12304 results for "cancer rna-seq"

in 31.91 milliseconds.

• Comprehensive assay for the molecular profiling of cancer by target enrichment from formalin-fixed paraffin-embedded specimens

  Tumor molecular profiling is becoming a standard of care for patients with cancer, but the optimal platform for cancer sequencing remains undetermined. We established a comprehensive assay, the Todai OncoPanel (TOP), which consists of DNA and RNA hybridization capture-based next-generation sequencing panels. A novel method for target enrichment, named the junction capture method, was developed for the RNA panel to accurately and cost-effectively detect 365 fusion genes as well as aberrantly spliced transcripts. The TOP RNA panel can also measure the expression profiles of an additional 109 genes. The TOP DNA panel was developed to detect single nucleotide variants and insertions/deletions for 464 genes, to calculate tumor mutation burden and microsatellite instability status, and to infer chromosomal copy number. Clinically relevant somatic mutations were identified in 32.2% (59/183) of patients by prospective TOP testing, signifying the clinical utility of TOP for providing personalized medicine to cancer patients.

  Study JGAS000164

• Functional and genomic heterogeneity of long-term self-renewing compartment as the origin of treatment resistance in pancreatic tumors

  Adaptive drug-resistance mechanisms allow human tumors to evade treatment through selection and expansion of treatment-resistant clones. Here, studying clonal evolution of tumor cells derived from human pancreatic tumors, we demonstrate that in vitro cultures and in vivo tumors are maintained by a common set of tumorigenic cells that can be used to establish clonal replica tumors (CRTs), large cohorts of animals bearing human tumors with identical clonal composition. Using CRTs to conduct quantitative assessments of adaptive responses to therapeutics, we uncovered a multitude of functionally heterogeneous subpopulations of cells with differential degrees of drug sensitivity. High-throughput isolation and deep characterization of unique clonal lineages showed genetic and transcriptomic diversity underlying functionally diverse subpopulations. Molecular annotation of gemcitabine-naïve clonal lineages with distinct responses to treatment in the context of CRTs generated signatures that can predict the response to chemotherapy, representing a potential biomarker to stratify patients with pancreatic cancer. RNA-Seq data on these clones are available on EBI ENA, under accession number: PRJEB27735.

  Study EGAS00001003442

• Tumor HTG EdgeSeq from metastatic castrate resistant prostate cancer

  This dataset contains tumor bulk HTG EdgeSeq from patients with metastatic castrate resistant prostate cancer. RNA libraries were prepared following manufacturer's user guide (HTG Molecular Diagnostics). Each library was sequenced in HTG EdgeSeq system.

  Study EGAS00001004852

• Tumor Profiler Ovarian Study

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. Technologies used are digital pathology, targeted NGS, single-cell RNA, single-cell DNA, bulk RNA, bulk proteotyping, single-cell CyTOF, imaging mass cytometry, pharmacoscopy, 4i Drug Response Profiling, and cell-free DNA. These technologies were applied to 240 tumor samples collected over 3 years across three cancer indications: metastatic melanoma, metastatic epithelial ovarian cancer, and acute myeloid leukemia (AML). Here, we publish the scRNA and scDNA data of the ovarian cancer cohort.

  Study EGAS50000000885

• Chromatin run-on and RNA sequencing of fibrolamellar carcinoma

  Fibrolamellar carcinoma (FLC) is a rare, therapeutically intractable liver cancer that disproportionately affects youth. Here we used chromatin run-on sequencing to characterize the enhancer landscape in FLC and RNA sequencing to identify dysregulated genes in FLC.

  Study EGAS00001004169

• Colorectal adenomas and carcinomas NKI-AvL TGO series Gut2009

  Colorectal cancer (CRC) develops from normal epithelium, through a benign precursor lesion called adenoma, by accumulation of genetic alterations affecting oncogenes and tumour suppressor genes. These CRC-related genomic alterations often result in specific RNA-expression patterns. RNA isolated from fresh frozen specimen of 32 adenomas and 29 CRCs was obtained from the previously published study (Carvalho et al. 2009) and RNA-sequencing was performed with the aim to examine RNA expression changes in colorectal adenoma-to-carcinoma progression.

  Study EGAS00001002758

• Single cell RNA sequencing of tumor and ascites in high grade ovarian cancer

  Fastq files for single cell RNA sequencing of cells from ovarian cancer tumor and ascites (10X chromium 5' v1.1 libraries). Multiple cases are pooled in each sequencing library.

  Dataset EGAD00001006627

• RaScALL: Rapid screening of RNA-seq in acute lymphoblastic leukaemia

  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 accerelated risk-stratification and therapeutic triage.

  Study EGAS00001006460

• APP p.V742L and control fibroblasts RNA-seq

  This dataset consists of 16 FASTQ file pairs containing 3` RNA-sequencing data of patient-derived fibroblasts and three age- and sex-matched control fibroblast lines (CTR1, CTR2, and CTR3). The patient and CTR1 fibroblast lines have three biological replicates, while CTR2 and CTR3 lines both have one sample. Each sample has two lanes.

  Dataset EGAD50000001825

• Single-cell RNA-seq of AML blasts pre and post culture

  This dataset contains 6 Fastq files from 3 samples (pre-culture (n=1), post culture in standard (n=1) or niche-llike (n=1) conditions) from 1 AML patient. They correspond to single-cell RNA sequencing on Illumina plateform of 3 libraries prepared with 10X Genomics gene expression V3.1 chemistry.

  Dataset EGAD00001008772

• RNA-seq samples

  Raw FASTQ files obtained by RNA sequencing of tumor samples from patients (age 12-29) with newly diagnosed, recurrent intermediate or high-grade sarcoma.

  Dataset EGAD00001008393

• University of Michigan ALS Biorepository

  We are collaborators at the University of Michigan (Ann Arbor, MI) studying amyotrophic lateral sclerosis (ALS), employing sequencing-based approaches (e.g. bulk RNA-seq of whole blood) in case-control studies.

  Dac EGAC50000000598

• RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Transcriptomic analysis of K7M2 murine osteosarcoma cells stably modified to overexpress or repress CYR61

  Dataset EGAD50000000747

• Biomarker data

  Biomarker data for KATHERINE: Biomarker data include RNA-seq time point, Percent of tumor content, PAM50 subtypes, normalized gene expression of ERBB2, CD8 and CD274, normalized immune signature expression.

  Dataset EGAD00001008786

• MSAT dataset

  Muscle SATellite cell study (MSAT) dataset comprises 39 samples of paired-end RNA-Seq sequences in fastq format.

  Dataset EGAD00001008984

• Whole transcriptome and whole exome sequencing of BPDCN patients

  Here, seven patients with BPDCN were characterized using RNA-seq and WXS.

  Dataset EGAD00001010314

• A Functional Network of Gastric-Cancer-Associated Splicing Events Controlled by Dysregulated Splicing Factors

  Except for a few genes known to have oncogenic spliceforms in gastric cancer, the full scope of aberrant splicing in gastric oncogenesis remains unclear. In this study, we elucidated the alternative splicing events associated with gastric carcinogenesis and identified upstream regulators governing these events. We performed RNA-seq on 19 matched tumor/normal pairs and a panel of gastric cancer cell lines, and identified 361 tumor associated (TA) alternative splicing events (ASEs), which included known oncogenic ASEs in genes such as INSR, FGFR2, CD44 and KRAS. We further identified 8 splicing factors dysregulated in gastric tumors, the expression of which are correlated to the splice ratio of the TA ASEs. We thereby constructed a dysregulated splicing network in gastric cancer, consisting of alternative splicing changes correlated to their potential regulators. This network featured three potential regulatory modules centered around the splicing factors ESRP2, MBNL1 and PTPB1. Knockdown of each splicing factor led to the expected changes in splicing of approximately half of the ASEs assayed. Thus, dysregulation of the splicing factors indeed was the cause of many of the TA ASEs. Pathway enrichment analysis showed that genes affected by tumor associated splicing were pre-dominantly involved in cytoskeletal organization. Concordant with this, knockdown of the splicing factors regulating the TA ASEs led to the expected changes in trans-well migration activity. Thus, we have established for the first time a comprehensive splicing network that likely drives gastric tumor progression, based on which novel therapeutic targets can be identified for further evaluation.

  Study EGAS00001002256

• Single cell RNA sequencing of colorectal cancer with diverse tissue dissociation protocols or fresh vs. frozen cell preparations.

  To evaluate 3 different tissue dissociation protocols or fresh vs. frozen cell preparations, we performed single-cell RNA sequencing on cancer or distant normal tissue dissociates from 2 colorectal cancer patients. Total 18,409 cells from 10 sample preparations were analyzed (5 primary colorectal cancer and 5 matched normal mucosa). The results suggest highly consistent cellular proportions were recovered with different sample preparation methods.

  Dataset EGAD00001005191

• De novo modeling of chromoplectic Ewing sarcoma tumors from patient-derived mesenchymal stem cells

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic (RNA-seq) and epigenetic (ChIP-seq) hallmarks of EwS.

  Dataset EGAD50000001673

• Whole scRNA-seq from pre frontal cortex patient biopsy

  The single- cell RNA-seq prefrontal cortex sample was selected from a cohort of patients with hydrocephalus ≥18 years of age planning to undergo CSF diversion surgery either with a ventriculoperitoneal shunt placement (VP) or ventriculocisternostomy (VCS). The tissue was dissociated followed by red cell and debris removal and counting of the cells to be sequenced with (scRNA-seq; 10x Genomics kit v2). After dissociation only non neuronal cells were retrieved.

  Dataset EGAD50000001542

• NextGen Consortium: GENESiPS Study: Identifying the Gene Networks of Insulin Resistance

  Variability in induced pluripotent stem cell (iPSC) lines remains a roadblock for disease modeling and regenerative medicine. Through linear mixed models we have described different sources of gene expression variability from RNA sequencing data in 317 human iPSC lines from 101 individuals. We found that ~50% of genome-wide expression variability is explained by variation across individuals and identified a set of expression quantitative trait loci that contribute to this variation. These analyses coupled with allele specific expression show that iPSCs retain a subject-specific gene expression pattern. Pathway enrichment and key driver analyses, based on predictive causal gene networks, found that Polycomb targets explain a significant part of the non-genetic variability present in iPSCs within and across individuals. These publically available iPSC lines and genetic datasets will be a resource to the scientific community and will open new avenues to reduce variability in iPSCs and improve their utility in disease modeling. SNP array data from individuals included in RNA-seq transcriptome profiling study of human induced pluripotent stem cells to characterize gene expression variation across individuals and within multiple iPSC lines from the same individual. Genotyping was performed on patient blood. Data availability: SNP-genotyping: dbGaP - current study RNA-seq counts: GEO - GSE79636 FASTQ files: SRA - SRP072417

  Study phs001139

• Landscape of Intratumoral NK Cell and ILC in Head and Neck Squamous Cell Carcinoma

  In this study, total innate lymphoid cells (ILCs), including natural killer (NK) cells, were FACS-sorted from eight dissociated primary head and neck squamous cell carcinoma (HNSCC) tumors. In addition, ILCs and NK cells were sorted from peripheral blood of tumor patients. The ILCs and NK cells were analyzed by single-cell RNA sequencing (scRNA-seq) using the Smart-seq2 approach.

  Study phs002002

• CD4 T Cell Subsets in Human Metastatic Melanoma

  We used single-cell RNA-sequencing (scRNA-seq) to define CD4+ T-cell subsets in melanoma tumors from patients undergoing tumor resection. All patients received immune checkpoint blockade prior to surgery. We identified multiple subsets in the tumor with transcriptional features of suppressive function, including TR1 cells and FOXP3+ Treg cells. Based on transcriptional profiles, classical helper T cell subsets were not prevalent.

  Study phs003816

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

  arious peripheral blood immune cell subsets from 5 rheumatoid (RA) donors were collected ("CD16p_Mono", "CL_Mono???, "DN_B", "Fr_II_eTreg???, "mDC???, "Mem_CD4" , "Naive_B" , "Naive_CD4" , ???Neu", "NK" , "pDC" , "Plasmablast", ???SM_B", "Tfh", "Th1", "Th17", "Th2" , "USM_B"). The patients were analyzed again longitudinally after abatacept treatment. RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered.

  Study JGAS000602

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

  Various peripheral blood immune cell subsets from 39 healthy volunteers and 50 rheumatoid (RA) donors were collected ("CD16p_Mono", "CL_Mono???, "DN_B", "Fr_II_eTreg???, "mDC???, "Mem_CD4" , "Naive_B" , "Naive_CD4" , ???Neu", "NK" , "pDC" , "Plasmablast", ???SM_B", "Tfh", "Th1", "Th17", "Th2" , "USM_B"). 15 RA patients were analyzed longitudinally. RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered.

  Study JGAS000598