15130 results for "cancer studies using rna-seq"

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• Genome-Wide Association Studies of Prematurity and Its Complications

  Preterm labor resulting in the delivery of a premature child is a complex problem with an enormous impact on individuals, families and society. An estimated 500,000 children are born prematurely in the U.S. each year, and 5 million worldwide die annually of prematurity and its complications. Prematurity is also the single largest contributor to disability-adjusted life years, a measure of the lifetime impact of a disease. Despite the importance of the problem and its disproportionate occurrence in poor and minority populations, its underlying etiology (or etiologies) remains unknown; the single best predictor for preterm delivery is a previous preterm birth. The largest single cause of prematurity is spontaneous preterm labor, and suspected triggers for this include infection, stress, poor nutrition and genetic factors. Family and twin studies provide strong evidence that genetic factors underlie about 40% of the risk for prematurity. A major challenge in studying genetic factors in prematurity is maternal/uterine factors, fetal/placental factors, or both may influence risk. Thus, any approach to studying preterm birth should account for both infant and maternal risk, environmental covariates and interactions. The Danish National Birth Cohort (DNBC) is a well-established, prospective cohort that enrolled women early in pregnancy, prior to any adverse pregnancy outcomes, to minimize bias in data collection and sampling. See details at: http://www.ssi.dk/English. The DNBC followed over 100,000 pregnancies beginning in the first trimester and has extensive biological material and epidemiologic data on health outcomes in both mother and child. The current study posted on dbGaP contains data from a genome-wide case/control study using approximately 1,000 preterm mother-child pairs from the DNBC most with spontaneous onset of labor or preterm premature rupture of membranes (PPROM), along with 1,000 control pairs where the child was born at ~40 weeks' gestation. After data cleaning some small changes in case/control status and other variables resulted in minor changes in numbers of cases or controls in certain categories. Environmental variables are being used as covariates in the analysis. To replicate positive findings, we are using additional mother-child pairs from the DNBC and from the general Danish population, as well as 2200 samples coming primarily from an African-American population known to have high rates of preterm labor and delivery. This group includes over 1000 mostly very low birthweight infants, over 500 infant term controls, 326 term mother/baby pairs and 180 preterm mother/baby pairs. The data from these additional cohorts will be available in separate dbGaP postings. The study is expected to yield a better understanding of the biology of parturition, identify common genetic factors that play a role in preterm birth and its complications and suggest environmental modifications that can prolong gestation, with the goal of improving both neonatal and adult outcomes. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to prematurity and its complications through large-scale genome-wide association studies of a well-characterized cohort of Danish mothers and babies. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000103

• Effects of 2DG, Galactose, or Oligomycin on the epigenome remodeling induce by T cells activation.

  T cell activation is known to require a metabolic shift towards glycolysis, triggered by TCR-engagement . To substantiate the role of glycolysis in transcriptional reprogramming during antigen-driven T cell activation, we utilized a well-established ex-vivo model to recapitulate the process of antigen stimulation without the requirement for additional antigen-presenting cells . We initially explored and validated the conditions for both metabolic and epigenetic reprogramming. Antigen-mediated CD4+ T cells activation initiates context-specific gene-expression programs that drive effector functions and cell fates through changes in the epigenetic landscape . To evaluate global changes in histone modifications, we isolated CD4+ T cells from peripheral blood (PB) of healthy control (HC) human donors and either maintained them in resting conditions or stimulated with anti-CD3/CD28 for 24h. Rapid changes in the CD4+ epigenome and transcriptome were observed within 24h as measured by RNA-sequencing (RNA-seq) and H3K27ac chromatin immunoprecipitation followed by DNA-sequencing (ChIP-seq).To explore the requirement for metabolic reprogramming in regulating transcriptional responses after initial TCR engagement, CD4+ T cells from PB of healthy donors were isolated and activated in either the presence or absence of oligomycin (inhibitor of ATP synthase blocking the production of ATP by OXPHOS), 2-deoxyglucose (2DG; competitively inhibiting production of glucose-6-phosphate from glucose), or replacement of glucose with galactose. Galactose is metabolized through glycolysis, utilizing the Leloir pathway which is energy neutral, forcing cells to use all the pyruvate production to sustain the TCA cycle for OXPHOS and ATP synthesis at the expense of lactate production. Employing ChIP-seq and RNA-seq, inhibition of OXPHOS-mediated ATP production by oligomycin had only a limited effect on H3K27-acetylation or activation-induced transcription during the first 24h of activation. In contrast, inhibition of glycolysis by 2DG treatment compromised both H3K27-acetylation and transcriptional changes. However, under conditions of galactose-metabolism where lactate production is abrogated, activated CD4+ T cells were still able to globally remodel H3K27 acetylation and reprogram the transcriptome.

  Study EGAS00001007115

• Title: Divergent levels of CD112 and INKA1 define a distinct subset of human long-term hematopoietic stem cells

  The data provided here was critical in establishing that human long-term hematopoietic stem cells (LT-HSC), previously described as the most primitive HSC population, is actually composed of distinct subsets that can be prospectively isolated. Via mechanistic studies centering around the Rho-GTPase effector kinase PAK4 and its inhibitor INKA1, we identified the immune checkpoint ligand CD112 as a marker for hematopoietic stem and progenitor cells, that is highest expressed on LT-HSC. More importantly, CD112 can be used to stratify functionally distinct subsets within LT-HSC: In response to regeneration-mediated stress, the CD112low subset exhibits a transient restraint (termed latency) before contributing to hematopoietic reconstitution, while the CD112high subset is primed to respond rapidly. High resolution RNA-seq of the CD112 surface expression spectrum within rare LT-HSC subsets (human umbilical cord blood) demonstrated that more genes are differentially upregulated in the deeper quiescent and less metabolic active subset. Genes enriched in this subset centre around cell adhesion and Rho-GTPase signaling. This is in agreement with the scRNAseq data from human G-CSF mobilized peripheral blood (mPB) generated here that was used as an model of in vivo activation/priming revealing via RNA-velocity and pseudo-time analysis that INKA1high versus PAK4high, CDK6high and CD112high enrichment are either detected early or late in diffusion pseudotime indicative of quiescent versus primed cell status, respectively. RNAseq following INKA1 overexpression in LT-HSC and ST-HSC revealed by GSEA an overall stemness preserving phenotype and particularly in LT-HSC, but not in short-term HSC (ST-HSC), suppression of transcriptional programs linked to activation. Collectively, our data decipher the molecular intricacies underlying HSC heterogeneity and self-renewal regulation and point to latency as an orchestrated physiological response that integrates quiescence control with HSC fate choices to preserve a stem cell reservoir.

  Dataset EGAD00001006541

• Genomics of acral lentiginous melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010126

• Comparison of 3 protocols for deriving pancreatic progenitors from hPSC with RNA-seq and ATAC-seq

  Several distinct differentiation protocols for deriving pancreatic progenitors (PP) from human pluripotent stem cells have been described but it remains to be shown how similar the PP are across protocols, and how well they resemble their in vivo counterparts. Here we evaluated three differentiation protocols; performed RNA and ATAC-seq on isolated PP derived with these, and compared them to fetal human pancreas populations. This enabled us to define a shared transcriptional and epigenomic signature of the PP, including several genes not previously implicated in pancreas development. Furthermore, we identified a significant and previously unappreciated cross-protocol variation of the PP through multi-omics analysis and demonstrate how such information can be applied to refine differentiation protocols for derivation of insulin-producing beta-like cells. Together, our study highlights the importance of a detailed characterization of defined cell populations derived from distinct differentiation protocols, and provides a valuable resource for exploring human pancreatic development.

  Study EGAS00001003513

• Identification of the Global miR-130a Targetome Reveals a Novel Role for TBL1XR1 in Hematopoietic Stem Cell Self-Renewal and t(8;21) AML

  In this study, we identified miR-130a as a regulator of HSC self-renewal and differentiation. To characterize gene expression changes following enforced expression of miR-130a OE, we performed RNA-seq in CD34+ cord blood (CB) cells transduced with control and miR-130a OE lentiviruses. To capture miRNA targets in an unbiased, transcriptome-wide manner, we perfomed enhanced CLIPseq procol in 2 replicates of CD34+ CB cells and Kasumi-1 cell line, which represent a model system for t(8;21) AML. We chose this cell line, as we found miR-130a to be highly expressed in this AML subtype where it is critical for maintaining the oncogenic molecular program mediated by AML1-ETO. Chimeric Ago2 eCLIPseq in CD34+ CB cells combined with Mass Spectrometry data analysis identified TBL1XR1 as a principal target of miR-130a. To elucidate gene expression changes associated with TBL1XR1 loss of function, we performed RNA-seq in CD34+CD38- CB cells transduced with control and shRNA targeted against TBL1XR1. To determine the functional significance of high miR-130a expression levels in Kasumi-1 cells on the molecular network controlled by AML1-ETO, we performed CUT&RUN assay and RNA-seq in Kasumi-1 cells following miR-130a knock-down (KD). Collectively, our findings reveal a unique role of miR-130a in regulating normal hematopoietic stem cell self-renewal and how elevated levels of miR-130a in t(8;21) AML contribute to the leukemogenesis of this AML subtype.

  Dataset EGAD00001008412

• (ChIP-seq) Shifted assembly and function of mSWI/SNF family subcomplexes underlie targetable dependencies in endometriod carcinomas

  ChIP-seq data of 18 samples from the VOA1066 undifferentiated endometrial carcinoma cell-line with various pulldowns: BRG1 (abcam, ab110642, GR3255117-11), BRD9 (CST, E4Q3F, Lot 1), ARID1A (CST, D2A8U, Lot 4), SS18 (CST, D6I4Z, Lot 1), PBRM1 (CST, D3F70, Lot 3), GLTSCR1 (CST, E6I3A, Lot 1), H3K27ac (CST, C36B11, Lot 16), or none. Sample were either untreated or received doxycycline-induced ARID1A treatment. Samples were sequenced on Illumina NextSeq 500 using 37 bp single-end sequencing parameters. Raw fastq files, along with processed bigwig files containing normalized genomic coverage, and called narrow peaks, are included for each sample.

  Dataset EGAD50000001473

• Colorectal-Cancer-Tumor-Spheres-H012-Microarray_Expression

  Gene expression of 12 colon cancer TSCs (sensitive or resistant) after 12h treatment with 3µM NCT02 or DMSO (control) was analyzed using Illumina microarrays (HumanHT-12 v4 BeadChip).

  Dataset EGAD00010001936

• Genotype data for African Esophageal squamous cell cancer cases and controls from South Africa

  This dataset contains the cleaned genotype data from 2173 African eosphageal squamous cell cancer cases and population controls. The genotype data was generated using the H3Africa Illumina Custom microarray.

  Dataset EGAD00010002575

• PacBio HiFi whole-genome sequencing of two microsatellite instability (MSI) gastric cancer

  We generated long-read whole-genome sequencing (WGS) data using PacBio HiFi from two human gastric cancer cell lines exhibiting microsatellite instability (MSI). The dataset contains aligned bam (hg38) files.

  Dataset EGAD50000002300

• Deep Sequencing of somatic cancer mutations

  We enriched a panel of cancer associated genes using the Custom Sure Select Target Enrichment Kit. Identified mutations were validated with deep sequencing in order to assess mutated allele frequencies more accurately.

  Dataset EGAD00001001313

• RaScALL: Rapid (Ra) screening (Sc) of RNA-seq data for prognostically significant genomic alterations in acute lymphoblastic leukaemia (ALL)

  RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia (ALL) have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early. However, a full RNA-seq Bioinformatics workflow is time-consuming and costly in a clinical setting where rapid detection and accurate reporting of clinically relevant alterations are essential. To accelerate the identification of ALL-specific alterations (including gene fusions, single nucleotide variants and focal gene deletions), we developed the rapid screening tool RaScALL, capable of identifying more than 100 prognostically significant lesions directly from raw sequencing reads. RaScALL uses the k-mer based targeted detection tool km and known ALL variant information to achieve a high degree of accuracy for reporting subtype defining genomic alterations compared to standard alignment-based pipelines. Gene fusions, including difficult to detect fusions involving EPOR and DUX4, were accurately identified in 98% (164 samples) of reported cases in a 180-patient Australian study cohort and 95% (n=63) of samples in a North American validation cohort. Pathogenic sequence variants were correctly identified in 75% of tested samples, including all cases involving subtype defining variants PAX5 p.P80R (n=12) and IKZF1 p.N159Y (n=4). Accurate detection of intragenic IKZF1 deletions resulting in aberrant transcript isoforms was also detectable with 98% accuracy. Importantly, the median analysis time for detection of all targeted alterations averaged 22 minutes per sample, significantly shorter than standard alignment-based approaches, ensuring accelerated risk-stratification and therapeutic triage.

  Dataset EGAD00001009087

• Variant analysis on FFPE specimen from NSCLC patients (OCAPlus)

  This study assessed the presence of somatic variants via the Oncomine Comprehensive Panel Plus panel (ThermoFisher) for commonly mutated cancer genes and measure tumor mutational burden using next-generation sequencing. It was performed on genomic DNA from FFPE tissue of tumor resections. Mutations were used to draw OncoPrints and to assess TMB in relation with response metrics.

  Study EGAS50000001136

• Prostate_Cancer_Whole_Genome_Validations

  We propose to definitively characterise the somatic genetics of Prostate cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing. This study will aim to validate the findings of the whole genome study by re-sequencing regions of interest using a bespoke pulldown bait. See ICGC website for more information: http://icgc.org/icgc/cgp/70/508/71331

  Study EGAS00001000427

• The molecular landscape of homologous recombination deficient, end-stage, high grade serous ovarian cancer

  High grade serous ovarian cancer (HGSC) is frequently characterized by homologous recombination (HR) DNA repair deficiency, and while most such tumors are sensitive to initial treatment, acquired resistance is common. We undertook a multi-omics approach to interrogating mechanisms of resistance, using multiple autopsy samples collected from 15 women with HR-deficient HGSC.

  Study EGAS00001006789

• Spatial targeted gene sequencing of metastatic melanoma

  We performed deep targeted DNA sequencing for a panel of 265 cancer-related genes. This included subsampling 35 different regions of a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor. Samples with cancer cell purity greater than 80% based on pathologic assessment were used for cancer gene panel DNA sequencing. Mean sequencing coverage was 861x and paired-end reads in FASTQ format were generated by the Illumina pipeline and aligned to the reference human genome hg19 build using the Burrows-Wheeler Alignment Tool (BWA, v0.7.5) with default settings. Aligned reads were further processed using GATK with best practices for removing duplicates, indel removal and recalibration.

  Dataset EGAD00001005821

• High-depth whole genome sequencing of 51 premalignant breast lesions

  Ductal carcinoma in situ (DCIS) is a non-obligate precursor lesion of breast cancer, representing 20-25% of newly diagnosed breast cancer lesions. It is currently not possible to predict which DCIS patients will progress to invasive breast cancer. The samples deposited here are part of a larger study using high-depth whole-genome sequencing (WGS) to investigate the somatic mutation genomic landscape of DCIS. Comprehensive evaluation of DCIS genomes aims to uncover biological insights into breast cancer progression and potential opportunities to stratify DCIS patients for personalised treatment options or active surveillance.

  Study EGAS50000001436

• Microsatellite unstable colorectal cancers

  Immune escape has been recognised as one of the hallmarks of cancer. Overcoming this immunomodulatory process by tumour cells has become a major therapeutic target. Here we utilize organoid technology to study immune-cancer interactions and assess immunomodulation by colorectal cancer (CRC). Transcriptional profiling and flow cytometry revealed that organoids maintain differential expression of immunomodulatory molecules present in primary tumours. Finally, we established a method to model antigen-specific epithelial cell killing and cancer immunomodulation in vitro using CRC organoids co-cultured with cytotoxic T cells. Our method may serve as a first step to rebuilding the tumor microenvironment in vitro.

  Study EGAS00001003366

• Single-cell RNA sequencing of blood immune cells before and after interleukin-2 immunotherapy

  Single-cell RNA sequencing of flow cytometry sorted human CD45+ immune cells from 3 systemic lupus erythematosus patients (SLE_002, SLE_004, and SLE_006) collected at baseline (day 0, before interleukin-2 immunotherpay) and day 5 (after 1 treatment cycle of interleukin-2 immunotherapy). Sorted immune cells were hash tagged and then stained with TotalSeq Human Universal Cocktail (Biolegend) before further processing for single-cell RNA sequencing using the 10X-Genomics platform. Samples from all 3 patients were pooled and loaded on 3 lanes of the chromium controller, resulting in 1 raw sequncing file for each lane.

  Dataset EGAD50000000662

• Assessing the impact of low frequency coding variants on disease risk using the Exomechip

  Following several rounds of Genome Wide Association (GWA) scans and subsequent meta-analyses of results multiple risk loci have been identified for many common diseases. However, in most instances the implicated common variants identified so far explain only a modest fraction of the genetic risk. In parallel to our efforts to identify the causative variants in the known loci it is necessary to assess the full spectrum of sequence variants for disease risk and in particular low frequency and rare variants that have not been tested in a comprehensive way so far. To this end an international effort by investigators who have performed whole exome sequencing in circa 12,000 individuals have assembled a set of ~250,000 exonic variants of low frequency – defined as seen in at least two studies and a minimum of three individuals (non-sysnonymous) or two individuals for SNPs altering splice sites / stop codons. The SNP content from the exome studies was complemented with additional interesting SNP sets totalling 25,000 markers (GWA tag SNPs, grid of common variants, HLA, Mitochondrial, Y-chromosome etc) and were used to generate a custom iSELECT array, the exome chip. Adequately powered association studies to test low frequency variants for association to disease risk are still very expensive if conducted by whole exome sequencing. The exome chip provides a cost efficient way to undertake such an experiment and the Wellcome Trust Cases Control Consortium will be applying this approach to eight diseases, type 1 and type 2 diabetes, coronary artery disease, hypertension, multiple sclerosis, rheumatoid arthritis, bipolar, and ankylosing spondylitis. The first objective will be to generate a large set of at least 10,000 common UK controls as analysis of lower frequency variants will require large sample sizes. This includes ~6000 samples from the 1958 Birth Cohort.

  Study EGAS00001000584