12000 results for "cancer rna-seq"

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• Molecular Profiling Reveals Unique Immune and Metabolic Features of Melanoma Brain Metastases. Cancer Discovery doi: 10.1158/2159-8290. PMID: 30787016 PMCID: PMC6497554

  The BAM files for WES and RNA seq used in the article "Molecular Profiling Reveals Unique Immune and Metabolic Features of Melanoma Brain Metastases." on cancer Discovery 2019. PMID: 30787016 PMCID: PMC6497554. Authors : Grant M Fischer, ..., Michael A Davies.

  Dataset EGAD00001005046

• Additional RNA-seq, ChIP-seq, and ATAC-seq files for PCGP SJERG

  This dataset contains RNA-seq, ATAC-seq, and ChIP-seq samples from the SJERG cohort. We applied ChIP-Seq for Dux4 on two B-cell ALL cell-lines(REH, Nalm6) along with INPUT. ATAC-Seq on two B-cell ALL cell-lines(REH, Nalm6) and xenograft of a B-cell ALL patient(ERG000016).

  Dataset EGAD00001002654

• Sputum RNA-Seq from Asthmatic Patients for Microbes and Genes

  RNA-seq files and other data associated with an investigation of the relationship between microbes, genes and immune cells present in the sputum of humans with asthma.

  Study phs002224

• bulk RNA-seq data

  a total number of 99 bulk RNA-seq lymphoma samples

  Dataset EGAD50000000631

• The Role of ZEB2 during Human Neural Crest Cell Formation

  This study examined the role of ZEB2 during human neural crest cell formation. Human neural crest cells were differentiated from WiCell H1 human embryonic stem cells (WA01). Genome-wide transcriptional analysis (RNA-seq) was performed at day-3 and day-5 of human neural crest cell formation following siRNA knockdown of ZEB2 and using an N-terminal ZEB2 mutant H1 human embryonic stem cell line generated using CRISPR genome editing. RNA-seq was also performed on edited and unedited H1 human embryonic stem cells. ATAC-seq analysis was performed at day-3 and day-5 human neural crest differentiated from the N-terminal ZEB2 mutant embryonic stem cell line. Together, these data reveal the regulatory role of ZEB2 in the human neural crest gene regulatory network. We provide raw sequencing files for all RNA-seq and ATAC-seq samples.

  Study phs002701

• RNA-seq data for study 'Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.'

  RNA-seq data from nasal and bronchial tissues in 649 subjects, many with lung cancer. Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

  Dataset EGAD50000000333

• RNA-seq of human astroblastomas

  RNA-seq for fusion gene discovery of human astroblastomas

  Dataset EGAD00001009664

• bulk Exome-seq of the 5 HCC patients which also have the single cell T cell RNA-seq data

  bulk Exome-seq data of the 5 HCC patinets. Single cell RNA seq data of these patients was under the accession number EGAD00001003337

  Dataset EGAD00001004149

• RNA-Seq of response to Tozinameran vaccination in individuals with KTx/dialysis or healthy controls.

  Low-input RNA-Seq (~200 cells per sample) of CD4+ T cells in patients with kidney transplants, dialysis, or healthy controls after the second dose of Tozinameran COVID-19 vaccine. RNA-Seq was performed using the Smart-Seq v4 ultra-low input protocol. The dataset includes 4 healthy control samples, 3 kidney transplant recipients, and 4 patients undergoing dialysis.

  Dataset EGAD00001007689

• WES and RNA-seq data of 11 cancer patients with multiple cancer types

  This dataset includes WES and RNAseq from 11 patients with metastatic melanoma, lung, kidney, and stomach cancers, enrolled in phase I clinical trials of TIL ACT (NCT03475134 & NCT04643574). WES was performed on matched cancer and healthy samples, whereas RNAseq was performed on cancer tissues, using Illumina HiSeq 2500/4000 and Illumina NextSeq 550 systems. Paired-end reads are provided in fastq format.

  Dataset EGAD00001010169