14983 results for "cancer studies using rna-seq"

in 19.86 milliseconds.

• HuBMAP: Single-Cell Multiplex Chromatin and RNA Interactions in Aging Human Brain

  The study employs the Multi-Nucleic Acid Interaction Mapping in Single Cell (MUSIC) technique to concurrently profile multiplex chromatin interactions, gene expression, and RNA-chromatin associations within individual nuclei, revealing dynamically organized chromatin complexes in human frontal cortex samples from elderly donors. The MUSIC technique allows for the exploration of chromatin architecture and transcription at cellular resolution in complex tissues. The study includes 14 human cortex tissues and employs MUSIC to delineate diverse cortical cell types and states, revealing that nuclei with fewer short-range chromatin interactions correlate with an "older" transcriptomic signature and Alzheimer's pathology. Additionally, the study elucidates that specific cell types, characterized by chromatin contacts between cis expression quantitative trait loci (cis eQTLs) and a promoter, are particularly susceptible to the regulatory impact of these cis eQTLs on target gene expression. Furthermore, the female cortical cells exhibit highly heterogeneous interactions between the X-inactive specific transcript (XIST) non-coding RNA and Chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploring chromatin architecture and transcription at cellular resolution in complex tissues.

  Study phs003568

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• RBSC11

  One retinoblastoma sample was studied by single-cell RNA-sequencing (10X genomics Chromium).

  Dataset EGAD00001007497

• Genomic Analysis of Mucinous Tumours (GAMuT) - RNA

  RNASeq for Genomic Analysis of Mucinous Tumours (GAMuT)

  Dataset EGAD00001005190

• AI_NF1glioma_RNAseq

  The dataset includes 29 tumor samples from NF1-glioma patients profiled by RNA sequencing.

  Dataset EGAD00001004376

• Single cell atlas of large B-cell lymphoma

  Large B-cell lymphomas (LBCL) are clinically and biologically heterogeneous lymphoid malignancies, shaped by complex tumor and microenvironments that play a critical role in disease progression. There has been no direct and comprehensive single-cell characterization of tumor microenvironment in LBCL that simultaneously captures lymphoid, myeloid, and stromal populations across a sufficiently large cohort to reveal reproducible and biologically meaningful patterns. Here, we performed single-nucleus multiome profiling, coupled with bulk DNA and RNA sequencing, on 232 tumor and control biopsies to comprehensively map cell subpopulations of LBCL. Through this integrative approach, we identified Lymphoma Microenvironment Archetype Profiles (LymphoMAPs)—distinct, reproducible patterns defined by the co-occurrence of functionally specialized cell subsets. We further characterized the cell-cell communication pathways that shape these transcriptional phenotypes within archetypes. Importantly, we discovered associations between specific LymphoMAPs and clinical and molecular features of LBCL, including response to CD19 CAR T-cell therapy. Our study provides a valuable resource of lymphoid, myeloid, and non-hematopoietic cell states in LBCL and offers a framework for understanding how the abundance and functional state of cells within the tumor microenvironment may drive inter-patient variability in therapeutic outcome.

  Study EGAS50000001022

• Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma

  Immune checkpoint inhibitors are effective cancer treatments, but molecular determinants of clinical benefit are unknown. Ipilimumab and tremelimumab are antibodies against cytotoxic T-lymphocyte antigen 4 (CTLA-4). Anti-CTLA-4 treatment prolongs overall survival in patients with melanoma. CTLA-4 blockade activates T cells and enables them to destroy tumor cells. We obtained tumor tissue from patients with melanoma who were treated with ipilimumab or tremelimumab. Whole-exome sequencing was performed on tumors and matched blood samples. Somatic mutations and candidate neoantigens generated from these mutations were characterized. Neoantigen peptides were tested for the ability to activate lymphocytes from ipilimumab-treated patients. Malignant melanoma exomes from 64 patients treated with CTLA-4 blockade were characterized with the use of massively parallel sequencing. A discovery set consisted of 11 patients who derived a long-term clinical benefit and 14 patients who derived a minimal benefit or no benefit. Mutational load was associated with the degree of clinical benefit (P = 0.01) but alone was not sufficient to predict benefit. Using genomewide somatic neoepitope analysis and patient-specific HLA typing, we identified candidate tumor neoantigens for each patient. We elucidated a neo-antigen landscape that is specifically present in tumors with a strong response to CTLA-4 blockade. We validated this signature in a second set of 39 patients with melanoma who were treated with anti-CTLA-4 antibodies. Predicted neoantigens activated T cells from the patients treated with ipilimumab.

  Study phs001041

• Birth Defects: Moebius Syndrome and Related Congenital Facial Weakness Disorders

  It is estimated that about 1 in every 33 infants in the United States is born with a birth defect. Among these, the subset of birth defect syndromes associated with facial weakness and lack of facial expression can have profound implications for social interactions and psychosocial development. Moebius syndrome is defined by congenital and non-progressive facial weakness and limited eye abduction, and most cases are believed to result from dysfunction of cranial nuclei/nerves VI and VII. Although rare, this syndrome causes significant impairment because of facial weakness and associated intellectual disabilities, autism, hearing loss, difficulty swallowing and breathing, peripheral neuropathy, muscle hypotonia, heart defects, chest wall abnormalities, and limb malformations. The phenotypic spectrum and the associated genetic and environmental factors underlying Moebius syndrome are poorly understood. The goal of this research is to identify causative gene mutations for Moebius syndrome and related conditions, such as Moebius-Poland or -Robin sequence, hereditary congenital facial paresis (HCFP), and oculoauriculovertebral dysplasia (Goldenhar syndrome). This proposal builds on an ongoing collaboration among researchers at Mount Sinai Medical Center, Boston Children's Hospital, NHGRI intramural program, and the Moebius Syndrome Foundation, but aims to greatly extend that work by collaboration with investigators in the NIH Clinical Center (CC). Our groups have already defined a new autosomal dominant syndrome with Moebius syndrome, Kallmann syndrome, cyclic vomiting resulting from a TUBB3 E410K substitution. We have also identified a new autosomal recessive Moebius-related syndrome with bilateral facial palsy, hearing loss, and strabismus resulting from a HOXB1 R207C substitution. Through collaborative efforts of these extramural teams with intramural investigators, whole exome sequencing (WES) has been conducted for four families with Moebius-like features, and data analyses are ongoing. The overall goal of this new grant application will be to conduct extensive phenotype analysis on approximately 24 families per year with Moebius and other undefined syndromes with facial weakness. Studies to be conducted at the CC include neurology, psychiatry, neurocognitive, rehabilitation medicine (muscle strength, speech/language pathology), ophthalmology, audiology, and genetics evaluations; autism screening; electromyography, nerve conduction, and blink reflex studies; videoscopy of quantitative eye movement recordings; 3D-CT craniofacial imaging; MRI of the brain, orbit, internal auditory canals, posterior fossa including brain diffusion tensor imaging for tractography; and genetic counseling. Jointly with the extramural teams, WES analysis and variant confirmation will be performed. A more comprehensive definition of the phenotypic and genotypic spectrum of these birth defects will have a significant impact on our understanding of the molecular pathways underlying dysmorphologies, cranial nerve development, and more common childhood disorders such as autism. Thus, this project will lead to strategies for prevention and treatment of birth defects.

  Study phs001383

• Action to Control Cardiovascular Risk in Diabetes (ACCORD) Clinical Trial

  The Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial was a randomized, multicenter, double 2 x 2 factorial design study involving 10,251 middle-aged and older participants with type-2 diabetes who are at high risk for CVD events because of existing CVD or additional risk factors. The purpose of ACCORD was to determine if intensive glycemic control, intensive lipid management and intensive blood pressure control could prevent major cardiovascular events (myocardial infarction, stroke or cardiovascular death) in adults with type 2 diabetes mellitus. Secondary hypotheses included treatment differences in other cardiovascular outcomes, total mortality, microvascular outcomes, health-related quality of life and cost-effectiveness. The ACCORD trial failed to show a beneficial effect of intensive blood pressure or lipid therapy on the primary outcome, and intensive glycemia management actually increased mortality. The hypothesis underlying this ancillary study is that the failure of ACCORD to achieve its goal of reducing cardiovascular risk in diabetic patients through intensive management of hyperglycemia, dyslipidemia, and hypertension may be the result of variation in drug response due to genetic variation between individual participants. Benefits of intensive therapy may accrue to subsets of subjects with specific genetic variants predisposing to efficacious responses to particular therapeutic regimens, and harms may accrue to those with other variants predisposing to poor efficacy or adverse events. Identifying these variants could lead to a precision medicine approach to treating diabetes where each patient's genetic profile could identify the most efficacious treatment regimen with the lowest likelihood of adverse events. To test this hypothesis, a genome-wide genetic analysis was undertaken, incorporating both common variants distributed across the genome and rare variants targeted to exonic regions. Associations of genetic variants with short term responses to individual medicines as well as long term outcomes were investigated. The dataset is composed of genetic data from the ~6100 participants who agreed to participate in the ACCORD optional genetic studies and who allowed broad investigator access to their samples and the data derived from those samples, and from whom a DNA sample of sufficient quality was obtained. While a total of 8514 participants consented to the optional genetics studies, not all consented to broad investigator access, and those who did not are not included in this dataset, although they were also genotyped. Access to these additional genotypes can only be obtained by direct collaboration with the investigators of this study. Phenotype data used in the association analyses are derived from the ACCORD public release clinical data set, which has been made available through BioLINCC.

  Study phs001411

• A Sequential Window of Opportunity Trial of Anti-PD-L1/TGF-β trap (M7824) Alone and in Combination with TriAd Vaccine and N-803 for Resectable Head and Neck Squamous Cell Carcinoma not Associated with Human Papillomavirus Infection

  This submission includes the whole exome and bulk RNA sequencing associated with the correlative study of clinical specimens from a prospective clinical study of neoadjuvant bintrafusp alfa in patients with newly diagnosed, surgically resectable oral cavity or laryngeal squamous cell carcinoma. 

  Study phs002849

• Spatiotemporal Analysis of the Human Cerebellum

  We sought to characterize neural progenitors within spatially demarcated regions of the human cerebellum at a molecular level during neurogenesis. We used laser-capture microdissection to enrich for cells within the ventricular zone and subventricular zone regions of the rhombic lip, external granule cell layer and Purkinje cell layer, then performed RNA-sequencing on the enriched samples.

  Study phs001908

• Vulnerabilities of Midbrain Dopaminergic Neurons to Parkinson's Disease Revealed by Single-Cell Genomics

  We developed a novel protocol for the enrichment of midbrain DA neurons from frozen tissue. We subsequently performed single-nuclei RNA-sequencing on enriched samples from postmortem midbrain tissue from human, macaque, tree shrew, rat, and mouse. We identified vulnerable and resistant populations from these data and associated genetic enrichments and differential expression changes.

  Study phs002879

• Personalized Treatment of Sezary Syndrome through a CTLA4:CD28 Fusion

  We sequenced two tumor and one normal whole genome libraries for a Sezary syndrome patient and also sequenced RNA libraries for each tumor. We identified a novel, highly expressed CTLA4:CD28 gene fusion that is predicted to results in a leading to stimulatory T-cell signaling in the presence of an inhibitory signal.

  Study phs000773

• Comprehensive genomic analysis of patient derived orthotopic xenograft model in primary central nervous system lymphoma

  The purpose of this study is to investigate genetic background of orthotopic xenograft cells and aseess consistency with parent tumor cells. For exome sequencing, we used two distinct PCNSL cells (YML9 and YML11). We also performed RNA sequencing for 7 PCNSL patient tumor cells to compare NF-kB pathway activation.

  Study JGAS000178

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  To elucidate the feature of age-associated helper T (ThA) cells and its contribution to autoimmune diseases, single-cell RNA-sequencing analysis of peripheral blood CD4+ T cells from healthy control, CD4+ T cells in muscles and bronchoalveolar lavage fluid (BALF) from patients with idiopathic inflammatory myopathy were conducted.

  Study JGAS000648

• Multi-modal single-cell analysis of salivary glands from patients with Sjogren's syndrome

  Sjogren's syndrome (SS) is an autoimmune disease that causes salivary gland dysfunction due to immune-mediated destruction. In this study, we apply multi-modal single-cell technologies - single-cell RNA sequencing and T-cell receptor sequencing - to salivary gland lesions, aiming to uncover transcriptional signatures and TCR sequence linked to autoantibody profiles.

  Study JGAS000808

• B-ALL bone marrow and CNS xenograft RNA sequencing

  This dataset includes TruSeq paired-end, total RNA sequencing data from primary B-precursor acute lymphoblastic leukaemia (B-ALL) xenografts. It comprises 43 pairs of matched bone marrow (BM) and central nervous system (CNS) human leukaemia cells from individual immunodeficient mice. Xenografts were generated from 6 patients with B-ALL and include samples taken at diagnosis and relapse from 3 of 6 patients.

  Dataset EGAD00001008183

• IG-MYC ALL - DNA and RNA sequencing

  The dataset is composed by the raw RNA sequencing (n=6), targeted DNA sequencing (n=18) and whole exome sequencing (n=17) from 19 patients with IG-MYC-rearrangements.

  Dataset EGAD00001008705

• Investigation of relapse prediction in infants with MLL-rearranged Acute Lymphoblastic Leukemia

  In infants with ALL, accurate relapse prediction would enable treatment strategies that take relapse risk into account, with potential benefits for both low- and high-risk patients. Through analysis of bone marrow biopsies taken at initial diagnosis, we show that single-cell RNA sequencing can predict future relapse occurrence.

  Study EGAS00001003986

• TTV018_RORC_IBD_associated_genotype_effects_on_RORgT_expression_and_function_in_ex_vivo_T_cells

  RNA sequencing of peripheral immune cells from patients +/- an IBD risk variant. Peripheral immune cells +/- in vitro test compound treatment.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 EGAS00001001590

• Multiomics analyses of Parkinson's disease midbrains

  Understanding the key pathological mechanisms underlying Parkinson's Disease pathology is fundamental for the development of novel and more effective therapeutic strategies. In this study, post-mortem human midbrain tissue from a cohort of 13 PD patients and 10 controls was analyzed with a set of multi-omics technologies including small RNA sequencing, transcriptomics and proteomics profiling.

  Study EGAS00001004966

• WTCCC case-control study for Inflammatory Bowel Disease, T1D and RA - combined cases

  WTCCC genome-wide case-control association study using three disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000008

• T1DGC GWAS 1958 British Birth Cohort controls

  T1DGC genome-wide case-control association study for Type 1 Diabetes (T1D) using the 1958 British Birth Cohort as controls. The cases for this study are made available from the NCBI dbGAP.

  Study EGAS00000000038

• RCC_HTA2.0_Reustle2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) related to Reustle et al., Clin Transl Med 12:2022 e883. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.26.0, R version 3.6.1). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 23).

  Dataset EGAD00010002352

• Genetic Etiology of Heterotaxy

  To understand the genetic etiology of heterotaxy, patients with heterotaxy were consented and recruited, with blood drawn for DNA extraction and exome sequencing. Using the exome sequencing dataset obtained, rare coding sequence variants were identified.

  Study phs001691

• Spatial Dynamics of the Developing Human Heart

  68 paired-end raw FASTQ files obtained from 38 tissue sections across 16 hearts, spanning embryonic human heart development between 5.5 and 14 postconceptional weeks. Some libraries were re-sequenced for better coverage. The tissue sections were processed using the 10x Genomics Visium Gene Expression kit, and libraries were paired-end sequenced using Nextseq2000 (Illumina).

  Dataset EGAD50000001615

• Establishment of iPS cells from Japanese healthy volunteers

  We performed whole exome sequencing of Japanese volunteers. We established iPSCs from those volunteers, and the iPSCs were deposited to Riken Bioresource Bank. The whole exome sequencing were performed using their PBMCs.

  Study JGAS000287

• Genome-Wide Bisulfite Sequencing of Urinary Cell-Free DNA

  The current sequencing dataset consists of 85 bisulfite sequencing data files (Fastq files) of human cell-free urine DNA samples. These extracted cfDNA samples were then constructed into DNA libraries using the KAPA HTP Library Preparation Kit (Kapa Biosystems) with bisulfite modification using the EpiTect Bisulfite Kit (Qiagen) and subsequently sequenced on the Nextseq500 platform (Illumina).

  Dataset EGAD50000001902

• The exploratory research of diagnositic biomarker and therapeutic targets of renal cell carcinoma.

  We search more effective markers, which predict worse prognosis in patients with RCC and become targets for therapy of RCC, using tissues of patients with RCC by global transcriptional analysis.

  Study JGAS000149

• WholeGenomeSeq-EGAS00001001306

  Whole Genome sequencing. 2 μg of genomic DNA from each sample was used for the construction of two short-insert paired-end sequencing libraries. Both types of libraries were sequenced in paired-end mode on Illumina GAIIx (2 × 151 bp) using Sequencing kit v4 or Illumina HiSeq2000 (2x101 bp) using TruSeq SBS Kit v3.

  Dataset EGAD00001001466