15020 results for "cancer studies using rna-seq"

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• Illumina whole genome sequencing data for two patients with congenital disease

  BAM files with sequencing reads derived from Illumina whole genome sequencing of two DNA samples from lymphoblastoid cell lines from two patients with congenital disease. Whole genome sequencing was performed using Illumina HiSeq X Ten and samples were prepared using TruSeq library prep.

  Dataset EGAD00001003510

• WES data generated in multifocal ileal NETs study

  This dataset includes whole-exome sequencing data for multifocal ileal tumor samples from two patients. Exonic sequences were enriched using the Agilent V2 capture probe set and sequenced by 76-bp paired-end reads using the Illumina Genome Analyzer IIx system with a mean coverage of 80x for each base

  Dataset EGAD00001006408

• Pancreatic Cancer Sequencing Initiative

  Pancreatic Cancer Sequencing Initiative for the International Cancer Genome Consortium at the Ontario Institute for Cancer Research.

  Study EGAS00001000343

• Non-invasive human skin transcriptome analysis using mRNA in skin surface lipids

  Non-invasive acquisition of mRNA data from the skin can be extremely useful for understanding skin physiology and diseases. Inspired by the holocrine process, in which the sebaceous glands secrete cell contents into the sebum, we focused on the possible presence of mRNAs in skin surface lipids (SSLs). We found that measurable levels of human mRNAs exist in SSLs, where the sebum protects them from degradation by RNases. The AmpliSeq transcriptome analysis was modified to measure SSL-RNA levels, and our results revealed that the SSL-RNAs predominantly comprised mRNAs derived from sebaceous glands, the epidermis, and hair follicles. Analysis of SSL-RNAs non-invasively collected from patients with atopic dermatitis revealed significantly increased expression of inflammation-related genes and decreased expression of terminal-differentiation���related genes, consistent with the results of previous reports. Further, we found that lipid-synthesis���related genes were downregulated in the sebaceous glands of patients with atopic dermatitis. These results indicate that the analysis of SSL-RNAs is a promising strategy to understand the pathophysiology of skin diseases.

  Study JGAS000416

• Non-invasive human skin transcriptome analysis using mRNA in skin surface lipids

  Non-invasive acquisition of mRNA data from the skin can be extremely useful for understanding skin physiology and diseases. Inspired by the holocrine process, in which the sebaceous glands secrete cell contents into the sebum, we focused on the possible presence of mRNAs in skin surface lipids (SSLs). We found that measurable levels of human mRNAs exist in SSLs, where the sebum protects them from degradation by RNases. The AmpliSeq transcriptome analysis was modified to measure SSL-RNA levels, and our results revealed that the SSL-RNAs predominantly comprised mRNAs derived from sebaceous glands, the epidermis, and hair follicles. Analysis of SSL-RNAs non-invasively collected from patients with atopic dermatitis revealed significantly increased expression of inflammation-related genes and decreased expression of terminal-differentiation���related genes, consistent with the results of previous reports. Further, we found that lipid-synthesis���related genes were downregulated in the sebaceous glands of patients with atopic dermatitis. These results indicate that the analysis of SSL-RNAs is a promising strategy to understand the pathophysiology of skin diseases.

  Study JGAS000418

• Non-invasive human skin transcriptome analysis using mRNA in skin surface lipids

  Non-invasive acquisition of mRNA data from the skin can be extremely useful for understanding skin physiology and diseases. Inspired by the holocrine process, in which the sebaceous glands secrete cell contents into the sebum, we focused on the possible presence of mRNAs in skin surface lipids (SSLs). We found that measurable levels of human mRNAs exist in SSLs, where the sebum protects them from degradation by RNases. The AmpliSeq transcriptome analysis was modified to measure SSL-RNA levels, and our results revealed that the SSL-RNAs predominantly comprised mRNAs derived from sebaceous glands, the epidermis, and hair follicles. Analysis of SSL-RNAs non-invasively collected from patients with atopic dermatitis revealed significantly increased expression of inflammation-related genes and decreased expression of terminal-differentiation���related genes, consistent with the results of previous reports. Further, we found that lipid-synthesis���related genes were downregulated in the sebaceous glands of patients with atopic dermatitis. These results indicate that the analysis of SSL-RNAs is a promising strategy to understand the pathophysiology of skin diseases.

  Study JGAS000417

• Pancreatic Cancer Sequencing Initiative OICR

  Pancreatic Cancer Sequencing Initiative for the International Cancer Genome Consortium at the Ontario Institute for Cancer Research.

  Study EGAS00001000395

• Whole exome sequencing and RNA sequencing of lineage-switched acute myeloid leukemia with KMT2A-AFF1 rearrangement

  We performed whole exome sequencing and RNA sequencing of lineage-switched acute myeloid leukemia (LS AML) with KMT2A-AFF1 rearrangement to elucidate the feature and potential treatment targets. Notably, LS AML possessed gene expression signatures of monocytic myeloid derived suppressor cells (M-MDSCs). Several known genes related to MDSCs were highly expressed in LS AML, which could be novel treatment targets.

  Study JGAS000631

• Single-cell RNA sequencing on single CD45+ immune cells isolated from peripheral blood, lymphnode, ascites, tumour and adjacent normal tissues from six hepatocellular carcinoma patients.

  Single-cell RNA sequencing on single CD45+ immune cells isolated from peripheral blood, lymphnode, ascites, tumour and adjacent normal tissues from six hepatocellular carcinoma patients. The transcriptional properties of these individual cells, were used to delineate the molecular subtypes, lineage, and functional properties of each cell group

  Study EGAS00001003449

• Identification of Long Non-coding RNA Biomarker of Human Lupus Nephritis Disease Activity

  Total RNA sequencing was performed on whole blood samples from 74 Lupus nephritis (LN) patients and 20 healthy controls. Differential expression analysis and weighted gene co-expression network analysis were performed to characterise expression changes of long non-coding RNAs (lncRNAs) in LN and identify lncRNAs with a key role in disease activity that could be used as potential blood-based biomarkers.

  Study EGAS00001007117

• Mosaic structural variation sample

  Mosaic Normal-Tumor genomes are generated from real normal-tumor pairs with validated somatic variants. In this case, validated variants from the GRIDSS2 paper. Mosaic genomes were generated using GenomeMosaicMaker, an open-source software tool designed and implemented for this specific purpose. The variants provided in the VCF truth file for each mosaic tumor/normal pair were annotated using funnSV for SVs and VEP for SNVs and indels. All CRAM files are aligned to GRCh37. Please see https://github.com/EUCANCan/oncoliner and https://github.com/Computational-Genomics-BSC/GenomeMosaicMaker for more information.

  Study EGAS50000000460

• Copy Number Abnormalities of Chr1 in Multiple Myeloma at the Single Cell Level

  Single-cell whole genome sequencing (scWGS) provides a tool to gain deeper insights into the clonal relationships of Chr1 copy number changes. Here, we study Chr1 copy number alteration (CNA) using Direct library preparation plus (DLP+), a scalable scWGS platform implemented by image-based object recognition, and open-source computational methods. We report scWGS of 2,046 cells with 400-650 single-cells per patient from 5 Multiple Myeloma patients selected from our biobank with chr1q gains identified by iFISH using a CKS1B probe (IRB S21-01218 and I19-01384)

  Study phs004109

• Copy number analysis by SNP array

  Hybridization-based genomic profiling arrays were performed using Genome-Wide Human SNP Array 6.0 or the CytoScan HD array, according to the manufacturer’s instructions (Affymetrix, Santa Clara, CA, USA) now part of Thermo Fisher Scientific (Thermo Fisher Scientific, Inc.) Following the procedures of sample preparation, hybridization, and scanning, the CEL file of Genome-Wide Human SNP Array 6.0 was analyzed as previously described (Magrangeas et al. 2012) and the CEL file of CytoScan HD array was analyzed using the Chromosome Analysis Suite (ChAS) software (Thermo Fisher Scientific, Inc).

  Study EGAS00001005125

• Mechanisms of patient response to Dabrafenib in Melanoma

  Samples will be from the BRF113683 (BREAK-3) study which is a Phase III Randomized, Open-label Study Comparing GSK2118436 to Dacarbazine (DTIC) in Previously Untreated Subjects With BRAF Mutation Positive Advanced (Stage III) or Metastatic (Stage IV) Melanoma (n=250 enrolled)*NGS [Agilent capture (Sanger V2 panel): 360 genes and 20 gene fusions; Illumina HiSEQ Sequencing]*CNV: [via NGS or Affy SNP 6.0 or Illumina Omni (TBD)]Bioinformatics: Analysis will be performed using core Sanger informatics pipelines similar to those previously described (Papaemmanuil E et al. (2013) Blood. 22:3616 -3627). Briefly, copy number analysis will be performed using the ASCAT algorithm, and base substitutions, small insertions and deletions using the CAVEMAN and Pindel algorithms, respectively. Statistical approaches including generalized linear models will be used to predict clinical variables such as maximum clinical response and duration of response using genetic data. Sanger and EBI to conduct analysis; Raw data and correlation with clinical endpoints to be analyzed by both EBI/Sanger and GSK (unique pipeline analyses to increase call confidence)

  Dataset EGAD00001001375

• Targeted Myeloid DNA-Panelsequencing, DKFZ

  Targeted myeloid DNA-Panelsequencing from purified bone marrow blasts of 104 treatment naive AML patients from the discovery cohort. For more details, we refere to Jayavelu, Wolf, Buettner et al. Libraries were prepared from 40 ng DNA using the QIASeq Human Myeloid Neoplasms Panel (Qiagen) according to the manufacturer’s protocol. Samples were tagged with the QIAseq 96-Unique Dual Index Set A for Illumina platforms (Qiagen) to yield unique combinations of i5 and i7 barcodes for each sample. Sample fragment size distribution and concentration was estimated using the Agilent High Sensitivity DNA kit on a 2100 Bioanalyzer (Agilent). Samples were pooled in an equimolar fashion, denatured, and diluted to 1.5 pM according to Illumina’s recommendations. The diluted library was sequenced on a NextSeq 500 benchtop sequencer (Illumina) using NextSeq High Output cartridges. Demultiplexing was performed using the BaseSpace cloud platform (Illumina).

  Dataset EGAD00001008501

• Rna_expression

  RNA expression microarray

  Dataset EGAD00010000869

• Lipomatous tumors with 12q amplification

  RNA sequencing of 20 tumors.

  Dac EGAC50000000036

• RNA sequencing of AD, MCI and control ONS cells

  Study EGAS00001006594

• The Extracellular RNA Quality Control (exRNAQC) study (phase 2)

  Study EGAS00001006499