15059 results for "cancer studies using rna-seq"

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• RNA sequencing of intestinal metaplasia

  We perform bulk RNA-seq of 10 and single cell RNAseq of 2 intestinal metaplasia samples. We also perform stereoseq spatial transcriptomic analysis of 4 gastric cancer samples. The dataset contain cram files from 10 bulk RNAseq samples, and raw fastq files from 2 single cell RNAseq and 4 stereo-seq samples.

  Dataset EGAD50000002010

• Extended longitudinal single-cell RNA-seq data from ovarian cancer across multiple treatment phases

  The dataset contains single-cell RNA-seq data of 73 tumor samples high-grade serous carcinoma (HGSC) patients sequenced with Novaseq. The samples were collected at primary, interval, and relapse treatment phases from multiple tissue sites. The files provided are fastq files.

  Dataset EGAD50000001855

• DESIGN II HNSCC RNA-Seq

  RNA-Seq data of 28 HPV-negative HNSCC specimens from patients treated at the Netherlands Cancer Institute (Amsterdam), VU Medical Centre (Amsterdam) or MAASTRO Clinic (Maastricht) in The Netherlands. HNSCC biopsy samples were obtained prior to treatment (chemo-radiotherapy) for the prospective study within the DESIGN project and used for polyA mRNA sequencing.

  Dataset EGAD00001005722

• Pilot study for Illumina TST170 NGS panel on cutaneous T cell lymphoma samples

  A number of genomic studies using next generation sequencing (NGS) techniques have attempted to understand the underlying genetic basis of cutaneous T-cell lymphoma and found alterations in genes that are involved in T-cell activation, NF-kB and JAK-signal transducer and activator of transcription (STAT) pathways. 8 diagnostic skin biopsy samples (2xplaque, 6xtumour) on FFPE blocks were selected from 8 MF patients (stage IB:n=1, IIB:n=6, IVA2:n=1). An H&E was performed in order to assess percentage of tumor cells, viable cells, necrosis and immune infiltration, to determine the number of slides required for NGS. Freshly cut unstained slides were manually macrodissected prior to DNA and RNA extraction. Targeted deep sequencing was performed using panel of 170 genes associated with common solid tumours (Illumina TruSight Tumour 170 NGS panel). VCF files generated via the Illumina’s Basespace platform.

  Study EGAS00001002567

• RNA-sequençing of 21 inflammatory hepatocellular adenomas

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors.The present series corresponds to 21 RNA-seq of IHCA samples. Aligned bam files correspond to hg38 human reference.

  Study EGAS00001003685

• Tumor detection by analysis of both symmetric- and hemi-methylation of plasma cell-free DNA

  Aberrant DNA methylation plays a critical role in tumorigenesis. While DNA methylation has been used for cancer detection and classification, DNA hemi-methylation, a novel epigenetic mark has not been analyzed extensively in cancer epigenomes. Here we report a strand-specific (ss) sequencing method (MeDIP-Seq) for plasma cell free (cf) DNA (sscf-MeDIP-Seq), which can analyze both symmetrically methylated DNA regions (DMRs) as well as hemi-methylated regions (DHMRs). Using the sscf-MeDIP-Seq method, we analyzed plasma cfDNA methylomes of 271 samples from subjects with liver cancer and brain cancer and from individuals without cancer (controls). Among them, 215 samples were chosen as the discovery cohort for the identification of DMRs and DHMRs specific in each subject group and for the training of machine learning models of multi-cancer detection (MCD) using DMRs, DHMRs and DMRs+DHMRs as inputs. These models were then used to predict the 56 samples in the validation cohort. We found that models trained with DMRs+DHMRs as inputs in general outperformed models trained with DMRs or DHMRs alone, with AUROC being 0.971, 0.981, and 0.99 in predicting control, liver and brain cancer samples in the validation cohort, respectively, by the DMR+DHMR-trained models.

  Study phs003462

• Very Low Tumor Mutation Burden Identifies Inflamed Recurrent Glioblastomas Responsive to Cancer Immunotherapy

  A subset of available tumors (with matched blood) from patients enrolled in a phase I clinical trial testing a recombinant poliovirus, published by Desjardins et al. NEJM 2018 (PMID:29943666), were analyzed by whole exome sequencing and RNA-seq. It was discovered that low tumor mutation burden correlated with survival outcome, and also discovered that low tumor mutation burden correlated with higher inflammatory gene signatures by RNA-seq.

  Study phs002270

• Interpreting molecular role of DNA variants associated with Crohn's Disease through integrative analysis of open chromatin, epigenome and transcriptome data in diverse and relevant tissues and cells

  Crohn's disease (CD), one of the two major inflammatory bowel diseases (IBD), results from an inappropriately directed inflammatory response to the enteric microbiota in a genetically susceptible host. Genome wide association studies (GWAS) have linked >200 specific single nucleotide polymorphisms (SNPs) to CD disease pathogenesis. Within these regions, there are over 5600 additional SNPs that are in linkage disequilibrium (LD) with the tag SNPs, and it is not known which of these contribute to CD. Most of these SNPs map to non-coding regions of the genome, suggesting that causal variants contribute to CD by modifying gene regulatory element activity. In ths study, we have generated genotype, open chromatin (FAIRE-seq), and transcriptome (RNA-seq) data from macroscopically uninflamed regions of colon tissue for 21 CD patients and 11 non-IBD controls. All patients are adults (>18 years old).

  Study phs001418

• Paired-end RNA-seq analysis of the Hypermutation and Malignant Progression in Low-grade Glioma Patients

  44 DNA samples were derived from the tumors of the low grade glioma patients and sequenced using Illumina RNAseq paired-end technology. Dataset contains 44 BAM files aligned to hg19 using Tophat 2.

  Dataset EGAD00001005387

• Landscape of Intratumoral NK Cell and ILC in Head and Neck Squamous Cell Carcinoma

  In this study, total innate lymphoid cells (ILCs), including natural killer (NK) cells, were FACS-sorted from eight dissociated primary head and neck squamous cell carcinoma (HNSCC) tumors. In addition, ILCs and NK cells were sorted from peripheral blood of tumor patients. The ILCs and NK cells were analyzed by single-cell RNA sequencing (scRNA-seq) using the Smart-seq2 approach.

  Study phs002002