12310 results for "cancer rna-seq"

in 18.90 milliseconds.

• 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

• 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

• 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

• 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