14970 results for "cancer studies using rna-seq"

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• Glucose Binds and Activates NSUN2 to Promote Translation and Epidermal Differentiation

  This study was undertaken to determine the role of NSUN2 in epidermal homeostasis. Primary neonatal foreskin keratinocytes were obtained from discarded surgical samples at a California hospital. Samples were anonymous and not selected. NSUN2 was found to promote epidermal differentiation and alter translation using the methods of RNA-seq, CLIP-seq and Ribo-seq.

  Study phs003767

• The UC San Diego Chronic Lymphocytic Leukemia (CLL) Study

  The UC San Diego Chronic Lymphocytic Leukemia Study is designed to identify genetic, epigenetic, and transcriptional changes important for CLL. This data release consists of samples collected to 1) identify genomic changes associated with CLL progression using serially collected tumor samples; 2) characterize the transcriptional consequences of SF3B1 mutation through RNA-seq; and 3) characterize the expression profiles of ROR1+ vs. ROR1- tumors. The samples were collected from participants at the University of California, San Diego Moores Cancer Center and the data was generated at UC San Diego or in collaboration with the BC Cancer Agency Genome Sciences Centre.

  Study phs000767

• WES and RNA-seq of triple-negative breast cancers from the MyBrCa cohort

  The dataset contains a genomics characterization of 35 triple-negative Asian breast tumours from the Malaysian Breast Cancer cohort. This includes whole-exome sequencing of tumour tissue at 80X, whole-exome sequencing of matched normal (blood) tissue at 40X, and RNA-seq of tumour tissue at 40X coverage (>15 million reads). Whole-exome libraries were prepared using the Nextera Rapid Capture Exome Kit; exome capture was performed in pools of 3 and subjected to paired end 75 sequencing on a NovaSeq 6000 platform. RNA libraries were prepared using the TruSeq Stranded Total RNA HT kit with Ribo-Zero Gold as per manufacturer’s instructions and also subjected to paired end 75 sequencing on a NovaSeq 6000 platform. Uploaded bam files have been mapped to the hs37d5 human genome and processed using the standard GATK pipelines. Paired clinical, demographic, genotyping, and overall survival data for these patients are available from the associated publications or by request.

  Dataset EGAD00001009311

• CCA RNA-seq data (60 CCA, 6 normal, 16 cell-line)

  Fastq files for RNA-seq for 60 CCAs, 6 normal bile duct tissues, 14 CCA cell-lines (including replicates), and 2 normal cholangiocyte cell-lines (including replicates). RNA was extracted using the Qiagen RNeasy Mini kit. Illumina Tru-Seq Stranded Total RNA kit (Illumina, San Diego, California, USA) was used to prepare RNA libraries from 1 µg of total RNA. Paired-end 150 bp sequencing was performed using Illumina HiSeq4000 sequencer with the paired-end 150 bp read option.

  Dataset EGAD00001011998

• Alpha synucleinopathy spectrum - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA seq dataset from prefrontal cortex for a total of N=44 samples. Tissue samples correspond to patients with different alpha synucleinopathies. Specifically, idiopathic Parkinson's disease (PD, N=20) monogenic PD caused by LRRK2 mutations (LRRK2-PD, N=7), multiple system atrophy (MSA, N=6) and neurologically healthy controls (N=11). RNA seq was carried out using ribosomal depletion. The totality of these samples were also sequenced using single nucleus RNA seq, and available within the same study as a separate dataset.

  Dataset EGAD50000000430

• Whole-exome sequencing and RNA-seq data of paired normal-tumour samples from MMR-proficient early-onset colorectal cancer patients

  This study aims to identify novel hereditary colorectal cancer predisposition genes by performing whole-exome sequencing and RNA-seq of paired normal colonic mucosa and colorectal cancer samples from 19 patients diagnosed with MMR-proficient colorectal cancer at an age of 50 years or younger. Both whole-exome and RNA sequencing were performed on the Illumina platform.

  Study EGAS50000001296

• SCANDARE HNSCC 3' Tag RNA-seq

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 264 FFPE samples at baseline from 90 HNSCC patients using 3'-tag RNA-seq technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001655

• Genentech gallbladder cancer study - RNA-seq

  Genentech gallbladder cancer study - RNA-seq

  Dataset EGAD00001004854

• Ovarian cancer EV RNA-seq

  Ovarian cancer EV RNA-seq

  Dataset EGAD00001008972

• NKI-AvL CRC-OVC scTCR RNA-seq

  The dataset “NKI-AvL CRC-OVC scTCR RNA-seq" includes 368 BAM files from paired-end RNA sequencing on Illumina MiSeq for 2 colorectal cancer and 2 ovarian cancer patients.

  Dataset EGAD00001004342

• RNAseq data to study PRPF6 regulated splice forms in colon cancer cell lines

  Alternative splicing plays critical roles in differentiation, development, and cancer (Pettigrew et al., 2008; Chen and Manley, 2009). The recent identification of specific spliceosome inhibitors has generated interest in the therapeutic potential of targeting this cellular process (van Alphen et al., 2009). Using an integrated genomic approach, we have identified PRPF6, an RNA binding component of the pre-mRNA spliceosome, as an essential driver of oncogenesis in colon cancer. Importantly, PRPF6 is both amplified and overexpressed in colon cancer, and only colon cancer cells with high PRPF6 levels are sensitive to its loss. Our data clearly point to an important role for PRPF6 in colon cancer growth and suggest that a better understanding of its role in alternative splicing in colon cancer is warranted. To determine the specific alternative splice forms that PRPF6 regulates in colon cancer, we plan three experiments: 1. The first involves knocking down expression of PRPF6 in two different cancer cell lines with 3 different siRNAs, and then completing RNA-seq to determine the gene expression changes that occur relative to a non-targeting control siRNA. Because of the role for PRPF6 in pre-mRNA splicing, we especially want to quantify the changes in splice-specific forms of all genes genome-wide to identify genes whose splicing is altered upon PRPF6 knockdown. 2. The second involves immunoprecipitating PRPF6 from two different cancer cell lines and isolating any RNA that is bound to PRPF6, since PRPF6 is an RNA-binding protein. We then want to carry out RNA-seq to identify which RNA molecules co-immunoprecipitated with PRPF6. This will help us determine possible functions for PRPF6 in regulating colon cancer growth. 3. The third involves overexpressing PRPF6 in cell lines and then carrying out RNA-seq to identify any changes in splice-specific gene expression. This will allow us to determine whether increased PRPF6 expression is sufficient to drive alternative splicing changes.

  Dataset EGAD00001000817

• Massachusetts General Hospital Cancer Center DAC for single cell RNA-seq data from small cell lung cancer primary tumors and CTCs

  single cell RNA-seq data from 10 small cell lung cancer primary tumors and circulating tumor cells of three small cell lung cancer patients

  Dac EGAC50000000808

• Single cell RNA-seq profiling of CD8 T cells from elder adults

  Single cell RNA-seq profiling of ~62k purified CD8+ T cell transcriptomes, from six healthy older adult donors using 10X genomics. Cells from each donor were separated based on their IL-7R protein expression (i.e. CD8+ IL7R+ and CD8+ IL7R- T cells).

  Study EGAS00001004255

• Comparison Between qPCR and RNA-Seq Reveals Challenges of Quantifying HLA Expression

  Human leukocyte antigen (HLA) class I and HLA class II loci are essential elements of innate and acquired immunity. Their exceptional influence on disease outcome is well documented by GWAS and candidate gene studies. The impact of HLA allelic variation on human disease through allele-specific presentation of antigenic peptides to T cells has been the main focus to determine HLA effects on disease susceptibility/pathogenesis. However, HLA expression levels have also been implicated in disease, adding another dimension to the extreme diversity of HLA that impacts variability in immune responses across individuals. HLA expression levels routinely rely on quantitative PCR (qPCR). An alternative is adoption of high throughput technologies such as RNA-Seq. This provides the opportunity to quantify HLA expression in large datasets, but also allows comparison between RNA-Seq and qPCR. In this study, we analyze expression data for HLA Class I genes for a matched set of individuals (N = 96) by RNA-Seq, qPCR and cell surface expression. Samples were obtained from the Research Donor Program (NCI-Frederick). We observed a moderate correlation between RNA-Seq and qPCR. We suggest technical and biological factors that might contribute to differences in the techniques.

  Study phs003177