14983 results for "cancer studies using rna-seq"

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• miRNASeq profiles from Indian HFrEF Cohort

  The dataset contains miRNA profiling from a cohort of 49 HFrEF patients. The myocardium samples were collected from these patients during heart transplant of LVAD implantation procedure. The RNA samples were collected in RNAlater. Small RNA libraries were prepared using QIAseq miRNA Library Kit, Qiagen and sequenced on Illumina HiSeq4000.

  Dataset EGAD50000001194

• Dicer and/or ADAR1 depleted HEK293-LGP2 cells

  This dataset includes bulk RNA-sequencing data from HEK293-L cells subjected to siRNA-mediated knockdown of Dicer and/or ADAR1. In total, 12 samples are included, representing four experimental groups with triplicate biological replicates. RNA was extracted using TRIzol according to standard protocols and sequenced on an Illumina NovaSeq 6000.

  Dataset EGAD50000002044

• Single-cell RNA sequencing of acute myeloid leukemia patients

  Single-cell RNA sequencing was performed on bone marrow mononuclear cells from 8 acute myeloid leukemia patients at diagnosis. The profiling was performed using 10x Genomics 3' (5 samples) and 5' (3 samples) platforms. The raw data are available as fastq files.

  Dataset EGAD00001006173

• Single cell RNA-sequencing of treatment naïve PDAC patient samples

  Single cell RNA-sequencing of treatment naïve PDAC patient samples. We have 10 samples, sequenced using the 10X genomics chromium platform with 3 prime chemistry. We are submitting FASTQ files representing the index files (I1), Read1 (R1) and Read2 (R2).

  Dataset EGAD00001008961

• Small molecule screen reveals synergy of cell cycle checkpoint kinase inhibitors with DNA-damaging chemotherapies in medulloblastoma (methylation dataset)

  human medulloblastoma xenograft isolated from mouse brain was frozen and genomic DNA or RNA was extracted. Bisulfite converted DNA was processed and hybridised to illumina EPIC or 450K arrays using standard protocols. RNAseq was performed on total RNA.

  Dataset EGAD00001006583

• Evaluation of somatic mutations in urine samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Purpose: Current diagnostic methods for endometrial cancer lack specificity, leading to many women undergoing invasive procedures. The aim of this study was to evaluate somatic mutations in urine to accurately discriminate endometrial cancer patients from controls. Experimental Design: Overall, 72 samples were analyzed using next-generation sequencing with molecular identifiers targeting 47 genes. We evaluated urine supernatant samples from women with endometrial cancer (n=19) and age-matched controls (n=20). Cell pellets from urine and plasma samples from seven cases were sequenced; further, we also evaluated paired tumor samples from all cases. Finally, immunohistochemical markers for molecular profiling were evaluated in all tumor samples. Results: Overall, we were able to identify mutations in DNA from urine supernatant samples in 100% of endometrial cancers. In contrast, only one control (5%) showed variants at a variant allele frequency (VAF)≥2% in the urine supernatant samples. The molecular classification obtained by using tumor samples and urine samples showed good agreement. Analyses in paired samples revealed a higher number of mutations and VAFs in urine supernatants than in urine cell pellets and blood samples. Conclusions: Evaluation of somatic mutations using urine samples may offer a user-friendly and reliable tool for endometrial cancer detection and molecular classification. The diagnostic performance for endometrial cancer detection was very high, and cases could be molecularly classified using these noninvasive and self-collected samples. Additional multi-center evaluations using larger sample sizes are needed to validate the results and understand the potential of urine samples for the early detection and prognosis of endometrial cancer.

  Study EGAS00001007396

• Dataset for GIST-EXON

  Rare cancer sequencing data of 64 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008875

• TK-EPN862 - Patient-dervied xenograft model of Posterior Fossa A Ependymoma - RNAseq

  Ependymomas (EPN) are the third most common malignant brain cancer in children. Treatment strategies for pediatric EPN have remained unchanged over recent decades, with 10-year survival rates stagnating at just 67% for children aged 0-14 years. Moreover, patients who survive treatment for the most common subtype of pediatric EPN (posterior fossa A (PFA)), often suffer long-term neurological side effects as a result of therapy. It is evident that there is a need for safer, more effective treatments for pediatric EPN patients. There are ten distinct subgroups of EPN, each with their own molecular and prognostic features. To identify and facilitate the testing of new treatments for EPN, in vivo laboratory models representative of the diverse molecular subtypes are required. Here, we describe the establishment of a patient-derived orthotopic xenograft (PDOX) model of PFA EPN, derived from a metastatic cranial lesion. Patient and PDOX tumors were analyzed using immunohistochemistry, DNA methylation profiling, whole genome sequencing (WGS) and RNA sequencing. Both patient and PDOX tumors classified as PFA EPN by methylation profiling, and shared similar histological features consistent with this molecular subgroup. RNA sequencing revealed that gene expression patterns were maintained across the primary and metastatic tumors, as well as the PDOX. Copy number profiling revealed gains of chromosomes 7, 8 and 19, and loss of chromosomes 2q and 6q in the PDOX and matched patient tumor. No clinically significant single nucleotide variants were identified, consistent with the low mutation rates observed in PFA EPN. Overexpression of EZHIP RNA and protein, a common feature of PFA EPN, was also observed. Despite the aggressive nature of the tumor in the patient, this PDOX was unable to be maintained past two passages in vivo. Others who have successfully developed PDOX models report some of the lowest success rates for EPN compared to other pediatric brain cancer types attempted, with loss of tumorigenicity not uncommon, highlighting the challenge in propagating these tumors in the laboratory. Here, we discuss our collective experiences with PFA EPN PDOX model generation and propose potential approaches to improve future success in establishing preclinical EPN models

  Study EGAS00001006844

• Bam files from Whole exome sequencing (WES, ~50x mean read depth) of metachronous bladder tumors

  In this study we characterized genomic alterations in two to five metachronous bladder tumors from 29 patients initially diagnosed with early stage disease. Fourteen patients (32 tumors) had non progressive disease (NPD) and 15 patients (34 tumors) had progressive disease (PD). Whole exome sequencing (WES, ~50x mean read depth and whole transcriptome RNA-seq was performed (RNA was not advalible for 4 tumors) Data provided here consist of 122 Bam files for WES (83 Tumors and 39 blood)

  Dataset EGAD00001002716

• Single nucleus RNA Seq of LUAD patient derived lung samples

  Fastq files of single nucleus RNA Sequencing data from 26 patients including 26 lung adenocarcioma and 12 matched healthy tissue samples for 8 young female never smokers, 8 young female smokers, 7 elderly female never smokers and 3 male never smokers.

  Dataset EGAD00001008955

• The effect of anti-HER2/CD3 TDB on transcription in human CD8 T cells (bulk RNA-seq)

  RNA was isolated from purified human CD8 cells that were incubated with anti-HER2/CD3 TDB in the presence of SK-BR-3 cells. Sequencing libraries were generated and submitted for transcriptome profiling by high-throughput sequencing. Experiments were performed in triplicates for anti-HER2/CD3 TDB treatment and control. This Dataset is associated with the following ArrayExpress Experiment: E-MTAB-8211 - The effect of anti-HER2/CD3 TDB on transcription in human CD8 T cells (bulk)

  Dataset EGAD00001005187

• Integrated Exome-seq analysis of tumor thrombus

  We prospectively enrolled 83 patients with a renal mass and TT scheduled to undergo surgical resection. To accurately integrate genomic and transcriptomic findings and enable histological co-registration, simultaneous isolation of DNA and RNA was performed from individual samples characterized histologically through immediately flanking sections

  Study EGAS00001005511

• Enzymatic Methyl-Seq Rectal Mucus

  Enzymatic methyl sequencing of rectal mucus samples from patients suspected to have colorectal cancer. This is 1 of 4 sequencing experiments on the same sample type.

  Study EGAS50000001314

• Data for noninvasive lung cancer subtyping study

  This dataset included cfMethyl-Seq data of 15 plasma cfDNA samples from 15 lung cancer patients and RRBS data of 58 lung tumor tissue samples from 58 lung cancer patients. The data were generated following the standard protocols.

  Dataset EGAD00001015344

• RNA-sequencing from duodenal bipsies of Celiac disease patients

  Samples, in a form of PAXgene fixed and paraffin-embedded biopsies, were collected from the multi-site, double-blind, randomized, placebo-controlled trial, aimed at dose-finding and assessing the efficacy and tolerability of a 6-week treatment with ZED1227 capsules vs. placebo in subjects with well-controlled celiac disease undergoing gluten challenge. Total RNA was extracted from the PaxFPE biopsy specimens (n = 116) using additional cuttings from the samples on which histomorphometry was previously assessed. For the extraction, an RNeasy Kit (Qiagen, Hilden, Germany) was used according to the manufacturer’s instructions. Library preparation and next-generation sequencing (NGS) were performed by the Qiagen NGS Service. A total of 10 ng of purified RNA was converted into cDNA NGS libraries. Library preparation was quality controlled using capillary electrophoresis. Based on the quality of the inserts and the concentration measurements, the libraries were pooled in equimolar ratios and then sequenced on a NextSeq (Illumina Inc., San Diego, USA) sequencing instrument according to the manufacturer’s instructions, with 100 bp read length for read 1 and 27bp for read 2. The raw data were de-multiplexed, and FASTQ files for each sample were generated using bcl2fastq2 software (Illumina Inc., San Diego, USA).

  Dataset EGAD50000000491

• Integrative Gene Regulatory Network Analysis Discloses Key Driver Genes of Fibromuscular Dysplasia

  Fibromuscular dysplasia (FMD) is a poorly understood vascular disease that can lead to hypertension, stroke, myocardial infarction and even death. In 2013 we initiated the DEFINE study (ClinicalTrials.gov Identifier: NCT01967511), which has now recruited > 440 subjects and which aims to unravel the pathobiological mechanisms of this disease. Here, by integrating DNA genotype and RNA sequence data from primary fibroblasts of 83 FMD patients and 71 matched healthy controls from the DEFINE study, and its precursor the CAUSE study, we inferred 18 gene regulatory co-expression networks, four of which were found to act together as an FMD-associated super network in the arterial wall. Molecular studies indicated that this super network, termed SN-A and with the top key driver gene UBR4, governs multiple aspects of vascular cell physiology and functionality, including collagen/matrix production. The effects of UBR4 knockdown were also investigated in commercially available aortic smooth muscle and fibroblast cell lines by RNA sequencing, and these results are included in these datasets.Note, that of the 154 subjects in this analysis, 62 did not provide consent to have their genomic data made publicly available. Therefore the human subject data available here is from the 92 study participants who provided written informed consent to share their deidentified genomic data publicly.

  Study phs003674

• Whole Mitochondrial Sequencing of Gingivo-buccal Cancer: ICGC-India Project

  As a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from blood and tumor tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Whole genome and other sequencing experiments are being performed at the National Institute of Biomedical Genomics, Kalyani. Whole mitochondria sequencing of 89 patients was performed in this study. The mean depth of sequencing was at least 2500X, but variable across platforms, 2689X and 9894X for amplicon sequencing in Ion Torrent PGM (Tumor-blood pairs=16) and Illumina HiSeq 2500 (Tumor-blood pairs =48), respectively; and, 14,190X for whole genome sequencing in Illumina HiSeq 2500 (Tumor-blood pairs =25). Associations of mutation data with important clinical aspects have been found.

  Study EGAS00001002425

• Automated system for scoring hematoxylin and eosin-stained ovarian cancer sections by identifying single cells uncovered that stromal cell ratio is a significant predictor for overall survival and progression-free survival.

  Concerted efforts in genomic studies have revealed profound insights in prognostic ovarian cancer subtypes. On the other hand, abundant histology slides have been generated to date, yet their uses remain very limited and largely qualitative. Our goal is to develop automated histology analysis as an alternative subtyping technology for ovarian cancer that is cost-efficient and do not rely on DNA quality. We develop an automated system for scoring hematoxylin and eosin-stained (H&E) primary tumour sections of 91 late-stage ovarian cancer to identify single cells including cancer and stromal cells. We demonstrated high accuracy of our system based on expert pathologists’ scores (cancer=97.1%, stromal=89.1%) as well as compared to immunohistochemistry scoring (correlation=0.87). Quantitative stromal cell ratio is significantly associated with poor overall survival after controlling for clinical parameters including debulking status and age (multivariate analysis p=0.0021, HR=2.54, CI=1.40-4.60) and progression-free survival (multivariate analysis p=0.022, HR=1.75, CI=1.09–2.82). We demonstrate how automated image analysis enables objective quantification of microenvironmental composition of ovarian tumours. Our analysis reveals a strong effect of the tumour microenvironment on ovarian cancer progression and highlights the potential of therapeutic interventions that target the stromal compartment or cancer-stroma signalling in the stroma-high, late-stage ovarian cancer subset.

  Study EGAS00001001694

• Type I Interferon and Cycling Lymphocytes in Macrophage Activation Syndrome

  We performed immune profiling of peripheral blood mononuclear cells from patients with Still's disease and macrophage activation syndrome (MAS) using bulk RNA sequencing and single-cell RNA sequencing. Three groups were included in the study: healthy controls, patients with Still's disease without macrophage activation syndrome, and patients with Still's disease and macrophage activation syndrome. We found that macrophage activation syndrome is associated with transcriptomic signatures of interferon upregulation and cell cycling. We identified cycling lymphocytes within T cell and NK cell populations that are correlated with MAS disease activity. All sequencing data are available through dbGaP.

  Study phs003310