14982 results for "cancer studies using rna-seq"

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• ABHD11 Autoimmunity Study DAC

  This DAC oversees controlled access to human RNA-seq data generated as part of the project “ABHD11 inhibition and T cell function in autoimmunity” at Swansea University. The DAC will evaluate and approve access requests based on scientific merit and alignment with participant consent. Data requests will be considered from academic researchers and healthcare professionals working on immunology or autoimmunity.

  Dac EGAC50000000750

• Single cell mRNA sequencing of primary GBM - SF 10679

  We collected fresh tissue from an untreated GBM (SF10679) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001003113

• Single cell mRNA sequencing of primary GBM - SF 10281

  We collected fresh tissue from an untreated GBM (SF10281) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001003114

• Islet RFX6 Study Manuscript Data

  This submission includes raw FASTQ files (for bulk RNA-seq and 10X joint snATAC+snRNA multiome profiling experiments), sample phenotype files, and genotypes for the data included in the manuscript.

  Dataset EGAD00001008777

• Gene expression in human monocyte differentiation

  This dataset consists of RNA-seq data from human monocytes, monocyte-derived dendritic cells or monocyte-derived macrophages as well as monocyte-derived cells that were subjected to siRNA treatment targeting CTCF or RAD21. In total, it includes 63 samples.

  Dataset EGAD00001007956

• Single cell mRNA sequencing of primary GBM - SF 10592

  We collected fresh tissue from an untreated GBM (SF10592) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001003112

• Microinjection of hIPSC-derived intestinal organoids with Salmonella Typhimurium

  To generate an RNA-Seq dataset for organoids apically stimulated with Salmonella Typhimurium.These data are 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 EGAD00001001363

• Single-Nuclei RNA-seq of healthy (post-mortem) and temporal lobe epilepsy (biopsy) subjects.

  To identify dysfunctional neuronal subtypes underlying seizure activity in the human brain, we have performed single-nucleus transcriptomics analysis of >110,000 neuronal transcriptomes derived from temporal cortex samples of multiple temporal lobe epilepsy and non-epileptic subjects.

  Dataset EGAD00001006575

• Proteogenomic Landscape of Squamous Cell Lung Cancer

  To provide a detailed analysis on how genomic and transcriptomic alterations related to proteome level changes in squamous cell lung cancer (SCC), we performed an integrated analysis incorporating DNA copy number, somatic mutations, expression RNA-sequencing, and expression proteomics in 108 SCC nested within clinical outcome, tumor pathology, and other clinically relevant data.

  Study phs001781

• DAC for study: "Combination pembrolizumab and radiotherapy induces systemic anti-tumor immune responses in immunologically-cold non-small cell lung cancer."

  This is Data Access Committee will oversee data sharing for sequence data in the EGA study: "Combination pembrolizumab and radiotherapy induces systemic anti-tumor immune responses in immunologically-cold non-small cell lung cancer." This dataset includes 116 bam files from whole exome sequencing on the Illumina HiSeq2500, 102 fastq files from RNA sequencing on the Illumina NovaSeq 6000. The samples analyzed include tumor/normal DNA samples and tumor RNA samples from 72 individuals with non-small cell lung cancer treated with pembrolizumab and SBRT or pembrolizumab alone on the NCT02492568 trial.

  Dac EGAC50000000202

• Integrated Somatic and Germline Molecular Properties Dictating Biological and Clinical Phenotypes in Cancer

  We performed single-nuclei matched RNA- and ATAC-sequencing of frozen biopsies from normal adjacent tissue, primary and metastatic esophageal adenocarcinoma specimens. The data was then further stratified into a tumor microenvironment and malignant compartment and was computationally analyzed to reveal cancer cell subtypes and programs driving malignancy.

  Study phs003438

• The Landscape of Antisense Gene Expression in Human Cancers

  High throughput RNA Sequencing has revealed that the human genome is widely transcribed. However, the extent of natural antisense transcription, the molecular mechanisms by which natural antisense transcripts (NATs) might affect their cognate sense genes, and the role of NATs in cancer are less well understood. Here, we use strand-specific paired-end RNA sequencing (ssRNASeq) on a cohort of 376 cancer patients covering 9 tissue types to comprehensively characterize the landscape of antisense expression. Our results reveal that greater than 60% of annotated transcripts have measureable antisense expression and the expression of sense and antisense transcript pairs is in general positively correlated. Furthermore, by studying the expression of sense/antisense pairs across tissues we identify lineage-specific, ubiquitous and cancer-specific antisense loci. Our results raise the possibility that NATs participate in the regulation of well-known tumor suppressors and oncogenes. Finally, this study provides a catalogue of cancer related genes with significant antisense transcription (oncoNAT). This resource will allow researchers to investigate the molecular mechanisms of sense/antisense regulation and further advance our understanding of their role in cancer.

  Study phs000937

• Precision Interception of Gastric Cancer Precursors Through Molecular and Cellular Risk Stratification

  The GAstric Precancerous conditions Study (GAPS, NCT04191551) is a cross-sectional study of patients undergoing endoscopy who are at increased risk of gastric cancer. Enrolled patients are administered a standardized questionnaire, undergo clinical biopsy collection using the Sydney system, and consent for the collection of saliva, blood, and additional gastric tissue. All patients are scored for intestinal metaplasia using the operative link on gastric intestinal metaplasia (OLGIM) scoring system.

  Study phs003648

• Shot-gun stool metagenomics and colorectal cancer risk.

  This study aims to identify metagenomics biomarkers in colorectal cancer (CRC). The study includes 156 samples of shot-gun stool metagenomics, corresponding to 51 patients with CRC, 54 patients with high-risk adenoma, and 51 healthy controls. The sequencing libraries were prepared with 2 µg of total DNA using the Nextera XT DN Sample Prep Kit (Illumina, San Diego, CA, USA). Sequencing was performed at 150 nucleotides, paired-end, using an Illumina HiSeq 4000 platform.

  Study EGAS00001007025

• Single-nuclei multiomic analysis of KOLF2.1J human induced pluripotent stem cells-derived differentiated dopaminergic neurons

  Datasets consists of 12 samples of nuclei from hIPSCs differentiated optimized protocols for generating dopaminergic neurons. 6 single nuclei (RNA-ATAC) samples of XMAS protocol with cells collected at days 0,11,16,28,42 and 56 after differentiation. 3 snRNA-seq samples from AMS protocol of cells collected at days 14,16 and 28 after differentiation and 3 snRNA-seq samples with AMS protocol until day 14 grafted and grafts processed after 5 months grafting.

  Dataset EGAD50000002054

• T cell transcriptional gradient

  There are two datasets: 1. scRNA-seq of human cutaneous immune cells from psoriasis patients. These include pre- and post-Tildrakizumab treated patients and come in a BAM file format. 19006FL-25-01 19006FL-38-01 19006FL-32-01-03 19006FL-33-01 19006FL-28-01-05 19006FL-35-01-01 2. RNA-seq of ZFP36L2 CRISPIR deleted Human T cells are FASTQ files. 19006XR-30-05 19006XR-30-04 19006XR-30-02 19006XR-30-01 19006XR-26-05 19006XR-26-04 19006XR-26-02 19006XR-26-01 19006R-22-04 19006R-22-08 19006R-22-05 19006R-22-01

  Dataset EGAD00001009677

• Combination_Immune_Checkpoint_Inhibition_in_Australian_Rare_Cancers_WES

  Combination immune checkpoint inhibition (ICI) with anti-CTLA-4 and anti-PD-1 blockade has demonstrated significant clinical activity across tumour types. Rare cancer patients have limited treatment options due to the scarcity of studies of novel treatment options, so they are often offered chemotherapies untested in their disease. ONJ2016-001/CA209-538 is a prospective, multicentre clinical trial of combination ICI (ipilimumab and nivolumab) in patients with advanced rare cancers, including biliary tract, adrenocortical, rare gynaecological and neuroendocrine cancers (https://clinicaltrials.gov/ct2/show/NCT02923934). The primary endpoint is clinical benefit rate (complete response + partial response + stable disease >3 months) by RECIST 1.1. This study involves generation and analysis of pre-treatment formalin fixed paraffin embedded (FFPE) tumour DNA sequencing data, paired with germline DNA sequencing data, to potentially identify genomic biomarkers that may associate with clinical benefit or other clinical efficacy / toxicity metrics.

  Study EGAS00001005709

• Single cell analysis reveals new evolutionary complexity in uveal melanoma

  Uveal melanoma (UM) is a rare eye cancer that is highly aggressive and leads to metastatic death in up to half of patients. Here, we conduct droplet-based single-cell RNA sequencing of 59,915 neoplastic and non-neoplastic cells from 8 primary and 3 metastatic UMs. Single-cell VDJ sequencing of RNA is conducted to determine clonally expanded B/T- cell populations. Single-cell DNA sequencing of 1 primary and 1 metastasis is utilized.

  Study phs001861

• Targeted sequencing of genes recurrently mutated in AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: ? Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. ? Correlation of prognosis with driver mutations and potentially gene-gene interactions ? Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ?personalised? prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Dataset EGAD00001000606

• Premalignant SOX2 overexpression in the fallopian tubes of ovarian cancer patients: Discovery and validation studies

  To identify early driver mutations in ovarian cancer cells, we used dense whole genome sequencing of micrometastases and microscopic residual disease collected at three time points from a single patient during treatment for high-grade serous ovarian cancer (HGSOC). Laser capture microdissection of tumour islets was performed on samples prior to chemotherapy, after three cycles of chemotherapy and at recurrence. Long frament read whole genome sequencing was performed and mutations were identified. To our knowledge, this is the first longitudinal study that attempts to investigate spatial and temporal micro-heterogeneity in cancer.

  Study EGAS00001001909

• Somatic mutation analysis based on Whole exome Sequencing (WES) of multiple tumor biopsies, patient-derived spheroids and leukocyte DNA from colorectal cancer patients (vcf files)

  Somatic mutations were called using whole exome Sequencing (WES) data from colorectal cancer samples (dataset EGAD00001003821) using MuTect2, with matched constitutional WES-data obtained from leukocytes samples as reference.

  Dataset EGAD00001003823

• RNA-Sequencing data of Fusobacterium nucleatum treated CAFs and HT-29 tumor spheroid exposed to Fusobacterium nucleatum treated CAFs conditioned medium.

  RNA-Sequencing data of CAFs (patient derived CAF180 and CAF181 as well as the CT5.3 CAF cell line) and HT-29 tumor spheroid samples performed in the context of the study of the interaction of Fusobacterium nucleatum with CRC CAFs. Fusobacterium nucleatum interacts with cancer-associated fibroblasts to enhance colorectal cancer progression

  Dataset EGAD50000001614

• Transcriptomic dataset from a phase II study of pembrolizumab and epigenetic modification with azacitidine in platinum-resistant epithelial ovarian cancer

  This dataset includes sequence files from bulk RNA sequencing of tissue biospecimens from a phase II study investigating epigenetic priming followed by immune checkpoint blockade in platinum-resistant epithelial ovarian cancer (NCT02900560). There are 48 bulk RNA sequencing files from 24 specimens included in this dataset.

  Dataset EGAD50000001664

• NeoRhea Bulk RNA and Single nuclei RNA & ATAC

  The aim of this study is to compare baseline and surgery samples of ER+/HER2- early breast cancer patients. Patients have been treated with endocrine therapy in combination with palbociclib. Samples have been collected pre and post treatment.

  Study EGAS50000001403

• Single-cell profiling maps the spectrum of crosstalk between glioma cells and tumor associated macrophages

  Tumor associated macrophages (TAMs) are a heterogeneous glioma infiltrate, implicated in cancer progression. We performed single-cell RNA-sequencing, to survey TAM response-patterns in glioma.

  Study EGAS00001002185