12086 results for "cancer rna-seq"

in 21.32 milliseconds.

• 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

• scRNA transcriptome and TCR sequencing data modeling treatment responses in eight renal cell carcinoma patient

  Single cell RNA sequencing and coupled TCR sequencing data generated following immunological treatments in patient-derived ex vivo tumor models. Dataset consist of 46 sequencing samples originating from eight individual patient-derived ex vivo models. Single cell RNA and TCR sequencing data is generated using 10X Genomics platform with 5´ sequencing. The submission contains 46 Fastq files where each patient-derived ex vivo model and it's transcriptomic response to specified treatment is a unique sequencing run. TCR sequencing runs are submitted as one file per individual model, gathering all the treatment conditions.

  Dataset EGAD50000001934

• 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

• 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

• 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

• Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) - OncoArray Genotypes

  Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) was one of five projects funded in 2010 as part of the NCI's Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (http://epi.grants.cancer.gov/gameon/). GAME-ON's overall goal was to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS. Specific goals included replication of previous GWAS findings and identification of new susceptibility loci through meta analyses of existing GWAS data and fine mapping of identified loci to better pinpoint causal variants; and identify germline variants that are associated with risk of multiple cancers. The other four funded GAME-ON projects were: the ColoRectal TransdisciplinaryStudy (CORECT), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Study (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL). To identify additional cancer risk loci, improve the precision of fine-mapping, and facilitate cross-cancer analyses, the GAME-ON projects and other consortia formed the OncoArray network (http://epi.grants.cancer.gov/oncoarray/), which developed and genotyped a new custom genotyping array (the "OncoArray") in large numbers of cancer cases and controls (over 400,000 samples). The OncoArray is a custom array manufactured by Illumina. The array includes a backbone of approximately 260,000 SNPs that provide genome-wide coverage of most common variants, together with markers of interest for each of the five GAME-ON cancers identified through genome-wide association studies (GWAS), fine-mapping of known susceptibility regions, sequencing studies, and other approaches. The array also includes loci of interest identified through studies of other cancer types, and other loci of interest to multiple cancer types (including loci associated with cancer related phenotypes, drug metabolism and radiation response). Additionally, SNPs relating to quantitative phenotypes such as body mass index (BMI), height, and breast density that correlate with common cancer risks are also included. The DRIVE data included under this dbGAP submission include OncoArray data from 60,015 breast cancer cases and controls genotyped at the Center for Inherited Disease Research (CIDR), University of Cambridge, National Cancer Institute, University of Copenhagen, University of Southern California and Mayo Clinic. Details on an additional approx. 80,000 breast cancer cases and controls genotyped at other centers can be found at http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/.

  Study phs001265