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

in 19.47 milliseconds.

• Single-cell RNA sequencing of 22 Hodgkin lymphoma tumors and 5 reactive lymph nodes

  Hodgkin lymphoma (HL) is characterized by an extensively dominant tumor microenvironment (TME) composed of different types of non-cancerous immune cells with rare malignant cells. Characterization of the cellular components and their spatial relationship is crucial to understanding crosstalk and therapeutic targeting in the TME. We performed single-cell RNA sequencing of more than 127,000 cells from 22 HL tissue specimens and 5 reactive lymph nodes, profiling for the first time the phenotype of the HL-specific immune microenvironment at single-cell resolution. Library preparation was performed using the 10x Genomics Chromium system, and Illumina sequencing was used to generate 3' gene expression data for every cell. Downstream analysis was performed in R to identify HL-specific microenvironment patterns and identify novel cell populations.

  Study EGAS00001004085

• HDAC inhibitors in synovial sarcoma cells

  Histone deacetylase (HDAC) inhibition has been shown in previous studies to disrupt the synovial sarcoma oncoprotein complex, resulting in apoptosis. To understand the molecular effects of HDAC inhibition, RNA-Seq transcriptome analysis was undertaken in six human synovial sarcoma cell lines. HDAC inhibition induced pathways of cell cycle arrest, neuronal differentiation and response to oxygen-containing species, effects also observed in other cancers treated with this class of drugs. More specific to synovial sarcoma, polycomb-group targets were reactivated including tumor suppressor CDKN2A, and pro-apoptotic transcriptional patterns were induced. Functional analyses revealed that ROS-mediated FOXO activation and pro-apoptotic factors BIK, BIM and BMF were important to apoptosis induction following HDAC-inhibition in synovial sarcoma

  Study EGAS00001002637

• Subclonal evolution of four ER+ breast cancers determined by WGS and scRNA-Seq

  We analyzed the subclonal evolution of four ER+ breast cancers over 2-15 years using whole-genome sequencing (WGS) and single-cell RNA-Seq (scRNA-Seq). For each patient we analyzed 2-6 cancer samples, generally metastatic pleural effusions or ascites, by WGS, along with germline DNA. Two of the samples per patient were selected for single-cell RNA-Seq.

  Study EGAS00001002436

• Clonal Evolution and Transcriptomic Analysis of Chronic Lymphocytic Leukemia Treated with Ibrutinib

  Disease progression has been increasingly appreciated with the use of ibrutinib to treat chronic lymphocytic leukemia (CLL). Understanding the pattern of clonal evolution and transcriptomic changes during the early treatment period with ibrutinib may provide insight into the mechanisms of resistance. We performed whole exome sequencing on sequential samples with matched germline controls from 61 patients with CLL during the first 12 months of ibrutinib monotherapy or ibrutinib in combination with rituximab. Additionally, RNA sequencing was done on a subset of 14 patients treated with ibrutinib monotherapy. The presence of clonal shifts was associated with an increased risk of disease progression, suggesting that resistant clones are more likely to emerge in CLL with greater evolutionary capacity.This cohort was later augmented with additional data (including data from 15 additional patients). In total, this second set of data contained whole exome sequencing (31 samples), RNA sequencing (6 samples) and reduced representation bisulfite sequencing (67 samples) for CLL samples and used them to identify expression subtypes of CLL. In an integrative analysis of genetic, transcriptomic, and epigenetic data, incorporating known and newly identified subtypes of CLL, we built new models to improve patient prognostication.

  Study phs001473

• KRT17High/CXCL8+ Tumor Cells Display Both Classical and Basal Features and Regulate Myeloid Infiltration in the Pancreatic Cancer Microenvironment

  Recent studies have uncovered the co-existence of basal and classical subtypes within pancreatic ductal adenocarcinoma (PDAC). We sought to characterize these intermediary cells using single-cell RNA sequencing of PDAC. We performed subtyping on 18 single-cell RNA sequencing human PDAC samples to identify multiple intermediary subtypes. We compared single-cell profiling of patient-matched blood and tumor samples to measure changes in the local and systemic immune microenvironments in CXCL8-high tumors vs. CXCL8-low tumors. Finally, we leveraged longitudinally patient-matched blood over the course of chemotherapy. In our studies we identified a cluster of KRT17high intermediary cancer cells that uniquely express high levels of CXCL8 and other cytokines which in turn influence the myeloid compartment both locally and systemically. We utilized sequencing data from dbGaP study accession phs002070. In addition to that, we included sequencing from new specimens which are deposited to this submission, consisting of one additional tumor specimen and 5 PBMC samples, sequenced after chemotherapy (longitudinally matched to PBMC samples in phs002071.v1.p1). FASTQ files of these sequencing runs are available through this dbGaP submission.

  Study phs003436

• Temporal Evolution Reveals Bifurcated Lineages in Aggressive Neuroendocrine Small Cell Prostate Cancer Trans-Differentiation

  Trans-differentiation from adenocarcinoma to small cell neuroendocrine (SCN) cancer is an adverse consequence of treatment escape in various cancers, including prostate, lung, and bladder cancers (Balanis and Sheu et al., PMID 31287989). Expression of dominant negative p53 (TP53DN), myrAkt1, RB1-shRNA, c-Myc, and Bcl2(PARCB forward transformation) using human naïve prostate basal epithelial cells recapitulated both transcriptional and histological characteristics of small cell neuroendocrine prostate cancer (NEPC) (Park et al., PMID 30287662). To study the temporal transcriptional landscape during this trans-differentiation process, we conducted a time course study using a PARCB model by integrating multi-omics sequencing, including bulk RNA-sequencing and ATAC-sequencing on samples taken at different time point, as well as single cell RNA sequencing on serial xenograft tumors. We found a common SCN pathway that resulted in two distinct end states defined by mutually exclusive expression of ASCL1 and ASCL2. Further investigation using CUT&RUN sequencing identified TFAP4 as a potential epigenetic regulator of both proteins. Our study reveals temporal and transcriptional changes from prostate adenocarcinoma to NEPC trans-differentiation.

  Study phs003230

• Cambridge Neoadjuvant Cancer of the Prostate (CANCAP03): A Window Study into the Effects of Olaparib ± Degarelix in Primary Prostate Cancer.

  Study: Cambridge Neoadjuvant Cancer of the Prostate (CANCAP03): A Window Study into the Effects of Olaparib ± Degarelix in Primary Prostate Cancer. EudraCT Number: 2014-004417-86 Clinicaltrials.gov Number: NCT02324998 Purpose: Investigate combined PARP and androgen inhibition in primary prostate cancer. Aim: To understand the biological mechanism(s) underlying clinical efficacy, especially in the absence of mutations in homologous recombination (HR) repair pathways. Dataset: Single-nuclear RNA sequencing data from post-treatment radical prostatectomy tissue cores for six patients, 3 from each of olaparib and olaparib and degarelix cohorts. Samples were processed for nuclear isolation and extraction, prior to single-nuclear RNA sequencing. 10x libraries were constructed using the 10x supplied protocol, briefly: individual nuclei were trapped into droplets with a single bead, and poly A transcripts were barcoded during reverse transcription. Complementary DNA was amplified, and libraries were prepared for sequencing on NovaSeq 6000 using S4 flow cell (100k reads per cell). FASTQ files were processed using CellRanger pipeline (10X Genomics). Outputs from the CellRanger pipeline were analysed using the Seurat package (v4.9.9.9049) in R (v4.2.0). Processed data is provided as a Seurat object.

  Study EGAS50000000880

• Hominin-specific NOTCH2 paralogs expand human cortical neurogenesis through regulation of Delta/Notch interactions.

  The human cerebral cortex has undergone rapid expansion and increased complexity during recent evolution. Hominid-specific gene duplications represent a major driving force of evolution, but their impact on human brain evolution remains unclear. Using tailored RNA sequencing (RNAseq), we profiled the spatial and temporal expression of Hominid-specific duplicated (HS) genes in the human fetal cortex, leading to the identification of a repertoire of 36 HS genes displaying robust and dynamic patterns during cortical neurogenesis. Among these we focused on NOTCH2NL, previously uncharacterized HS paralogs of NOTCH2. NOTCH2NL promote the clonal expansion of human cortical progenitors by increasing self-renewal, ultimately leading to higher neuronal output. NOTCH2NL function by activating the Notch pathway, through inhibition of Delta/Notch interactions. Our study uncovers a large repertoire of recently evolved genes linking genomic evolution to human brain development, and reveals how hominin-specific NOTCH paralogs may have contributed to the expansion of the human cortex. The dataset contains raw sequences (FASTQ files) from the Illumina 2x150bp paired-end RNA sequencing profiles of 11 fetal human brain samples at 7, 9, 12, 15 and 21 gestational weeks.

  Study EGAS00001002798

• Changes in alternative splicing and associated neo-antigens due to therapy

  Recent studies have identified alternative splicing (AS) as a novel source of neoantigens for immunotherapy. Surprisingly little is known about the AS milieu in recurrent glioblastoma (GBM), despite this being the venue for most clinical trials. We profiled 29 primary-recurrent paired human GBM specimens via RNA sequencing and re-analyzed RNA-sequencing data from non-malignant human brain tissues. From these data, we reconstructed the landscape of AS in GBM through recurrence and contrasted that to isoforms observed in non-malignant brain. The AS events we identified were cross-referenced with single-cell GBM atlases to determine cell-type specific splicing patterns. From this we identified novel splicing events in cell-surface proteins that are suitable targets for engineered T-cell therapies. We found recurrent-specific isoforms of mitogen-activated kinase pathway genes which are expressed exclusively by GBM stem-like cells that enhance invasiveness. These studies shed light on the effect of therapy on AS and identify novel targets for emerging immunotherapies.

  Study EGAS00001004524

• bulk RNAseq from metastatic uveal melanoma tumour biopsies

  Tumour biopsies were obtained from uveal melanoma patients (n = 35) pre and 16 days post treatment with tebentafusp. Biopsies, which were either snap frozen or put in RNA later, were analysed by bulk RNA sequencing (50 million reads per sample) using the Illumina NovaSeq system.

  Dac EGAC50000000519

• RNA-seq data from 121 tumor samples with muscle invasive bladder cancer.

  In this study, a total of 300 patients with MIBC receiving chemotherapy were included; 62 received NAC before cystectomy and 245 received first-line chemotherapy upon detection of locally-advanced (T4b) or metastatic disease. Treatment response, defined as pathological downstaging (< pTa,CIS,N0) after NAC or complete or partial response after first-line treatment (RECIST criteria). RNA-seq was performed using the QuantSeq kit FWD HT kit (Lexogen) using 500 ng input RNA from 121 tumor samples. Data provided here consist of 780 fastq files for RNA-seq.

  Study EGAS00001004505

• RNA-Seq in Patients with Primordial Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in the interpretation of likely causal genetic variation through identification of altered transcript abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating transcript structure and abundance The primary aim of this pilot project is to investigate to what degree integrating exome-Seq and RNA-Seq data on the same individual can accelerate the identification of causal alleles for rare genetic diseases. There are two main strands to this: (i) identifying which variants discovered in exome-seq appear to be having a functional impact on transcripts, and (ii) identifying transcript outliers, especially among known causal genes, that may not necessarily have a causal variant identified from exome sequencing. The latter may identify the presence of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites deep within introns, or loss of long range regulatory elements), which can be confirmed with further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g. nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs). This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with primordial dwarfism syndromes, for 10 of these samples we have previously generate exome data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining samples are positive controls where the causal mutation is known, and is known to affect transcript structure and/or abundance. Primordial dwarfism is a prime candidate for these RNA-seq studies because all known causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the products of the causal genes are typically ubiquitously expressed. Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity. 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 EGAD00001000640

• WGS and RNA-Seq data from a GBM patient PT-GB9186

  WGS and RNA-Seq data from a GBM patient PT-GB9186

  Dataset EGAD00001004237

• WGS and RNA-Seq data from a GBM patient PT-AH1410

  WGS and RNA-Seq data from a GBM patient PT-AH1410

  Dataset EGAD00001004223

• WGS and RNA-Seq data from a GBM patient PT-AK7565

  WGS and RNA-Seq data from a GBM patient PT-AK7565

  Dataset EGAD00001004224

• WGS and RNA-Seq data from a GBM patient PT-GR2309

  WGS and RNA-Seq data from a GBM patient PT-GR2309

  Dataset EGAD00001004241

• WGS and RNA-Seq data from a GBM patient PT-GB9483

  WGS and RNA-Seq data from a GBM patient PT-GB9483

  Dataset EGAD00001004238

• WGS and RNA-Seq data from a GBM patient PT-HN6692

  WGS and RNA-Seq data from a GBM patient PT-HN6692

  Dataset EGAD00001004242

• WGS and RNA-Seq data from a GBM patient PT-BK0248

  WGS and RNA-Seq data from a GBM patient PT-BK0248

  Dataset EGAD00001004228

• WGS and RNA-Seq data from a GBM patient PT-LS4891

  WGS and RNA-Seq data from a GBM patient PT-LS4891

  Dataset EGAD00001004252

• WGS and RNA-Seq data from a GBM patient PT-AB0029

  WGS and RNA-Seq data from a GBM patient PT-AB0029

  Dataset EGAD00001004221

• WGS and RNA-Seq data from a GBM patient PT-LR9369

  WGS and RNA-Seq data from a GBM patient PT-LR9369

  Dataset EGAD00001004251

• WGS and RNA-Seq data from a GBM patient PT-JP2405

  WGS and RNA-Seq data from a GBM patient PT-JP2405

  Dataset EGAD00001004247

• WGS and RNA-Seq data from a GBM patient PT-JB1730

  WGS and RNA-Seq data from a GBM patient PT-JB1730

  Dataset EGAD00001004245

• WGS and RNA-Seq data from a GBM patient PT-RL7940

  WGS and RNA-Seq data from a GBM patient PT-RL7940

  Dataset EGAD00001004258