3883 results for "RNA AND sequencing OR transcriptome"

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• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX057_SA535X5XB02887_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005174

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX057_SA535X5XB02887_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005175

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX049_SA928_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005176

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX049_SA928_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005177

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX049_SA928_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005178

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX067_VOA12024_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005179

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX067_VOA12024_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005180

• RNA-Seq of vocal fold fibroblasts in Reinke’s edema and control subjects

  The voice disorder Reinke’s edema (RE) is a smoking- and voice-abuse associated benign lesion of the vocal folds, defined by an edema of the Reinke space, accompanied with pathological microvasculature changes and immune cell infiltration. Vocal fold fibroblasts (VFF) are the main cell type of the lamina propria and play a key role in the disease progression. Current therapy is restricted to symptomatic treatment. Hence, there is an urgent need for a better understanding of the molecular causes of the disease. In the present study, we investigated differential expression profiles of RE and control VFF by means of RNA sequencing. In addition, fast gene set enrichment analysis (FGSEA) was performed in order to obtain involved biological processes, mRNA and protein levels of targets of interest were further evaluated. We identified 74 differentially regulated genes in total, 19 of which were upregulated and 55 downregulated. Differential expression analysis and FGSEA revealed upregulated genes and pathways involved in extracellular matrix (ECM) remodeling, inflammation and fibrosis. Downregulated genes and pathways were involved in ECM degradation, cell cycle control and proliferation. The current study addressed for the first time a direct comparison of VFF from RE to control and evaluated immediate functional consequences.

  Study EGAS00001005130

• Small RNA sequencing of endometrial cancer patients with samples collected prior to diagnosis and controls

  This dataset contains unpaired FASTQ files of 316 endometrial cancer cases and 316 matched controls representing circulating RNAs. RNA count files are provided as the output of sncRNA pipeline and represent 12 RNA types (isomiR, lncRNA, precursor miRNA, miRNA, miscRNA, mRNA, piRNA, scaRNA, snoRNA, snRNA, tRF, and tRNA). We also provide metadata of the samples.

  Dataset EGAD50000000391

• Pediatric Papillary Thyroid Carcinoma RNA-Seq

  Papillary thyroid carcinoma (PTC) is the most common malignancy amongst adolescent and young adult women. Clinical and genomic features of PTC in children differ from those in adults. Historically, a substantial proportion (~50%) of pediatric PTC (PPTC) lack any of the common driver mutations typical of adult PTC. Thus, molecular diagnostics developed for adults may not be valid in children. We applied novel bioinformatic pipelines to RNASeq analysis of pediatric thyroid tumors to identify known and novel fusion oncogenes as drivers of tumorigenesis and to define gene expression patterns among tumors. Analysis of 38 samples resulted in identification of 16 previously reported oncogenic fusions and three novel candidate fusions. In conducting these analyses, we reduced the proportion of cancers with unknown drivers from approximately 50% to 6%. Gene expression analysis identified three distinct categories of tumors. These studies represent the first unbiased genomic approach to childhood PTC. Novel bioinformatic pipeline. GEC Identified 3 distinct classes. DICER1, PTEN segregated with benign tumors. >90% of PPTC carry identifiable ongognic driver variants, however, the landscape differs from that in adults and existing tools for tumor genotyping in adults may not be applicable to pediatric tumors. BACKGROUND: Papillary thyroid carcinoma demonstrates clinically distinct behaviour in pediatric patients when compared to adults, with increased regional and distal metastases, more frequent recurrence, yet overall highly favourable prognosis. Recent tumor genotyping has demonstrated that in pediatric tumors, ***-*** do not carry the most common genomic variants found in adult PTC, leaving a substantial proportion of driver-unknown or “dark matter” tumors. METHODS: We established a cohort of 52 pediatric PTC and performed quantitative-PCR genotyping followed in a subset by whole exome and whole transcriptome (RNASeq) sequencing using a novel, robust bioinformatic pipeline to identify oncogenic fusion transcripts. Gene expression analysis was used to derive distinct clusters. RESULTS: In 52 pediatric PTC, genotyping identified BRAFV600E(21%), NRASQ61R(2%), RET/PTC1 (21%), RET/PTC3 (17%) or PAX8-PPAR in 33 (63%) of tumors. Among the remaining 19 tumors, oncogenic variants were identified in /19 (%). The variants included SNVs in DICER1, ETV6-NTRK3, PTEN and 9 additional oncogenic fusions including two previously-undescribed fusion transcripts, *** and ***. CONCLUSIONS: The genomic landscape of PTC differs between children and adults. In children, there is a substantial fraction of tumors that are unexplained by variants typical of adult PTC. This discrepancy is explained largely by uncommon oncogenic fusions which can be identified by whole-transcriptome analysis.

  Study EGAS00001005182