataset EGAD00001006342

• RNA sequecing of primary B cells infected with Epstein-Barr virus (EBV) or stimulated with heat-inactivated EBV

  Naïve (CD27-IgD+) B cells were isolated from buffy coat preparations of healthy donors using CD19 magnetic beads, followed by reals of CD19 beads and incubation with IgD-biotin and anti-biotin magnetic beads. B cells were infected with EBV by spinoculation or stimulated with heat-inactivated EBV and control cells were left uninfected. RNA was extracted immediately after isolation in un-infected B cells. From EBV-infected B cells and B cells stimulated with heat-inactivated virus, RNA was extracted 24 and 96 hours after infection / stimulation.

  Dataset EGAD50000000305

• Ribosomal profiling on Epstein-Barr virus transformed B-lymphoblastoid cell lines

  Epstein-Barr virus-transformed B-lymphoblastoid cell lines from six individuals (HG00114, HG00282, NA12005, NA12044, NA12717 and NA12751) of the GEUVADIS Project were selected for ribosomal profiling. For each EBV-LCL, 20 million cells were treated with 2 μg/ml harringtonine and 100 μg/ml cycloheximide. After lysing cells in lysis buffer supplemented with 100 μg/ml cycloheximide, ribosome complexes were purified by density purification. Small RNA molecules were isolated using the NucleoSpin miRNA Kit (Bioke, Leiden, Netherlands), followed by RNA PAGE gel separation. Universal linkers were added after dephosphorylation. After reverse transcription, the cDNA was circularized and, after ribosomal RNA depletion, barcoded and sequenced on Illumina NextSeq 500.

  Dac EGAC50000000209

• DIPG RNA and exome sequencing

  DIPG is a paediatric high-grade glioma that diffusely infiltrates the brainstem and is the leading cause of paediatric brain tumour death. Here we performed RNA and whole exome sequencing on DIPG and control samples to analyse transcriptomic and genetic alterations associated with this devastating disease, and to understand the relationship between them.

  Study EGAS00001004749

• Spinocerebellar ataxia type 3 RNA-sequencing study

  RNA-Sequencing from human post-mortem Spinocerebellar ataxia type 3 patients. This sequencing experiment was carried out to validate that the transcriptional changes of an Ataxin-3 knock-in mouse model (expressing an expansion of 304 CAG/CAAs either heterozygous or homozygous in the murine Ataxin-3 locus) represent that transcriptional changes seen in the human disease.

  Study EGAS00001004241

• Single-cell RNA-sequencing of CSF cells and PBMCs from individuals with neurological disorders

  We undertook single-cell RNA sequencing to establish gene expression and lymphocyte receptor sequences of CSF and peripheral blood leukocytes derived from patients with a variety of inflammatory, infectious and non-inflammatory neurological disorders. The aim of the study was the investigation of functional changes of the cells involved in neuroinflammatory responses.

  Study EGAS00001007954

• TCELL PILOT ATAC-SEQ

  This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001001317

• scRNA-seq

  This dataset gather scRNAseq data performed for MM.1S cell line in control and dex conditions at 4h and 24h

  Dataset EGAD00001011139

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• Phase II Study of Cryoablation and Post-Progression Immune Checkpoint Inhibition in Metastatic Melanoma

  Percutaneous cryoablation guided by imaging is a well-established, minimally invasive treatment for oncological conditions. We posited that cryoablation could alter the immune microenvironment by directly influencing the tumor, potentially eliciting an anti-tumor response in cases resistant to immune checkpoint inhibition (ICI). In this non-randomized phase II single-center study (NCT03290677), individuals with unresectable melanoma experiencing progression on ICI underwent cryoablation in a single progressing metastasis, while ICI was continued for at least two additional cycles. The main objectives were to assess safety and feasibility and to evaluate tumor response in non-ablated lesions. Between May 2018 and July 2020, 17 patients participated in the study. The treatment regimen proved safe, revealing an objective response rate of 23.5% and a disease control rate of 41% (comprising 4 partial responses and 3 stable diseases). In our investigation into the factors influencing response to cryoablation therapy in ICI-resistant melanoma, we conducted single-cell RNA sequencing (scRNA-seq) using both 10x Genomics and Smart-seq2 technologies on biopsies from metastatic sites of 15 patients. We collected pre-treatment samples from all patients and post-treatment samples from 5 patients, totaling 20 samples. After quality control, excluding cells specific to anatomical sites or rare cell types (e.g., alveolar type II, neurons), and batch correction, we analyzed 49,071 single cells spanning melanocyte, endothelial, stromal, T, myeloid, and B/plasma cell lineages. Differential gene expression (DGE) analysis between myeloid cells identified the genes MARCKS and IL10, two genes involved in anti-inflammatory responses that can inhibit macrophages activation to be associated with failed response. Moreover, DGE analysis of T cells identified the gene TXK, which acts as a Th1 transcription factor, and the gene CMKLR1 (chemerin-like-receptor-1), which triggers migration of CD8 T-cells to be upregulated in patients who benefited from cryoablation treatment. In contrast, MTHFD2 and GGH, two genes involved in one-carbon metabolism and the folate cycle, were upregulated in T cells from patients who did not respond to therapy. Our analysis revealed a significant increase in B/plasma cells in patients who responded positively to the therapy combination, along with an enrichment of oxidative phosphorylation in T cells among non-responsive patients with progressive disease. These findings advocate for further investigation into this innovative and synergistic therapeutic approach.

  Study phs003579

• Tumor reactive γδ T cells contribute to a complete response to PD-1 blockade in a Merkel cell carcinoma patient

  Single cell RNA and TCR sequencing of gamma delta T cells from two Merkel cell carcinoma patients

  Study EGAS50000000102

• Transcriptome-wide gene expression analysis of cocaine use disorder in postmortem human brain tissue

  Dataset contains raw fastq-files from RNA-sequencing analysis of total RNA extracted from Brodmann Area 9 human postmortem brain tissue samples.

  Dataset EGAD50000000212

• Single-cell RNA and TCR-sequencing of treatment-refractive immune-mediated arthritis

  Single-cell RNA and TCR-sequencing of three patients with treatment-refractive immune-mediated arthritis. The dataset consists of synovial tissue CD4+ and CD8+ T cells and peripheral blood CD45+ leukocytes.

  Dataset EGAD50000000749

• Reconstitution of Human Brain Cell Diversity in Organoids via Four Protocols

  This dataset contains single-cell RNA sequencing and time-course bulk RNA sequencing data of brain organoids grown from multiple cell lines using four different protocols recapitulating dorsal and ventral forebrain, midbrain, and striatum.

  Dataset EGAD50000000938