15000 results for "cancer studies using rna-seq"

in 17.65 milliseconds.

• cfDNA from fractionated and paired unfractionated plasma samples of lung cancer patients

  Plasma from lung cancer patients from EDTA tubes was fractionated using size exclusion chromatography. Fractions 1-5, 7-11, 12-15, 16-20 were pooled, cfDNA was extracted from the fractions and paired unfractionated samples and PE150bp sequencing was performed on an Illumina Novaseq S4 flowcell. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001009780

• Mannheim Liquid Biopsy Unit, Heidelberg University & DKFZ

  The dataset consists of sequenced cell free DNA (cfDNA) samples from colorectal cancer patients. The samples were sequenced on an Illumina MiSeq machine using a custom amplicon sequencing approach. These amplicons were designed to cover the most common mutation hotspots in colorectal cancer. The data include 138 cfDNA samples from 34 different patients. For each patient several samples are available derived from blood drawn at different time points during treatment. In addition the data include samples from 22 histology slides and 30 samples derived from HT29/HCT116 cell lines that were used as controls.

  Dataset EGAD00001004574

• Hereditary Cancer Diagnostics with I2HCP gene panel

  Germline blood DNA sequencing data generated in routine diagnostics of hereditary cancer using the I2HCP gene panel (~135 genes). There are 130 samples sequenced in a MiSeq machine and 108 sequenced in a HiSeq machine. There is a partial overlap between those two sets, meaning that some samples were sequenced in both machines. There is a strong enrichment in samples with copy-number variants (CNV), both single- and multi-exon, since this dataset was compiled for a benchmarking effort of CNV calling tools for genetic diagnostics.

  Dataset EGAD00001006171

• Gene Expression between PMD and Control LCLs at Baseline, E2, and E2 Withdrawal

  In this study, lymphoblastoid cell lines (LCLs) derived from women with past perimenopausal depression (PMD) (n = 8) and asymptomatic controls (n = 9) were compared via poly(A)-selected transcriptome sequencing (RNA-seq). LCLs were cultured in three experimental conditions: at vehicle baseline (ovarian steroid-free), during estradiol (E2) treatment, and following E2-withdrawal. Transcriptomic analysis revealed significant differences in transcript expression in PMD LCLs compared to controls in all experimental conditions, and significant overlap in genes that were changed in PMD regardless of experimental condition. Among these, chemokine CXCL10 was upregulated in women with PMD, but most so after E2-WD and CYP7B1, an enzyme intrinsic to DHEA metabolism, was upregulated in PMD across experimental conditions. Finally, this in vitro model identified gene networks dysregulated in PMD which included inflammatory response, early/late E2-response, and cholesterol homeostasis. Data available will include the normalized counts for each subject in the study.

  Study phs003003

• A Comprehensive Platform for Analyzing Longitudinal Multi-Omics Data

  PALMO (Platform for Analyzing Longitudinal Multi-omics data) is a platform for analyzing longitudinal data from bulk as well as single cell. It allows to identify inter-, intra-donor variations in genes over longitudinal time points. The analysis can be done on bulk expression dataset without known cell type information or single cell with cell type or user defined groups. It allows to infer stable and variable features in a given donor and each cell type or a user defined group. The outlier analysis can be performed to identify technical/biological perturbed samples in a donor or a participant. Further, differential analysis can be performed to decipher time-wise changes in gene expression in a cell type. The data that is available in the dbGaP is the demo longitudinal samples used in the study, which includes hashed raw fastq files for single-cell RNA-sequencing (scRNA-seq) and non-hashed fastq files for single-cell ATAC-sequencing (scATAC) experiment.

  Study phs003203

• Multi-Ethnic Study of Atherosclerosis (BioLINCC)

  The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Data available for request include phenotypic data previously released on BioLINCC as well as raw images (E.g. Echocardiogram) and raw tracing data files (e.g. Electrocardiogram). These new data are intended to be made available to interested researchers via BioData Catalyst, will include participants irrespective of participation in genetics (i.e. the full MESA cohort), and may be merged with currently posted (to dbGaP) phenotype and molecular datasets (WGS, GWA, RNA Seq, Methylation, Metabolomics, and Proteomics).

  Study phs003288

• Integrative Somatic and Germline Computational Biology to Redefine Clinical Actionability in Solid Tumors

  Neuroendocrine tumors (NETs) are rare cancers that arise in the gastrointestinal tract and pancreas. The fundamental mechanisms driving gastroenteropancreatic NETs (GEP-NETs) growth remain incompletely elucidated; however, the heterogeneous clinical behavior of GEP-NETs suggests that both cellular lineage dynamics and tumor microenvironment influence tumor pathophysiology. Here, we performed single-cell RNA-sequencing (scRNA-seq) of fresh resections of GEP-NETs, including four pancreatic NETs, three small intestinal NETs, and one perigastric NET. We used single-cell sequencing to investigate the tumor and immune cellular landscapes of GEP-NET patients. Malignant GEP-NET gene and regulon expression was compared with normal, gastrointestinal endocrine cell differentiation and fate determination stages. We further characterized immune-immune and immune-tumor interaction networks within GEP-NETs, identifying novel therapeutic opportunities in the myeloid compartment of the microenvironment. Our findings highlight the transcriptomic heterogeneity that distinguishes the cellular landscapes of GEP-NET anatomic subtypes and reveal potential avenues for future precision medicine therapeutics.

  Study phs003141

• Genome sequencing identifies splice-disrupting variants in childhood heart disease

  We used genome sequencing (GS) to identify cardiac specific splice disrupting variants that were subsequently validated in a subset of participants. In turn, we developed a heart-specific model for canonical and non-canonical splice variants, which was applied to patients with congenital heart disease (CHD). These included patients with two of the most common forms of cyanotic CHD i.e. tetralogy of Fallot (TOF) and dextro-transposition of the great arteries (TGA). In addition to identifying canonical splice-disrupting variants in known CHD-related genes in 1% cases, this approach identified putatively damaging non-canonical splice-disrupting variants in 11% of isolated CHD, with deeply intronic variants representing 53% of non-canonical splice-disrupting variants in CHD genes. GS was critical for the identification of variants that would not be captured by routine clinical genetic tests including exome sequencing, while cardiac RNA-Seq allowed for high specificity in the interpretation of splice-disrupting effects in the heart.

  Study EGAS50000000586

• Single Cell Transcriptional Analysis of Human Adenoids Identifies Molecular Features of Airway Microfold Cells

  We aimed to characterize the cellular composition and molecular features of the human adenoid, a mucosa-associated lymphoid tissue located in the upper airway, with a focus on epithelial populations involved in immune surveillance. To this end, we performed single-nucleus RNA sequencing (snRNA-seq) on adenoid tissue obtained from 6 human donors (age 2 – 14; 3 males and 3 females) undergoing routine adenoidectomy. The donor cohort includes clinically annotated samples with no known immunodeficiency or chronic airway disease.Our analysis uncovered distinct epithelial populations, including transcriptionally defined immature and mature microfold (M) cells, and a previously unrecognized interferon-stimulated epithelial population enriched for antiviral response genes, which we term WISP cells (Waldeyer's ring Interferon-Stimulated Population). We validated key transcriptomic findings through multiplex immunofluorescence microscopy in independent donor tissues, confirming the spatial localization of WISP and M cells and their predicted interactions with specific immune subsets.

  Study phs004103

• Searching for variants associated with endometriosis

  We explored regulatory mechanism of a SNP on chromosome 9p21 associated with endometriosis by leveraging “allele-specific” functional genomic approaches. By re-sequencing 1.29 Mb of 9p21 region and scrutinizing DNase-seq data from the ENCODE project, we prioritized rs17761446 as a candidate functional variant that was in perfect linkage disequilibrium with the original GWAS SNP (rs10965235) and located on DNase I hypersensitive site. Chromosome conformation capture followed by high-throughput sequencing revealed that the protective G allele of rs17761446 exerted stronger chromatin interaction with ANRIL promoter. We demonstrated that the protective allele exhibited preferential binding affinities to TCF7L2 and EP300 by bioinformatics and chromatin immunoprecipitation (ChIP) analyses. ChIP assays for histone H3 lysine 27 acetylation and RNA polymerase II reinforced the enhancer activity of the SNP site. The allele specific expression analysis for eutopic endometrial tissues and endometrial carcinoma cell lines showed that rs17761446 was a cis-regulatory variant where G allele was associated with increased ANRIL expression.

  Study EGAS00001001741

• RNA_seq_of_Toxoplasma_gondii_response_in_human_macrophages

  Toxoplasmosis is a zoonotic disease caused by a ubiquitous protozoan parasite called Toxoplasma gondii, which caninfect all mammal and bird species throughout the world. seroprevalence varies widely between countries. Studieshave estimated that between 7-34% of people in the UK have been infected with T. gondii. The vast majority of thesepeople will not have noticed any symptoms, however about 10% of people develop a mild to moderate self limitingflu-like illness. Following the acute active stage of the infection the parasite persists in the body in the form of cysts,particularly in heart and skeletal muscle and nervous system tissues, for many years, and usually for life. Inimmunocompetent persons these cysts do not pose a health risk. We will use RNA-seq to quantify the transcriptionalresponse of macrophages to T gondii infection.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/

  Study EGAS00001001708

• Single_Cell_RNAseq_at_various_stages_of_HiPSCs_differentiating_toward_definitive_endoderm_and_endoderm_derived_lineages

  When comparing the differentiation capacities of pluripotent stem cell lines that have different genetic backgrounds, batch to batch experimental variablility poses a significant challenge, especially when trying to identify smaller effects. One way to address this issue is to differentiate several different lines in the same culture dish, thereby elimating experimental variation. In addition, it allows researchers to analyze many more lines with less experiments. Parallel single cell RNA-Seq exploits that individual cells are tagged and hence each cell can be reliably assigned to the donor of origin based on the genetic variants it contains. In addition, analyzing the genetic signature of single cells within a differentiating population can reveal differentation stages that are not easily detected in bulk RNAseq data. 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/

  Study EGAS00001002278

• Myoepithelial progenitors as founder cells of hyperplastic human breast lesions upon PIK3CA transformation

  The myoepithelial (MEP) lineage of human breast comprises bipotent and multipotent progenitors in ducts and terminal duct lobular units (TDLUs). We here assess whether this heterogeneity impacts on oncogenic PIK3CA transformation. Single cell RNA sequencing (scRNA-seq) and multicolor imaging reveal that terminal ducts represent the most enriched source of cells with ductal MEP markers including a-smooth muscle actin (a-SMA), keratin K14, K17 and CD200. Furthermore, we find neighboring CD200high and CD200low progenitors within terminal ducts. When sorted and kept in ground state conditions, their CD200low and CD200high phenotypes are preserved. Upon differentiation, progenitors remain multipotent and bipotent, respectively. Immortalized progenitors are transduced with shp53 and mutant PIK3CA. Upon transplantation, CD200low MEP progenitors distinguish from CD200high by the formation of multilayered structures with a hyperplastic inner layer of luminal epithelial cells. We suggest a model with spatially distributed MEP progenitors as founder cells of biphasic breast lesions with implications for early detection and prevention strategies.

  Study EGAS00001005933

• Oncogenic cooperation in a human de novo T-ALL model

  We previously modelled T-cell acute lymphoblastic leukemia (T-ALL) by over-expressing four oncogenes (activated NOTCH1, LMO2, TAL1, and BMI1) in healthy human umbilical cord blood cells through lentiviral transduction (Kusakabe et al, Nat Commun 10, 2913 (2019). https://doi.org/10.1038/s41467-019-10510-8). We have now tested individual effects of the four oncogenes by transducing human cells with all possible combinations of one, two, three, and four oncogenes. We also tested the effects of additional known T-ALL oncogenes including HOXA9, LYL1, MEF2C, NXK2.1, TLX1, and TLX3. In addition to culture in vitro on OP9-DL1 feeders, we also injected transduced cells into immunodeficient NSG mice. We observed differing abilities of the various oncogene combinations to support growth in vitro and frank leukemia in vivo. This study includes RNA-seq data from samples of transduced cells cultured in vitro as well as cells harvested from clinically moribund mice after development of leukemia in vivo.

  Study EGAS00001006055

• Local In Time Statistics for processual research

  Background: Functional genomics in a processual analysis cover the time-dependent changes in transcriptomics and epigenetics before diagnosis of a disease, reflecting the changes in both life style and disease processes. The aim of this paper is to explore the dynamic, time-dependent mechanisms of the metastatic processes, using blood transcriptomics and including time in a continuous manner. For achieving this goal we develop new statistical methods based on statistics that are local in time. Methods: The new statistical method, Local In Time Statistics (LITS), is based on calculating statistics in moving windows and randomization. The method has been tested for the analysis of a dataset that collectively provides information on the blood transcriptome up to eight years before breast cancer diagnosis. The dataset from the NOWAC Post-genome Cohort consists of 467 case-control pairs matched on birth year and time of blood sampling. The data for a pair is the difference in log2 gene expression between the case and control. The stratified analyses are based on important biological differences like metastatic versus non-metastatic cancer, and the mode of cancer detection, i.e. screening detected versus clinically detected cancers. The dataset was used for examining whether the gene expression profile varies between cases and controls, with time, or between cases with and without metastases. Results: The null hypotheses of no differences between cases and controls, no time-dependent changes, and no differences between different strata were all rejected. For screening detected cancers the probability of correct prediction of metastasis status was best in year 1 before diagnosis compared to year 3 and 4 before diagnosis for clinically detected cancers. The predictor was not very sensitive to the number of genes included.Conclusions: Using a new statistical method, LITS, we have demonstrated time-dependent changes of the blood transcriptome up to eight years before breast cancer diagnosis.

  Study EGAS00001002520

• Samples obtained within X-pand project

  This dataset contains five bone marrow samples and three mobilised peripheral blood ones from different healthy individuals. The three bone marrow samples have been sequence with the 10x multiome kit using Illumina sequencers. The three mobilised peripheral blood ones have been split in two aliquots, one for 10x multiome and the other for 10x CITE-seq. Both libraries types have been sequenced with an Illumina sequencer. Raw data has been processed with cell-ranger and map to the human genome (GRCh38) to obtain the bam files.

  Dataset EGAD50000001108

• Whole-exome sequencing of 20 samples of actinic keratosis (10s) and cutaneous squamous cell carcinoma (10s)

  Whole-exome sequencing of 20 samples of actinic keratosis (10) and cutaneous squamous cell carcinoma (10) was performed to investigate a potential relationship between DNA methylation-based subtypes and genetic mutation patterns. 7 samples were shown to belong to the stem cell-like subclass (4 AK and 2 SCC), 12 - to the keratinocyte-like subtype (6 AK and 6 SCC) and one SCC sample is unclassified (was not included in the methylation analysis). Exome regions were captured using Agilent Low Input Exome-Seq Human v5 kit and sequenced on Illumina Hiseq4000 with paired-end 100-nucleotide reads.

  Dataset EGAD00001003765

• EGAD00010000744

  Subset 2 of osteoarthritis cases genotyped on Illumina 610k from the arcOGEN Consortium (http://www.arcogen.org.uk/) with consent for osteoarthritis studies only.

  Dataset EGAD00010000744

• Dataset for HCPlus_WES

  WES/WGS sequencing data of 234 chromothriptic tumor and control runs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001009272